05 Bronner Richards
•Download as PPT, PDF•
0 likes•443 views
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this technology can extract knowledge to help the Army make more informed decisions for combating insurgencies.
Report
Share
Report
Share
![Agenda ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommended
Thomas
Keerthi Thomas is a PhD student at the Open University, supervised by Prof. Bashar Nuseibeh, Dr. Arosha Bandara, and Mr. Blaine Price. Her research focuses on eliciting and analyzing users' privacy requirements for mobile applications. Previous work has shown privacy requirements vary based on users' changing contexts. However, most existing approaches do not address challenges of understanding privacy needs for mobile apps. Thomas proposes a systematic approach using a user-centric model combining contextual and interaction data to capture how privacy requirements are "distilled" from empirical studies of mobile social networking app users.
Practical Approaches to Sharing Information
The document summarizes the results of Raytheon's efforts to improve their information management and search capabilities. It found that most information was unstructured and not tagged, leading to duplication and difficulty finding information. User surveys identified needs like filtering searches by attributes. Raytheon implemented taxonomies in key areas and saw improvements like increased search and category usage after launching an updated search tool.
Reality Mining
Uma visão geral sobre Reality Mining e pesquisas que foram e estão sendo desenvolvidas neste contexto. O conteúdo dos slides foram extraídos dos estudos e experimentos do MIT Media Lab (http://hd.media.mit.edu/) dirigido pelo Prof. Alex Pentland
Research Proposal
This document describes a research study exploring the development of computational algorithmic thinking (CAT) skills in African American middle school girls over three years through a program called SCAT. The study aims to understand how the girls' CAT skills develop over time, challenges they may face, and how participating in SCAT impacts their views of computer science and their self-efficacy. Data will be collected through journals, surveys, videos and artifacts to analyze the development of the girls' CAT skills, problem-solving, confidence and ability to apply these skills socially. The goal is to provide insights on better supporting students of color in developing CAT skills and improving computer science education.
Qual, Mixed, Machine and Everything in Between
1) The document discusses qualitative research methods and computer-assisted qualitative data analysis software. It explores the researcher's background and experience with both qualitative and mixed methods approaches.
2) It describes both traditional and newer computer software for qualitative data analysis, noting both benefits like organization and efficiency, as well as concerns around over-reliance on software.
3) Collaboration, measurement, human and machine learning are discussed. Iterative processes of human coding and machine learning are emphasized to improve classification over time.
Semantics in the Enterprise: Roles & Capabilities
The document provides information about various roles that are important for an expert semantic technology team, including information scientists, information architects, cognitive scientists, developers, business analysts, leaders, project managers, security experts, and legal advisors, briefly outlining some of the key responsibilities for each role.
Empowering the Intelligent Enterprise
The document discusses how semantic technologies can empower the intelligent enterprise by providing meaningful context and connections across vast amounts of data. It highlights trends toward hybrid human-AI solutions that leverage both manual and automated techniques to generate rich metadata and entity relationships. Finally, it describes how semantic approaches can help organizations gain strategic insights, shorten decision cycles, and power mobility by making relevant information accessible anywhere.
Reality Mining (Nathan Eagle)
Reality mining aims to map an organization's cognitive infrastructure by capturing detailed data on human networks using sensors. It analyzes conversations, topics, locations and relationships between individuals to infer expertise, social networks and how communication may change. This could help with applications like knowledge management, team formation and understanding global influences in an organization. However, it also raises privacy concerns that would need to be addressed.
Recommended
Thomas
Keerthi Thomas is a PhD student at the Open University, supervised by Prof. Bashar Nuseibeh, Dr. Arosha Bandara, and Mr. Blaine Price. Her research focuses on eliciting and analyzing users' privacy requirements for mobile applications. Previous work has shown privacy requirements vary based on users' changing contexts. However, most existing approaches do not address challenges of understanding privacy needs for mobile apps. Thomas proposes a systematic approach using a user-centric model combining contextual and interaction data to capture how privacy requirements are "distilled" from empirical studies of mobile social networking app users.
Practical Approaches to Sharing Information
The document summarizes the results of Raytheon's efforts to improve their information management and search capabilities. It found that most information was unstructured and not tagged, leading to duplication and difficulty finding information. User surveys identified needs like filtering searches by attributes. Raytheon implemented taxonomies in key areas and saw improvements like increased search and category usage after launching an updated search tool.
Reality Mining
Uma visão geral sobre Reality Mining e pesquisas que foram e estão sendo desenvolvidas neste contexto. O conteúdo dos slides foram extraídos dos estudos e experimentos do MIT Media Lab (http://hd.media.mit.edu/) dirigido pelo Prof. Alex Pentland
Research Proposal
This document describes a research study exploring the development of computational algorithmic thinking (CAT) skills in African American middle school girls over three years through a program called SCAT. The study aims to understand how the girls' CAT skills develop over time, challenges they may face, and how participating in SCAT impacts their views of computer science and their self-efficacy. Data will be collected through journals, surveys, videos and artifacts to analyze the development of the girls' CAT skills, problem-solving, confidence and ability to apply these skills socially. The goal is to provide insights on better supporting students of color in developing CAT skills and improving computer science education.
Qual, Mixed, Machine and Everything in Between
1) The document discusses qualitative research methods and computer-assisted qualitative data analysis software. It explores the researcher's background and experience with both qualitative and mixed methods approaches.
2) It describes both traditional and newer computer software for qualitative data analysis, noting both benefits like organization and efficiency, as well as concerns around over-reliance on software.
3) Collaboration, measurement, human and machine learning are discussed. Iterative processes of human coding and machine learning are emphasized to improve classification over time.
Semantics in the Enterprise: Roles & Capabilities
The document provides information about various roles that are important for an expert semantic technology team, including information scientists, information architects, cognitive scientists, developers, business analysts, leaders, project managers, security experts, and legal advisors, briefly outlining some of the key responsibilities for each role.
Empowering the Intelligent Enterprise
The document discusses how semantic technologies can empower the intelligent enterprise by providing meaningful context and connections across vast amounts of data. It highlights trends toward hybrid human-AI solutions that leverage both manual and automated techniques to generate rich metadata and entity relationships. Finally, it describes how semantic approaches can help organizations gain strategic insights, shorten decision cycles, and power mobility by making relevant information accessible anywhere.
Reality Mining (Nathan Eagle)
Reality mining aims to map an organization's cognitive infrastructure by capturing detailed data on human networks using sensors. It analyzes conversations, topics, locations and relationships between individuals to infer expertise, social networks and how communication may change. This could help with applications like knowledge management, team formation and understanding global influences in an organization. However, it also raises privacy concerns that would need to be addressed.
