An Efficient Framework for Predicting and Recommending M-Commerce Patterns Ba...Editor IJCATR
1) The document proposes a framework for predicting and recommending mobile commerce patterns using a graph diffusion method.
2) It constructs a graph based on items purchased by mobile users and ranks the items based on transactions to analyze user behavior and recommend ranked items.
3) This framework is said to produce more efficient and accurate item recommendations than previous frameworks by overcoming problems with high false positive rates and efficiency.
This document proposes using collaborative filtering to improve upon an existing mobile commerce framework. The existing framework uses data mining to analyze user transaction and location data to predict future purchases and locations. However, it only considers frequently visited locations and popular items. The proposed approach aims to make recommendations in new locations by considering item ratings from other users in those locations, rather than just frequent patterns. It will use collaborative filtering instead of the existing PMCP-Mine algorithm to provide more personalized recommendations beyond frequent items and locations.
The document provides details about Ananth Aditya, including his educational qualifications, work experience, skills, and personal objectives. It indicates that he has a B.Com degree and 7 years of experience working in an accountants office. It also mentions that he has ideas related to global warming, solar energy, fuel efficiency, and other research areas, but has been unable to pursue research due to his family's financial background. He is seeking guidance and a job opportunity in a research field.
The document discusses 5 social networks that the author uses: Facebook, Whatsapp, Instagram, Tango, and Viber. Facebook is used to share information between people from different continents including images, chat, text messages, and sharing files. Whatsapp is used to send quick videos and photos in chat. Instagram allows sharing images and videos where people can like and comment. Tango and Viber are used to send text messages, images, and make free video calls without additional costs as long as connected to the internet.
IBM: The Long term investment Myth | Multi-ActMulti-Act
In 2011, Warren Buffett overcame his inherent mistrust of the IT sector to invest heavily in International Business Machines (IBM). Mr Buffett might have given IBM his vote of confidence (Berkshire Hathway owns $12.5 billion of IBM stock), but a quality of earnings analysis (QoEA) of this tech mammoth (1999-2011) does not inspire such trust.
Read More @ http://multi-act.com/ibm-big-blue-shows-red/
Website - http://multi-act.com/
Contact Us - http://multi-act.com/contact
The document describes ISPARK, an interactive visual analytics system developed by researchers at Georgia Tech to help locate fire stations. ISPARK analyzes fire incident data, existing infrastructure, response times, and other factors to determine optimal fire station locations. It uses visualizations and maps to show fire station locations, incident clusters, and response time comparisons between urban and rural areas. The system was demonstrated on 300,000 fire incident records from Massachusetts and Maine. ISPARK aims to reduce response times and thereby decrease injuries, deaths and property damage from fires.
An introduction of Stockholm University Library, held at DEFF Master Class "Experiences Implementing Open Source Library Systems" in Copenhagen, Denmark (August 2015).
An Efficient Framework for Predicting and Recommending M-Commerce Patterns Ba...Editor IJCATR
1) The document proposes a framework for predicting and recommending mobile commerce patterns using a graph diffusion method.
2) It constructs a graph based on items purchased by mobile users and ranks the items based on transactions to analyze user behavior and recommend ranked items.
3) This framework is said to produce more efficient and accurate item recommendations than previous frameworks by overcoming problems with high false positive rates and efficiency.
This document proposes using collaborative filtering to improve upon an existing mobile commerce framework. The existing framework uses data mining to analyze user transaction and location data to predict future purchases and locations. However, it only considers frequently visited locations and popular items. The proposed approach aims to make recommendations in new locations by considering item ratings from other users in those locations, rather than just frequent patterns. It will use collaborative filtering instead of the existing PMCP-Mine algorithm to provide more personalized recommendations beyond frequent items and locations.
The document provides details about Ananth Aditya, including his educational qualifications, work experience, skills, and personal objectives. It indicates that he has a B.Com degree and 7 years of experience working in an accountants office. It also mentions that he has ideas related to global warming, solar energy, fuel efficiency, and other research areas, but has been unable to pursue research due to his family's financial background. He is seeking guidance and a job opportunity in a research field.
