The document summarizes a panel discussion at the North Carolina Federal Advanced Technologies Symposium on May 9, 2013 about human/social sciences and advanced analytics. The panel was hosted by various government and academic organizations and discussed IntePoint's work on the DARPA ACSES project integrating multiple social science theories into an agent-based modeling simulation. IntePoint demonstrated how this simulation could be combined with infrastructure analysis to evaluate plans of action. IntePoint has over 10 years of experience transitioning research into usable modeling capabilities through projects for the US government.
Resume as of 21 October 2015. Program Manager, Project Manager, Product Manager, System Engineering, System Integration, System Final Acceptance Testing for contractual requirements, Leadership
Despite the large investments in the field of e-Government (e-Gov) around the world, little is known about the impact such investment. This is due to the lack of guidance evaluation, absence of appropriate tools to
measure the impact of e-Gov on the private sector, as well as the lack of effective management to resolve or eliminate the barriers to e-Gov services that led to the failure or delay of many projects. This paper is primarily concerned in determining the impact of e-Gov services on the private sector. A combination of Modified Technology Acceptance Model (TAM), DeLone and McLean's of IS success will be utilized as a research model and e-Gov Economics Project (eGEP) framework to measure âEfficiency, Democracy
& Effectiveness impactâ for G2B services. The research result will help e-Gov decision makers to recognize the critical factors that are responsible for G2B success, specifically factors they need to pay attention to gain the highest return on their technology investment, hence enabling them to measure the impact for e-Gov on the private sector. The paper has also demonstrated the usefulness of Structural
Equation Modeling (SEM) in analysis of small data sets and in exploratory research.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Strategic Management of Intellectual Property: R&D Investment Appraisal Using...Editor IJCATR
Â
Company executives are under increasing pressure to proactively evaluate the benefits of the huge amounts of investment into intellectual property (IP). The main goal of this paper is to propose a Dynamic Bayesian Network as a tool for modeling the forecast of the distribution of Research and Development (R&D) investment efficiency towards the strategic management of IP. Dynamic Bayesian Network provides a framework for handling the uncertainties and impression in the qualitative and quantitative data that impact the effectiveness and efficiency of investments on R&D. This paper specifies the process of creating the graphical representation using impactful variables, specifying numerical link between the variables and drawing inference from the network.
Resume as of 21 October 2015. Program Manager, Project Manager, Product Manager, System Engineering, System Integration, System Final Acceptance Testing for contractual requirements, Leadership
Despite the large investments in the field of e-Government (e-Gov) around the world, little is known about the impact such investment. This is due to the lack of guidance evaluation, absence of appropriate tools to
measure the impact of e-Gov on the private sector, as well as the lack of effective management to resolve or eliminate the barriers to e-Gov services that led to the failure or delay of many projects. This paper is primarily concerned in determining the impact of e-Gov services on the private sector. A combination of Modified Technology Acceptance Model (TAM), DeLone and McLean's of IS success will be utilized as a research model and e-Gov Economics Project (eGEP) framework to measure âEfficiency, Democracy
& Effectiveness impactâ for G2B services. The research result will help e-Gov decision makers to recognize the critical factors that are responsible for G2B success, specifically factors they need to pay attention to gain the highest return on their technology investment, hence enabling them to measure the impact for e-Gov on the private sector. The paper has also demonstrated the usefulness of Structural
Equation Modeling (SEM) in analysis of small data sets and in exploratory research.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Strategic Management of Intellectual Property: R&D Investment Appraisal Using...Editor IJCATR
Â
Company executives are under increasing pressure to proactively evaluate the benefits of the huge amounts of investment into intellectual property (IP). The main goal of this paper is to propose a Dynamic Bayesian Network as a tool for modeling the forecast of the distribution of Research and Development (R&D) investment efficiency towards the strategic management of IP. Dynamic Bayesian Network provides a framework for handling the uncertainties and impression in the qualitative and quantitative data that impact the effectiveness and efficiency of investments on R&D. This paper specifies the process of creating the graphical representation using impactful variables, specifying numerical link between the variables and drawing inference from the network.
this presentation is made for the students who finds data structures a complex subject
this will help students to grab the various topics of data structures with simple presentation techniques
best regards
BCA group
(pooja,shaifali,richa,trishla,rani,pallavi,shivani)
Standard Safeguarding Dataset - overview for CSCDUG.pptxRocioMendez59
Â
13 July, 2023 - CSCDUG Online Event
Presenting the Sector-led Standard Safeguarding Dataset
Colleagues from Data to Insight, the LA-led service for childrenâs safeguarding data professionals, are delivering a DfE-funded project in partnership with LAs to define a new âstandard safeguarding datasetâ which all LAs will be able to produce from their safeguarding information systems.
