BIG IOT AND SOCIAL NETWORKING DATA FOR SMART
CITIES:
Algorithmic improvements on Big Data Analysis in the context of RADICAL city
applications
Evangelos Psomakelis12,Fotis Aisopos1, Antonios Litke1, Konstantinos Tserpes21, Magdalini
Kardara1 and Pablo Martínez Campo3
1Distributed Knowledge and Media Systems Group, National Technical University of Athens, Zografou Campus, Athens,
Greece
2Informatics and Telematics Dept, Harokopio University of Athens, Greece
3Communications Engineering department, University of Cantabria, Santander, Spain
{fotais, litke, nkardara, tserpes, vpsomak}@mail.ntua.gr,[email protected]
Keywords: Internet of Things, Social Networking, Big Data Aggregation and Analysis, Smart City applications,
Sentiment Analysis, Machine Learning
Abstract: In this paper we present a SOA (Service Oriented Architecture)-based platform, enabling the retrieval and
analysis of big datasets stemming from social networking (SN) sites and Internet of Things (IoT) devices,
collected by smart city applications and socially-aware data aggregation services. A large set of city
applications in the areas of Participating Urbanism, Augmented Reality and Sound-Mapping throughout
participating cities is being applied, resulting into produced sets of millions of user-generated events and
online SN reports fed into the RADICAL platform. Moreover, we study the application of data analytics such
as sentiment analysis to the combined IoT and SN data saved into an SQL database, further investigating
algorithmic and configurations to minimize delays in dataset processing and results retrieval.
1 INTRODUCTION
Modern cities are increasingly turning towards
ICT technology for confronting pressures associated
with demographic changes, urbanization, climate
change (Romero Lankao, 2008) and globalization.
Therefore, most cities have undertaken significant
investments during the last decade in ICT
infrastructure including computers, broadband
connectivity and recently sensing infrastructures.
These infrastructures have empowered a number of
innovative services in areas such as participatory
sensing, urban logistics and ambient assisted living.
Such services have been extensively deployed in
several cities, thereby demonstrating the potential
benefits of ICT infrastructures for businesses and the
citizens themselves. During the last few years we
have also witnessed an explosion of sensor
deployments and social networking services, along
with the emergence of social networking (Conti et al.,
2011) and internet‐of‐things technologies (Perera et
al., 2013; Sundmaeker et al., 2010) Social and sensor
networks can be combined in order to offer a variety
of added‐value services for smart cities, as has
already been demonstrated by various early internet‐
of‐things applications (such as WikiCity(Calabrese et
al., 2007), CitySense(Murty et al., 2007),
GoogleLatitude(Page and Kobsa, 2010)), as ...
Applicability of big data techniques to smart cities deploymentsNexgen Technology
GET IEEE BIG DATA,JAVA ,DOTNET,ANDROID ,NS2,MATLAB,EMBEDED AT LOW COST WITH BEST QUALITY PLEASE CONTACT BELOW NUMBER
FOR MORE INFORMATION PLEASE FIND THE BELOW DETAILS:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com
Mobile: 9791938249
Telephone: 0413-2211159
www.nexgenproject.com
APPLICABILITY OF BIG DATA TECHNIQUES TOSMART CITIES DEPLOYMENTSNexgen Technology
GET IEEE BIG DATA,JAVA ,DOTNET,ANDROID ,NS2,MATLAB,EMBEDED AT LOW COST WITH BEST QUALITY PLEASE CONTACT BELOW NUMBER
FOR MORE INFORMATION PLEASE FIND THE BELOW DETAILS:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com
Mobile: 9791938249
Telephone: 0413-2211159
www.nexgenproject.com
Analysing Transportation Data with Open Source Big Data Analytic Toolsijeei-iaes
Big data analytics allows a vast amount of structured and unstructured data to be effectively processed so that correlations, hidden patterns, and other useful information can be mined from the data. Several open source big data analytic tools that can perform tasks such as dimensionality reduction, feature extraction, transformation, optimization, are now available. One interesting area where such tools can provide effective solutions is transportation. Big data analytics can be used to efficiently manage transport infrastructure assets such as roads, airports, bus stations or ports. In this paper an overview of two open source big data analytic tools is first provided followed by a simple demonstration of application of these tools on transport dataset.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
Applicability of big data techniques to smart cities deploymentsNexgen Technology
GET IEEE BIG DATA,JAVA ,DOTNET,ANDROID ,NS2,MATLAB,EMBEDED AT LOW COST WITH BEST QUALITY PLEASE CONTACT BELOW NUMBER
FOR MORE INFORMATION PLEASE FIND THE BELOW DETAILS:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com
Mobile: 9791938249
Telephone: 0413-2211159
www.nexgenproject.com
APPLICABILITY OF BIG DATA TECHNIQUES TOSMART CITIES DEPLOYMENTSNexgen Technology
GET IEEE BIG DATA,JAVA ,DOTNET,ANDROID ,NS2,MATLAB,EMBEDED AT LOW COST WITH BEST QUALITY PLEASE CONTACT BELOW NUMBER
FOR MORE INFORMATION PLEASE FIND THE BELOW DETAILS:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com
Mobile: 9791938249
Telephone: 0413-2211159
www.nexgenproject.com
Analysing Transportation Data with Open Source Big Data Analytic Toolsijeei-iaes
Big data analytics allows a vast amount of structured and unstructured data to be effectively processed so that correlations, hidden patterns, and other useful information can be mined from the data. Several open source big data analytic tools that can perform tasks such as dimensionality reduction, feature extraction, transformation, optimization, are now available. One interesting area where such tools can provide effective solutions is transportation. Big data analytics can be used to efficiently manage transport infrastructure assets such as roads, airports, bus stations or ports. In this paper an overview of two open source big data analytic tools is first provided followed by a simple demonstration of application of these tools on transport dataset.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
SEMANTIC TECHNIQUES FOR IOT DATA AND SERVICE MANAGEMENT: ONTOSMART SYSTEMijwmn
In 2020 more than50 billions devices will be connected over the Internet. Every device will be connected to
anything, anyone, anytime and anywhere in the world of Internet of Thing or IoT. This network will
generate tremendous unstructured or semi structured data that should be shared between different
devices/machines for advanced and automated service delivery in the benefits of the user’s daily life. Thus,
mechanisms for data interoperability and automatic service discovery and delivery should be offered.
Although many approaches have been suggested in the state of art, none of these researches provide a fully
interoperable, light, flexible and modular Sensing/Actuating as service architecture. Therefore, this paper
introduces a new Semantic Multi Agent architecture named OntoSmart for IoT data and service
management through service oriented paradigm. It proposes sensors/actuators and scenarios independent
flexible context aware and distributed architecture for IoT systems, in particular smart home systems.
An Innovative, Open, Interoperable Citizen EngagementCloud P.docxgreg1eden90113
An Innovative, Open, Interoperable Citizen Engagement
Cloud Platform for Smart Government and Users’
Interaction
Diego Reforgiato Recupero1,6 & Mario Castronovo2 &
Sergio Consoli1 & Tarcisio Costanzo3 &
Aldo Gangemi1,4 & Luigi Grasso3 & Giorgia Lodi1 &
Gianluca Merendino3 & Misael Mongiovì1 &
Valentina Presutti1 & Salvatore Davide Rapisarda2 &
Salvo Rosa2 & Emanuele Spampinato5
Received: 10 November 2015 /Accepted: 20 January 2016 /
Published online: 30 January 2016
# Springer Science+Business Media New York 2016
Abstract This paper introduces an open, interoperable, and cloud-computing-based
citizen engagement platform for the management of administrative processes of public
administrations, which also increases the engagement of citizens. The citizen engage-
ment platform is the outcome of a 3-year Italian national project called PRISMA
(Interoperable cloud platforms for smart government; http://www.ponsmartcities-
prisma.it/). The aim of the project is to constitute a new model of digital ecosystem
that can support and enable new methods of interaction among public administrations,
citizens, companies, and other stakeholders surrounding cities. The platform has been
defined by the media as a flexible (enable the addition of any kind of application or
service) and open (enable access to open services) Italian Bcloud^ that allows public
administrations to access to a vast knowledge base represented as linked open data to
be reused by a stakeholder community with the aim of developing new applications
(BCloud Apps^) tailored to the specific needs of citizens. The platform has been used
by Catania and Syracuse municipalities, two of the main cities of southern Italy, located
J Knowl Econ (2016) 7:388–412
DOI 10.1007/s13132-016-0361-0
* Diego Reforgiato Recupero
[email protected]
1 National Research Council (CNR), Via Gaifami 18, 95126 Catania, Italy
2 Sielte, Via Cerza 4, 95027 San Gregorio di Catania, Italy
3 Datanet, Syracuse, Contrada Targia 58, 96100 Syracuse, Italy
4 Paris Nord University, Sorbonne Citè CNRS UMR7030, France
5 Etna Hitech, Viale Africa 31, 95129 Catania, Italy
6 Department of Mathematics and Computer Science, University of Cagliari, Cagliari, Italy
http://www.ponsmartcities-prisma.it/
http://www.ponsmartcities-prisma.it/
http://crossmark.crossref.org/dialog/?doi=10.1007/s13132-016-0361-0&domain=pdf
in the Sicilian region. The fully adoption of the platform is rapidly spreading around the
whole region (local developers have already used available application programming
interfaces (APIs) to create additional services for citizens and administrations) to such
an extent that other provinces of Sicily and Italy in general expressed their interest for
its usage. The platform is available online and, as mentioned above, is open source and
provides APIs for full exploitation.
Keywords Smartcity.Smartgovernance.Linkedopendata.Citizenengagement.Cloud
computing
Introduction
Smart governance is defined as a subset of the s.
Sustainability - The Software PerspectivePatricia Lago
This is a guest lecture for the course Software Architectures at the University of L'Aquila, Italy. It provides 3 takeaways:
(1) software can help or hinder sustainability
(2) software architecture may provide the right "big picture"
(3) decision making must be informed
Join us for an exciting session where you can explore the future of open-source technology and innovation projects based on FIWARE and supported by FIWARE team. Our experts will share their insights on how FIWARE standards and components are revolutionizing the tech industry. Attendees will have the opportunity to hear from a variety of presenters showcasing ongoing projects that leverage FIWARE. From dynamic digital twins to satellite open data for smart cities, to boosting EU high-value datasets, this session will provide a glimpse into the exciting possibilities of FIWARE technology. Don't miss out on this chance to learn about the latest innovation and collaborate with like-minded professionals!
MULTI-AGENT BASED IOT SMART WASTE MONITORING AND COLLECTION ARCHITECTUREijcseit
Solid waste management is one of the existing challenges in urban areas and it is becoming a critical issue
due to rapid increase in population. Appropriate solid waste management systems are important for
improving the environment and the well-being of residents. In this paper, an Internet of Things(IoT)
architecture for real time waste monitoring and collection has been proposed; able to improve and
optimize solid waste collection in a city. Netlogo Multi-agent platform has been used to simulate real time
monitoring and smart decisions on waste management. Waste filling level in bins and truck collection
process are abstracted to a multi-agent model and citizen are involved by paying the price for waste
collection services. Furthermore, waste level data are updated and recorded continuously and are provided
to decision algorithms to determine the vehicle optimal route for waste collection to the distributed bins in
the city. Several simulation cases executed and results validated. The presented solution gives substantial
benefits to all waste stakeholders by enabling the waste collection process to be more efficient
MULTI-AGENT BASED IOT SMART WASTE MONITORING AND COLLECTION ARCHITECTURE ijcseit
Solid waste management is one of the existing challenges in urban areas and it is becoming a critical issue due to rapid increase in population. Appropriate solid waste management systems are important for improving the environment and the well-being of residents. In this paper, an Internet of Things(IoT) architecture for real time waste monitoring and collection has been proposed; able to improve and optimize solid waste collection in a city. Netlogo Multi-agent platform has been used to simulate real time monitoring and smart decisions on waste management. Waste filling level in bins and truck collection process are abstracted to a multi-agent model and citizen are involved by paying the price for waste collection services. Furthermore, waste level data are updated and recorded continuously and are provided to decision algorithms to determine the vehicle optimal route for waste collection to the distributed bins in the city. Several simulation cases executed and results validated. The presented solution gives substantial benefits to all waste stakeholders by enabling the waste collection process to be more efficient
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
MOBILE APPLICATION FOR DONATION OF ITEMSvivatechijri
Development of NGO is also development of society prestige, which makes significance contribution to diverse areas. Since NGO are non-profit organization, they always lack resources. Thus, to fulfill the requirements “UNNATI SAMAJ “app will be a rescue. Using this app any donor can donate food, clothes, and other items which can be utilize by needy ones. For e.g. from big organized parties, often food gets wasted, so using the app’s Google API technology people can donate the food to nearest NGO without needed to search up for contact information. Thus, our app will be a direct bridge between all NGOs and donors.
BUS M02C – Managerial Accounting SLO Assessment project .docxhartrobert670
BUS M02C – Managerial Accounting
SLO Assessment project
Randy’s Kayaks, Inc. manufactures and sells one-person fiberglass kayaks. Randy’s balance sheet at the end
of 2011 was as follows:
RANDY’S KAYAKS, INC.
Balance Sheet
December 31, 2011
ASSETS LIABILITIES
Cash $ 52,000 Accounts payable $ 131,000
Accounts receivable 1,200,000
Raw materials inventory* 120,000 STOCKHOLDERS’EQUITY
Finished goods inventory** 287,500 Common Stock 1,600,000
Plant assets, net of accumulated Retained Earnings 2,063,500
Depreciation 2,135,000
Total Assets $ 3,794,500 Total Liabilities & SE $ 3,794,500
*40,000 pounds
**1,000 kayaks
The following additional data is available for use in preparing the budget for 2012:
Cash collections (all sales are on account):
Collected in the quarter of sale 40%
Collected in the quarter after sale 60%
(Bad debts are negligible and can be ignored)
Cash disbursements for raw materials (all purchases are on account):
Cash paid in the quarter of purchase 70%
Cash paid in the quarter after purchase 30%
Desired quarterly ending Raw materials inventory 40% of next quarter’s production needs
Desired quarterly ending Finished goods inventory 10% of next quarter’s sales
Budgeted sales:
1
st
quarter 2012 10,000 kayaks
2
nd
quarter 2012 15,000 kayaks
3
rd
quarter 2012 16,000 kayaks
4
th
quarter 2012 14,000 kayaks
1
st
quarter 2013 10,000 kayaks
2
nd
quarter 2013 12,000 kayaks
Anticipated equipment purchases:
1
st
quarter 2012 $30,000
2
nd
quarter 2012 $0
3
rd
quarter 2012 $0
4
th
quarter 2012 $150,000
Quarterly dividends to be paid each quarter in 2012 $4,000
Expected sales price per unit $400
Standard cost data:
Direct materials 10 pounds per kayak @ $3 per pound
Direct labor 10 hours per kayak @ $20 per hour
Variable manufacturing overhead $5 per direct labor hour
Fixed manufacturing overhead (includes $9,000 depreciation) $103,125 per quarter
Variable selling expenses $25 per kayak
Fixed selling and administrative expenses:
Insurance $45,000 per quarter
Sales salaries $30,000 per quarter
Depreciation $6,000 per quarter
Income tax rate 30%
Estimated income tax payments planned in 2012:
1
st
quarter $0
2
nd
quarter $50,000
3
rd
quarter $400,000
4
th
quarter $500,000
Randy’s desires to have a minimum cash balance at the end of each quarter of $50,000. In order to maintain
this minimum balance, Randy’s may borrow from its bank in $10,000 increments with an interest rate of 6%.
Money is borrowed at the beginning of the quarter in which a shortage is expected. Repayments of all or a
portion of the principle (plus accrued interest on the amount being repaid) are made at the end of any quarter
in which the cash balance exceeds the required minimum.