"Reproducibility from the Informatics Perspective"
Dr. Altman will provide expert comment on the need for informatics modeling as part of the National Academies workshop: Statistical Challenges in Assessing and Fostering the Reproducibility of Scientific Results
This workshop focuses on the topic of addressing statistical challenges in assessing and fostering the reproducibility of scientific results by examining three issues from a statistical perspective: the extent of reproducibility, the causes of reproducibility failures, and potential remedies.
Multi-objective NSGA-II based community detection using dynamical evolution s...
Community detection is becoming a highly demanded topic in social networking-based applications. It involves finding the maximum intraconnected and minimum inter-connected sub-graphs in given social networks. Many approaches have been developed for community’s detection and less of them have focused on the dynamical aspect of the social network. The decision of the community has to consider the pattern of changes in the social network and to be smooth enough. This is to enable smooth operation for other community detection dependent application. Unlike dynamical community detection Algorithms, this article presents a non-dominated aware searching Algorithm designated as non-dominated sorting based community detection with dynamical awareness (NDS-CD-DA). The Algorithm uses a non-dominated sorting genetic algorithm NSGA-II with two objectives: modularity and normalized mutual information (NMI). Experimental results on synthetic networks and real-world social network datasets have been compared with classical genetic with a single objective and has been shown to provide superiority in terms of the domination as well as the convergence. NDS-CD-DA has accomplished a domination percentage of 100% over dynamic evolutionary community searching DECS for almost all iterations.
Managing Confidential Information – Trends and Approaches
Personal information is ubiquitous and it is becoming increasingly easy to link information to individuals. Laws, regulations and policies governing information privacy are complex, but most intervene through either access or anonymization at the time of data publication.
Trends in information collection and management -- cloud storage, "big" data, and debates about the right to limit access to published but personal information complicate data management, and make traditional approaches to managing confidential data decreasingly effective.
This session presented as part of the the Program on Information Science seminar series, examines trends information privacy. And the session will also discuss emerging approaches and research around managing confidential research information throughout its lifecycle.
Linking Data to Publications through Citation and Virtual Archives
This document discusses linking data to publications through citation and virtual archives. It argues that data citation and sharing infrastructure are necessary for scientific reproducibility and open data. It outlines elements of data management plans and requirements for data sharing infrastructure, including persistence, provenance, access control and incentives. The document advocates for data citations as first-class objects and emerging practices like assigning DOIs to datasets. It presents several use cases for the Dataverse network, a virtual archive designed for research data sharing through federated and organizational models.
Eliciting and Visualising Trust Expectations using Persona Trust Characterist...
Developers and users rely on trust to simplify complexity when building and using software. Unfortunately, the invisibility of trust and the richness of a system's context of use means that factors influencing trust are difficult to see, and assessing its implications before a system is built is complex and time-consuming. This paper presents an approach for eliciting and visualising differences between trust expectations using persona cases, goal models, and complementary tool support. We evaluate our approach by using it to identify misplaced trust expectations in a software infrastructure by its users and application developers.
Reproducibility from an infomatics perspective
Scientific reproducibility is most viewed through a methodological or statistical lens, and increasingly, through a computational lens. Over the last several years, I've taken part in collaborations to that approach reproducibility from the perspective of informatics: as a flow of information across a lifecycle that spans collection, analysis, publication, and reuse.
These slides sketch of this approach, and were presented at a recent workshop on reproducibility at the National Academy of Sciences, and at one our Program on Information Science brown bag talks. See: informatics.mit.edu
Deep Neural Networks for Machine Learning
This is the slideshow for a presentation I gave as part of my graduate coursework at the Institute for Innovation and Public Purpose at University College London (UCL IIPP). Drawing on the work of IIPP professors including Carlota Perez (techno-economic paradigms), Mariana Mazzucato (“The Entrepreneurial State”), and Tim O’Reilly, I evaluate the innovation trajectory of Deep Neural Networks as a method of machine learning. I trace the history of machine learning to its present-day and conclude that while Deep Neural Networks have not yet reached technological maturity, they are already starting to encounter barriers to exponential growth and innovation. These slides were designed to be read independently from the spoken portion. If you found this useful or interesting, please message me on LinkedIn! - Justin Beirold
Semantics for Bioinformatics: What, Why and How of Search, Integration and An...
Amit Sheth's Keynote at Semantic Web Technologies for Science and Engineering Workshop (held in conjunction with ISWC2003), Sanibel Island, FL, October 20, 2003.
Model bias in AI
We now live in a world where we trust intelligent systems blindly, believing in their rationality and objectivity. However, in reality this is far from the truth.
In this talk given at the City.AI Singapore chapter, we explored the nature, implications and handling strategies for Model Bias in AI.
BROWN BAG TALK WITH MICAH ALTMAN, SOURCES OF BIG DATA FOR SOCIAL SCIENCES
This talk, is part of the MIT Program on Information Science brown bag series (http://informatics.mit.edu)
This talk reviews emerging big data sources for social scientific analysis and explores the challenges these present. Many of these sources pose distinct challenges for acquisition, processing, analysis, inference, sharing, and preservation.
Dr Micah Altman is Director of Research and Head/Scientist, Program on Information Science for the MIT Libraries, at the Massachusetts Institute of Technology. Dr. Altman is also a Non-Resident Senior Fellow at The Brookings Institution. Prior to arriving at MIT, Dr. Altman served at Harvard University for fifteen years as the Associate Director of the Harvard-MIT Data Center, Archival Director of the Henry A. Murray Archive, and Senior Research Scientist in the Institute for Quantitative Social Sciences.
Dr. Altman conducts research in social science, information science and research methods -- focusing on the intersections of information, technology, privacy, and politics; and on the dissemination, preservation, reliability and governance of scientific knowledge.
BROWN BAG TALK WITH MICAH ALTMAN INTEGRATING OPEN DATA INTO OPEN ACCESS JOURNALS
This talk, is part of the MIT Program on Information Science brown bag series (http://informatics.mit.edu)
This talk discusses findings from an analysis of data sharing and citation policies in Open Access journals and describes a set of novel tools for open data publication in open access journal workflows. Bring your lunch and enjoy a discussion fit for scholars, Open Access fans, and students alike.
Dr Micah Altman is Director of Research and Head/Scientist, Program on Information Science for the MIT Libraries, at the Massachusetts Institute of Technology.