The document discusses 5 social networks that the author uses: Facebook, Whatsapp, Instagram, Tango, and Viber. Facebook is used to share information between people from different continents including images, chat, text messages, and sharing files. Whatsapp is used to send quick videos and photos in chat. Instagram allows sharing images and videos where people can like and comment. Tango and Viber are used to send text messages, images, and make free video calls without additional costs as long as connected to the internet.
IBM: The Long term investment Myth | Multi-ActMulti-Act
In 2011, Warren Buffett overcame his inherent mistrust of the IT sector to invest heavily in International Business Machines (IBM). Mr Buffett might have given IBM his vote of confidence (Berkshire Hathway owns $12.5 billion of IBM stock), but a quality of earnings analysis (QoEA) of this tech mammoth (1999-2011) does not inspire such trust.
Read More @ http://multi-act.com/ibm-big-blue-shows-red/
Website - http://multi-act.com/
Contact Us - http://multi-act.com/contact
The document describes ISPARK, an interactive visual analytics system developed by researchers at Georgia Tech to help locate fire stations. ISPARK analyzes fire incident data, existing infrastructure, response times, and other factors to determine optimal fire station locations. It uses visualizations and maps to show fire station locations, incident clusters, and response time comparisons between urban and rural areas. The system was demonstrated on 300,000 fire incident records from Massachusetts and Maine. ISPARK aims to reduce response times and thereby decrease injuries, deaths and property damage from fires.
An introduction of Stockholm University Library, held at DEFF Master Class "Experiences Implementing Open Source Library Systems" in Copenhagen, Denmark (August 2015).
StatsCraft 2015: The problem (Keynote) - Nir CohenStatsCraft
The document outlines the agenda for the StatsCraft Monitoring Conference, which includes understanding what monitoring is, example use cases, and learning methodologies and tools. It then discusses common problems with monitoring such as monitoring the wrong things, treating logs as secondary, lacking important data, separating monitoring from applications, reacting instead of proactively monitoring, prioritizing uptime over quality, dealing with arbitrary limits, and alert fatigue. The document argues that proper monitoring requires the right people beyond just operations and is overall hard to implement well.
Luigi Antonio Piu is an experienced Italian executive chef and culinary director with over 30 years of experience working in hotels, resorts, clubs, and restaurants around the world. He graduated from culinary school in Italy in 1972 and has held executive chef and director positions in Europe, the Middle East, and Asia Pacific. Currently, he is the Director of Executive Chef and Food & Beverage at the Abu Dhabi Country Club in the UAE, overseeing all food operations.
This document is a curriculum vitae for Dr. Robert King, a lecturer in applied psychology at University College Cork. It outlines his educational background, including a PhD in psychology from Birkbeck College and qualifications in teaching. It details his areas of teaching, university service, supervision of students, recent grant applications, employment history, academic service/consultancy, publications, conference presentations, and references. The CV provides a comprehensive overview of Dr. King's academic and professional experience and accomplishments in the field of psychology.
This document provides a list of 5 gift ideas for birthdays that will make the occasion special. The gifts include a sleek bracelet bangle to complete an outfit, a personalized mobile phone case to protect a phone, a peak-a-boo teddy bear to relive old memories, a personalized cushion as a lifetime gift, and message bottles to show unconditional love.
Project MyRecycle is a vision to promote recycling awareness starting in schools. It aims to inspire children and the community towards a cleaner Malaysia. The project will build Recycle Hubs in schools through corporate adoption to generate recycling awareness among students and the local community. It will implement ongoing educational and competitive activities to motivate recycling as a habit. The project provides solutions for corporations to adopt schools and support recycling awareness campaigns through branded merchandise and school activities.