Requirements:
1. Use the above information to prepare the following components of th ...
BUS 409 – Student Notes(Prerequisite BUS 310)COURSE DESCR.docxhartrobert670
BUS 409 – Student Notes
(Prerequisite: BUS 310)
COURSE DESCRIPTION
Introduces and analyzes the basic concepts of compensation administration in organizations. Provides an intensive study of the wage system, methods of job evaluation, wage and salary structures, and the legal constraints on compensation programs.
INSTRUCTIONAL MATERIALS
Required Resources
Martocchio, J. J. (2013). Strategic compensation:A human resource management approach (7th ed.). Upper Saddle River, NJ: Prentice Hall / Pearson.
Supplemental Resources
Andersen, S. (2012). The keys to effective strategic account planning. Velocity, 14(1), 23-26.
Burkhauser, R. V., Schmeiser, M. D., & Weathers II, R. R. (2012). The importance of anti-discrimination and workers’ compensation laws on the provision of workplace accommodations following the onset of a disability. Industrial & Labor Relations Review, 65(1), 161-180.
Employee compensation: 12 trends for 2012. (2012). HR Specialist, 10(2), 1-2.
Survey of the Month: Companies Focus On Updating Compensation in 2012. (2011). Report on Salary Surveys, 18(12), 1-5.
The Society of Human Resources Management (2012). General format. Retrieved fromhttp://www.shrm.org
WorldatWork. (n.d.). General format. Retrieved fromhttp://www.worldatwork.org
COURSE LEARNING OUTCOMES
1. Analyze how compensation practice can be applied to positively impact an organization and its stakeholders.
2. Examine the ways in which laws, labor unions, and market factors impact companies’ compensation practices.
3. Evaluate the effectiveness of traditional bases for pay (seniority and merit) against incentive-based and person-focused compensation approaches.
4. Compare and contrast internally consistent and market-competitive compensation systems.
5. Analyze the fundamental principles of pay structure design.
6. Evaluate the role of benefits in strategic compensation.
7. Suggest viable options to current practices regarding executive compensation.
8. Make recommendations for leveraging flexible and contingent workers for any given organization.
9. Determine the best possible approach for the compensation of expatriates.
10. Analyze differences between compensation, benefits, and legal and regulatory influences in the United States and the rest of the world.
11. Use technology and information resources to research issues in compensation management.
12. Write clearly and concisely about compensation management using proper writing mechanics.
WEEKLY COURSE SCHEDULE
The standard requirement for a 4.5 credit hour course is for students to spend 13.5 hours in weekly work. This includes preparation, activities, and evaluation regardless of delivery mode.
Week
Preparation, Activities, and Evaluation
Points
1
Preparation
· Reading(s)
· Chapter 1: Strategic Compensation
· Chapter 1, Case: Competitive Strategy at Sportsman Shoes
Activities
· Introduction Discussion
· Discussions
Evaluation
· None
20
20
2
Preparation
· Reading(s)
· Chapter 2: Contextual Influe ...
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An Innovative, Open, Interoperable Citizen Engagement
Cloud Platform for Smart Government and Users’
Interaction
Diego Reforgiato Recupero1,6 & Mario Castronovo2 &
Sergio Consoli1 & Tarcisio Costanzo3 &
Aldo Gangemi1,4 & Luigi Grasso3 & Giorgia Lodi1 &
Gianluca Merendino3 & Misael Mongiovì1 &
Valentina Presutti1 & Salvatore Davide Rapisarda2 &
Salvo Rosa2 & Emanuele Spampinato5
Received: 10 November 2015 /Accepted: 20 January 2016 /
Published online: 30 January 2016
# Springer Science+Business Media New York 2016
Abstract This paper introduces an open, interoperable, and cloud-computing-based
citizen engagement platform for the management of administrative processes of public
administrations, which also increases the engagement of citizens. The citizen engage-
ment platform is the outcome of a 3-year Italian national project called PRISMA
(Interoperable cloud platforms for smart government; http://www.ponsmartcities-
prisma.it/). The aim of the project is to constitute a new model of digital ecosystem
that can support and enable new methods of interaction among public administrations,
citizens, companies, and other stakeholders surrounding cities. The platform has been
defined by the media as a flexible (enable the addition of any kind of application or
service) and open (enable access to open services) Italian Bcloud^ that allows public
administrations to access to a vast knowledge base represented as linked open data to
be reused by a stakeholder community with the aim of developing new applications
(BCloud Apps^) tailored to the specific needs of citizens. The platform has been used
by Catania and Syracuse municipalities, two of the main cities of southern Italy, located
J Knowl Econ (2016) 7:388–412
DOI 10.1007/s13132-016-0361-0
* Diego Reforgiato Recupero
[email protected]
1 National Research Council (CNR), Via Gaifami 18, 95126 Catania, Italy
2 Sielte, Via Cerza 4, 95027 San Gregorio di Catania, Italy
3 Datanet, Syracuse, Contrada Targia 58, 96100 Syracuse, Italy
4 Paris Nord University, Sorbonne Citè CNRS UMR7030, France
5 Etna Hitech, Viale Africa 31, 95129 Catania, Italy
6 Department of Mathematics and Computer Science, University of Cagliari, Cagliari, Italy
http://www.ponsmartcities-prisma.it/
http://www.ponsmartcities-prisma.it/
http://crossmark.crossref.org/dialog/?doi=10.1007/s13132-016-0361-0&domain=pdf
in the Sicilian region. The fully adoption of the platform is rapidly spreading around the
whole region (local developers have already used available application programming
interfaces (APIs) to create additional services for citizens and administrations) to such
an extent that other provinces of Sicily and Italy in general expressed their interest for
its usage. The platform is available online and, as mentioned above, is open source and
provides APIs for full exploitation.
Keywords Smartcity.Smartgovernance.Linkedopendata.Citizenengagement.Cloud
computing
Introduction
Smart governance is defined as a subset of the s.
Sustainability - The Software PerspectivePatricia Lago
This is a guest lecture for the course Software Architectures at the University of L'Aquila, Italy. It provides 3 takeaways:
(1) software can help or hinder sustainability
(2) software architecture may provide the right "big picture"
(3) decision making must be informed
Join us for an exciting session where you can explore the future of open-source technology and innovation projects based on FIWARE and supported by FIWARE team. Our experts will share their insights on how FIWARE standards and components are revolutionizing the tech industry. Attendees will have the opportunity to hear from a variety of presenters showcasing ongoing projects that leverage FIWARE. From dynamic digital twins to satellite open data for smart cities, to boosting EU high-value datasets, this session will provide a glimpse into the exciting possibilities of FIWARE technology. Don't miss out on this chance to learn about the latest innovation and collaborate with like-minded professionals!
MULTI-AGENT BASED IOT SMART WASTE MONITORING AND COLLECTION ARCHITECTUREijcseit
Solid waste management is one of the existing challenges in urban areas and it is becoming a critical issue
due to rapid increase in population. Appropriate solid waste management systems are important for
improving the environment and the well-being of residents. In this paper, an Internet of Things(IoT)
architecture for real time waste monitoring and collection has been proposed; able to improve and
optimize solid waste collection in a city. Netlogo Multi-agent platform has been used to simulate real time
monitoring and smart decisions on waste management. Waste filling level in bins and truck collection
process are abstracted to a multi-agent model and citizen are involved by paying the price for waste
collection services. Furthermore, waste level data are updated and recorded continuously and are provided
to decision algorithms to determine the vehicle optimal route for waste collection to the distributed bins in
the city. Several simulation cases executed and results validated. The presented solution gives substantial
benefits to all waste stakeholders by enabling the waste collection process to be more efficient
MULTI-AGENT BASED IOT SMART WASTE MONITORING AND COLLECTION ARCHITECTURE ijcseit
Solid waste management is one of the existing challenges in urban areas and it is becoming a critical issue due to rapid increase in population. Appropriate solid waste management systems are important for improving the environment and the well-being of residents. In this paper, an Internet of Things(IoT) architecture for real time waste monitoring and collection has been proposed; able to improve and optimize solid waste collection in a city. Netlogo Multi-agent platform has been used to simulate real time monitoring and smart decisions on waste management. Waste filling level in bins and truck collection process are abstracted to a multi-agent model and citizen are involved by paying the price for waste collection services. Furthermore, waste level data are updated and recorded continuously and are provided to decision algorithms to determine the vehicle optimal route for waste collection to the distributed bins in the city. Several simulation cases executed and results validated. The presented solution gives substantial benefits to all waste stakeholders by enabling the waste collection process to be more efficient
The internet of things is an emerging technology that is currently present in most processes and devices, allowing to improve the quality of life of people and facilitating the access to specific information and services. The main purpose of the present article is to offer a general overview of internet of things, based on the analysis of recently published work. The added value of this article lies in the analysis of the main recent publications and the diversity of applications of internet of things technology. As a result of the analysis of the current literature, internet of things technology stands out as a facilitator in business and industrial performance but above all in improving the quality of life. As a conclusion to this document, the internet of things is a technology that can overcome the challenges in terms of security, processing capacity and data mobility, as long as the development related to other technologies follows its expected course.
MOBILE APPLICATION FOR DONATION OF ITEMSvivatechijri
Development of NGO is also development of society prestige, which makes significance contribution to diverse areas. Since NGO are non-profit organization, they always lack resources. Thus, to fulfill the requirements “UNNATI SAMAJ “app will be a rescue. Using this app any donor can donate food, clothes, and other items which can be utilize by needy ones. For e.g. from big organized parties, often food gets wasted, so using the app’s Google API technology people can donate the food to nearest NGO without needed to search up for contact information. Thus, our app will be a direct bridge between all NGOs and donors.
Similar to BIG IOT AND SOCIAL NETWORKING DATA FOR SMART CITIES Alg.docx (20)
BUS M02C – Managerial Accounting SLO Assessment project .docxhartrobert670
BUS M02C – Managerial Accounting
SLO Assessment project
Randy’s Kayaks, Inc. manufactures and sells one-person fiberglass kayaks. Randy’s balance sheet at the end
of 2011 was as follows:
RANDY’S KAYAKS, INC.
Balance Sheet
December 31, 2011
ASSETS LIABILITIES
Cash $ 52,000 Accounts payable $ 131,000
Accounts receivable 1,200,000
Raw materials inventory* 120,000 STOCKHOLDERS’EQUITY
Finished goods inventory** 287,500 Common Stock 1,600,000
Plant assets, net of accumulated Retained Earnings 2,063,500
Depreciation 2,135,000
Total Assets $ 3,794,500 Total Liabilities & SE $ 3,794,500
*40,000 pounds
**1,000 kayaks
The following additional data is available for use in preparing the budget for 2012:
Cash collections (all sales are on account):
Collected in the quarter of sale 40%
Collected in the quarter after sale 60%
(Bad debts are negligible and can be ignored)
Cash disbursements for raw materials (all purchases are on account):
Cash paid in the quarter of purchase 70%
Cash paid in the quarter after purchase 30%
Desired quarterly ending Raw materials inventory 40% of next quarter’s production needs
Desired quarterly ending Finished goods inventory 10% of next quarter’s sales
Budgeted sales:
1
st
quarter 2012 10,000 kayaks
2
nd
quarter 2012 15,000 kayaks
3
rd
quarter 2012 16,000 kayaks
4
th
quarter 2012 14,000 kayaks
1
st
quarter 2013 10,000 kayaks
2
nd
quarter 2013 12,000 kayaks
Anticipated equipment purchases:
1
st
quarter 2012 $30,000
2
nd
quarter 2012 $0
3
rd
quarter 2012 $0
4
th
quarter 2012 $150,000
Quarterly dividends to be paid each quarter in 2012 $4,000
Expected sales price per unit $400
Standard cost data:
Direct materials 10 pounds per kayak @ $3 per pound
Direct labor 10 hours per kayak @ $20 per hour
Variable manufacturing overhead $5 per direct labor hour
Fixed manufacturing overhead (includes $9,000 depreciation) $103,125 per quarter
Variable selling expenses $25 per kayak
Fixed selling and administrative expenses:
Insurance $45,000 per quarter
Sales salaries $30,000 per quarter
Depreciation $6,000 per quarter
Income tax rate 30%
Estimated income tax payments planned in 2012:
1
st
quarter $0
2
nd
quarter $50,000
3
rd
quarter $400,000
4
th
quarter $500,000
Randy’s desires to have a minimum cash balance at the end of each quarter of $50,000. In order to maintain
this minimum balance, Randy’s may borrow from its bank in $10,000 increments with an interest rate of 6%.
Money is borrowed at the beginning of the quarter in which a shortage is expected. Repayments of all or a
portion of the principle (plus accrued interest on the amount being repaid) are made at the end of any quarter
in which the cash balance exceeds the required minimum.
Requirements:
1. Use the above information to prepare the following components of th ...
BUS 409 – Student Notes(Prerequisite BUS 310)COURSE DESCR.docxhartrobert670
BUS 409 – Student Notes
(Prerequisite: BUS 310)
COURSE DESCRIPTION
Introduces and analyzes the basic concepts of compensation administration in organizations. Provides an intensive study of the wage system, methods of job evaluation, wage and salary structures, and the legal constraints on compensation programs.
INSTRUCTIONAL MATERIALS
Required Resources
Martocchio, J. J. (2013). Strategic compensation:A human resource management approach (7th ed.). Upper Saddle River, NJ: Prentice Hall / Pearson.
Supplemental Resources
Andersen, S. (2012). The keys to effective strategic account planning. Velocity, 14(1), 23-26.
Burkhauser, R. V., Schmeiser, M. D., & Weathers II, R. R. (2012). The importance of anti-discrimination and workers’ compensation laws on the provision of workplace accommodations following the onset of a disability. Industrial & Labor Relations Review, 65(1), 161-180.
Employee compensation: 12 trends for 2012. (2012). HR Specialist, 10(2), 1-2.
Survey of the Month: Companies Focus On Updating Compensation in 2012. (2011). Report on Salary Surveys, 18(12), 1-5.
The Society of Human Resources Management (2012). General format. Retrieved fromhttp://www.shrm.org
WorldatWork. (n.d.). General format. Retrieved fromhttp://www.worldatwork.org
COURSE LEARNING OUTCOMES
1. Analyze how compensation practice can be applied to positively impact an organization and its stakeholders.
2. Examine the ways in which laws, labor unions, and market factors impact companies’ compensation practices.
3. Evaluate the effectiveness of traditional bases for pay (seniority and merit) against incentive-based and person-focused compensation approaches.
4. Compare and contrast internally consistent and market-competitive compensation systems.
5. Analyze the fundamental principles of pay structure design.
6. Evaluate the role of benefits in strategic compensation.
7. Suggest viable options to current practices regarding executive compensation.
8. Make recommendations for leveraging flexible and contingent workers for any given organization.
9. Determine the best possible approach for the compensation of expatriates.
10. Analyze differences between compensation, benefits, and legal and regulatory influences in the United States and the rest of the world.
11. Use technology and information resources to research issues in compensation management.
12. Write clearly and concisely about compensation management using proper writing mechanics.
WEEKLY COURSE SCHEDULE
The standard requirement for a 4.5 credit hour course is for students to spend 13.5 hours in weekly work. This includes preparation, activities, and evaluation regardless of delivery mode.
Week
Preparation, Activities, and Evaluation
Points
1
Preparation
· Reading(s)
· Chapter 1: Strategic Compensation
· Chapter 1, Case: Competitive Strategy at Sportsman Shoes
Activities
· Introduction Discussion
· Discussions
Evaluation
· None
20
20
2
Preparation
· Reading(s)
· Chapter 2: Contextual Influe ...
BUS LAW2HRM Management Discussion boardDis.docxhartrobert670
BUS LAW 2
HRM Management Discussion board
Discuss what challenges an HR department may face when their company decides to expand into other countries. Do you think it would be beneficial if the company that is expanding is already affiliated with an international union? How would it affect the challenges that HR is already faced with?