Rainey resume 2 25-2021
Larry B. Rainey has extensive experience as a space systems engineer specializing in modeling and simulation. He has held positions at various government contractors and universities. Some of his accomplishments include authoring several pioneering textbooks, developing new modeling techniques, and initiating the nation's first collaborative organization focused on emergent behavior in systems of systems.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this technology can extract knowledge to help the Army make more informed decisions for combating insurgencies.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this technology can extract knowledge to help the Army make more informed decisions for combating insurgencies.
T R A I N I N G M O D U L E K K O F F I C E
This document provides information about Union Pacific Limited (UPL), a New Zealand-based online forex brokerage company. It outlines UPL's trading systems and services, including a fully automated trading platform available 24/5 with low fees. It also describes Optimum Management Services, the company appointed to promote UPL's platform through client registration, education, and account management. Details are given on forex trading methodology, available currency pairs, account types, position size, and the online platform for monitoring trades and making withdrawals. Risk management procedures like stop orders and margin calls are also summarized.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapidly making accurate decisions to improve outcomes over time. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, and a 3D virtual world to model and observe insurgency behavior and assess outcomes of decisions.
ElectroHex
This is a Product Brief of an electronic card game i designed together with Ziv KItaro and Avi Sabbag at Cedar Design Group.
Corporate governance in psu
The document discusses corporate governance guidelines for Central Public Sector Undertakings (CPSEs) in India as issued by the Department of Public Enterprises (DPE). It outlines the composition and functions of boards of directors, audit committees, and remuneration committees according to DPE guidelines. However, some CPSEs are not fully complying with the guidelines regarding representation of independent directors and functioning of audit committees. Improving governance of CPSEs could help raise their performance and competitiveness.
A Survey of Building Robust Business Models in Pervasive Computing
Pervasive computing is one of the most challenging and difficult computing domains nowadays. It includes many architectural challenges like context awareness, adaptability, mobility, availability, and scalability. There are currently few approaches which provide methodologies to build suitable architectural models that are more suited to the nature of the pervasive domain. This area still needs a lot of enhancements in order to let the software business analyst (BA) cognitively handle pervasive applications by using suitable tasks and tools. Accordingly, any proposed research topic that would attempt to define a development methodology can greatly help BAs in modeling pervasive applications with high efficiency. In this survey paper we address some of the most significant and current software engineering practices that are proving to be most effective in building pervasive systems.
For citation:
Osama M. Khaled and Hoda M. Hosny. A Survey of Building Robust Business Models in Pervasive Computing. An accepted paper in the 2014 World Congress in Computer Science Computer Engineering and Applied Computing
Below are various theories and models that have been used and can
Below are various theories and models that have been used and can be used in research (from Dr. Steve Brown)
Behavioral et. al.
Absorptive capacity Theory
Accountability Theory
Activity Theory
Adaptive Structuration Theory
Administrative Behavior Theory
Argumentation Theory
Asch Conformity
Behavioral Decision Model
Belief Action Outcome Framework
Chaos Theory
Cognitive Fit Theory
Cognitive Load Theory
Cognitive Behavioral Therapy
Classical Conditioning
Conditioned Emotional Response
Cognitive Dissonance
Cognitive “purposive” Behaviorism
Consequentialist Ethics
Critical Theory
Csíkszentmihályi’s Flow
Cultural Theory
Deontological Ethics
Diffusion of Innovations Theory
Dynamic Capabilities
Distributed Cognitions Theory
Embodied social presence theory
Equity theory
Evolutionary theory
Eysenck’s Theory
Expectancy-value theory
Expectation Confirmation Theory
False Memory Syndrome
Field Theory
Fishbein's Attitude
General Deterrence Theory
Gestalt Theory of Personality
General Strain theory
Goal Contagion Theory
Gompertz Model (based upon Social Conflict Theory)
Grounded Theory
Hermeneutics
Illusion of Control
Impression Management Theory
Information Processing Theory
Impression Management Theory
Information Asymmetry Theory
Information Security Management Theory
Institutional Theory
Integrated Systems Theory
Keller's Motivational Model
Language action perspective
Law of Effect
Law of Emotion
Learned Helplessness Theory
McClelland’s Needs Theory
Neutralization Theory
Operant Conditioning
Mitchel’s Personality theory
Prospect Theory
Protection Motivation Theory
Self Determination Theory
Self-Efficacy Theory
Social Action Theory
Social Conflict Theory
Social Cognitive Theory
Social Exchange Theory
Social Identity Theory
Social Influence Theory
Social Learning Theory
Socio Technical Systems Theory
Task Closure Theory
Technology Acceptance Model
Technology Threat Avoidance Theory
Theory of Contextualism
Theory of Contiguity
Theory of Equipotentiality
Theory of Planned Behavior
Theory of Protection Motivation
Theory of Reasoned Action
Theory of Planned Behavior
Trait Theory
Virtue Ethics
Unified theory of acceptance and use of technology (UTAUT)
Universal Law of Generalization
Non-Behavioral
Accountability obfuscation
Actor Network theory
Attack Tree and Vague Sets
Bayes Theorem
Bayesian Inference
Bayesian Belief Network
Bayesian Networks
Boundary Object Theory
Broadbent’s Filter Theory Model
Complexity Theory
Cooperative game theory
Conformity Theory
Critical Realism Theory
Customer Based Discrepancy Theory
Customer Focus Theory
Deferred Action Theory
Design Theory
Elaboration Likelihood Model
Fit-Viability Theory
Flow Theory
Game Theory
Garbage Can Theory
General Systems Theory
General Deterrence Theory
Hebbian Theory
Human Agency Theory
Information Warfare
Institutional theory
International Information Systems Theory
Internationalization Theory
Information Technology Portfolio
Knowledge Management
Noncooperative game theory
Organization Based Access C ...
Social media platform and Our right to privacy
The advancement of Information Technology has hastened the ability to disseminate information across the globe. In particular, the recent trends in ‘Social Networking’ have led to a spark in personally sensitive information being published on the World Wide Web. While such socially active websites are creative tools for expressing one’s personality it also entails serious privacy concerns. Thus, Social Networking websites could be termed a double edged sword. It is important for the law to keep abreast of these developments in technology. The purpose of this paper is to demonstrate the limits of extending existing laws to battle privacy intrusions in the Internet especially in the context of social networking. It is suggested that privacy specific legislation is the most appropriate means of protecting online privacy. In doing so it is important to maintain a balance between the competing right of expression, the failure of which may hinder the reaping of benefits offered by Internet technology
More Related Content
What's hot
"Reproducibility from the Informatics Perspective"
Dr. Altman will provide expert comment on the need for informatics modeling as part of the National Academies workshop: Statistical Challenges in Assessing and Fostering the Reproducibility of Scientific Results
This workshop focuses on the topic of addressing statistical challenges in assessing and fostering the reproducibility of scientific results by examining three issues from a statistical perspective: the extent of reproducibility, the causes of reproducibility failures, and potential remedies.