At this session, they shared what theyâve learned so far from user research with LA colleagues and discussed their early thinking about what a better standard dataset might look like. Participants shared their own thoughts about how to improve these systems and processes.
Presenters
Alistair Herbert
Alistair is the lead officer for Data to Insight, the LA-led service for childrenâs safeguarding data professionals. With a career focused on local authority childrenâs services data work, he knows about safeguarding data, information systems, and cross-organisation collaboration.
John Foster
John is a Data Manager for Data to Insight. He has supported a range of childrenâs services data work, most recently at Shropshire Council. He led Data to Insightâs project to introduce the first national benchmarking dataset for Early Help, and is the user research lead for Data to Insightâs Standard Safeguarding Dataset project.
Rob Harrison and Joe Cornford-Hutchings
Rob and Joe are new Data Managers joining Data to Insight from the private and public sector respectively. They bring between them a wealth of experience and technical expertise, and will be working together to support design and implementation of the new Standard Safeguarding Dataset through 2023-24.
In the present paper, applicability and
capability of A.I techniques for effort estimation prediction has
been investigated. It is seen that neuro fuzzy models are very
robust, characterized by fast computation, capable of handling
the distorted data. Due to the presence of data non-linearity, it is
an efficient quantitative tool to predict effort estimation. The one
hidden layer network has been developed named as OHLANFIS
using MATLAB simulation environment.
Here the initial parameters of the OHLANFIS are
identified using the subtractive clustering method. Parameters of
the Gaussian membership function are optimally determined
using the hybrid learning algorithm. From the analysis it is seen
that the Effort Estimation prediction model developed using
OHLANFIS technique has been able to perform well over normal
ANFIS Model.
Effective performance engineering is a critical factor in delivering meaningful results. The implementation must be built into every aspect of the business, from IT and business management to internal and external customers and all other stakeholders. Convetit brought together ten experts in the field of performance engineering to delve into the trends and drivers that are defining the space. This Foresights discussion will directly influence Business and Technology Leaders that are looking to stay ahead of the challenges they face with delivering high performing systems to their end users, today and in the next 2-5 years.
A Framework for Geospatial Web Services for Public Health by Dr. Leslie LenertWansoo Im
Â
A Framework for Geospatial Web Services for Public Health
by Leslie Lenert, MD, MS, FACMI, Director
National Center for Public Health Informatics, CCHIS, CDC
June 8 2009 URISA Public Health Conference
uploaded by Wansoo Im, Ph.D.
URISA Membership Committee Chair
http://www.gisinpublichealth.org
this presentation is made for the students who finds data structures a complex subject
this will help students to grab the various topics of data structures with simple presentation techniques
best regards
BCA group
(pooja,shaifali,richa,trishla,rani,pallavi,shivani)
Standard Safeguarding Dataset - overview for CSCDUG.pptxRocioMendez59
Â
13 July, 2023 - CSCDUG Online Event
Presenting the Sector-led Standard Safeguarding Dataset
Colleagues from Data to Insight, the LA-led service for childrenâs safeguarding data professionals, are delivering a DfE-funded project in partnership with LAs to define a new âstandard safeguarding datasetâ which all LAs will be able to produce from their safeguarding information systems.
At this session, they shared what theyâve learned so far from user research with LA colleagues and discussed their early thinking about what a better standard dataset might look like. Participants shared their own thoughts about how to improve these systems and processes.
Presenters
Alistair Herbert
Alistair is the lead officer for Data to Insight, the LA-led service for childrenâs safeguarding data professionals. With a career focused on local authority childrenâs services data work, he knows about safeguarding data, information systems, and cross-organisation collaboration.
John Foster
John is a Data Manager for Data to Insight. He has supported a range of childrenâs services data work, most recently at Shropshire Council. He led Data to Insightâs project to introduce the first national benchmarking dataset for Early Help, and is the user research lead for Data to Insightâs Standard Safeguarding Dataset project.
Rob Harrison and Joe Cornford-Hutchings
Rob and Joe are new Data Managers joining Data to Insight from the private and public sector respectively. They bring between them a wealth of experience and technical expertise, and will be working together to support design and implementation of the new Standard Safeguarding Dataset through 2023-24.
In the present paper, applicability and
capability of A.I techniques for effort estimation prediction has
been investigated. It is seen that neuro fuzzy models are very
robust, characterized by fast computation, capable of handling
the distorted data. Due to the presence of data non-linearity, it is
an efficient quantitative tool to predict effort estimation. The one
hidden layer network has been developed named as OHLANFIS
using MATLAB simulation environment.
Here the initial parameters of the OHLANFIS are
identified using the subtractive clustering method. Parameters of
the Gaussian membership function are optimally determined
using the hybrid learning algorithm. From the analysis it is seen
that the Effort Estimation prediction model developed using
OHLANFIS technique has been able to perform well over normal
ANFIS Model.