References
Noe, R. A., Hollenbeck, J. R., Gerhart, B., & Wright, P. M. (2011). Fundamentals of human resource management (4thed.). Chicago, IL: McGraw-Hill.
HRM Management Discussion board
Discuss what challenges an HR department may
face when their company decides to
expand into other countries. Do you think it would be beneficial if the company that is
expanding is already affiliated with an international union? How would it affect the
challenges that HR is already faced with
?
R
eferences
Noe, R. A., Hollenbeck, J. R., Gerhart, B., & Wright, P. M. (2011).
Fundamentals of human
resource management
(4
th
ed.). Chicago, IL: McGraw
-
Hill.
HRM Management Discussion board
Discuss what challenges an HR department may face when their company decides to
expand into other countries. Do you think it would be beneficial if the company that is
expanding is already affiliated with an international union? How would it affect the
challenges that HR is already faced with?
References
Noe, R. A., Hollenbeck, J. R., Gerhart, B., & Wright, P. M. (2011). Fundamentals of human
resource management (4
th
ed.). Chicago, IL: McGraw-Hill.
BILTRITE PRACTICE CASE
Module XV of the Biltrite audit practice case contains an audit report exercise.
This exercise may be completed at this time.
Module XV: Audit Report
The Denise Vaughan audit team completed its audit field work on February 15,
2010. A conference was held on that date involving members of the audit
firm and Biltrite management. Participants in the conference were Denise
Vaughan, partner in charge of the Biltrite engagement; Carolyn Volmar,
audit manager; Richard Derick, in-charge auditor; Trevor Lawton, Biltrite’s
CEO; Gerald Groth, Biltrite’s controller; and Marlene McAfee, Biltrite’s trea-
surer. The Biltrite representatives agreed to all of the audit adjustments and
reclassifications proposed by the audit team, and they agreed to reflect them
in the December 31, 2009, financial statements. They also agreed to modify
and/or add footnote disclosures as recommended by the audit team.
At the conclusion of the conference, the audit team obtained a client repre-
sentation letter from Biltrite management and presented management with a
copy of the “significant deficiencies” letter outlining discovered internal control
deficiencies. The original of this letter was sent to Biltrite’s audit committee.
The legal action initiated against Biltrite by Rollfast, a competitor, for
alleged patent infringement, was not yet settled as of February 15. Because the
letter obtained by Derick from Biltrite’s outside legal couns ...
BUS 571 Compensation and BenefitsCompensation Strategy Project.docxhartrobert670
BUS 571 Compensation and Benefits
Compensation Strategy Project
Techtron Corporation is a developer and manufacturer of electronic window systems for small and medium-size automobiles. It has several international customers, including Vauxhall Motors (UK) and General Motors Holden Ltd. (Port Melbourne, Australia). Techtron has recently landed a contract to produce electronic window systems for the Hyundai Sonata, manufactured in Montgomery, Alabama. They have nearly completed a manufacturing facility within the suburban perimeter of the largest city in your state, and the senior leadership and support staff are in place. The company is now ready to begin the recruiting and hiring process for production floor employees.
Here is the projected income statement for Techtron in its first year:
Revenues (from sales and all sources) $35,000,000
Manufacturing expenses:
Cost of materials (10,000,000)
Cost of manufacturing operations (2,000,000)
(includes all plant and equipment
maintenance and depreciation) (12,000,000)
Administrative Costs and Overhead
Administrative Overhead and Expense (1,000,000)
Research and Development (1,000,000)
Employee Expenses (10,500,000)
(target is 30% of sales over time) (12,500,000)
Capital Budget
Capital purchases (2,000,000)
Loans payable (4,000,000)
(for the first seven years, then
dependent on plant expansion) (6,000,000)
___________
Projected Pretax income for the first year of startup 4,500,000
Depending on tax policy of state and federal governments,
net income may be used for additional research and development,
capital purchases, reduction of debt, dividends, and/or retained earnings.
The company projects that sales for years 2-6 will increase by 2%, 4%. -3%, 3%, and 4%.
The company projects that materials and overhead costs will rise by approximately the current rate of inflation (about 2.4%) for years 2-6.
Techtron will require approximately 140 hourly production technicians, 3 production supervisors, 2 manufacturing engineers, 1 process engineer, and 1 computer technician for their floor operations. Minimum qualifications and job descriptions for these jobs are as follows:
Hourly production technicians: Responsible for production and assembly of electronic window system components and subassemblies. Responsible for quality control of manufactured products. Minimal educational requirement is an associate’s degree in business or manufacturing technology; applicants must have general mathematics skills and be able to interpret control charts and basic computer output. Prior experience valued but not required.
Production supervisor: Responsible for supervision of manufacturing processes, including troubleshooting problems and interfacing between production technicians and other company functions such as HR, Information Systems, etc. Minimal educational requirement is a BA degree in industrial management or quality managemen ...
BUS 210 Exam Instructions.Please read the exam carefully and a.docxhartrobert670
BUS 210 Exam Instructions.
Please read the exam carefully and answer all of the questions.
When considering the legal issues, structure your answers as follows:
1. State the relevant issue;
2. Make the arguments of the parties involved;
3. State the applicable rule of law;
4. State your conclusion and the reasons therefore.
You may consult the text to answer the exam questions. However, your answers MUST be your own work and you may not consult with anyone in or outside of the class.
BUS 210
Be specific in your answers and state the applicable law used to reach your conclusions.
Question #1
Mike is a homeowner. Jill runs a snowplowing business. Mike asks Jill to provide an estimate for how much she would charge to snowplow Mike’s driveway. After Jill inspects Mike’s driveway, the parties have the following conversation on September 1, 2011:
Jill: “$50 each time I snowplow your driveway.”
Mike: “OK, sounds good. Please do so.”
Jill regularly snowplows Joe’s driveway during the 2011-12 season. In May 2012, Jill sends a bill to Mike for all visits she made in the 2011-12 season, and Mike promptly pays that bill in full without any other communication taking place between Jill and Mike.
• Jill regularly snowplows Mike’s driveway during the 2012-13 season and sends a bill for those visits in March 2013. What are the rights and responsibilities of the parties under contract law?
• Instead, assume that Jill does not come during the first major snowfall in 2012. Does Mike have any contractual rights against JILL? Explain fully.
• Ignore the previous bullets. Instead, assume Mike promptly pays the 2011-12 bill in full without any other communication. On September 1, 2012, Jill raises her prices 20% for all of her customers, and she notifies Mike of this fact. He does not respond. Jill regularly snowplows Mike’s driveway during the 2012-13 season and in March 2013 sends Mike a bill for those visits reflecting her increased prices. What are the right and responsibilities of the parties under contract law.
Question #2:
At the wedding of Tom and Mary, Tom’s father, Frank, told them that he wanted to live with them and to have them care for him for the rest of his life. He said, “If you agree to do this, I will deliver to you, within two years, a deed to my home.” Tom and Mary told Frank they accepted his offer and promised to look after Frank with loving care in Frank’s home. They immediately moved in with him.
Soon after moving into Frank’s home, Tom and Mary used their own money to add a new wing to the house, pay the outstanding property taxes, and pay off an existing mortgage of $25,000.
One year after Tom and Mary moved into the home, Tom reminded Frank of his promise to convey the property to them. Frank became angry, and refused to execute the deed and ordered Tom and Mary to leave the premises.
Answer the following questions by arguing both sides of the issues and applying ...
BUS 137S Special Topics in Marketing (Services Marketing)Miwa Y..docxhartrobert670
BUS 137S Special Topics in Marketing (Services Marketing)
Miwa Y. Merz, Ph.D.
Service Journal Entry Form
Your Name:
Name of Firm: T-Mobile
Type of Service (industry): Phone Company
Date of Encounter: September 27, 2015
Time of Encounter: 4PM
1. How did the encounter take place (e.g., in person, by phone, via a self-service technology)?
In person
2. What specific circumstances led to this encounter?
My girlfriend bought a new phone and she wanted to put a screen protector
3. Exactly what did the firm/employee say or do?
The employee directly showed us the different type of screen protector. He also explained in detailed about the advantage and disadvantage for each of the screen protector.
4. How would you rate your level of satisfaction with this encounter? (Circle the most appropriate number).
Very dissatisfied
1
2
3
4
5
6
7
Very satisfied
5. What exactly made you feel this way?
I was so surprised that the employee still remembered my girlfriend and I. A week ago we went to the T-Mobile to ask about the IPhone 6s.
6. What could the employee/firm have done to increase your level of satisfaction with the encounter?
Nothing because I am completely satisfied with their service
7. What improvements need to be made to this service system?
I don’t think they need to improve anything because the employees always ask the customer if they need help or not as soon as they saw the customers.
8. How likely is it that you will go back to this service firm?
Very Unlikely
1
2
3
4
5
6
7
Very Likely
Please provide the reason(s). I will definitely go back because the employees are so kind, patient and really helpful.
Service Journal Entry Form
Your Name:
Name of Firm: 99 Chickens
Type of Service (industry): Restaurant
Date of Encounter: September 19, 2015
Time of Encounter: 5 PM
1. How did the encounter take place (e.g., in person, by phone, via a self-service technology)?
In person
2. What specific circumstances led to this encounter?
We wanted to eat the chicken
3. Exactly what did the firm/employee say or do?
They didn’t say a single word. They just took our order and then directly leave.
4. How would you rate your level of satisfaction with this encounter? (Circle the most appropriate number).
Very dissatisfied
1
2
3
4
5
6
7
Very satisfied
5. What exactly made you feel this way?
Because the employee did not talk at all
6. What could the employee/firm have done to increase your level of satisfaction with the encounter?
They should treat the customer better. The service is seriously so bad. I feel that they are actually really rude.
7. What improvements need to be made to this service system?
Actually the service system is not bad because it is a self-service restaurant. But I think the company should tell the employees to have more interaction with the customers to make a good and friendly impression.
8. How likely is it that you will go back to this service firm?
Very Unlikely
1
2
3
4
5
6
7
Ver ...
BUS 313 – Student NotesCOURSE DESCRIPTIONThis course intro.docxhartrobert670
BUS 313 – Student Notes
COURSE DESCRIPTION
This course introduces the students to the key components of entrepreneurship. Topics covered include identifying new venture opportunities, getting started in a new venture, creating a business plan, financing and marketing ideas, and organizing and managing a small business.
INSTRUCTIONAL MATERIALS
Required Resources
Kaplan, J. M., & Warren, A. C. (2013). Patterns of entrepreneurship management (4th ed.). Danvers, MA: John Wiley & Sons.
Supplemental Resources
Fast Company. (2013). General format. Retrieved from www.fastcompany.com
Hess, E. D. (2012). Grow to greatness: Smart growth for entrepreneurial businesses. Stanford, CA: Stanford University Press.
Inc. Magazine. (2013).General format. Retrieved from www.inc.com
Schweikart, L. & Pierson, D. L. (2010). American entrepreneur: The fascinating stories of the people who
defined business in the United States. New York, NY: American Management Association.
Stanford Graduate School of Business. (2013). Center for Entrepreneurial Studies. Retrieved from http://www.gsb.stanford.edu/ces/resources/links.html
COURSE LEARNING OUTCOMES
1. Examine entrepreneurship and different types of entrepreneurs.
2. Analyze the stages in the entrepreneurial process.
3. Examine the process of innovating and developing ideas and business opportunities.
4. Analyze different innovative business models to determine the best model for a specific venture.
5. Analyze the market, customers, and competition of entrepreneurs.
6. Examine the process of developing a business plan and setting up the company.
7. Analyze money sources for finding and managing funds.
8. Compare the different forms of intellectual property and how they differ.
9. Analyze the management of a successful innovative company.
10. Determine the most effective communication process to present the business to investors.
11. Analyze methods for exiting the venture.
12. Use technology and information resources to research issues in entrepreneurship.
13. Write clearly and concisely about entrepreneurship using proper writing mechanics.
WEEKLY COURSE SCHEDULE
The standard requirement for a 4.5 credit hour course is for students to spend 13.5 hours in weekly work. This includes preparation, activities, and evaluation regardless of delivery mode.
Week
Preparation, Activities, and Evaluation
Points
1
Preparation
· Reading(s)
· Chapter 1: Getting Started as an Entrepreneur
· Chapter 2: The Art of Innovation
Activities
· Introduction Discussion
· Discussions
Evaluation
· None
20
20
2
Preparation
· Reading(s)
· Chapter 3: Designing Business Models
· e-Activities
· Go to Minority Business Entrepreneur (MBE) Website and explore the organization’s offerings, located at http://www.mbemag.com/. Then, go to the MBE Business Resource Directory, located at http://www.mbemag.com/index.php/resources/mwbe-resource-directory, and consider two to three businesses that would be good partners for one another. Be ...
BUS 1 Mini Exam – Chapters 05 – 10 40 Points S.docxhartrobert670
BUS 1
Mini Exam – Chapters 05 – 10
40 Points
Short Answer – Mind your time
Answer four questions from #1 - #6. Must answer #3 and #6. Answer
the XC question for extra credit. Question point count weighted equally.
It is all about business, so make sure to demonstrate / synthesize the bigger picture of business in each and
every answer.
Like all essays, specifying an exacting target word count is rather problematic. I am thinking each answer
would be about 250 - 300 words each, depending upon writing style. If you tend to be descriptive and whatnot,
that number could be 350 - 450 words.
Sidebar: Gauge your knowledge level in this way. This exam should take about 90 – 120 minutes to complete.
Students taking much longer may want to work with me to assess / discuss ways to help master this material in
a future conference session.
1. Although most new firms start out as sole proprietorships, few large firms are organized this way. Why
is the sole proprietorship such a popular form of ownership for new firms? What features of the sole
proprietorship make it unattractive to growing firms?
2. List and discuss at least three causes of small business failure. Workarounds, fixes, or methods to avoid
failure should be discussed.
3. Describe three different leadership styles and give an example of a situation in which each style could be
most used effectively.
4. Discuss Max Weber's views on organization theory. Is there a few principles that particularly resonate
in business today?
5. How has the emphasis of quality control changed in recent years? Describe some of the modern quality
control techniques that illustrate this change in emphasis.
6. Explain how managers could motivate employees by using the principles outlined in expectancy
theory? Create a story/example of expectancy theory at work, incorporating the three questions that
according to expectancy theory employees will ask.
7. XC – What is selective perception? Can you describe a business-centric scenario where selective
perception may hinder a businessperson’s ability to respond to a customer need?
I
Fireworks, Manifesto, 1974.
The Architectural Paradox
1. Most people concerned with architecture feel some sort
of disillusion and dismay. None of the early utopian ideals
of the twentieth century has materialized! none of its social
aims has succeeded. Blurred by reality! the ideals have turned
into redevelopment nightmares and the aims into bureau
cratic policies. The split between social reality and utopian
dream has been total! the gap between economic constraints
and the illusion of all-solving technique absolute. Pointed
Space
out by critics who knew the limits of architectural remedies,
this historical split has now been bypassed by attempts to
reformulate the concepts of architecture. In the process, a
new split appears. More complex, it is not the symptom of
prof ...
BullyingIntroductionBullying is defined as any for.docxhartrobert670
Bullying
IntroductionBullying is defined as any form of severe physical or psychological consequences.Bullying has been identified as a social issue in schools, homes and communities.Bullying can lead to both short term and long negative side effects.
Bullying is defined as any form of severe physical or pervasive act that includes communication in writing, electronically that is aimed at a student, or a group of student and it could have the following effects on the target. Bullying has been identified as a social issue in schools, homes and communities. Bullying can lead to both short term and long negative side effects. Many people tend to develop psychological problems as a result of engaging in bullying activities. Adopting effective measures to prevent bullying would also help to deal with the problem once and for all.
*
Forms of BullyingMere teasing.Talking trash about other peopleTrading insults.Physical harassment
The following actions have been identified as physical conduct forms that demonstrate forms of bullying. They include; Mere teasing.