Multi-objective NSGA-II based community detection using dynamical evolution s...
Community detection is becoming a highly demanded topic in social networking-based applications. It involves finding the maximum intraconnected and minimum inter-connected sub-graphs in given social networks. Many approaches have been developed for community’s detection and less of them have focused on the dynamical aspect of the social network. The decision of the community has to consider the pattern of changes in the social network and to be smooth enough. This is to enable smooth operation for other community detection dependent application. Unlike dynamical community detection Algorithms, this article presents a non-dominated aware searching Algorithm designated as non-dominated sorting based community detection with dynamical awareness (NDS-CD-DA). The Algorithm uses a non-dominated sorting genetic algorithm NSGA-II with two objectives: modularity and normalized mutual information (NMI). Experimental results on synthetic networks and real-world social network datasets have been compared with classical genetic with a single objective and has been shown to provide superiority in terms of the domination as well as the convergence. NDS-CD-DA has accomplished a domination percentage of 100% over dynamic evolutionary community searching DECS for almost all iterations.
Managing Confidential Information – Trends and Approaches
Personal information is ubiquitous and it is becoming increasingly easy to link information to individuals. Laws, regulations and policies governing information privacy are complex, but most intervene through either access or anonymization at the time of data publication.
Trends in information collection and management -- cloud storage, "big" data, and debates about the right to limit access to published but personal information complicate data management, and make traditional approaches to managing confidential data decreasingly effective.
This session presented as part of the the Program on Information Science seminar series, examines trends information privacy. And the session will also discuss emerging approaches and research around managing confidential research information throughout its lifecycle.
Linking Data to Publications through Citation and Virtual Archives
This document discusses linking data to publications through citation and virtual archives. It argues that data citation and sharing infrastructure are necessary for scientific reproducibility and open data. It outlines elements of data management plans and requirements for data sharing infrastructure, including persistence, provenance, access control and incentives. The document advocates for data citations as first-class objects and emerging practices like assigning DOIs to datasets. It presents several use cases for the Dataverse network, a virtual archive designed for research data sharing through federated and organizational models.
Eliciting and Visualising Trust Expectations using Persona Trust Characterist...
Developers and users rely on trust to simplify complexity when building and using software. Unfortunately, the invisibility of trust and the richness of a system's context of use means that factors influencing trust are difficult to see, and assessing its implications before a system is built is complex and time-consuming. This paper presents an approach for eliciting and visualising differences between trust expectations using persona cases, goal models, and complementary tool support. We evaluate our approach by using it to identify misplaced trust expectations in a software infrastructure by its users and application developers.
Reproducibility from an infomatics perspective
Scientific reproducibility is most viewed through a methodological or statistical lens, and increasingly, through a computational lens. Over the last several years, I've taken part in collaborations to that approach reproducibility from the perspective of informatics: as a flow of information across a lifecycle that spans collection, analysis, publication, and reuse.
These slides sketch of this approach, and were presented at a recent workshop on reproducibility at the National Academy of Sciences, and at one our Program on Information Science brown bag talks. See: informatics.mit.edu
Deep Neural Networks for Machine Learning
This is the slideshow for a presentation I gave as part of my graduate coursework at the Institute for Innovation and Public Purpose at University College London (UCL IIPP). Drawing on the work of IIPP professors including Carlota Perez (techno-economic paradigms), Mariana Mazzucato (“The Entrepreneurial State”), and Tim O’Reilly, I evaluate the innovation trajectory of Deep Neural Networks as a method of machine learning. I trace the history of machine learning to its present-day and conclude that while Deep Neural Networks have not yet reached technological maturity, they are already starting to encounter barriers to exponential growth and innovation. These slides were designed to be read independently from the spoken portion. If you found this useful or interesting, please message me on LinkedIn! - Justin Beirold
Semantics for Bioinformatics: What, Why and How of Search, Integration and An...
Amit Sheth's Keynote at Semantic Web Technologies for Science and Engineering Workshop (held in conjunction with ISWC2003), Sanibel Island, FL, October 20, 2003.
Model bias in AI
We now live in a world where we trust intelligent systems blindly, believing in their rationality and objectivity. However, in reality this is far from the truth.
In this talk given at the City.AI Singapore chapter, we explored the nature, implications and handling strategies for Model Bias in AI.
BROWN BAG TALK WITH MICAH ALTMAN, SOURCES OF BIG DATA FOR SOCIAL SCIENCES
This talk, is part of the MIT Program on Information Science brown bag series (http://informatics.mit.edu)
This talk reviews emerging big data sources for social scientific analysis and explores the challenges these present. Many of these sources pose distinct challenges for acquisition, processing, analysis, inference, sharing, and preservation.
Dr Micah Altman is Director of Research and Head/Scientist, Program on Information Science for the MIT Libraries, at the Massachusetts Institute of Technology. Dr. Altman is also a Non-Resident Senior Fellow at The Brookings Institution. Prior to arriving at MIT, Dr. Altman served at Harvard University for fifteen years as the Associate Director of the Harvard-MIT Data Center, Archival Director of the Henry A. Murray Archive, and Senior Research Scientist in the Institute for Quantitative Social Sciences.
Dr. Altman conducts research in social science, information science and research methods -- focusing on the intersections of information, technology, privacy, and politics; and on the dissemination, preservation, reliability and governance of scientific knowledge.
BROWN BAG TALK WITH MICAH ALTMAN INTEGRATING OPEN DATA INTO OPEN ACCESS JOURNALS
This talk, is part of the MIT Program on Information Science brown bag series (http://informatics.mit.edu)
This talk discusses findings from an analysis of data sharing and citation policies in Open Access journals and describes a set of novel tools for open data publication in open access journal workflows. Bring your lunch and enjoy a discussion fit for scholars, Open Access fans, and students alike.
Dr Micah Altman is Director of Research and Head/Scientist, Program on Information Science for the MIT Libraries, at the Massachusetts Institute of Technology.
Rainey resume 2 25-2021
Larry B. Rainey has extensive experience as a space systems engineer specializing in modeling and simulation. He has held positions at various government contractors and universities. Some of his accomplishments include authoring several pioneering textbooks, developing new modeling techniques, and initiating the nation's first collaborative organization focused on emergent behavior in systems of systems.
What's hot (12)
"Reproducibility from the Informatics Perspective"
"Reproducibility from the Informatics Perspective"
Multi-objective NSGA-II based community detection using dynamical evolution s...