Effective performance engineering is a critical factor in delivering meaningful results. The implementation must be built into every aspect of the business, from IT and business management to internal and external customers and all other stakeholders. Convetit brought together ten experts in the field of performance engineering to delve into the trends and drivers that are defining the space. This Foresights discussion will directly influence Business and Technology Leaders that are looking to stay ahead of the challenges they face with delivering high performing systems to their end users, today and in the next 2-5 years.
A Framework for Geospatial Web Services for Public Health by Dr. Leslie LenertWansoo Im
Â
A Framework for Geospatial Web Services for Public Health
by Leslie Lenert, MD, MS, FACMI, Director
National Center for Public Health Informatics, CCHIS, CDC
June 8 2009 URISA Public Health Conference
uploaded by Wansoo Im, Ph.D.
URISA Membership Committee Chair
http://www.gisinpublichealth.org
This proposes is a Privacy-aware Personal Data Storage,
able to automatically take privacyaware decisions on third parties access requestsin
accordance with user preferences. The system relies on active learning complemented
with strategies to strengthen user privacy protection. As discussed in the paper, we run
several experiments on a realistic dataset exploiting a group of 360 evaluators. The
obtained results show the effectiveness of the proposed approach. We plan to extend
this work along several directions. First, we are interested to investigate how P-PDS
could scale in the IoT scenario, where access requests decision might depend also on
contexts, not only on user preferences. Also, we would like to integrate P-PDS with
cloud computing services (e.g., storage and computing) so as to design a more powerful
P-PDS by, at the same time, protecting users privacy.
The software development process is complete for computer project analysis, and it is important to the evaluation of the random project. These practice guidelines are for those who manage big-data and big-data analytics projects or are responsible for the use of data analytics solutions. They are also intended for business leaders and program leaders that are responsible for developing agency capability in the area of big data and big data analytics .
For those agencies currently not using big data or big data analytics, this document may assist strategic planners, business teams and data analysts to consider the value of big data to the current and future programs.
This document is also of relevance to those in industry, research and academia who can work as partners with government on big data analytics projects.
Technical APS personnel who manage big data and/or do big data analytics are invited to join the Data Analytics Centre of Excellence Community of Practice to share information of technical aspects of big data and big data analytics, including achieving best practice with modeling and related requirements. To join the community, send an email to the Data Analytics Centre of Excellence
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Human/Social Sciences/Cultural & Behavioral Dynamics and Advanced Analytics
1. North Carolina Federal Advanced Technologies Symposium
May 9, 2013
Human/Social Sciences/Cultural & Behavioral Dynamics and Advanced Analytics Panel
Hosted by:
Office of Senator Richard Burr
NC Military Business Center
NC Military Foundation
Institute for Defense & Business
University of North Carolina System
Reception Sponsor:
Bronze Sponsor:
2. Š IntePoint LLC. Proprietary
ď§ IntePoint partnered with the Complex Systems Institute (UNCC), Oak
Ridge National Lab, and Georgia Tech on for the ACSES DARPA
project
ď§ We demonstrated the capability to computationally combine
and compare multiple social science theories to provide
robust plausible futures
ď§ The multi-model CAS simulation was incorporated into Vu, an
interdependency consequence analysis capability to extend
the results to include critical infrastructure
ď§ Team is currently authoring a book on complicated CAS
modeling techniques
ď§ The ACSES model has been applied to Mali and Kenya for an ERDC
program
ď§ We continue to drive to a rigorous and actionable modeling
framework that supports more granular, less tightly coupled agent
models
ď§ This unique approach is immediately applicable for training exercises
and JIPOE supporting analysis
ď§ Will require 2 â 3 years of additional development and V&V before
being deployable as a planning and campaign tool.
ACSES project review, ongoing
HSCB capabilities, applicability
1
Bottom Line Up Front
Mark Armstrong, President
IntePoint, LLC.
Cell â 704.502.1655
Mark.Armstrong@IntePoint.com
3. Š IntePoint LLC. Proprietary
For the DARPA ACSES project the team developed a platform that integrated
multiple, alternative social science theories into a unified simulation
framework. Additionally, using existing capabilities, we integrated that CAS
model with an infrastructure analysis for a PMESII/COA analysis.
ď§ Social science theories included citizen allegiance and ideology, behavior of
citizen agents, and social mobilization theories
ď§ Demonstrated quantifiable and realistic effects and identified threshold
events for simulation of nonlinear phenomena including both expected and
unexpected results
ď§ Simulates dynamic networks of repeated feedback systems among agents
ď§ Exposes causal relationships that support analysis and insight for DIME
options
The team leveraged the Vu
interdependency analysis
capability for a DARPA project
that incorporated multiple social
science (CAS/agent) leadership
models to obtain a more robust
understanding of population
responses to events/COAs
2
ACSES HSCB &
Interdependency
Modeling
and Analysis
COA
Result
Summary
Detailed
Temporal
Analysis
Multiple
Logical Views of
Effects of COA
Events
2D/3D Map
and Imagery
of COA
Events
Details of
interaction
s
Plausible outcome of social impact in
Afghanistan
Details of
interaction
s
Details of
interactions
4. Š IntePoint LLC. Proprietary
ď§ IntePoint has teamed with UNC-Charlotte since 2003 to provide the
integrated modeling and simulation capability for a USG program by
translating research into actionable tools.