This document outlines some potential demerits of India's Smart City plan, including that innovations for mobility and transport within smart cities need to avoid unnecessary transport and make transport more reliable for users. It also notes that India lacks the necessary capital to build 100 smart cities simultaneously, and there is a risk that corruption could become more sophisticated or the gap between rich and poor could increase if housing is not affordable for working classes.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Big Data Telco Solution by Dr. Laura Wynterwkwsci-research
Presented during the WKWSCI Symposium 2014
21 March 2014
Marina Bay Sands Expo and Convention Centre
Organized by the Wee Kim Wee School of Communication and Information at Nanyang Technological University
various studies of prediction E-consumer omaraldabash
The document discusses several studies that use recurrent neural networks to predict customer behavior from e-commerce data. Specifically, it examines research that uses RNNs to predict future customer purchases and product ratings. It also describes experiments on datasets from online retailers and reviews the results of predicting customer shopping patterns and lifetime value with RNN models.
1) The document discusses the Cyclic Model Analysis (CMA) technique for sequential pattern mining which aims to predict customer purchasing behavior.
2) CMA calculates the Trend Distribution Function from sequential patterns to model purchasing trends over time. It then uses Generalized Periodicity Detection and Trend Modeling to identify periodic patterns and construct an approximating model.
3) The Cyclic Model Analysis algorithm is applied to further analyze the patterns, dividing the domain into segments where the distribution function is increasing or decreasing and applying the other techniques recursively to fully model the cyclic behavior.
The document describes applying a multi-server queue model (M/M/C) to analyze waiting lines at bank ATMs. Data was collected on customer arrival and service times at 5 ATMs over 5 days. The M/M/C model was used to calculate performance metrics like average wait times and server utilization. It was found that the busy time was 2.6 hours while idle time was 7.4 hours, showing efficient service. The utilization rate of 26% indicated no need for additional servers. The study demonstrated how queue models can help banks evaluate ATM performance and waiting lines.
Today, enterprises are looking for innovative ways to digitally transform their businesses - a crucial step forward to remain competitive and enhance profitability. Streaming analytics is a key technology enabler that supports this effort by providing real-time insights on data in motion to help organizations gain the business intelligence they need.
Every industry has its unique challenges, especially where data is concerned. A key advantage of streaming analytics is that it can be customized to create solutions that meet the specific requirements of a particular industry. With years of expertise adapting our analytics products to customer needs, we’ve designed solution templates that target prominent pain points in specific industries.
In this webinar Nirmal will,
Introduce WSO2 Analytics Solutions and theirs use cases (finance and banking, retail, location analytics, IT operations analytics, etc.)
Demonstrate our fleet management solution that gives you the ability to
Know where your fleet is at the moment
Analyze your drivers’ behavior (do they obey speed limits and use optimal routes?)
Find the optimal routes (predict congestion)
Check whether the driver and the cargo are safe
Receive alerts on violation of rules based on Geo-fences
Explain how to customize WSO2 Analytics Solutions
Discuss how to reach out to us
A Survey on Mobile Sensing Technology and its PlatformEswar Publications
Now a days, mobile networks is increasingly becoming important part of everyday life due which there is a rapid evolution mobile phone. Mobile phone comes into a powerful sensing platform. There are many scientists which are engaged in the emerging field of mobile sensing from a variety of existing communities, such as, mobile systems, machine learning and human computer interaction. The research and development in this field is rapid resulting in indispensable carry-on of daily life. But with the increase in development, data integrity and security has also become an important factor to take into consideration. Importantly, today’s smart phones are programmable and come with a growing set of cheap powerful embedded sensors, which are enabling the emergence of personal, group, and community scale sensing applications. The mobile sensing platform provides many facilities like, it helps to communicate to Wireless sensor networks through a mobile sensor router Which attached to a users mobile phone. It helps in analysis of the sensed data which is derived from networks by cooperating with sensor middle- ware on a remote server to capture ones contexts. It also helps in providing context aware services for mobile users of cellular telephones. In this paper, we will discuss about
different mobile sensing platforms that provides context-aware services for mobile users by accessing the surrounding wireless sensor networks. Along with this, we will briefly discuss some of the emerging sensing paradigms.