Multi-objective NSGA-II based community detection using dynamical evolution s...
Managing Confidential Information – Trends and Approaches
Managing Confidential Information – Trends and Approaches
Linking Data to Publications through Citation and Virtual Archives
Linking Data to Publications through Citation and Virtual Archives
Eliciting and Visualising Trust Expectations using Persona Trust Characterist...
Eliciting and Visualising Trust Expectations using Persona Trust Characterist...
Semantics for Bioinformatics: What, Why and How of Search, Integration and An...
Semantics for Bioinformatics: What, Why and How of Search, Integration and An...
BROWN BAG TALK WITH MICAH ALTMAN, SOURCES OF BIG DATA FOR SOCIAL SCIENCES
BROWN BAG TALK WITH MICAH ALTMAN, SOURCES OF BIG DATA FOR SOCIAL SCIENCES
BROWN BAG TALK WITH MICAH ALTMAN INTEGRATING OPEN DATA INTO OPEN ACCESS JOURNALS
BROWN BAG TALK WITH MICAH ALTMAN INTEGRATING OPEN DATA INTO OPEN ACCESS JOURNALS
Viewers also liked
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this technology can extract knowledge to help the Army make more informed decisions for combating insurgencies.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this technology can extract knowledge to help the Army make more informed decisions for combating insurgencies.
T R A I N I N G M O D U L E K K O F F I C E
This document provides information about Union Pacific Limited (UPL), a New Zealand-based online forex brokerage company. It outlines UPL's trading systems and services, including a fully automated trading platform available 24/5 with low fees. It also describes Optimum Management Services, the company appointed to promote UPL's platform through client registration, education, and account management. Details are given on forex trading methodology, available currency pairs, account types, position size, and the online platform for monitoring trades and making withdrawals. Risk management procedures like stop orders and margin calls are also summarized.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapidly making accurate decisions to improve outcomes over time. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, and a 3D virtual world to model and observe insurgency behavior and assess outcomes of decisions.
ElectroHex
This is a Product Brief of an electronic card game i designed together with Ziv KItaro and Avi Sabbag at Cedar Design Group.
Corporate governance in psu
The document discusses corporate governance guidelines for Central Public Sector Undertakings (CPSEs) in India as issued by the Department of Public Enterprises (DPE). It outlines the composition and functions of boards of directors, audit committees, and remuneration committees according to DPE guidelines. However, some CPSEs are not fully complying with the guidelines regarding representation of independent directors and functioning of audit committees. Improving governance of CPSEs could help raise their performance and competitiveness.
Viewers also liked (7)
Similar to 05 Bronner Richards
A Survey of Building Robust Business Models in Pervasive Computing
Pervasive computing is one of the most challenging and difficult computing domains nowadays. It includes many architectural challenges like context awareness, adaptability, mobility, availability, and scalability. There are currently few approaches which provide methodologies to build suitable architectural models that are more suited to the nature of the pervasive domain. This area still needs a lot of enhancements in order to let the software business analyst (BA) cognitively handle pervasive applications by using suitable tasks and tools. Accordingly, any proposed research topic that would attempt to define a development methodology can greatly help BAs in modeling pervasive applications with high efficiency. In this survey paper we address some of the most significant and current software engineering practices that are proving to be most effective in building pervasive systems.
For citation:
Osama M. Khaled and Hoda M. Hosny. A Survey of Building Robust Business Models in Pervasive Computing. An accepted paper in the 2014 World Congress in Computer Science Computer Engineering and Applied Computing
Below are various theories and models that have been used and can
Below are various theories and models that have been used and can be used in research (from Dr. Steve Brown)
Behavioral et. al.
Absorptive capacity Theory
Accountability Theory
Activity Theory
Adaptive Structuration Theory
Administrative Behavior Theory
Argumentation Theory
Asch Conformity
Behavioral Decision Model
Belief Action Outcome Framework
Chaos Theory
Cognitive Fit Theory
Cognitive Load Theory
Cognitive Behavioral Therapy
Classical Conditioning
Conditioned Emotional Response
Cognitive Dissonance
Cognitive “purposive” Behaviorism
Consequentialist Ethics
Critical Theory
Csíkszentmihályi’s Flow
Cultural Theory
Deontological Ethics
Diffusion of Innovations Theory
Dynamic Capabilities
Distributed Cognitions Theory
Embodied social presence theory
Equity theory
Evolutionary theory
Eysenck’s Theory
Expectancy-value theory
Expectation Confirmation Theory
False Memory Syndrome
Field Theory
Fishbein's Attitude
General Deterrence Theory
Gestalt Theory of Personality
General Strain theory
Goal Contagion Theory
Gompertz Model (based upon Social Conflict Theory)
Grounded Theory
Hermeneutics
Illusion of Control
Impression Management Theory
Information Processing Theory
Impression Management Theory
Information Asymmetry Theory
Information Security Management Theory
Institutional Theory
Integrated Systems Theory
Keller's Motivational Model
Language action perspective
Law of Effect
Law of Emotion
Learned Helplessness Theory
McClelland’s Needs Theory
Neutralization Theory
Operant Conditioning
Mitchel’s Personality theory
Prospect Theory
Protection Motivation Theory
Self Determination Theory
Self-Efficacy Theory
Social Action Theory
Social Conflict Theory
Social Cognitive Theory
Social Exchange Theory
Social Identity Theory
Social Influence Theory
Social Learning Theory
Socio Technical Systems Theory
Task Closure Theory
Technology Acceptance Model
Technology Threat Avoidance Theory
Theory of Contextualism
Theory of Contiguity
Theory of Equipotentiality
Theory of Planned Behavior
Theory of Protection Motivation
Theory of Reasoned Action
Theory of Planned Behavior
Trait Theory
Virtue Ethics
Unified theory of acceptance and use of technology (UTAUT)
Universal Law of Generalization
Non-Behavioral
Accountability obfuscation
Actor Network theory
Attack Tree and Vague Sets
Bayes Theorem
Bayesian Inference
Bayesian Belief Network
Bayesian Networks
Boundary Object Theory
Broadbent’s Filter Theory Model
Complexity Theory
Cooperative game theory
Conformity Theory
Critical Realism Theory
Customer Based Discrepancy Theory
Customer Focus Theory
Deferred Action Theory
Design Theory
Elaboration Likelihood Model
Fit-Viability Theory
Flow Theory
Game Theory
Garbage Can Theory
General Systems Theory
General Deterrence Theory
Hebbian Theory
Human Agency Theory
Information Warfare
Institutional theory
International Information Systems Theory
Internationalization Theory
Information Technology Portfolio
Knowledge Management
Noncooperative game theory
Organization Based Access C ...