Talking trash about other people. This shows an example of bullying that is practiced by people. Trading insults has also been widely recognised as a form of bullying. Physical harassment
*
Effects of BullyingBullying can lead to both long term and short term side effects.Bullying can change personalities, psychological wellbeing and even lead to physical injuries.Negatively affecting the students’ mental or physical health
Bullying has serious negative consequences for the people who do practice it. Bullying can lead to both long term and short term side effects.
Bullying can change personalities, psychological wellbeing and even lead to physical injuries. People who have been bullied tend to development long term problems such as depression. Development of stress tends to happen once people have engaged in actions that lead to bullying. This is because the actions against bullying tend to overpower the minds and also brings in psychological problems,.
*
A graphic showing No to Bullying
All forms of bullying are not acceptable in the society.
*
How to Prevent BullyingTaking immediate action.Dealing with bullies physically.Criminalizing actions against bullying.
In order to deal with bullying effectively, several measures should be enacted to prevent any form of bullying. Measures such as taking immediate action upon any case of bullying would help to deter the action from ever arising again. The other solutions entail taking immediate forms of action would also help to prevent the act from ever occurring. Dealing with bullies physically and also criminalizing actions against bullying helps to prevent it at all costs. Social and emotional learning is a bullying prevention mechanism aimed at ensuring that students do not fall victim to bullying by equipping them with social and emotional skills. This technique is aimed at ensuring that students are equipp ...
BUS1001 - Integrated Business PerspectivesCourse SyllabusSch.docxhartrobert670
BUS1001 - Integrated Business Perspectives
Course Syllabus
School of Professional Studies
BUS1001- Integrated Business Perspectives
Note to Instructors: Items highlighted in yellow apply to on ground courses, those in blue apply to online courses, and those in green apply to blended courses. Please select the appropriate sections for your course (eliminate the highlighting), and delete the other sections. Items highlighted in magenta must be completed prior to publishing the syllabus. Items highlighted in grey are for your information only and should be removed before publishing the syllabus.
*All activities listed in the syllabus must be administered in order to meet the credit requirements for this course
Contents
Overview4
Course ID4
Course Name4
Department4
Credits4
Prerequisites4
Instructor4
Telephone4
E-mail4
Office4
Office Hours4
Class Meetings4
Classroom4
Learning Management System4
Course Description4
College Information5
Centenary Greater Expectation Learning Outcomes (CGEs)5
Business Department Learning Outcomes5
Classroom Conduct5
Academic Code6
Academic Honesty6
“Publication” of Written Work and Assignments6
Academic Assistance7
Accommodations7
Technical Support7
Course Information7
Course Material7
Reference Websites7
Instructional Techniques7
Course Objectives7
Student Evaluation7
Attendance9
Participation9
Assignments10
Late Assignments10
Course Schedule11
Session 111
Session 211
Session 311
Session 412
Session 512
Session 613
Session 713
Session 813
Activities and Rubrics15
Threaded Discussion Requirements15
Threaded Discussion Rubric15
Project and Teamwork Exercise16
Project and Teamwork Exercise Rubric16
Web Assignment17
Web Assignment Rubric17
Case Study Exercise18
Case Study Rubric18
Part Ending Project19
Part Ending Project Rubric19
Launching Your Career20
Launching Your Career Rubric20
Activities Calendar21
Overview
Course ID:BUS1001Course Name:Integrated Business PerspectivesDepartment:
Business - UndergraduateCredits:
4 CreditsPrerequisites:
None
Studentsshould be competent in Microsoft WordInstructor:
Jane ZhaoE-mail:
[email protected]Class Meetings:
Thursday 6:00 pm from January 14th to March 3rd Classroom:
TBALearning Management System:
Access the Moodle student tutorial at: http://www.centenarycollege.edu/cms/en/moodle-help-center/moodle-help-center/students/ for instructions on how to log in, navigate, and submit assignments.
Moodle accessibility versions are available for download; please contact the IT Help Desk at ext. 2362 or [email protected] for assistance.Course Description:
This Business course provides the student with the opportunity to discover the role of business in society and to explore career opportunities. The relations among different business disciplines are analyzed. Students learn team building and communication and apply that learning as they work in teams to create, implement, and assess projects.
College InformationCentenary Greater Expectation Learning Outcomes (CGEs):
In ...
BUMP implementation in Java.docxThe project is to implemen.docxhartrobert670
BUMP implementation in Java.docx
The project is to implement the BUMP client in java, with window size 1. Here is an overview of the three WUMP protocols (BUMP, HUMP, and CHUMP). Here are the files wumppkt.java, containing the packet format classes, and wclient.java, which contains an outline of the actual program. Only the latter file should be modified; you should not have to make changes to wumppkt.java.
What you are to do is the following, by modifying and extending the wclient.java outline file:
· Implement the basic transfer
· Add all appropriate packet sanity checks: timeouts, host/port, size, opcode, and block number
· Generate output. The transferred file is to be written to System.out. A status message about every packet (listing size and block number) is to be written to System.err. Do not confuse these!
· Terminate after a packet of size less than 512 is received
· Implement an appropriate "dallying" strategy
· send an ERROR packet if it receives a packet from the wrong port. The appropriate ERRCODE in this case is EBADPORT.
An outline of the program main loop is attached
recommended that you implement this in phases, as follows.
1. Latch on to the new port: save the port number from Data[1], and make sure all ACKs get sent to this port. This will mean that the transfer completes. You should also make sure the client stops when a packet with less than 512 bytes of data is received. Unless you properly record the source port for Data[1], you have no place to which to send ACK[1]!
2. For each data packet received, write the data to System.out. All status messages should go to System.err, so the two data streams are separate if stdout is redirected. To write to System.out, use System.out.write:
System.out.write(byte[] buf, int offset, int length);
For your program, offset will be 0, buf will typically be dpacket.data(), where dpacket is of type DATA (wumppkt.DATA). The length will be dpacket.size() - wumppkt.DHEADERSIZE (or, equivalently, dg.getLength() - wumppkt.DHEADERSIZE, where dg is a DatagramPacket object).
3. Add sanity checks, for (in order) host/port, packet size, opcode, and block number.
4. Handle timeouts, by retransmitting the most recently sent packet when the elapsed time exceeds a certain amount (4 seconds?). One way to do this is to keep a DatagramPacket variable LastSent, which can either be reqDG or ackDG, and just resend LastSent. Note that the response to an InterruptedIOException, a "true" timeout, will simply be to continue the loop again.
5. Add support for an dallying and error packets. After the client has received the file, dallying means to wait 2.0 - 3.0 timeout intervals (or more) to see if the final data packet is retransmitted. If it is, it means that the final ACK was lost. The dally period gives the client an opportunity to resend the final ACK. Error packets are to be sent to any sender of an apparent data packet that comes from the wrong port.
vanilla Normal transfer
lose Lose ever ...
BUS 303 Graduate School and Further Education PlanningRead and w.docxhartrobert670
BUS 303 Graduate School and Further Education Planning
Read and watch pieces on Planning for Graduate School. Answer related questions and write an essay.
· Read about earning a Master’s Degree.
· https://www.gradschools.com/masters/business
· Choose and read about two Master’s degree programs from the left hand column of Subject Selection options (image below) found on the webpage https://www.gradschools.com/masters/business
1-Report - List two subject that you selected to read/research:
One: ____________________
Two: _____________________
2-Discover:
Conduct research on two Master’s degree programs related to your undergraduate major that are offered by Virginia, DC, or Maryland Universities. Choose programs at two separate universities. If you are interested in other universities outside of this area, please feel free to research them as alternatives.
Discover information such as: What are the application processes, preferred GPA, required entrance exams, or prerequisites. What are the options for study (full time study, part time study, face-to-face classes or online classes)? What is the typical timeframe for completing the graduate program? What are the typical career opportunities for graduates from the Master’s program?
Section One- First - University and Graduate Program:
List the university and graduate program that you researched. Answer the research questions with words, phrases, or sentences.
· University and graduate program that you researched
(Enter information here)
· What are the application processes, preferred GPA, required entrance exams, or prerequisites?
· What are the options for study (full time study, part time study, face-to-face classes or online classes)?
· What is the typical timeframe for completing the graduate program?
· What are the typical career opportunities for graduates from the Master’s program?
Section Two: Second - University and Graduate Program
List the university and graduate program that you researched. Answer the research questions with words, phrases, or sentences.
· University and graduate program that you researched
· What are the application processes, preferred GPA, required entrance exams, or prerequisites?
· What are the options for study (full time study, part time study, face-to-face classes or online classes)?
· What is the typical timeframe for completing the graduate program?
· What are the typical career opportunities for graduates from the Master’s program?
3-Write:
Questions to answer in an essay with at least 400 words. The expectation is that the essay in made up of flowing sentences that are organized in to paragraphs. WORD formatted document is required.
· What did you learn about Master’s degree programs and earning a Master’s degree? If you have researched graduate programs in the past, what are the most important aspects of information that you learned about graduate education opportunities?
(At least one paragraph)
· List and discu ...
Bulletin Board Submission 10 Points. Due by Monday at 900 a.m..docxhartrobert670
Bulletin Board Submission: 10 Points. Due by Monday at 9:00 a.m.
As you've learned, it is important to be able to determine the elements of a crime and there are several places to turn for assistance in doing so.
First - Look at the statute for the crime. For example, in New York, the statute for Petit Larceny is Penal Law 155.25.
Second - Check to see if any of the terms in the statute are defined in another statute. For example, in New York, Larceny is defined in Penal Law 155.05
Third - If the elements are not clear from the statute, you may want to research case law to see if the courts have established the elements for the crime.
Fourth - Always remember to check the Jury Instructions.
They are an excellent source for identifying the elements, as this is how the court explains the crime to the jury.
Many states are now posting their Jury Instructions on the internet.
Section One –
Keeping the above in mind, please provide the statute under which a Defendant in your state would be charged with Rape (1st Degree if your state breaks it down in that manner) In addition, provide any relevant statutory definitions and an overview of the Jury Instructions. Then, provide cases addressing at least one of the elements of the statute.
Section Two –
Discuss whether or not a woman can be charged with Rape in your state. If not, what could she be charged with?
...
BUS 371Fall 2014Final Exam – Essay65 pointsDue Monda.docxhartrobert670
BUS 371
Fall 2014
Final Exam – Essay
65 points
Due: Monday, December 9 at 11:59 p.m. EST (Blackboard submission)
Directions:
Part One (this part) of your final exam is to be just that – yours! I expect you will work independently of your classmates to complete the exam.
As always in BUS 371, your grade will be affected by the quality of your writing – clarity, spelling, grammar, syntax, etc.
1. How has this course changed your view and/or understanding of management and its role in contemporary organizations? In your answer, compare your understanding/perception of management at the beginning of the class with your current understanding/perception. Be specific and honest. (10 points)
2. Would you describe your experience with your class team in BUS 371 as better than most of your experiences with previous class teams, about the same as most of your experiences with previous class teams, or worse than most of your experiences with previous class teams? Be specific and explain what happened with your team for you to form your impression. (10 points)
Depending on your answer to question 2, you will answer EITHER question 3 or question 4.
3. If your experience with your class team was better than most of your experiences with previous class teams, what do you think contributed to the positive experience? From what you’ve learned in BUS 371 this semester, what can you do, as an individual student, in future class (and workplace) teams to contribute to their success? Be specific in your answer. (If your experience with your class team in BUS 371 this semester was about the same or worse than your previous experiences with class teams, skip this question and answer question 4.) Be specific in your answer, referring to course material as appropriate. (10 points)
4. If your experience with your class team was about the same or worse than your experiences with previous class teams, what can you do, as an individual student, in future class (and workplace) teams to increase their success? Be specific in your answer, referring to course material as appropriate. (10 points)
5. What do you consider to be your most important “take aways” from this course? In other words, what concepts and/or ideas have you found most interesting? What elements of the course do think will be most likely to be useful to you when you become a manager?
NOTE: Be sure to include both what you’ve found most interesting and most likely to be useful from the course. (10 points)
6. Define, compare and contrast content, process and reinforcement theories of motivation, giving and explaining an example of each. How could a manager apply each of the theories in the workplace? Your answer should be specific and clearly demonstrate your understanding of these motivation theories and their application. (25 points)
feedback for group work:
Business 371 - Fall 2014
Individual Assignment Five
Peer Assessment – Round Two
Due: Friday, December 5 (submitted i ...
BUS 305 SOLUTIONS TOPRACTICE PROBLEMS EXAM 21) B2) B3.docxhartrobert670
BUS 305: SOLUTIONS TO
PRACTICE PROBLEMS EXAM 2
1) B
2) B
3) No, fan pattern (heteroscedasticity)
4) No, nonlinear relationship between X and Y
5) The black line is the regression line because it get closest to the sample points (minimizes error between the points and the line). The red line has a larger error; that is, larger total distance from points to the line.
6) Because it is reasonable to suppose that costs are dependent on production volume (since units are produced, directly resulting in costs), then regression is more appropriate for this data since regression is appropriate when an cause-and-effect relationship is assumed.
7) C
8) a) r = 0.8;
b) T = 1.31;
c) p = 0.117
d) There is no evidence of a significant correlation between X and Y in the population because we did not reject the null of H0: = 0.
9) Note: the following are not complete answers to Question 11; they are just enough for you to know whether your short answer addressed the correct things.
a) 1 = population slope, b1 = sample slope. On exam, would also want to address what you know (or don’t know) about each of these and how each is found.
b) An outlier can “drag” the regression line toward it. On the exam, also think about how this would affect the quality of your regression model and the predictions.
10) Yes, there appears to be a straight line relationship between the variables. Linear regression appears to be appropriate. The regression output is:
11) a) T = -0.09, p = 0.929, do not reject Ho, conclude there is no evidence of a relationship
b) R2 = 0.002 = 0.2%, No because value is very close to zero
c) Correlation = r = -0.0421. No, there is not a strong relationship between these variables. The correlation is nearly 0.
d) Regression line is Y^ = 1.26 – 0.035X.
Y^ = 1.26 – 0.035(100) = 1.26 – 3.5 = -2.24. No this does not make sense because you cannot have a negative number of near misses. It is not wise to predict with this model. The R-squared value is extremely low (essentially 0%), which means that there is no relationship at all between near misses and flights in this data. Therefore, predicting misses from flights is meaningless.
e) b1 = -0.035. As Number of flights increases by 1, we expect number of near misses to go down by 0.035. Or, put another way, as flights increases by 1000, we expect number of near misses to go down by 35. No, this does not make sense. We would assume that as flights increase, so would near misses.
12) a. Multiple regression is a direct extension of simple regression, except that now we have more than one independent (X) variable.
b. Note: the following is not a complete answer; it is just enough for you to know whether your short answer addressed the correct things: Multicollinearity is when the independent variables are highly correlated with one another. On the exam, also indicate how this affects the model, how one can identify if it is present, and what can be done to correct it.
c. Dummy variables are us ...
Burgerville- Motivation Goals.
Peer-reviewed articles.