This document provides an overview of clickstream analytics and practical applications using Markov chains. It defines clickstream data as records of webpage visits and navigation paths on a website. The document discusses using Google Analytics to access clickstream data and introduces the clickstream R package for clickstream analysis. Three useful applications are highlighted: frequent path analysis, future click prediction with Markov chains, and transition probabilities with Markov chains. Markov chains are defined as a mathematical system for modeling probabilistic transitions between states. The presentation aims to demonstrate practical clickstream analysis techniques.
Performance Simulation and Analysis for LTESystem Using Human Behavior Queue ...ijwmn
Understanding the nature of traffic has been a key concern of the researchers particularly over the last
two decades and it has been noticed through extensive high quality studies that traffic found in different
kinds of IP/wireless IP networks is human operators . Despite the recent findings of real time human
behavior in measured traffic from data networks, much of the current understanding of IP traffic
modeling is still based on simplistic probability distributed traffic. Unlike most existing studies that are
primarily based on simplistic probabilistic model and traditional scheduling algorithms, this research
presents an analytical performance model for real time human behavior queue systems with intelligent
task management traffic input scheduled by a novel and promising scheduling mechanism for 4G-LTE
system. Our proposed model is substantiated on human behavior queuing system that considers real time
of traffic exhibiting homogeneous tasks characteristics. We analyze the model on the basis of newly
proposed scheduling scheme for 4G-LTE system. We present closed form expressions of expected
response times for real time traffic classes. We develop a discrete event simulator to understand the
behavior of real time of arriving tasks traffic under this newly proposed scheduling mechanism for 4GLTE system . The results indicate that our proposed scheduling algorithm provides preferential treatment
to real-time applications such as voice and video but not to that extent that data applications are starving
for bandwidth and outperforms all other scheduling schemes that are available in the market.
IRJET- Criminal Recognization in CCTV Surveillance VideoIRJET Journal
This document presents research on criminal recognition in CCTV surveillance videos using deep learning. It proposes a method where a user can upload faces of known criminals. When CCTV footage is recorded, the application will monitor for these faces. If a face is recognized, the CCTV camera will track the identified person through multiple cameras by alerting other cameras. The system segments video into images, acquires images, recognizes human faces, constructs motion flows between cameras to track individuals. Experimental results on a dataset show the system's ability to extract patterns from faces and cluster images of different angled faces. The system aims to identify criminals across surveillance camera networks.
StatsCraft 2015: The problem (Keynote) - Nir CohenStatsCraft
The document outlines the agenda for the StatsCraft Monitoring Conference, which includes understanding what monitoring is, example use cases, and learning methodologies and tools. It then discusses common problems with monitoring such as monitoring the wrong things, treating logs as secondary, lacking important data, separating monitoring from applications, reacting instead of proactively monitoring, prioritizing uptime over quality, dealing with arbitrary limits, and alert fatigue. The document argues that proper monitoring requires the right people beyond just operations and is overall hard to implement well.
Luigi Antonio Piu is an experienced Italian executive chef and culinary director with over 30 years of experience working in hotels, resorts, clubs, and restaurants around the world. He graduated from culinary school in Italy in 1972 and has held executive chef and director positions in Europe, the Middle East, and Asia Pacific. Currently, he is the Director of Executive Chef and Food & Beverage at the Abu Dhabi Country Club in the UAE, overseeing all food operations.
This document is a curriculum vitae for Dr. Robert King, a lecturer in applied psychology at University College Cork. It outlines his educational background, including a PhD in psychology from Birkbeck College and qualifications in teaching. It details his areas of teaching, university service, supervision of students, recent grant applications, employment history, academic service/consultancy, publications, conference presentations, and references. The CV provides a comprehensive overview of Dr. King's academic and professional experience and accomplishments in the field of psychology.