Social media platform and Our right to privacy
The advancement of Information Technology has hastened the ability to disseminate information across the globe. In particular, the recent trends in ‘Social Networking’ have led to a spark in personally sensitive information being published on the World Wide Web. While such socially active websites are creative tools for expressing one’s personality it also entails serious privacy concerns. Thus, Social Networking websites could be termed a double edged sword. It is important for the law to keep abreast of these developments in technology. The purpose of this paper is to demonstrate the limits of extending existing laws to battle privacy intrusions in the Internet especially in the context of social networking. It is suggested that privacy specific legislation is the most appropriate means of protecting online privacy. In doing so it is important to maintain a balance between the competing right of expression, the failure of which may hinder the reaping of benefits offered by Internet technology
Requirement analysis, architectural design and formal verification of a multi...
This paper presents an approach based on the analysis, design, and formal verification of a multi-agent
based university Information Management System (IMS). University IMS accesses information, creates
reports and facilitates teachers as well as students. An orchestrator agent manages the coordination
between all agents. It also manages the database connectivity for the whole system. The proposed IMS is
based on BDI agent architecture, which models the system based on belief, desire, and intentions. The
correctness properties of safety and liveness are specified by First-order predicate logic.
Goal Dynamics_From System Dynamics to Implementation
1) The document describes a PhD research proposal on developing dynamic modeling methods for goal dynamics and multi-agent systems.
2) The research aims to analyze and capture goal dynamics in social contexts and provide intelligent agents that can handle complex, distributed events in real-time.
3) The methodology involves defining artifacts and processes, modeling tools, and evaluating the results against objectives through case studies and simulations.
ANALYSIS OF DEVELOPMENT COOPERATION WITH SHARED AUTHORING ENVIRONMENT IN ACAD...
Team work is an important training element of future software engineers. However, the evaluation of the
performance of collaboration among individuals is very subjective. Meanwhile, how to effectively
promote the collaboration in an academic setting is an even more challenging task. The lack of a common
standard or method for the assessment is a practical issue in software engineering projects. With the
rapid development of shared authoring environments, such as Wiki, more and more educational
institutions are studying the adaptability of such kind of collaborative platforms. In order to study the
applicability of adopting wiki-based shared authoring environments in software engineering education,
we have proposed three major research questions. By solving these problems, we try to answer some of
the most important questions in adopting shared authoring platforms in academic settings.
Agent-Based Problem Solving Methods In Big Data Environment
This document introduces a special issue of the journal Web Intelligence and Agent Systems focusing on using agent-based methods to solve problems arising from big data. The issue includes four research papers covering topics like distributed problem solving, agent-based data mining, and recommendation systems applied to data from e-commerce, social networks, and other online sources. The guest editors introduce the challenges of big data and how agent-based approaches can help process large volumes of data efficiently.
STUDY OF AGENT ASSISTED METHODOLOGIES FOR DEVELOPMENT OF A SYSTEM
STUDY OF AGENT ASSISTED METHODOLOGIES FOR DEVELOPMENT OF A SYSTEMInternational Journal of Technical Research & Application
This document discusses and compares several agent-assisted methodologies for developing multi-agent systems:
- It reviews Gaia, HLIM, PASSI, and Tropos methodologies, outlining their key models and phases. Gaia focuses on analysis and design, HLIM models internal and external agent behavior, and PASSI and Tropos incorporate UML modeling.
- It then proposes a new MAB methodology intended to address shortcomings of existing approaches. MAB includes requirements, analysis, design, and implementation phases and models such as use case maps and agent roles.
- Finally, it concludes that agent technologies represent a promising approach for developing complex software systems, but that matching methodologies to problem domains and developing principTerrorism Analysis through Social Media using Data Mining
This document presents a study that uses deep learning models like Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN) to analyze terrorism through detecting toxicity in social media text data. The study aims to classify text data into categories like toxicity, severe toxicity, obscenity, threat, insult or identity hate. It provides an overview of DNN and CNN models for text classification and compares their methodology, architecture and performance. The models are trained on preprocessed social media data related to terrorist activities and aim to accurately predict the toxicity level and classify tweets for concerned authorities to make informed decisions.
social networking site
This document is a project report for developing a social networking site submitted as part of a master's degree program. It discusses the existing system's limitations in allowing people to voice violations, injustice, and corruption happening around them. The proposed system aims to provide a common platform for citizens of India to discuss these issues and take appropriate action. It describes the system's modules, development strategy using prototyping, and technical feasibility of the project. In summary, the document outlines a social media platform to promote social responsibility in India by enabling citizens to report issues and participate in online discussions.
From Representation to Mediation: A New Agenda for Conceptual Modeling Resear...
From Representation to Mediation: A New Agenda for Conceptual Modeling Resear...Jan Recker @ University of Hamburg
Presentation to the Universiteit Hasselt about a paper appearing in the journal MIS Quarterly (2021), Vol. 45, Iss. 1, DOI: 10.25300/MISQ/2021/16027.MACHINE LEARNING AND DEEP LEARNING TECHNIQUES FOR DETECTING ABUSIVE CONTENT O...
This document discusses machine learning and deep learning techniques for detecting abusive content on Twitter. It presents an overview of cyber abuse and sentiment analysis. A literature review covers past research on cyberbullying detection. The methodology uses a dataset of over 32k tweets, which are preprocessed and analyzed using machine learning algorithms and an LSTM deep learning model. Results show that the LSTM model achieves 99.5% accuracy and 74.8% F1 score, outperforming machine learning models for detecting abusive tweets. The conclusion is that deep learning more effectively identifies abuse but continued experimentation is needed to address this important social media problem.
Exploratory Data Analysis and Feature Selection for Social Media Hackers Pred...
In machine learning, the intelligence of a developed model is greatly influenced by the dataset used for the
target domain on which the developed model will be deployed. Social media platform has experienced
more of hackers’ attacks on the platform in recent time. To identify a hacker on the platform, there are two
possible ways. The first is to use the activities of the user while the second is to use the supplied details the
user registered the account with. To adequately identify a social media user as hacker proactively, there
are relevant user details called features that can be used to determine whether a social media user is a
hacker or not. In this paper, an exploratory data analysis was carried out to determine the best features
that can be used by a predictive model to proactively identify hackers on the social media platform. A web
crawler was developed to mine the user dataset on which exploratory data analysis was carried out to
select the best features for the dataset which could be used to correctly identify a hacker on a social media
platform.
EXPLORATORY DATA ANALYSIS AND FEATURE SELECTION FOR SOCIAL MEDIA HACKERS PRED...