ď§ IntePoint has experience in net-centric and desktop software
development services in both classified and non-classified environments
ď§ Ideas have been taken from initial concept through research, design,
development, testing, DODIIS accreditation and deployment (TRL 1 â 9)
ď§ IntePoint has a 100% success record in completing all contract deliverables,
within-budget and often ahead of schedule
ď§ The USG invested >$14M in cumulative funding to develop the capability
for interdependency analysis and modeling & simulation capability used
to support functional defeat and system of systems analysis
ď§ By capturing the intellectual property created through these contracts,
IntePoint has independently developed a web-based COTS product (Vu),
obtained three patents, has several pending patents, and 15+ publications
in academic literature
ď§ Our interdependency experience has been applied in multiple DOD
agencies, DHS, and commercially at Wachovia Bank and Wells Fargo
ď§ Recently signed a teaming agreement to leverage Vu to support state of
the art monitoring and analysis for the electric power grid
The IntePoint team has 10+
years of successful collaboration
in transitioning ideas through
research into useful capabilities.
3
Interdependency
Analytics bona fides
5. Š IntePoint LLC. Proprietary
ď§ For a USG program, the team researched, designed, and developed an accredited and
deployed interdependency analysis capability used to support system of systems analysis
ď§ Vu is a domain agnostic analytics capability for integrated modeling and simulation that
helps analysts to better understand multiple complex, interdependent infrastructure
networks (e.g., electrical power, road/rail, petroleum & telecoms, etc.) in context (E.g.,
functional, spatial, temporal, socialâŚ)
ď§ Vu helps analysts to visual, understand, and explore:
ď§ Network behaviors
ď§ Network interdependency behaviors
ď§ Cascading effects
ď§ Disruptive and reconstructive events
ď§ Vu supports a broad range of objectives including vulnerability analysis, impact analysis,
training, reconstruction, stability operations
ď§ Visual analytics consist of geospatial, temporal, and logical network graphs
ď§ Extensible platform designed to modularly incorporate external domain models,
relationship modules and data
ď§ Effective in both high and low fidelity data environments
IntePoint is a web enabled
interdependency M&S and
analytics for multiple complex
networks
4
Vu Overview
6. Š IntePoint LLC. Proprietary
ď§ The CSI team has several sets of proven
technologies that apply to the study of the impacts
of changes in commodity flows
ď§ CAS using agent based models
ď§ Vu interdependency analytics
ď§ Fusion integration of multiple agent models The IntePoint/CSI technology suite
has components that have been
proven in previous research and
deployment. The capabilities range
from TRL 1 â 9.
5
Existing Technology
8. 1. Humans are more
important than
hardware.
2. Quality is better than
quantity.
3. Special Operations
Forces cannot be mass
produced.
4. Competent Special
Operations Forces
cannot be created after
emergencies occur.
5. Most special operations
require non-SOF
assistance.
12. 7
DART
Data Architecture Requirements Tool
Power of Simulation for Better Solutions
Support for decisions of critical issues that may be emerging, rapidly changing,
and/or not easily defined.
Automation with best practices to deliver data assessments and planning support
in significantly less time and cost than traditional methods.
Capabilities
Domain Applications
Accessible through a web browser consisting of standard HTML and Javascript
using a PC (laptop), smart phone, or tablet.
Supported by U.S. Patent No. 8,423,498;
⢠Front End Analysis
⢠Data Operations
⢠Analysis
⢠Data Operations
⢠Execution Planning
⢠Program Management
⢠Front End Analysis
⢠Program Assessment
⢠Gap Analysis
⢠Strategic Planning
⢠Acquisition Planning
⢠Media Analysis
⢠Organizational Analysis
⢠Survey services
⢠Facilitation Support
⢠Language & Culture
16. 11
DART
HSBC Support
Determine:
⢠Scenario based issues that are important at different levels of fidelity
⢠Obtain inputs from worldwide sources
⢠Real time assessment of selected issues
Provide visualization of quantitative data:
⢠Determine gaps to be filled
⢠How the importance and status for critical issues change over-time
Support:
⢠Online preparing, monitoring, and reporting of Plans
⢠Track changes and provide historical reviews
⢠Data downloads, including PDF, CVS, and summary status charts
⢠Online preparation of next generation plans with linkages to current and
historical plans