This document provides a list of 5 gift ideas for birthdays that will make the occasion special. The gifts include a sleek bracelet bangle to complete an outfit, a personalized mobile phone case to protect a phone, a peak-a-boo teddy bear to relive old memories, a personalized cushion as a lifetime gift, and message bottles to show unconditional love.
Project MyRecycle is a vision to promote recycling awareness starting in schools. It aims to inspire children and the community towards a cleaner Malaysia. The project will build Recycle Hubs in schools through corporate adoption to generate recycling awareness among students and the local community. It will implement ongoing educational and competitive activities to motivate recycling as a habit. The project provides solutions for corporations to adopt schools and support recycling awareness campaigns through branded merchandise and school activities.
This document outlines some potential demerits of India's Smart City plan, including that innovations for mobility and transport within smart cities need to avoid unnecessary transport and make transport more reliable for users. It also notes that India lacks the necessary capital to build 100 smart cities simultaneously, and there is a risk that corruption could become more sophisticated or the gap between rich and poor could increase if housing is not affordable for working classes.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Big Data Telco Solution by Dr. Laura Wynterwkwsci-research
Presented during the WKWSCI Symposium 2014
21 March 2014
Marina Bay Sands Expo and Convention Centre
Organized by the Wee Kim Wee School of Communication and Information at Nanyang Technological University
various studies of prediction E-consumer omaraldabash
The document discusses several studies that use recurrent neural networks to predict customer behavior from e-commerce data. Specifically, it examines research that uses RNNs to predict future customer purchases and product ratings. It also describes experiments on datasets from online retailers and reviews the results of predicting customer shopping patterns and lifetime value with RNN models.
1) The document discusses the Cyclic Model Analysis (CMA) technique for sequential pattern mining which aims to predict customer purchasing behavior.
2) CMA calculates the Trend Distribution Function from sequential patterns to model purchasing trends over time. It then uses Generalized Periodicity Detection and Trend Modeling to identify periodic patterns and construct an approximating model.
3) The Cyclic Model Analysis algorithm is applied to further analyze the patterns, dividing the domain into segments where the distribution function is increasing or decreasing and applying the other techniques recursively to fully model the cyclic behavior.
The document describes applying a multi-server queue model (M/M/C) to analyze waiting lines at bank ATMs. Data was collected on customer arrival and service times at 5 ATMs over 5 days. The M/M/C model was used to calculate performance metrics like average wait times and server utilization. It was found that the busy time was 2.6 hours while idle time was 7.4 hours, showing efficient service. The utilization rate of 26% indicated no need for additional servers. The study demonstrated how queue models can help banks evaluate ATM performance and waiting lines.
Today, enterprises are looking for innovative ways to digitally transform their businesses - a crucial step forward to remain competitive and enhance profitability. Streaming analytics is a key technology enabler that supports this effort by providing real-time insights on data in motion to help organizations gain the business intelligence they need.
Every industry has its unique challenges, especially where data is concerned. A key advantage of streaming analytics is that it can be customized to create solutions that meet the specific requirements of a particular industry. With years of expertise adapting our analytics products to customer needs, we’ve designed solution templates that target prominent pain points in specific industries.
In this webinar Nirmal will,
Introduce WSO2 Analytics Solutions and theirs use cases (finance and banking, retail, location analytics, IT operations analytics, etc.)
Demonstrate our fleet management solution that gives you the ability to
Know where your fleet is at the moment
Analyze your drivers’ behavior (do they obey speed limits and use optimal routes?)