In machine learning, the intelligence of a developed model is greatly influenced by the dataset used for the
target domain on which the developed model will be deployed. Social media platform has experienced
more of hackers’ attacks on the platform in recent time. To identify a hacker on the platform, there are two
possible ways. The first is to use the activities of the user while the second is to use the supplied details the
user registered the account with. To adequately identify a social media user as hacker proactively, there
are relevant user details called features that can be used to determine whether a social media user is a
hacker or not. In this paper, an exploratory data analysis was carried out to determine the best features
that can be used by a predictive model to proactively identify hackers on the social media platform. A web
crawler was developed to mine the user dataset on which exploratory data analysis was carried out to
select the best features for the dataset which could be used to correctly identify a hacker on a social media
platform.
IRJET - Real-Time Cyberbullying Analysis on Social Media using Machine Learni...
This document presents a system for real-time analysis of cyberbullying on social media using machine learning and text mining. The system aims to detect abusive conversations and censor harmful words to protect victims. It uses an artificial neural network machine learning algorithm to analyze words that could psychologically affect individuals. The system identifies abusive words in posts and comments and replaces them with censored content. This aims to prevent innocent users from being exposed to depressing or criminal activities online. The document discusses the system architecture, including tools for sentiment analysis, monitoring discussions, identifying abusive words, and updating a word database. Diagrams show the data flow, use cases, and interactions between system components.
THE INTEREST OF HYBRIDIZING EXPLAINABLE AI WITH RNN TO RESOLVE DDOS ATTACKS: ...
In this paper, we suggest a new method to address attack detection problems in IoT networks, by using a specific emphasis on the user’s and network’s requirements regarding the application provider and giving a defence against intruders and malicious users. The paper focuses on resolving the problem of detection of attacks in IoT networks using Recurrent Neural Networks and an explainable artificial intelligence technique (XAI) named SHAP. XAI refers to a collection of methods and procedures for explaining how AI models make decisions. Although XAI is useful for understanding the motivations underlying AI models, the information utilized in these discoveries may be a risk. Machine learning models are vulnerable to attacks such as model inversion, model extraction, and membership inference. Such attacks could concentrate on the learning model or on the data used to train and build the model, depending on the involved circumstances and parties. Hence, when the owner of an AI model wishes to grant only black-box access and does not expose the model's parameters and architecture to third parties, solutions like XAI can notably enhance the susceptibility to model extraction attacks.
To guarantee the users regarding possible violations, the proposed RNN-SHAP method is based on a decentralized topology relying on a set of cooperative independent parties including the users of IoT network. Another advantage of the suggested approach is the capitalization on the trust relationships that are part of IoT networks in real life to build trusted mechanisms in the network. Compared to other methods using different metrics, the suggested RNN-SHAP shows its efficiency in resolving the DDoS problem.
Security and Privacy Measurements in Social Networks: Experiences and Lessons...
We describe our experience gained while exploring practical security and privacy problems in a real-world, large- scale social network (i.e., Facebook), and summarize our conclu- sions in a series of “lessons learned”. We first conclude that it is better to adequately describe the potential ethical concerns from the very beginning and plan ahead the institutional review board (IRB) request. Even though sometimes optional, the IRB approval is a valuable point from the reviewer’s perspective. Another aspect that needs planning is getting in touch with the online social network security team, which takes a substantial amount of time. With their support, “bending the rules” (e.g., using scrapers) when the experimental goals require so, is easier. Clearly, in cases where critical technical vulnerabilities are found during the research, the general recommendations for responsible disclosure should be followed. Gaining the audience’s engagement and trust was essential to the success of our user study. Participants felt more comfortable when subscribing to our experiments, and also responsibly reported bugs and glitches. We did not observe the same behavior in crowd-sourcing workers, who were instead more interested in obtaining their rewards. On a related point, our experience suggests that crowd sourcing should not be used alone: Setting up tasks is more time consuming than it seems, and researchers must insert some sentinel checks to ensure that workers are not submitting random answers.
From a logistics point of view, we learned that having at least a high-level plan of the experiments pays back, especially when the IRB requires a detailed description of the work and the data to be collected. However, over planning can be dangerous because the measurement goals can change dynamically. From a technical point of view, partially connected to the logistics remarks, having a complex and large data-gathering and analysis framework may be counterproductive in terms of set-up and management overhead. From our experience we suggest to choose simple technologies that scale up if needed but, more importantly, can scale down. For example, launching a quick query should be straightforward, and the frameworks should not impose too much overhead for formulating it. We conclude with a series of practical recommendations on how to successfully collect data from online social networks (e.g., using techniques for network multi presence, mimicking user behavior, and other crawling “tricks”’) and avoid abusing the online service, while gathering the data required by the experiments.
Complete-SRS.doc
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
Trends in Information Management
This document contains an annotated bibliography on trends in information security with summaries of 6 sources. The sources discuss topics including biometric authentication alternatives, network integration design, and green computing in the cloud. Each annotation provides a brief summary of the source content and strengths/weaknesses.
H1803044651
1) The document discusses various ways that artificial intelligence can be applied to different phases of the software engineering lifecycle, including requirements specification, design, coding, testing, and estimation.
2) It provides examples of using techniques like natural language processing to clarify requirements, knowledge graphs to manage requirements information, and computational intelligence for requirements prioritization.
3) For design, the document discusses using intelligent agents to recommend patterns and designs to satisfy quality attributes from requirements and assist with assigning responsibilities to components.
Similar to 05 Bronner Richards (20)
A Survey of Building Robust Business Models in Pervasive Computing
A Survey of Building Robust Business Models in Pervasive Computing
Below are various theories and models that have been used and can
Below are various theories and models that have been used and can
Requirement analysis, architectural design and formal verification of a multi...
Requirement analysis, architectural design and formal verification of a multi...
Goal Dynamics_From System Dynamics to Implementation
Goal Dynamics_From System Dynamics to Implementation
ANALYSIS OF DEVELOPMENT COOPERATION WITH SHARED AUTHORING ENVIRONMENT IN ACAD...
ANALYSIS OF DEVELOPMENT COOPERATION WITH SHARED AUTHORING ENVIRONMENT IN ACAD...
Agent-Based Problem Solving Methods In Big Data Environment
Agent-Based Problem Solving Methods In Big Data Environment
STUDY OF AGENT ASSISTED METHODOLOGIES FOR DEVELOPMENT OF A SYSTEM
STUDY OF AGENT ASSISTED METHODOLOGIES FOR DEVELOPMENT OF A SYSTEM
Terrorism Analysis through Social Media using Data Mining
Terrorism Analysis through Social Media using Data Mining
From Representation to Mediation: A New Agenda for Conceptual Modeling Resear...