Here are some articles I found:
1) Employees Motivation in Organizations: An integrative literature
Review:
http://www.ipedr.com/vol10/106-
S10089.pdf
2) Impact of Employees Motivation on Organizational
Effectiveness:
http://iiste.org/Journals/index.php/EJBM/article/viewFile/265/150
3) Shareholders win when employees are motivated:
http://www.forbes.com/2009/08/23/employee-motivation-stocks-intelligent-investing-returns.html
1. THE THEORY OF PURPOSEFUL- WORK BEHAVIOR: THE ROLE OF PERSONALITY, HIGHER-ORDER GOALS, AND JOB CHARACTERISTICS
http://web.a.ebscohost.com/ehost/pdfviewer/pdfviewer?sid=fa02d089-2c07-4af2-8637-23192c8c3b1f%40sessionmgr4004&vid=14&hid=4209
0. Relative Importance and Utilityof Positive Worker States: A Reviewand Empirical Examination
http://web.a.ebscohost.com/ehost/pdfviewer/pdfviewer?sid=fa02d089-2c07-4af2-8637-23192c8c3b1f%40sessionmgr4004&vid=27&hid=4209
Cam Sommer
1. http://psycnet.apa.org/journals/apl/72/4/658/
Comparative analysis of goal setting theories across cultures
0. http://amj.aom.org/content/29/2/305.short
Effects of Team building and goal setting on productivity: A field Experiment
The first employee’s interview
Mr. Kay Nguyen is working at Burgerville for over 2 years. He said that working at Burgerville is only temporary while attending school. The hour he works is outside of his school time, so it helps pay for tuition. The work is very busy during high traffic hours, especially at the drive-through during dinnertime. His main responsibility is handling cashier, but he often help others where needed. He starts pay at minimum wages.
His supervisor encourages employees from time to time, but the wage is very low for employee to stay. He explains that turnover at Burgerville is below average compare to other place he has worked before.
Goal Setting:
What did you learn from this job? How does it impact your future? I encounter customers every day, I learn a lot about customer service in person. He dealt with all type of customers. He learned about servicing and created a friendly environment for customers
While studying and working, his self-motivation can encourage his learning and success, whatever be the scenario. He won’t stop staying here as a cashier. He will keep pushing himself to reach his goal setting
What are your obstacles? How do you deal with it? The most frustrate situation he endures during his tenure at Burgerville is the irresponsibility of other employees. They sometime either do not show up for work or call in. This creates a lot of pressure at work, as he has to cover for their shift. He usually has to stay extra hours to clean up and cover for other shifts.
Does BurgerVille create rewards or something to motivate its employee? Does it make you feel happy or comfortable when working there? Mr. Nguyen’s supervisor usually awards his employees with movie tickets for their performances. Also, they are a ...
Bullying Bullying in Schools PaperName.docxhartrobert670
Bullying
Bullying in Schools Paper
Name
Class
Date
Professor
Bullying in Schools Paper
Bullying is mean spirited and unwanted intimidation by another student. Bullying can come in many different forms but the result is an imbalance of power where one student suffers physical and verbal attacks as well as social exclusion. The bully repeatedly focuses in on their victims and subjects them to continued harassment and false rumors. Bullying causes the victims extreme emotional damage and lifelong pain but occurs most commonly in the school setting. In order to ensure that bullying is prevented the educational system will need to become more proactive and create programs and services designed to educate, reduce, deter and punish bullying.
Types and Extent of Bullying
The three types of bullying experienced by the youthful victim in the school setting consist of verbal and physical assaults as well as social exclusions. The types of verbal threats the victims of bullying suffer are name calling, false gossip, lewd sexual comments, taunts, and threats to cause harm. Physical assaults include hitting, kicking, pushing, tripping, pinching, and spitting on the victim. Social exclusions includes the bully taking steps to isolate the victim from peers by leaving them out of social events or gatherings and talking rudely about them to other peers. Other students will fear the bully and go along with their mean spirited actions. The victim will be isolated and the bully will take steps to embarrass the student in front of other peers. The bully will spread malicious rumors and make rude comments to the victim.
Adolescents are extremely sensitive to rejection and the opinions of peers, both of which can serve as catalysts for revenge (Booth, 2011). The result is the bullying becomes escalated and the victim takes revenge on the bully or physical altercations occur. Bullying is a major problem in society. While bullying occurs most in the school setting there are other places where bullying occurs. Bullies target victims using social networks and will bully them at social events. Victims of bullies are harassed and attacked on school buses and on school playgrounds as well as in the victim’s neighborhood. While bullying can happen anywhere it is most prevalent in schools making it the responsibility of educational systems to take steps to see it stopped.
In 2001 in a report conducted by the Bureau of Juvenile Justice Statistics it was discovered that 20% of all students will be bullied while in high school while the number creeps up to almost 30% when dealing with school children from second to sixth grade (DeVoe, 2009). This comes to one in seven students from kindergarten to twelfth grade being victims of bullying. Over half of the students surveyed have been witness to bullying in the school setting and over 70% find bullying is a real issue in their school as well as the report found girls where far more ...
Building Design and Construction FIRE 1102 – Principle.docxhartrobert670
Building Design and
Construction
FIRE 1102 – Principles of Fire Science
Reference: Chapter 4 of Cote, Fundamentals of Fire Protection
UAE Tamweel Tower
Objectives of Fire-Safe Building Design
1. Life Safety
2. Property Protection
3. Continuity of Operations
4. Environmental Protection
5. Historical Preservation
Life Safety
• Achieved by early warning of a fire, extinguishment
of a fire, proper egress for prompt escape
• Can the occupants get out before the room becomes
untenable?
– We know that flashover is a time when the room
is untenable,
– However there may be a time before flashover
where a room is untenable where concentration
of fire gases (CO) can create such a situation.
• We can do modeling of how long it takes for
occupants to evacuate out of a building and predict
when a room becomes untenable.
• Human Behavior Research
Fire Modeling of Station Night Club Fire
Human Behavior Research
Property Protection
• Materials that can be replaced which have a dollar
value assigned to them.
• Billions of dollars are lost due to fires each year.
• Achieved by installing proper fire extinguishing
systems, compartmentation features to limit spread
and construction of building materials.
Heritage Preservation
• Irreplaceable items and artifacts.
• Accomplished using appropriate fire
extinguishing systems.
Mona Lisa Original Copy of
Declaration of
Independence
Hand Written Quran
National Museum of Saudi Arabia
Continuity of Operations
• Getting back to business
• Accomplished by installation of proper fire
extinguishing systems
Environmental Preservation
• Protecting our environment from fire and/or
fire extinguishing agent.
• Installation of fire extinguishing systems that
limit fire size, minimize run-off from water,
using agents that do not adversely affect the
ozone layer.
Types of Building Construction
• NonCombustible Construction
– Type I
– Type II
• Combustible Construction
• Type III
• Type IV
• Type V
Type I Construction
Non-combustible
• Fire Resistive
• Constructed of concrete
and protected steel
• Columns and beams are
covered with fire resistive
spray on material.
• Primary hazard are the
contents in the structure.
• High-rise office buildings,
shopping centers
Type II Construction
Non-combustible
• Non-Combustible
• Lower degree of fire resistance than
Type I.
• Fire resistant rating on all exterior
and interior load bearing walls.
• May have combustible non-
loadbearing partition walls.
• Columns and beams are not
protected and will be exposed
during a fire.
• Office buildings, warehouses,
automobile repair shops.
Type III Construction
Combustible
• Ordinary Construction
• Office buildings, retail stores, mixed
occupancies with store on first
floor and dwelling on second floor.
• Exterior walls of the building have
2-hr fire resistance rating and non-
com ...
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Delivering Micro-Credentials in Technical and Vocational Education and TrainingAG2 Design
Explore how micro-credentials are transforming Technical and Vocational Education and Training (TVET) with this comprehensive slide deck. Discover what micro-credentials are, their importance in TVET, the advantages they offer, and the insights from industry experts. Additionally, learn about the top software applications available for creating and managing micro-credentials. This presentation also includes valuable resources and a discussion on the future of these specialised certifications.
For more detailed information on delivering micro-credentials in TVET, visit this https://tvettrainer.com/delivering-micro-credentials-in-tvet/
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
BIG IOT AND SOCIAL NETWORKING DATA FOR SMART CITIES Alg.docx
1. BIG IOT AND SOCIAL NETWORKING DATA FOR SMART
CITIES:
Algorithmic improvements on Big Data Analysis in the context
of RADICAL city
applications
Evangelos Psomakelis12,Fotis Aisopos1, Antonios Litke1,
Konstantinos Tserpes21, Magdalini
Kardara1 and Pablo Martínez Campo3
1Distributed Knowledge and Media Systems Group, National
Technical University of Athens, Zografou Campus, Athens,
Greece
2Informatics and Telematics Dept, Harokopio University of
Athens, Greece
3Communications Engineering department, University of
Cantabria, Santander, Spain
{fotais, litke, nkardara, tserpes,
vpsomak}@mail.ntua.gr,[email protected]
Keywords: Internet of Things, Social Networking, Big Data
Aggregation and Analysis, Smart City applications,
Sentiment Analysis, Machine Learning
Abstract: In this paper we present a SOA (Service Oriented
Architecture)-based platform, enabling the retrieval and
2. analysis of big datasets stemming from social networking (SN)
sites and Internet of Things (IoT) devices,
collected by smart city applications and socially-aware data
aggregation services. A large set of city
applications in the areas of Participating Urbanism, Augmented
Reality and Sound-Mapping throughout
participating cities is being applied, resulting into produced sets
of millions of user-generated events and
online SN reports fed into the RADICAL platform. Moreover,
we study the application of data analytics such
as sentiment analysis to the combined IoT and SN data saved
into an SQL database, further investigating
algorithmic and configurations to minimize delays in dataset
processing and results retrieval.
1 INTRODUCTION
Modern cities are increasingly turning towards
ICT technology for confronting pressures associated
with demographic changes, urbanization, climate
change (Romero Lankao, 2008) and globalization.
Therefore, most cities have undertaken significant
investments during the last decade in ICT
infrastructure including computers, broadband
3. connectivity and recently sensing infrastructures.
These infrastructures have empowered a number of
innovative services in areas such as participatory
sensing, urban logistics and ambient assisted living.
Such services have been extensively deployed in
several cities, thereby demonstrating the potential
benefits of ICT infrastructures for businesses and the
citizens themselves. During the last few years we
have also witnessed an explosion of sensor
deployments and social networking services, along
with the emergence of social networking (Conti et al.,
2011) and internet‐of‐things technologies (Perera et
al., 2013; Sundmaeker et al., 2010) Social and sensor
networks can be combined in order to offer a variety
of added‐value services for smart cities, as has
already been demonstrated by various early internet‐
of‐things applications (such as WikiCity(Calabrese et
al., 2007), CitySense(Murty et al., 2007),
GoogleLatitude(Page and Kobsa, 2010)), as well as
applications combining social and sensor networks
4. (as for example provided by (Breslin and Decker,
2007; Breslin et al., 2009) and (Miluzzo et al., 2007).
Recently, the benefits of social networking and
internet‐of‐things deployments for smart cities have
also been demonstrated in the context of a range of
EC co‐funded projects (Hernández-Muñoz et al.,
2011; Sanchez, 2010).
Current Smart City Data Analysis implies a wide
set of activities aiming to turn into actionable data the
outcome of complex analytics processes. This
analysis comprises among others: i) analysis of
thousands of traffic, pollution, weather, waste, energy
and event sensory data to provide better services to
the citizens, ii) event and incident analysis using near
real-time data collected by citizens and devices
sensors, iii) turning social media data related to city
issues into event and sentiment analysis , and many
5. others. Combining data from physical
(sensors/devices) and social sources (social
networks) can give more complete, complementary
data and contributes to better analysis and insights. In
overall, smart cities are complex social systems and
large scale data analytics can contribute into their
sustainability, efficient operation and welfare of the
citizens.
Motivated by the modern challenges in smart
cities, the RADICAL approach (RADICAL, 2016)
opens new horizons in the development, deployment
and operation of interoperable social networking and
Internet of Things services in smart cities, notably
services that could be flexibly and successfully
customized and replicated across multiple cities. Its
main goal is to provide the means for cities and SMEs
to rapidly develop, deploy, replicate, and evaluate a
diverse set of sustainable ICT services that leverage
6. established IoT and SN infrastructures. Application
services deployed and pilotedinvolve: i) Cycling
Safety Improvement, ii) Products Carbon Footprint
Management, iii) Object‐driven Data Journalism, iv)
Participatory Urbanism, v) Augmented Reality, vi)
Eco‐ consciousness, vii) Sound map of a city and viii)
City-R-Us: a crowdsourcing app for collecting
movement information using citizens smartphones.
The RADICAL platform is an open platform
having as added value the capability to easily
replicate the services in other smart cities, the ability
to co-design services with the involvement of cities'
Living Labs, and the use of added value services that
deal with the application development, the
sustainability analysis and the governance of the
services.
The RADICAL approach emphasizes on the
sustainability of the services deployed, targeting both
environmental sustainability and business viability.
7. Relevant indicators (e.g., CO2 emissions, Citizens
Satisfaction) are established and monitored as part of
the platform evaluation.End users (citizens) in
modern smart cities are increasingly looking for
media‐rich services offered under different space‐,
context‐, and situational conditions. The active
participation and interaction of citizens can be a key
enabler for successful and sustainable service
deployments in future cities. Social networks hold the
promise to boost such participation and interaction,
thereby boosting participatory connected governance
within the cities. However, in order to enable smart
cities get insight information on how citizens think,
act and talk about their city it is important to
understand their opinion and sentiment polarity on
issues related to their city context. This is where
sentiment analysis can play a significant role. As
social media data bring in significant Big Data
challenges (especially for unstructured data streams)
8. it will be important to find effective ways to analyse
sentimentally those data for extracting value
information and within specific time windows.
This paper has the following contributions:
uniform social and IoT big data aggregation
and combination.
t Analysis
techniques efficiency, to reduce record,
retrieval, update and processing time.
-grams storage and
frequency representation in the context of big
data Sentiment Analysis.
The rest of the paper is structured as follows:
Section 2 gives an overview of related and similar
works that can be found in the international literature
and in projects funded by the European Commission.
Section 3 presents the RADICAL architecture and
approach. Section 4 presents details about the
Sentiment Analysis problem and related experiments,
9. while in section 5 we provide the future work to be
planned in the context of RADICAL and the
conclusions we have come into.
2 RELATED WORK
Recently, various analytical services such as
sentiment analysis found their way into Internet of
Things (IoT) applications. With the devices that are
able to convey human messages over the internet
meeting an exponential growth, the challenge now
revolves around big data issues. Traditional
approaches do not cope with the requirements posed
from applications for analytics in e.g. high velocity
rates or data volumes. As a result, the integration of
IoT with social sensor data put common tasks like
feature extraction, algorithm training or model
updating to the test.
Most of the algorithms are memory-resident and
assume a small data size (He et al., 2010) and once
this threshold is exceeded, the algorithms’ accuracy
and performance degrades to the point they are
useless. Therefore even if we focused solely on
volume challenges, it is intuitively expected that the
accuracy of the supervised algorithms will be
affected. An attempt from (Liu et al., 2013) to use
Naïve Bayes in an increasingly large data volume,
showed that a rapid fall of the algorithms accuracy is
followed by a continuous, smooth increase
10. asymptotically tending from the lower end to the
baseline (best accuracy under normal data load).
Rather than testing the algorithm’s limitations,
most of the other approaches are focusing on
implementing parallel and distributed versions of the
algorithms such as (He et al., 2010; Read et al., 2015).
In fact most of them rely on the Map-Reduce
framework so as to achieve high throughput
classification (Amati et al., 2014; Sakaki et al., 2013;
Wang et al., 2012; Zhao et al., 2012) whereas a
number of toolkits have been presented with
implementations of distributed or parallel versions of
machine learning algorithms such as (“Apache
Mahout: Scalable machine learning and data mining,”
n.d., “MEKA: A Multi-label Extension to WEKA,”
n.d.; Bifet et al., 2010). While these solutions put
most of the emphasis in the model and the
optimization of the classification task in terms of
accuracy and throughput, there is a rather small body
of research dealing with the problem of feature
extraction in high pace streams. The standard solution
that is considered is the use of a sliding window and
the application of standard feature extraction
techniques in this small set. In cases where the
stream’s distribution is variable, a sliding window
kappa-based measure has been proposed (Bifet and
Frank, 2010).