Find the optimal routes (predict congestion)
Check whether the driver and the cargo are safe
Receive alerts on violation of rules based on Geo-fences
Explain how to customize WSO2 Analytics Solutions
Discuss how to reach out to us
A Survey on Mobile Sensing Technology and its PlatformEswar Publications
Now a days, mobile networks is increasingly becoming important part of everyday life due which there is a rapid evolution mobile phone. Mobile phone comes into a powerful sensing platform. There are many scientists which are engaged in the emerging field of mobile sensing from a variety of existing communities, such as, mobile systems, machine learning and human computer interaction. The research and development in this field is rapid resulting in indispensable carry-on of daily life. But with the increase in development, data integrity and security has also become an important factor to take into consideration. Importantly, today’s smart phones are programmable and come with a growing set of cheap powerful embedded sensors, which are enabling the emergence of personal, group, and community scale sensing applications. The mobile sensing platform provides many facilities like, it helps to communicate to Wireless sensor networks through a mobile sensor router Which attached to a users mobile phone. It helps in analysis of the sensed data which is derived from networks by cooperating with sensor middle- ware on a remote server to capture ones contexts. It also helps in providing context aware services for mobile users of cellular telephones. In this paper, we will discuss about
different mobile sensing platforms that provides context-aware services for mobile users by accessing the surrounding wireless sensor networks. Along with this, we will briefly discuss some of the emerging sensing paradigms.
This document provides an overview of clickstream analytics and practical applications using Markov chains. It defines clickstream data as records of webpage visits and navigation paths on a website. The document discusses using Google Analytics to access clickstream data and introduces the clickstream R package for clickstream analysis. Three useful applications are highlighted: frequent path analysis, future click prediction with Markov chains, and transition probabilities with Markov chains. Markov chains are defined as a mathematical system for modeling probabilistic transitions between states. The presentation aims to demonstrate practical clickstream analysis techniques.
Performance Simulation and Analysis for LTESystem Using Human Behavior Queue ...ijwmn
Understanding the nature of traffic has been a key concern of the researchers particularly over the last
two decades and it has been noticed through extensive high quality studies that traffic found in different
kinds of IP/wireless IP networks is human operators . Despite the recent findings of real time human
behavior in measured traffic from data networks, much of the current understanding of IP traffic
modeling is still based on simplistic probability distributed traffic. Unlike most existing studies that are
primarily based on simplistic probabilistic model and traditional scheduling algorithms, this research
presents an analytical performance model for real time human behavior queue systems with intelligent
task management traffic input scheduled by a novel and promising scheduling mechanism for 4G-LTE
system. Our proposed model is substantiated on human behavior queuing system that considers real time
of traffic exhibiting homogeneous tasks characteristics. We analyze the model on the basis of newly
proposed scheduling scheme for 4G-LTE system. We present closed form expressions of expected
response times for real time traffic classes. We develop a discrete event simulator to understand the
behavior of real time of arriving tasks traffic under this newly proposed scheduling mechanism for 4GLTE system . The results indicate that our proposed scheduling algorithm provides preferential treatment
to real-time applications such as voice and video but not to that extent that data applications are starving
for bandwidth and outperforms all other scheduling schemes that are available in the market.
IRJET- Criminal Recognization in CCTV Surveillance VideoIRJET Journal
This document presents research on criminal recognition in CCTV surveillance videos using deep learning. It proposes a method where a user can upload faces of known criminals. When CCTV footage is recorded, the application will monitor for these faces. If a face is recognized, the CCTV camera will track the identified person through multiple cameras by alerting other cameras. The system segments video into images, acquires images, recognizes human faces, constructs motion flows between cameras to track individuals. Experimental results on a dataset show the system's ability to extract patterns from faces and cluster images of different angled faces. The system aims to identify criminals across surveillance camera networks.
This document proposes a Mobility Prediction as a Service (MPaaS) system that leverages telecommunication networks and cloud computing facilities to predict users' future locations. It discusses three observations that motivate the research: (1) mobility prediction can improve mobile services, (2) telecom systems continuously track user locations, and (3) telecom clouds provide computing power for real-time prediction. The document then outlines the MPaaS system, formulates the prediction problem, analyzes mobility data patterns, and designs Markov-based and collective behavior pattern-based prediction algorithms. Evaluation results and the need for further deployment and dataset expansion are also discussed.