From Representation to Mediation: A New Agenda for Conceptual Modeling Resear...
MACHINE LEARNING AND DEEP LEARNING TECHNIQUES FOR DETECTING ABUSIVE CONTENT O...
MACHINE LEARNING AND DEEP LEARNING TECHNIQUES FOR DETECTING ABUSIVE CONTENT O...
Exploratory Data Analysis and Feature Selection for Social Media Hackers Pred...
Exploratory Data Analysis and Feature Selection for Social Media Hackers Pred...
EXPLORATORY DATA ANALYSIS AND FEATURE SELECTION FOR SOCIAL MEDIA HACKERS PRED...
EXPLORATORY DATA ANALYSIS AND FEATURE SELECTION FOR SOCIAL MEDIA HACKERS PRED...
IRJET - Real-Time Cyberbullying Analysis on Social Media using Machine Learni...
IRJET - Real-Time Cyberbullying Analysis on Social Media using Machine Learni...
THE INTEREST OF HYBRIDIZING EXPLAINABLE AI WITH RNN TO RESOLVE DDOS ATTACKS: ...
THE INTEREST OF HYBRIDIZING EXPLAINABLE AI WITH RNN TO RESOLVE DDOS ATTACKS: ...
Security and Privacy Measurements in Social Networks: Experiences and Lessons...
Security and Privacy Measurements in Social Networks: Experiences and Lessons...
More from tjoozey tjoozey
Social Computing : Virtual Worlds
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this software engineering approach can extract useful knowledge for more informed military decisions regarding insurgencies.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this technology can extract knowledge to help the Army make more informed decisions for combating insurgencies.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this technology can extract knowledge to support more informed decisions for combating insurgencies.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapidly making accurate decisions to improve outcomes over time. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, and a 3D virtual world to model and observe insurgency behavior and assess outcomes of decisions. The framework is intended to extract knowledge useful for more informed military decision making.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying this software engineering approach can extract knowledge to help the Army make more informed decisions for combating insurgencies.
Social Computing
This document discusses developing an Insurgency Information Framework (IIF) using multi-agent technology and cognitive modeling. The research aims to provide decision support systems for rapid, accurate decision making to address insurgencies. The methodology uses an agent-oriented development environment, object-oriented development life cycle, model driven architecture, and multi-agent development process. Tools include JADE, Jadex, databases, and Second Life for virtual world visualization and experimentation. The conclusion states that applying software engineering to sociological analysis can provide an updatable structure to extract knowledge and support more informed decisions for addressing the insurgency crisis.
More from tjoozey tjoozey (6)
Recently uploaded
UiPath Test Automation using UiPath Test Suite series, part 6
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Removing Uninteresting Bytes in Software Fuzzing
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
“I’m still / I’m still / Chaining from the Block”
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Essentials of Automations: The Art of Triggers and Actions in FME
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Pushing the limits of ePRTC: 100ns holdover for 100 days
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
Communications Mining Series - Zero to Hero - Session 1
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
20240605 QFM017 Machine Intelligence Reading List May 2024
Everything I found interesting about machines behaving intelligently during May 2024
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Recently uploaded (20)
UiPath Test Automation using UiPath Test Suite series, part 6
UiPath Test Automation using UiPath Test Suite series, part 6
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Climate Impact of Software Testing at Nordic Testing Days
Climate Impact of Software Testing at Nordic Testing Days
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
05 Bronner Richards
- 1. LeeRoy Bronner, Ph.D., P.E. Master Student: Akeila Richards Morgan State University Department of Industrial, Manufacturing, and Information Systems Engineering 5200 Perring Parkway Baltimore, MD 21251 Integrating Multi-Agent Technology with Cognitive Modeling to Develop an Insurgency Information Framework (IIF)
- 4. Definitions Insurgency : an armed rebellion by any irregular armed force that rises up against an established authority, government, or administration . Those carrying out an insurgency are insurgents. Insurgents conduct sabotage and harassment . Insurgents usually are in opposition to a civil authority or government primarily in the hope of improving their condition. Terrorism: systematic use of terror , manifesting itself in violence and intimidation. Those carrying out terrorism are terrorist. Terrorist conduct violence for the purpose of creating fear in order to achieve a political, economic, religious, or ideological goal . Framework: A logical structure for classifying and organizing complex information.
- 6. How are insurgencies planned for and what is the process? How are insurgencies carried out and what is the process? Are there any consistencies in the locations and surroundings where insurgencies are carried out? Why are more Iraqi women becoming insurgents? Sample Insurgency Questions That might be Addressed by This Research
- 8. METHODOLOGY
- 9. Agent Oriented Development Environment User Knowledge Interacts With Guides Verifies
- 10. Object-Oriented Development Life Cycle Implemented using Enterprise Architect Reference: Tsang, Curtis, et al., “Object-Oriented Technology,” McGraw Hill, 2005. Activity Diagram
- 11. Model Driven Architecture (MDA)
- 12. BDI Agent System Jadex BDI Architecture Goal-Oriented Reasoning Engine Agent BDI Model
- 13. Multi-Agent Systems Reference: Jennings, Nick, “Agent-Based Computing: Promise and Perils,” Presentation, Dept of Electronics and Computer Science, University of Southampton.
- 14. 3D Electronic Institution Concept Only systems that have a high degree of interactions need to be structured in order to avoid violations Reference: Bogdanovych, Esteva, et al, “A Methodology for developing MAS as 3D Electronic Institutions, Proceedings from 8th International Workshop on Agent Oriented Software Engineering (AOSE'07).
- 15. Integrated Multi-Agent Development Process Microsoft Access Cognitive Modeling Application JADEX Software/ JADE Platform Ontology Database Problem Domain Database Communication Server Electronic Institution Developmental Cycle Design Verify Test Deployment Development Simulate ISLANDER: graphical tool for specification of rules & protocols in eI AMELI: software platform to run eI aBuilder: agent development tool SIMDEI: simulation tool to animate & analyze eI iGrafix FlowCharter Enterprise Architect 2 nd Life Virtual World Technology Visualization Layer Behavioral Experimentation Insurgency Questions to be Answered
- 16. Runtime Architecture Reference: Bogdanovych, Esteva, et al., “A Methodology for developing MAS as 3D Electronic Institutions, Proceedings from 8th International Workshop on Agent Oriented Software Engineering (AOSE'07). Second Life ©
- 18. Development of an Insurgency Information Framework Using Multi-Agent Technololgy