As reported in (Strohbach et al., 2015), another
domain of intense research in the area of scalable
analytics is for an architecture that combines both
batch and stream processing over social and IoT data
while at the same time considering a single model for
different types of documents (e.g. tweets Vs
11. blogposts). Sentiment analysis is a typical task that
requires batch modeling in order to generate the
golden standards for each of the classes. This process
is also the most computationally intense, as the
classification task itself is usually a CPU bound task
(i.e. run the classification function). In a data
streaming scenario the golden standards must be
updated in a batch mode, whereas the feature
extraction and classification must take place in real
time.
Perhaps the most prominent example of such an
architecture is the Lambda Architecture (Marz and
Warren, 2015) pattern which solves the problem of
computing arbitrary functions on arbitrary data in
realtime by combining a batch layer for processing
large scale historical data and a streaming layer for
processing items being retrieved in real time from an
input queue or analytics in e.g. high velocity rates or
data volumes. As a result, the integration of IoT with
social sensor data put common tasks like feature
extraction, algorithm training or model updating to
the test.Most of the algorithms are memory-resident
and assume a small data size (He et al., 2010) and
once this threshold is exceeded, the algorithms’
accuracy and performance degrades to the point they
are useless. Therefore even if we focused solely on
volume challenges, it is intuitively expected that the
accuracy of the supervised algorithms will be
affected. An attempt from Liu et al (Liu et al., 2013)
to use Naïve Bayes in an increasingly large data
volume, showed that a rapid fall of the algorithms
accuracy is followed by a continuous, smooth
increase asymptotically tending from the lower end to
the baseline (best accuracy under normal data load).
12. 3. THE RADICAL APPROACH
The RADICAL platform integrates components
and tools from (SocIoS, 2013) and (SmartSantander,
2013) projects, in order to support innovative smart
city services, leveraging information stemming from
Social Networks (SN) and Internet of Things devices.
Using the aforementioned tools, it can collect,
combine, analyze, process, visualize and provide
uniform access to big datasets of Social Network
content (e.g. tweets) and Internet of Things
information (e.g. sensor measurements or citizen
smartphone reports).
The architecture of the RADICAL platform is
depicted in Figure 1. As can be observed, all IoT data
are pushed into the platform through the respective
Application Programming Interfaces (IoT API and
Repository API) and are forwarded to the RADICAL
Repository, comprised by a MySQL database, formed
13. based on the RADICAL Object Model. The device-
related data, as dictated by this object model, are
saved in the form of Observations and Measurements.
Observations correspond to general IoT events
reported (e.g. a sensor report or bicycle "check-in"
event), while Measurements to more specific metrics
included in an Observation (e.g. Ozone
measurements (mpcc) or bicycle current speed
(km/h)). On the other hand, SN data are accessed in
real time from the underlying SN adaptors, by
communicating with the respective Networks’ APIs.
In cases of Social Networks like Foursquare that
provide plain venues and statistics, the adaptor-like
data structures do not make sense, thus relevant
Social Enablers are used to retrieve venue-related
information data.
On top of the main platform, RADICAL delivers
a set of tools (Application Management layer) that
14. allow end users to make better use of the RADICAL
platform, such as configuring the registered IoT
devices or extracting general activity statistics,
through the RADICAL Configuration API. Lastly,
the RADICAL Data API allows smart city services to
access the different sources of information (social
networks, IoT infrastructures, city applications),
combine data and perform data analysis by using the
appropriate platform tools.
Figure 1: RADICAL Platform Architecture
As can be seen in the Service Application Layer,
in the context of RADICAL a wide range of Smart
City services of various scopes has been developed:
izen journalism and Participatory
Urbanism: Those two interrelated services
allow citizens reporting events ofinterest in the
15. city, by posting images, text and metadata
through their smartphones.
sensors can report the situation in the city
streets through their smartphones.
products, people and services: By using a
range of sensors, the CO2 emissions in specific
places in a city may be monitored.
d Reality in Points of Interest
(POI): Tourists use their smartphones to
identify and receive information about points
of interest in a city.
-consciousness:Leverages
on the viral effect in the propagation of
information in the social networks as well as
the recycling policy of a city, through
monitoring and reporting relevant actions on
citizens' smartphones.
-Orientated Urban Noise Decibel
16. Measurement Application: Noise sensors are
employed throughout the city and citizens are
able to report and comment noise-related
information through SNs under a hashtag.
Urban Services: This service gathers sensory
data along with SN check-ins in city venues, to
construct a traffic map throughout the city,
leveraging the process load of anycentralized
decision making process.
The aforementioned services are piloted in six
European participating cities: Aarhus, Athens,
Genoa, Issy les Moulineaux, Santander and the region
of Cantabria. Figure 2illustrates a screenshot example
of the RADICAL Cities' Dashboard, where general
statistics on device registration and activity for a
service throughout different cities in a specific time
RADICAL
Data
17. Repository
City
Applications
Radical Data API
Service Application Layer
Sound MAPP
Municipality
Cockpit
City R-US
Service
aggregator
Repository
Gateway
Application Management Tools
Governance
Toolkit
Application
Development
Toolkit
Sustainability
services
Resource
18. Directory
Service
Storer
IoT Manager Event Broker
Node
Manager
Data Rep.
Configurator
Radical Configuration API
IoT devices
Repository API
Configuration Tools
Social Media
…
Register
Manager
IOT API SN Adaptors
SocIoS Core Service
SN Enablers
Event
Detection
19. Sentiment
Analysis
GWFPSens GW4IoT Devices GW4Serv…
Platform Tools
Carbon
Footprint
Augmented
Reality
Eco-
Conciousness
Object Driven
Journalism
Participatory
Urbanism
Cycling
Safety
Social Networks -
Venues Services
period is provided. In overall, during the last pilot
20. iteration, RADICAL Repository had captured a total
of 5.636 active IoT devices sending 728.253
Observations and 5.461.776 Measurements.
Most of the services above depend on the
aggregation of those IoTdata with social data
stemming from online Social Network sites. E.g. in
the Participatory Urbanism service, citizens' reports
sent through smartphones and saved in RADICAL
Repository are combined with relevant tweets (under
a city service hashtag), as well as POI information
that can be collected from similar SNs.
Figure 2: RADICAL Cities Dashboard presents smartphone
registrations and measurements for the AR service in the cities
of Santander and Cantabria over a period
Thus, given the size of the datasets acquired by
smart city services, along with the rich social media
content that can be retrieved through the RADICAL
21. platform adaptors, big data aggregation and analysis
challenges arise. Data Analysis tools are the ones that
further process the data in order to provide
meaningful results to the end user, i.e. Event
Detection or Sentiment Analysis.
When it comes to Big Data, as in the RADICAL
case, where millions of user-reported events are
aggregated along with millions of SN posts and an
extraction of general results is required, the challenge
accrued is two-fold: First, the tool must ensure the
accuracy of the analysis, in the sense that data
classification is correct to a certain and satisfactory
extent, and second, processing time must be kept
under certain limits, so that results retrieval process
delay is tolerable by end-users. Moreover, it is
apparent in such analysis that a trade-off between
effectiveness and efficiency exists. The latter is a
most crucial issue in Big Data analysis and apart from
22. the policy followed in data querying (e.g. for queries
preformed in an SQL database), it is also related to
the algorithmic techniques employed foranalyzing
those datasets.
In the context of this work, we focus on the
Sentiment Analysis on the big IoT and SN related
datasets of RADICAL, as this was the most popular
functionality among participating cities and almost all
of the RADICAL Smart City services presented
above make use of it. The goal of the Sentiment
Analysis service is to extract sentiment expressive
patterns from user-generated content in social
networks or IoT-originated text posts. The service
comes to the aid of the RADICAL city administrators,
helping them to categorize polarized posts, meaning
sentimentally charged text, e.g. analyse citizens’
posts to separate subjective from objective opinions
or count the overall positive and negative feedback,
23. concerning a specific topic or event in the city.
4. SENTIMENT ANALYSIS
EXPERIMENTS AND
PERFORMANCE IMPROVEMENT
4.1 Introduction
The term Sentiment Analysis refers to an
automatic classification problem. Its techniques are
trying to distinguish between sentences of natural
language conveying positive (e.g. happiness, pride,
joy), negative (e.g. anger, sadness, jealously) or even
neutral (no sentiment texts like statements, news,
reports)emotion (called sentiment for our purposes)
(Pang et al., 2002).
A human being is capable of understanding a
great variety of emotions from textual data. This
process of understanding is based on complicated
learning procedures that we all go through while
using our language as a means of communication, be
it actively or passively. It requires imagination and
subjectivity in order to fully understand the meaning
and hidden connections of each word in a sentence,
two things that machines lack.
The most common practice is to extract numerical
features out of the natural language (Godbole et al.,
2007). This process translates this complex means of
communication into something the machine can
process.
24. 4.2 Natural Language Processing
In order to process the natural language data, the
computer has to take some pre-processing actions.
These actions include the cleansing of irrelevant,
erroneous or redundant data and the transformation of
the remaining data in a form more easily processed.
Cleansing the data has become a subjective task,
depending on the purposes of each researcher and the
chosen machine learning algorithms. The
transformation of the sentences in another form now
is clearly studied and each approach has some
advantages and disadvantages. This paper will detail
three approaches, two widely used and one that had
some success in improving the accuracy of the
algorithms: the bag of word, N-Gramsand N-Gram
Graphs(Aisopos et al., 2012; Fan and Khademi, 2014;
Giannakopoulos et al., 2008; Pang and Lee, 2008).
The bag of words approach is perhaps the most
simple and common one. It regards each sentence as
a set of words, disregarding their grammatical
connections and neighbouring relations. It splits each
sentence based on the space character (in most
languages) and then forms a set of unrelated words (a
bag of words as it is commonly called). Then each
word in this bag can be disregarded or rated by a
numerical value, in order to create a set of numbers
instead of words.
The N-Grams are a bit more complex. They also
form a bag of words but now each sentence is split
into pseudo-words of equal length. A sliding window
25. of N characters is rolling on the sentence creating this
bag of pseudo-words. For example if N=3 the
sentence “This is a nice weather we have today!” will
be split in the bag {‘Thi’, ‘his’, ‘is ’, ‘s i’, ‘ is’, ‘is ’,
‘s a’, ‘ a ’, ‘a n’, ‘ ni’, ‘nic’, ‘ice’, ‘ce ’, ‘e w’, ‘ we’,
‘wea’, ‘eat’, ‘ath’, ‘the’, ‘her’, ‘er ’, ‘r w’, ‘ we’, ‘we
’, ‘e h’, ‘ ha’, ‘hav’, ‘ave’, ‘ve ’, ‘e t’, ‘ to’, ‘tod’,
‘oda’, ‘day’, ‘ay!’}.
This technique takes into regard the direct
neighbouring relations by creating a continuous
stream of words, it still ignores the indirect relations
between words and even the relations between the
produced N-Grams. Of course it is impossible to have
a predefined set of numerical ratings for each one of
these pseudo-words because each sentence and each
N number (which is defined arbitrarily by the
researcher) produces a different set of pseudo-
words(Psomakelis et al., 2014). So machine learning
is commonly used to replace these words with
numerical values and create sets of numbers which
can be aggregated to sentence level.
An improvement on that approach aims to take
into consideration the neighbouring relations between
the produced N-Grams. This approach is called N-
Gram Graphs and its main concept is to create a graph
connecting each N-Gram with its neighbours in the
original sentence. So each node in this graph is an N-
Gram and each edge is a neighbouring
relation(Giannakopoulos et al., 2008). This approach
gives a variety of new informationto the researchers
and to the machine learning algorithms, including
information about the context of words, making it a
clear improvement of the simple N-Grams(Aisopos et
al., 2012). The only drawbacks are the complexity it
26. adds to the process and the difficulties of storing,
accessing and updating a graph of textual data.
4.3 Dataset Improvements
At the core of sentiment analysis is its dataset. We
are gathering and employing bigger and bigger
datasets in order to better train the algorithms to
distinguish what is positive and what is negative.
Classic storage techniques are proving more and more
cumbersome for large datasets. ArrayLists and most
Collections are adding a big overhead to the data so
they are not only enlarging the space requirements for
its storage but they are also delaying the analysis
process. So new techniques for data storage and
retrieval are needed, techniques that will enable us to
store even bigger datasets and access them with even
smaller delays.
The most commonly used such technique is the
27. Hash List(Fan and Khademi, 2014), which first
hashes the data in a certain, predefined amount of
buckets and then creates a List in each bucket to
resolve any collisions. This method’s performance is
heavily dependent on the quality of the hash function
and its ability to equally split the data into the buckets.
The target is to have as small lists as possible. That is
the case because finding the right bucket for a certain
piece of data is done in O(1) time but looking through
the List in that bucket for the correct spot to store the
piece of data is done in O(n) time where n is the
number of data pieces in the List.
Moreover, in Java which is the programming
language that we are using, each List is an object
containing one object for each data piece. All these
objects create an overhead that is not to be ignored. In
detail the estimated size that a hash list will occupy is
calculated as:
28. 12 + ((B − E) ∗ 12) + (E ∗ 4)
+ (U ∗ (N ∗ 2 + 72))
Equation 1: Size estimation of Hash List where N=NGram
Length, U=Unique NGrams, B=Bucket Size, E=Empty
Buckets.
The worst case for storage but best for access time
is when almost each data piece has its own bucket. In
this case, for N=5, S=11881376, U=S, B=(26^N)*2,
E=11914220, we have a storage size of 1110 MB. The
best case for storage but worse for access time is when
all data pieces are in a small number of buckets, in big
lists. In this case for N=5, S=11881376, U=1,
B=(26^N)/2, E=200610 we have a storage size of 23
MB. In an average case of N=5, S=11881376,
U=7510766, B=26^N, E=2679046 we have 682 MB
of storage space needed. The sample for the above
examples was the complete range of 5-Grams for the
26 lowercase English characters which are 26^5 =
29. 11881376.
Our proposed technique now, the one that we call
Dimensional Mapping, has a standard storage space,
depending only on the length of the N-Grams. The
idea is to store only the weight of each N-Gram with
the N-Gram itself being the pointer to where it is
stored. That is achieved by creating an N-dimensional
array of integers where each character of the N-Gram
is used as an index. So, in order to access the weight
of the 5-Gram ‘fdsgh’ in the table DM we would just
read the value in cell DM[‘f’][‘d’][‘s’][‘g’][‘h’]. A
very simple mapping is used between the characters
and an integers: after a very strict cleansing process
where we convert all characters in lowercase and
discard all characters but the 26 in the English
alphabet, we are just subtracting the ASCII value of
‘a’. Due to the serial nature of the characters that
gives us an integer between 0 and 26 that we can use
30. as an index. A more complex mapping can be used in
order to include more characters or even punctuation
that we now ignore.
The Dimensional Mapping has a standard storage
size requirement, dependent only on the length of the
N-Grams as we mentioned before. The size it
occupies can be estimated by the following formula:
(26� ) ∗ 4 + ∑ ((26�−� ) ∗ 12)
�=�
�=1
Equation 2: Dimensional Mapping size estimation with N
being the length of N-Grams.
This may seem large but for the 5-Grams the
estimated size is just 51 MB. Compared to the worst
case of Hash Lists (1110 MB) or even the average
case (682 MB) it seems like a huge improvement.
This is caused due to the fact that the
31. multidimensional array stores primitive values and
not objects, which reduces the overhead greatly.
Moreover, we can now say that accessing and
updating a certain data piece can be done in O(1) time
with absolute certainty, with no dependency on the
data itself or a hash function. This had significant
results in speeding up the execution times of the
analysis, enabling us to look into streaming data and
semi-supervised machine learning algorithms.
4.4 Results
We measured three main KPIs for the result
comparison. Two of them (success ratio, kappa
variable) were measuring the success ratio of
classification and one (execution time) the
algorithmic improvement. We present them bellow.