The document discusses stream processing models. It describes the key components as data sources, stream processing pipelines, and data sinks. Data sources refer to the inputs of streaming data, pipelines are the processing applied to the streaming data, and sinks are the outputs where the results are stored or sent. Stateful stream processing requires ensuring state is preserved over time and data consistency even during failures. Frameworks like Apache Spark use sources and sinks to connect to streaming data sources like Kafka and send results to other systems, acting as pipelines between different distributed systems.
This document describes 4 projects:
1. An electronic vending machine that allows customers to order items from a shop without visiting in person or using the internet by authenticating via RFID and selecting items on a graphical LCD. Orders are sent via GSM to the customer and shop for delivery.
2. An autonomous vehicle parking system that uses sensors to detect an empty parking space and perpendicularly parks the vehicle without human intervention to reduce accidents and provide driver comfort.
3. A line follower robot that uses IR sensors and a microcontroller to follow a black line on the ground and stop when it detects obstacles. This project provided practical experience with microcontrollers.
4. A case study of OTDR instruments
Nfc based stock maintainance and billing system with auto alert to customerseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Information about NCC funded projects to be submitted here today
are hereby presented in this document. In the next section, you will
read about the approaches and processes developed for MOES
card and this will be followed by short introduction to the
development of Mobile Communication Enabled Walking Stick.
A New Data Stream Mining Algorithm for Interestingness-rich Association RulesVenu Madhav
Frequent itemset mining and association rule generation is
a challenging task in data stream. Even though, various algorithms
have been proposed to solve the issue, it has been found
out that only frequency does not decides the significance
interestingness of the mined itemset and hence the association
rules. This accelerates the algorithms to mine the association
rules based on utility i.e. proficiency of the mined rules. However,
fewer algorithms exist in the literature to deal with the utility
as most of them deals with reducing the complexity in frequent
itemset/association rules mining algorithm. Also, those few
algorithms consider only the overall utility of the association
rules and not the consistency of the rules throughout a defined
number of periods. To solve this issue, in this paper, an enhanced
association rule mining algorithm is proposed. The algorithm
introduces new weightage validation in the conventional
association rule mining algorithms to validate the utility and
its consistency in the mined association rules. The utility is
validated by the integrated calculation of the cost/price efficiency
of the itemsets and its frequency. The consistency validation
is performed at every defined number of windows using the
probability distribution function, assuming that the weights are
normally distributed. Hence, validated and the obtained rules
are frequent and utility efficient and their interestingness are
distributed throughout the entire time period. The algorithm is
implemented and the resultant rules are compared against the
rules that can be obtained from conventional mining algorithms
Performance Evaluation of Trajectory Queries on Multiprocessor and Clustercsandit
In this study, we evaluate the performance of traje
ctory queries that are handled by Cassandra,
MongoDB, and PostgreSQL. The evaluation is conducte
d on a multiprocessor and a cluster.
Telecommunication companies collect a lot of data f
rom their mobile users. These data must be
analysed in order to support business decisions, su
ch as infrastructure planning. The optimal
choice of hardware platform and database can be dif
ferent from a query to another. We use data
collected from Telenor Sverige, a telecommunication
company that operates in Sweden. These
data are collected every five minutes for an entire
week in a medium sized city. The execution
time results show that Cassandra performs much bett
er than MongoDB and PostgreSQL for
queries that do not have spatial features. Statio’s
Cassandra Lucene index incorporates a
geospatial index into Cassandra, thus making Cassan
dra to perform similarly as MongoDB to
handle spatial queries. In four use cases, namely,
distance query, k-nearest neigbhor query,
range query, and region query, Cassandra performs m
uch better than MongoDB and
PostgreSQL for two cases, namely range query and re
gion query. The scalability is also good for
these two use cases.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
3. ABSTRACT
• Due to a wide range of potential applications, research on mobile
commerce has received a lot of interests from both of the industry and
academia.
• Among them, one of the active topic areas is the mining and prediction of
users’ mobile commerce behaviors such as their movements and purchase
transactions.
• In this paper, we propose a novel framework, called Mobile Commerce
Explorer (MCE), for mining and prediction of mobile users’ movements and
purchase transactions under the context of mobile commerce.
4. INTRODUCTION
• The rapid advance of wireless communication technology and the
increasing popularity of powerful portable devices, mobile users not only
can access worldwide information from anywhere at any time but also use
their mobile devices to make business transactions easily.
• E.g., via digital wallet.
• Meanwhile, the availability of location- acquisition technology.
• E.g., Global Positioning System (GPS), facilitates easy acquisition
of a moving trajectory, which records a user movement history.
• Thus, we envisage that, in the coming future of Mobile
Commerce age , some m-commerce services will be able to capture the
moving trajectories and purchase transactions of users.
5. RELATED WORK
We review and classify relevant previous studies into three categories:
• Mobile pattern mining techniques
•Mobile behavior predictions.
•Similarity measures
6. PROBLEM FORMULATION
• We first define some terms used in discussion of our research work
and then specify our research goal.
• Let MT S ¼ <ðs1 ; I1 Þ; ðs2 ; I2 Þ; ... ; ðsn ; In Þ > be a mobile
transaction sequence of length n for a user, where (st ; It ) denotes that
the user purchases the item set It in the store st ; 81 t n.
• The elements of the sequence are in ascend- ing order of time.
8. PROPOSED METHOD
Our design of a personal mobile commerce mining and prediction
framework, called MCE which incorporates three innovative techniques,
including
1) Similarity Inference Model for measuring the similarities among
stores and items, which are two basic mobile commerce entities
considered in this paper.
2) Personal Mobile Commerce Pattern Mine algorithm for efficient
discovery of mobile users’ Personal Mobile Commerce Patterns .
3) Mobile commerce Behaverior Predictor for prediction of possible
mobile user behaviors.
9. DISCOVERY OF PMCPs
• We describe the PMCP-Mine algorithm to mine the personal mobile
commerce patterns efficiently.
• The PMCP-Mine algorithm is inspired by the TJPF algorithm which is an
Apriori-like algorithm.
• However, we observe that the TJPF algorithm does not consider user
identification, which is essential for discovering personal mobile behaviors.
• In other words, the TJPF algorithm cannot be employed in our
framework.
• The PMCP-Mine algorithm is performed in a bottom-up manner.
10. PERFORMANCE OF THE PROPOSED
ALGORITHMS
• This experiment evaluates the performance of the proposed algorithms in
the MCE framework, including SIM, PMCP- Mine, and MCBP in terms of
execution time.
• The execution time for SIM remains constant while the execution time
for both PMCP-Mine and MCBP increases as the support threshold
decreases.
• Since the number of stores and items is constant after the mobile
transaction database is transformed into SID and ISD, the execution time of
SIM is constant.
• As the support threshold decreases, the number of discovered PMCPs
increases. Hence, the PMCP-Mine needs more time to mine the
PMCPs.
11. CONCLUSIONS AND FUTURE WORK
In this paper, we have proposed a novel framework, namely MCE, for
mining and prediction of mobile users movements and transactions in
mobile commerce environments. In the MCE framework, we have
proposed three major techniques:
1) SIM for measuring the similarities among stores and items.
2) PMCP-Mine algorithm for efficiently discovering mobile users
PMCPs.
3) MCBP for predicting possible mobile user behaviors.
4) To our best knowledge, this is the first work that facilitates mining and
prediction of personal mobile commerce behaviors that may recommend
stores and items previously unknown to a user.
12. References
• R.Agrawal,A.Swami, “Mining Association Rule between Sets of Items
in Large DataBases”.May-1993.
• J.Han and Y.Fu,”Discovery of Multiple-Level Association Rules in
Large Databases”.Sep-1995.