We run experiments on 5-Grams stored in classic
ArrayList format, in Hash Lists and in Dimensional
Mapping. After storing the N-Grams in these formats
32. we applied a 10-fold cross validation on each one of
the seven machine learning algorithms we chose:
Naïve Bayesian Networks, C4.5, Support Vector
Machines, Logistic Regression, Multilayer
Perceptrons, Best-First Trees and Functional Trees.
Then we recorded the three KPIs for each one of these
21 experiments. The results for the first two KPIs are
shown in the bar chart that follows. In the same chart
we have included the KPIs for a threshold based
classification, using an arbitrarily set threshold.
Figure 3: A comparison of the three KPIs as shown in the
sentiment analysis experiments
As of the execution times the following table
contains a summary of the results:
Table 1: Execution time in seconds summary - comparing
33. for the various algorithms and techniques
ArrayLists Hash
List
Dimensional
Mapping
Thresholds 1691 5 4
Naïve
Bayes
12302 7 7
C4.5 21535 9 8
SVM 20662 147 177
Logistic
Regression
22251 9 11
MLP 21224 41 48
BFTree 23319 25 19
FTree 22539 16 16
5. CONCLUSIONS
34. RADICAL platform, as presented in the current
work, successfully combines citizens' posts retrieved
through smartphone applications and Social
Networks in the context of smart city applications, to
produce a testbed for applying multiple analysis
functionalities and techniques. The exploitation of
resulting big aggregated datasets pose multiple
challenges, with timely-efficient analysis being the
most important. Focusing on data storage and
representation, multiple techniques were examined in
the experiments performed, in order to come up with
the optimal algorithmic approach of Dimensional
Mapping. In the future the authors plan to use even
larger and more complex datasets, further leveraging
on the effectiveness of these social networking
services.
ACKNOWNLEDGEMENTS
This work has been supported by RADICAL and
35. Consensus projects and has been funded by the
European Commission's Competitiveness and
Innovation Framework Programme under grant
agreements no 325138 and 611688 respectively.
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Pang, B., Lee, L., 2008. Opinion mining and
sentiment analysis. Found. Trends Inf. Retr.
2, 1–135.
Pang, B., Lee, L., Vaithyanathan, S., 2002. Thumbs
up? Sentiment Classification Using Machine
Learning Techniques, in: emnlp2002.
Philadelphia, Pennsylvania, pp. 79–86.
Perera, C., Zaslavsky, A.B., Christen, P.,
Georgakopoulos, D., 2013. Sensing as a
Service Model for Smart Cities Supported
by Internet of Things. CoRR abs/1307.8198.
Psomakelis, E., Tserpes, K., Anagnostopoulos, D.,
Theodora, V., 2014. Comparing Methods for
Twitter Sentiment Analysis. Proc. 6th Int.
Conf. Knowl. Discov. Inf. Retr. - KDIR
2014 225–232.
42. RADICAL, 2016. Rapid Deployment for Intelligent
Cities and Living, FP7 EU funded Research
project [WWW Document]. URL
http://www.radical-project.eu
Read, J., Martino, L., Olmos, P.M., Luengo, D., 2015.
Scalable multi-output label prediction: From
classifier chains to classifier trellises.
Pattern Recognit. 48, 2096–2109.
doi:10.1016/j.patcog.2015.01.004
Romero Lankao, P., 2008. Urban areas and climate
change: Review of current issues and trends.
Issues Pap. 2011 Glob. Rep. Hum. Settl.
Sakaki, T., Okazaki, M., Matsuo, Y., 2013. Tweet
analysis for real-time event detection and
earthquake reporting system development.
Knowl. Data Eng. IEEE Trans. On 25, 919–
43. 931.
Sanchez, L., 2010. SmartSantander: Experimenting
The Future Internet in the City of the Future.
Presented at the PIMRC2010, Istanbul,
Turkey.
SmartSantander, 2013. SmartSantander, FP7 EU
funded Research project [WWW
Document]. URL
http://www.smartsantander.eu/
SocIoS, 2013. Exploiting Social Networks for
Building the Future Internet of Services, FP7
EU funded Research project [WWW
Document]. URL
http://www.sociosproject.eu/
Strohbach, M., Ziekow, H., Gazis, V., Akiva, N.,
2015. Towards a big data analytics
framework for IoT and smart city
applications, in: Modeling and Processing
44. for Next-Generation Big-Data
Technologies. Springer, pp. 257–282.
Sundmaeker, H., Guillemin, P., Friess, P., Woelfflé,
S. (Eds.), 2010. Vision and Challenges for
Realising the Internet of Things.
Publications Office of the European Union,
Luxembourg.
Wang, H., Can, D., Kazemzadeh, A., Bar, F.,
Narayanan, S., 2012. A System for Real-
time Twitter Sentiment Analysis of 2012
U.S. Presidential Election Cycle., in: ACL
(System Demonstrations). The Association
for Computer Linguistics, pp. 115–120.
Zhao, J., Dong, L., Wu, J., Xu, K., 2012. MoodLens:
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1528–1531.
45. 1
ELEG-548: Low Power VLSI Circuit Design, Spring 2020, Final
Exam
Name: ____________________________________ Student
ID: ______________________
Note: Use very brief answer for each question. Your grade is
decided by the accuracy instead of the
length of your answer.
1. (30’) A State Transition Graph (STG) for a sequential circuit
is shown in Figure 1. We need to
assign the states for four states S1, S2, S3 and S4 with two state
registers.
Figure 1. State transition graph (STG) of a sequential circuit
1). Assume all primary inputs patterns (AB=00, 01, 10, 11) are
equally probable. Based on STG,
find out conditional transition probabilities for all the
transitions, and mark them in the STG.
2). Assume the state probabilities of states are:
46. P(S1)=1/12, P(S2)=1/6, P(S3)=5/12, P(S4)=1/3.
Find the absolute transition probabilities Paij for all transitions
between states Si and Sj (i≠j), and
mark them in the STG.
3). Based on the results, find the weights Wij for all the
transitions between states Si and Sj (i≠j).
4). Based on the weighted STG, can you find out a low power
state assignment for the above
sequential circuit with minimum power cost function (Fc)
value? Please clearly show how you
achieve the low power state assignment step by step. Please
show your state assignment matrix,
and clearly mark the state assignment for each state (S1=? S2=?
S3=? S4=?).
5). For your low power state assignment, find out the power
cost function value Fc=?
2. (25’) A 16-bit carry-select full adder circuit is shown in
Figure 2. It takes two 16-bit inputs A, B:
A=A15A14…A0, B=B15B14…B0, and computes: SUM=A+B.
The carry-select full adder uses two 8-bit full adders to
precompute the sum of higher eight bits of
inputs assuming the carry-out from the sum of lower eight bits
to be “0” or “1” separately. The
47. actual carry-out from the lower eight bits will decide which
higher 8-bit SUM to be passed to the
final output (SUM<8:15>).
(1). This circuit can be revised to implement type-2 logic shut-
down technique to save power. The
A7, B7 bits can be used to construct predictor functions. Derive
the “1”-predictor function g1 and
“0”-predictor function g2 for the carryout of lower 8-bit full
adder. Whenever the carryout of lower
8-bit full adder can be predicted, one of the two higher 8-bit
full adders can be shut down to save
power.
2
(2). Re-plot the circuit separately to show how type-2 logic
shut-down technique is implemented.
You need to show clearly how g1 and g2 are connected in the
circuit. (Hint: You may need to add
LE (load_enable) for some registers.)
(3). Assume 1-probabilities p(A<i>)=0.25, p(B<i>)=0.82,
(i=0~15) what is the probabilities when
the circuit can be in shut-down mode? Assume average power of
48. each one-bit full adder as Padder,
the power of 8-bit full-adder block is 8Padder. If we only
consider the power consumption of
full-adders, while ignoring power consumption of other
gates/registers/Load_Enables, what would
be the approximate percentage power saving we can achieve by
using type-2 logic shut-down
technique (just a rough estimation)?
Figure 2. 16-bit carry-select full adder circuit
3. (25’) Low Power Data Communication: An 8-bit data bus is
driven by an 8-bit counter, as
shown in Figure 3.
1). If a regular binary counter is used, what is the average
number of bit switches per clock cycle
on the 8-bit data bus? Derive the equation to find out the
average number of bit switches per clock
cycle for N-bit binary counter. Show your proof of the equation
step by step.
2). If a gray-code counter is used, what is the average number
of bit switches per clock cycle on
the 8-bit data bus? What is the number of bit switches per clock
cycle for N-bit gray code counter?
49. 3). If bus-inversion encoding technique is used to reduce the
power of data communication, sketch
how you are going to implement the bus-inversion encoding
logic (circuit design) on the 8-bit data
bus. For what patterns will the data be inverted? What is the
average number of bit switches per
clock cycle on the 8-bit data bus with bus-inversion encoding
technique?
4). Based on above 3 choices, which option gives the lowest
power consumption?
3
Figure 3. Data communication: 8-bit counter driving an 8-bit
data bus
4.(20’) A transmission gate based one-bit full adder circuit is
shown in Figure 4.
1). Based on the circuit design, what are the logic functions
implemented at P, S and Co? Derive its
logic expression, and use Boolean transformation to prove it
does implement the correct function
of Sum and Carry-out for one-bit full adder as below.
50. 2). For this circuit in Figure 4, how are you going to measure its
power consumption using PSPICE
power simulation? Draw the complete circuit with auxiliary
power measurement circuitry and
clearly show where you are going to insert dummy voltage
sources.
Figure 4. A transmission gate based full adder
Due on 05/05/2020 (Tuesday) online in Canvas before 5pm.
Analysis on the Demand of Top Talent Introduction
in Big Data and Cloud Computing Field in China
Based on 3-F Method
Zhao Linjia, Huang Yuanxi, Wang Yinqiu, Liu Jia
National Academy of Innovation Strategy, China Association
for Science and Technology, Beijing, P.R.China
Abstract—Big data and cloud computing, which can help
China to implement innovation-driven development strategy and
promote industrial transformation and upgrading, is a new and
emerging industrial field in China. Educated, productive and
healthy workforces are necessary factor to develop big data and
cloud computing industry, especially top talents are essential.
51. Therefore, a three-step method named 3-F has been introduced
to help describing the distribution of top talents globally and
making decision whether they are needed in China. The 3-F
method relies on calculating the brain gain index to analysis the
top talent introduction demand of a country. Firstly, Focus on
the
high-frequency keywords of a specific field by retrieving the
highly cited papers. Secondly, using those keywords to Find out
the top talents of this specific field in the Web of Science.
Finally,
Figure out the brain gain index to estimate whether a country
need to introduce top talents of a specific field abroad. The
result
showed that the brain gain index value of China's big data and
cloud computing field was 2.61, which means China need to
introduce top talents abroad. Besides P. R. China, those top
talents mainly distributed in the United States, the United
Kingdom, Germany, Netherlands and France.
I. INTRODUCTION
Big data and cloud computing is a new and emerging
industrial field[1], and increasing widely used in China[2-4].
Talents’ experience is a source of technological mastery[5],
essentially for developing and using big data technologies.
Most European states consider the immigration of foreign
workers as an important factor to decelerate the decline of
national workforces[6]. Lots of universities and research
institutes have set up undergraduate and/or postgraduate
courses on data analytics for cultivating talents[7]. EMC
corporation think that vision, talent, and technology are
necessary elements to providing solutions to big data
management and analysis, insuring the big data success[8].
Bibliometrics research has appeared as early as 1917[9],
and has been proved an effective method for assessing or
52. identifying talents. Based on analyses of publication volume,
journals and their impact factors, most cited articles and
authors, preferred methods, and represented countries,
Gallardo-Gallardo et. al[10] assess whether talent management
should be approached as an embryonic, growth, or mature
phenomenon.
In this paper, we intend to analysis whether China need to
introduce top talents in the field of big data and cloud
computing by using bibliometrics. In section 2, the 3-F method
for top talent introduction demand analysis will be discussed.
In section 3, we will analysis the demand of top talent
introduction in big data and cloud computing field in China.
II. METHOD
In general, metering indicators contain the most productive
authors, journals, institutions, and countries, and the
collaboration networks between authors and institutions[11,
12]. Based on the commonly used bibliometrics method, 3-F
method for top talent introduction demand analysis is proposed.
3-F method has three steps:
Firstly, searching the literature database and forming a
high-impact literature collection in a specific field. Focusing on
the high-frequency keywords in the high-impact literature
collection by using the text analysis method as the research
hotspots. Just to be clear, the high-impact literature refers to the
journal literature whose number of cited papers ranked in the
top 1% in the same discipline and in the same year.
Secondly, retrieving those keywords in the Web of Science
to find out where those top talents of this specific field are.
Find the top talents by collected the information about talents’
country distribution, the institutions distribution and so on
54. Using 3-F method to analysis the top talents introduction
demand in the big data and cloud computing field. We
collected the high-impact literatures from January 1, 2006 to
July 31, 2016. The literature Language was English and the
literature type was article. Combining with the above
conditions, we got 546 high-impact literatures in the big data
and cloud computing field. Then the high-frequency keywords
have been obtained (Table 1) and served as the research
hotspots set.
TABLE I. THE RESEARCH HOTSPOTS OF THE HIGH-
IMPACT LITERATURES IN
BIG DATA AND CLOUD COMPUTING FIELD
Order Keywords Frequency
1 cloud computing 48
2 big data 24
3 virtualization 11
4 cloud manufacturing 9
5 internet of things (IoT) 8
6 mobile cloud computing 8
7 bioinformatics 6
8 climate change 6
9 Hadoop 6
10 software-defined networking (SDN) 6
55. ……
At the same time, we displayed the frequency distribution
of research hotspots in the way of cloud chart(fig. 1).
Fig. 1. The cloud chart of research hotspots that in the field of
big data and
cloud computing
Then, we find the information about nationality (Table 2),
institutes (Table 3) of top talents in the high-impact literature
collection. Results showed there were 662 top talents
worldwide in the big data and cloud computing field. The top
ten countries or regions who had the most top talents were the
United States, P.R.China, the United Kindom, Germany, the
Netherlands, France, Canada, Australia, Italy and Switzerland
and Spain tied for the tenth.
TABLE II. THE NATIONALITY DISTRIBUTION OF TOP
TALENTS IN THE BIG
DATA AND CLOUD COMPUTING FIELD
Order Country or Region Number of the top talent
1 US 268
2 P. R. China 48
3 UK 47
4 Germany 39
5 Netherlands 28
6 France 27
7 Canada 22
8 Australia 21
9 Italy 19
56. 10 Switzerland 13
Spain 13
12 Japan 10
13 Korea 8
Malaysia 8
15 Singapore 7
New Zealand 7
17 Austria 6
18 Belgium 5
Sweden 5
India 5
Chinese Taipei 5
……
TABLE III. THE INSTITUTES DISTRIBUTION OF TOP
TALENTS IN THE BIG
DATA AND CLOUD COMPUTING FIELD
Order Country or Region Number of the top talent
1 Harvard University (US) 10
2 Purdue University (US) 7
University of Malaya (Malaysia) 7
University of Maryland (US) 7
Unversity of Melbourne (Australia) 7
University of Missouri (US) 7
7 Oxford Unversity (UK) 6
8 Chinese Academy of Sciences (P.R.China) 5
57. ETH Zurich (Switzerland) 5
Massachusetts General Hospital (US) 5
Northwestern University (US) 5
University of British Columbia (Canada) 5
UC, Berkeley (US) 5
UC, San Diego (US) 5
University of Texas at Austin (US) 5
University of Washington (US) 5
……
2017 Proceedings of PICMET '17: Technology Management for
Interconnected World
From table 2 and 3 we can see that China was in the second
place worldwide. However, China's top talent is much less than
the United States. In addition, the overall strength of Chinese
research institutions is not strong. So, whether China should
introduce top talents from other countries is need to be
discussed.
According to the formula of the brain gain index, and using
the world population data as well as the Chinese mainland
population data released by the World Bank, the value of the
Chinese brain gain index of big data and cloud computing was
2.61. In comparison, the brain gain index value of the United
58. States was 0.11. That means China need to introduce top talent
in the field of big data and cloud computing.
IV. CONCLUSION
In the knowledge economy era, the international flow of top
talent has become convenient and frequent. Facing the world's
top talent shortage, China and the world's major countries have
developed overseas top talent introduction programs. Until
2007, almost all European countries had introduced some
skillselective migration policies in order to attract the top
talents. To make the overseas top talent introduction programs
more effective and targeted is helpful for occupying the
strategic high ground in the global top talent competition.
This paper improved the traditional talent evaluation
function of bibliometric method, and presented the 3-F analysis
method, which was applied to analyze the demand of top
talents. The 3F method could help the government official to
make decision whether need to introduce top talents to develop
a new industry field and lock these top talents geographic
location.
REFERENCES
[1] .Xu, B.M., X.G. Ni. Development Trend and Key Technical
Progress of
Cloud Computing[J]. Bulletin of the Chinese Academy of
Sciences,
2015. 30(2), pp. 170-180.
[2] Xiao, Y., Y. Cheng, Y.J. Fang, Research on Cloud
Computing and Its
Application in Big Data Processing of Railway Passenger Flow,
in
Iaeds15: International Conference in Applied Engineering and
59. Management, P. Ren, Y. Li, and H. Song, Editors. 2015, Aidic
Servizi
Srl: Milano. pp. 325-330.
[3] Zhu, Y.Q., P. Luo, Y.Y. Huo et. al, Study on Impact and
Reform of Big
Data on Higher Education in China, in 2015 3rd International
Conference on Social Science and Humanity, G. Lee and Y. Wu,
Editors. 2015, Information Engineering Research Inst, USA:
Newark. p.
155-161.
[4] Wang, X., L.C. Song, G.F. Wang et.al. Operational Climate
Prediction
in the Era of Big Data in China: Reviews and Prospects[J].
Journal of
Meteorological Research, 2016. 30(3), pp. 444-456.
[5] Dahlman, C., L. Westphal, Technological effort in industrial
development——An Interpretative Survey of Recent
Research[R]. 1982.
[6] Cerna, L., M. Czaika, European Policies to Attract Talent:
The Crisis
and Highly Skilled Migration Policy Changes, in High-Skill
Migration
and Recession. 2016, Springer. pp. 22-43.
[7] Jin, X., B.W. Wah, X. Cheng et. al. Significance and
challenges of big
data research[J]. Big Data Research, 2015. 2(2), pp. 59-64.
[8] Fang, H., Z. Zhang, C.J. Wang et. al. A survey of big data
research[J].
IEEE Network, 2015. 29(5), pp. 6-9.
60. [9] Cole, F.J., Eales, N. B. The history of comparative
anatomy[J]. science
Progress, 1917. 11, pp. 578-596.
[10] Gallardo-Gallardo, E., S. Nijs, N. Dries et. al. Towards an
understanding
of talent management as a phenomenon-driven field using
bibliometric
and content analysis[J]. Human Resource Management Review,
2015.
25, pp. 264-279.
[11] Clarke, B.L. Multiple authorship trends in scientific
papers[J]. Science,
1964. 143(3608), pp. 822-824.
[12] Gonzalez-Valiente, C.L., J. Pacheco-Mendoza, R.
Arencibia-Jorge. A
review of altmetrics as an emerging discipline for research
evaluation[J].
Learned Publishing, 2016. 29(4), pp. 229-238.
2017 Proceedings of PICMET '17: Technology Management for
Interconnected World
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71. in Big Data and Cloud Computing Field in China
Based on 3-F Method
Zhao Linjia, Huang Yuanxi, Wang Yinqiu, Liu Jia
National Academy of Innovation Strategy, China Association
for Science and Technology, Beijing, P.R.China
Abstract—Big data and cloud computing, which can help
China to implement innovation-driven development strategy and
promote industrial transformation and upgrading, is a new and
emerging industrial field in China. Educated, productive and
healthy workforces are necessary factor to develop big data and
cloud computing industry, especially top talents are essential.
Therefore, a three-step method named 3-F has been introduced
to help describing the distribution of top talents globally and
making decision whether they are needed in China. The 3-F
method relies on calculating the brain gain index to analysis the
top talent introduction demand of a country. Firstly, Focus on
the
high-frequency keywords of a specific field by retrieving the
highly cited papers. Secondly, using those keywords to Find out
the top talents of this specific field in the Web of Science.
Finally,
Figure out the brain gain index to estimate whether a country
need to introduce top talents of a specific field abroad. The
result
showed that the brain gain index value of China's big data and
cloud computing field was 2.61, which means China need to
introduce top talents abroad. Besides P. R. China, those top
talents mainly distributed in the United States, the United
Kingdom, Germany, Netherlands and France.
I. INTRODUCTION
72. Big data and cloud computing is a new and emerging
industrial field[1], and increasing widely used in China[2-4].
Talents’ experience is a source of technological mastery[5],
essentially for developing and using big data technologies.
Most European states consider the immigration of foreign
workers as an important factor to decelerate the decline of
national workforces[6]. Lots of universities and research
institutes have set up undergraduate and/or postgraduate
courses on data analytics for cultivating talents[7]. EMC
corporation think that vision, talent, and technology are
necessary elements to providing solutions to big data
management and analysis, insuring the big data success[8].
Bibliometrics research has appeared as early as 1917[9],
and has been proved an effective method for assessing or
identifying talents. Based on analyses of publication volume,
journals and their impact factors, most cited articles and
authors, preferred methods, and represented countries,
Gallardo-Gallardo et. al[10] assess whether talent management
should be approached as an embryonic, growth, or mature
phenomenon.
In this paper, we intend to analysis whether China need to
introduce top talents in the field of big data and cloud
computing by using bibliometrics. In section 2, the 3-F method
for top talent introduction demand analysis will be discussed.
In section 3, we will analysis the demand of top talent
introduction in big data and cloud computing field in China.
II. METHOD
In general, metering indicators contain the most productive
authors, journals, institutions, and countries, and the
collaboration networks between authors and institutions[11,
73. 12]. Based on the commonly used bibliometrics method, 3-F
method for top talent introduction demand analysis is proposed.
3-F method has three steps:
Firstly, searching the literature database and forming a
high-impact literature collection in a specific field. Focusing on
the high-frequency keywords in the high-impact literature
collection by using the text analysis method as the research
hotspots. Just to be clear, the high-impact literature refers to the
journal literature whose number of cited papers ranked in the
top 1% in the same discipline and in the same year.
Secondly, retrieving those keywords in the Web of Science
to find out where those top talents of this specific field are.
Find the top talents by collected the information about talents’
country distribution, the institutions distribution and so on
through the high-impact literature collection. Among them, the
top talent refers to the first author or the communication author
of the high-impact literatures.
Finlly, Figure out the brain gain index to determine the top
talents introduction demand of a certain country. The brain gain
index is calculated as following formulas:
Iik = (Twk / Tik) / (Pw / Pi) (1)
Among them, Iik means the brain gain index value of
country (i) in the field (k), Twk means the number of world’s
top
talents in the field (k), Tik means the number of country’s (i)
top
talents in the field (k), Pw means the world population, Pi
means the country’s (i) population. If Iik was more than 1, that
means the country (i) has less top talents in the field (k),
therefore the talent introduction demand will be relatively
strong. In contrast, if Iik was less than 1, that means the
75. 3 virtualization 11
4 cloud manufacturing 9
5 internet of things (IoT) 8
6 mobile cloud computing 8
7 bioinformatics 6
8 climate change 6
9 Hadoop 6
10 software-defined networking (SDN) 6
……
At the same time, we displayed the frequency distribution
of research hotspots in the way of cloud chart(fig. 1).
Fig. 1. The cloud chart of research hotspots that in the field of
big data and
cloud computing
Then, we find the information about nationality (Table 2),
institutes (Table 3) of top talents in the high-impact literature
collection. Results showed there were 662 top talents
worldwide in the big data and cloud computing field. The top
ten countries or regions who had the most top talents were the
United States, P.R.China, the United Kindom, Germany, the
Netherlands, France, Canada, Australia, Italy and Switzerland
76. and Spain tied for the tenth.
TABLE II. THE NATIONALITY DISTRIBUTION OF TOP
TALENTS IN THE BIG
DATA AND CLOUD COMPUTING FIELD
Order Country or Region Number of the top talent
1 US 268
2 P. R. China 48
3 UK 47
4 Germany 39
5 Netherlands 28
6 France 27
7 Canada 22
8 Australia 21
9 Italy 19
10 Switzerland 13
Spain 13
12 Japan 10
13 Korea 8
Malaysia 8
15 Singapore 7
New Zealand 7
17 Austria 6
18 Belgium 5
Sweden 5
India 5
Chinese Taipei 5
……
TABLE III. THE INSTITUTES DISTRIBUTION OF TOP
TALENTS IN THE BIG
DATA AND CLOUD COMPUTING FIELD
Order Country or Region Number of the top talent
77. 1 Harvard University (US) 10
2 Purdue University (US) 7
University of Malaya (Malaysia) 7
University of Maryland (US) 7
Unversity of Melbourne (Australia) 7
University of Missouri (US) 7
7 Oxford Unversity (UK) 6
8 Chinese Academy of Sciences (P.R.China) 5
ETH Zurich (Switzerland) 5
Massachusetts General Hospital (US) 5
Northwestern University (US) 5
University of British Columbia (Canada) 5
UC, Berkeley (US) 5
UC, San Diego (US) 5
University of Texas at Austin (US) 5
University of Washington (US) 5
……
2017 Proceedings of PICMET '17: Technology Management for
78. Interconnected World
From table 2 and 3 we can see that China was in the second
place worldwide. However, China's top talent is much less than
the United States. In addition, the overall strength of Chinese
research institutions is not strong. So, whether China should
introduce top talents from other countries is need to be
discussed.
According to the formula of the brain gain index, and using
the world population data as well as the Chinese mainland
population data released by the World Bank, the value of the
Chinese brain gain index of big data and cloud computing was
2.61. In comparison, the brain gain index value of the United
States was 0.11. That means China need to introduce top talent
in the field of big data and cloud computing.
IV. CONCLUSION
In the knowledge economy era, the international flow of top
talent has become convenient and frequent. Facing the world's
top talent shortage, China and the world's major countries have
developed overseas top talent introduction programs. Until
2007, almost all European countries had introduced some
skillselective migration policies in order to attract the top
talents. To make the overseas top talent introduction programs
more effective and targeted is helpful for occupying the
strategic high ground in the global top talent competition.
This paper improved the traditional talent evaluation
function of bibliometric method, and presented the 3-F analysis
method, which was applied to analyze the demand of top
talents. The 3F method could help the government official to
make decision whether need to introduce top talents to develop
79. a new industry field and lock these top talents geographic
location.
REFERENCES
[1] .Xu, B.M., X.G. Ni. Development Trend and Key Technical
Progress of
Cloud Computing[J]. Bulletin of the Chinese Academy of
Sciences,
2015. 30(2), pp. 170-180.
[2] Xiao, Y., Y. Cheng, Y.J. Fang, Research on Cloud
Computing and Its
Application in Big Data Processing of Railway Passenger Flow,
in
Iaeds15: International Conference in Applied Engineering and
Management, P. Ren, Y. Li, and H. Song, Editors. 2015, Aidic
Servizi
Srl: Milano. pp. 325-330.
[3] Zhu, Y.Q., P. Luo, Y.Y. Huo et. al, Study on Impact and
Reform of Big
Data on Higher Education in China, in 2015 3rd International
Conference on Social Science and Humanity, G. Lee and Y. Wu,
Editors. 2015, Information Engineering Research Inst, USA:
Newark. p.
155-161.
[4] Wang, X., L.C. Song, G.F. Wang et.al. Operational Climate
Prediction
in the Era of Big Data in China: Reviews and Prospects[J].
Journal of
Meteorological Research, 2016. 30(3), pp. 444-456.
[5] Dahlman, C., L. Westphal, Technological effort in industrial
development——An Interpretative Survey of Recent
80. Research[R]. 1982.
[6] Cerna, L., M. Czaika, European Policies to Attract Talent:
The Crisis
and Highly Skilled Migration Policy Changes, in High-Skill
Migration
and Recession. 2016, Springer. pp. 22-43.
[7] Jin, X., B.W. Wah, X. Cheng et. al. Significance and
challenges of big
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Research Paper - Data Science and Big Data Analytics
This week's reading centered around how Big Data analytics can
be used with Smart Cities. This is exciting and can provide
many benefits to individuals as well as organizations. For this
week's research assignment, you are to search the Internet for
other uses of Big Data in RADICAL platforms. Please pick an
organization or two and discuss the usage of big data in
RADICAL platforms including how big data analytics is used in
those situations as well as with Smart Cities. Be sure to use the
UC Library for scholarly research. Google Scholar is the 2nd
best option to use for research.
Your paper should meet the following requirements:
• Be approximately 3-5 pages in length, not including the
required cover page and reference page.
• Follow APA guidelines. Your paper should include an
introduction, a body with fully developed content, and a
conclusion.
• Support your response with the readings from the course and
at least five peer-reviewed articles or scholarly journals to
support your positions, claims, and observations. The UC
Library is a great place to find resources.
• Be clear with well-written, concise, using excellent grammar
92. and style techniques. You are being graded in part on the
quality of your writing.
References:
L. Zhao, Y. Huang, Y. Wang and J. Liu, "Analysis on the
Demand of Top Talent Introduction in Big Data and Cloud
Computing Field in China Based on 3-F Method," 2017 Portland
International Conference on Management of Engineering and
Technology (PICMET), Portland, OR, 2017, pp. 1-3. doi:
10.23919/PICMET.2017.8125463
Discussion 1 – Data Science and Big Data Analytics
In this week's reading, the concept of 3-F Method is introduced.
Discuss the purpose of this concept and how it is calculated.
Also perform your own research/analysis using these factors and
provide your assessment on whether the United States need to
introduce top talents in the field of big data and cloud
computing by using bibliometrics.
Please make your initial post and two response posts
substantive. A substantive post will do at least TWO of the
following:
Ask an interesting, thoughtful question pertaining to the topic
Answer a question (in detail) posted by another student or the
instructor
Provide extensive additional information on the topic
Explain, define, or analyze the topic in detail
Share an applicable personal experience
Provide an outside source (for example, an article from the UC
Library) that applies to the topic, along with additional
information about the topic or the source (please cite properly
in APA)
Make an argument concerning the topic.
At least one scholarly source should be used in the initial
93. discussion thread. Be sure to use information from your
readings and other sources from the UC Library. Use proper
citations and references in your post.
References:
L. Zhao, Y. Huang, Y. Wang and J. Liu, "Analysis on the
Demand of Top Talent Introduction in Big Data and Cloud
Computing Field in China Based on 3-F Method," 2017 Portland
International Conference on Management of Engineering and
Technology (PICMET), Portland, OR, 2017, pp. 1-3. doi:
10.23919/PICMET.2017.8125463
Psomakelis, E., Aisopos, F., Litke, A., Tserpes, K., Kardara,
M., & Campo, P.M. (2016). Big IoT and Social Networking
Data for Smart Cities - Algorithmic Improvements on Big Data
Analysis in the Context of RADICAL City Applications.
CLOSER.
Discussion 2 – Information Governance
Chapter 1 : The Onslaught of Big Data and the Information
Governance Imperative
Organizations are struggling to reduce and right-size their
information foot-print, using data governance techniques like
data cleansing and de-duplication. Why is this effort
necessary?
Requirements:
· APA Format
· 300 – 400 Words
· 2 Scholarly References
TextBook:
Smallwood, R. F. (2014). Information Governance : Concepts,
Strategies, and Best Practices. Wiley. ISBN: 9781118218303