Group-Based Social Network Characterisation of Hidden Terrorist Networks

Hidden networks arise in high-dimensional network structures when the hidden network members camouflage their existence by appearing randomly connected to the larger network structure, but in reality ensure they remain in persistent contact with one another over time. This paper takes a first step towards determining how to locate such hidden networks through the novel use of group-based social network metrics to characterise the features of hidden networks. Micro, meso and macro-level network analyses of the September 11 network and a selection of popular simulated terrorist network structures will show that the simulated networks are highly visible whereas the hidden networks display low visibility except at the macro level. Moreover these hidden networks aid to camouflage a highly prominent terrorist network of trusted prior contacts

Brain semantic segmentation: a deep learning approach in human and Rat MRI studies

Dissertação de mestrado em Biomedical Engineering Dissertation (área de especialização em Field of Medical informatics)Magnetic Resonance Imaging (MRI) provides information about anatomy and pathology. This type of technique is the most popular used for the study of rat and human brain. Classifying voxels according to the presence of relevant anatomic features is an important step in the pre-processing of the data. A precise delineation and automatic segmentation of the brain structures is required in preclinical rodent imaging field and can substitute the manual segmentation where time consuming or human-error problems can occur. Current solutions are based on traditional segmentation algorithms that raise accuracy issues and generally need human intervention during or after the segmentation process. In the humans’ field, most of the tools created in DL (deep learning) are used in tumour or lesion segmentation. Brain segmentation tissues are not as explored as oncology problems and lesions complications. In the rats’ field, there are no segmentation studies in DL. It was decided to use a DL approach in Rats to solve some of the old techniques’ problems. This dissertation will present an approach on semantic segmentation of white matter and gray matter in Human’s images, evaluate the algorithm’s performance with outliers. It will also present an FCN (fully convolutional network) solution for on semantic segmentation using rat’s and human’s MRI of anatomical features. A two-dimensional convolution (slice-by-slice) approach and a three-dimensional (volume) convolutions approach were evaluated. At the end, the results found, using FCN U-NET in rats’ MRI for a 2D convolutions approach, DSC were 94.65 % for WM, 91.03% for GM and 76.89 % for cerebrospinal fluid. Using the 3D convolutions approach, the results using DSC found are 93.81 % for WM, 89.69 % for GM and 74.68 % for cerebrospinal fluid. The results using humans’ MRI using DSC were 91.59% for WM and 84,58% for GM.Imagens de ressonância magnética providenciam informação acerca da anatomia humana e possíveis patologias existentes. Este é o tipo de técnica mais popular entre os estudos na área da neurociência, tanto em humanos como em roedores. A classificação de voxéis de acordo com a presença de informação anatómica relevante é um importante passo no pré-processamento de dados na comunidade científica na área da neurociência. Uma delineação precisa das várias estruturas do cérebro humano ou roedor é uma das requisições para a maioria dos estudos clínicos de imagens de ressonância magnética. A segmentação automática através de inteligência artificial pode vir a substituir ferramentas ou algoritmos semiautomáticos já existentes ou substituir também a segmentação manual que se trata de um processo muito demorado que está ligado a erro-humano. O avanço tecnológico provocou um estudo mais aprofundado no Deep Learning (DL) a partir de 2012, provando que estas técnicas de inteligência artificial estão a revelar-se melhores do que o que já existe na área médica. Dos estudos com ressonância magnética em humanos, a maioria das ferramentas criadas que utilizam DL são usadas na segmentação de tumores ou lesões cerebrais. A segmentação de tecidos cerebrais não está tão explorada como problemas oncológicos ou lesões cerebrais. Dos estudos com ressonância magnética em roedores, não existem ferramentas que utilizam as técnicas de DL. Tendo em conta que as técnicas de segmentação que já existem ainda têm muitas complicações e erros, foi decidido tentar uma abordagem de DL em Roedores, também. Esta dissertação irá apresentar uma abordagem de segmentação semântica de massa branca e massa cinzenta utilizando técnicas de DL em humanos. Irá também verificar a capacidade de generalização com casos de pacientes idosos. Irá ser apresentado uma técnica de DL nas imagens de ressonância magnética em roedores para a segmentação semântica de massa branca, massa cinzenta e líquido cérebroespinal. No final irá ser comparado as técnicas entre as duas espécies e também entre a utilização de convoluções com duas dimensões e de convoluções com três dimensões nos roedores. No final, os resultados encontrados utilizando uma FCN em Ratazanas numa abordagem 2D, os valores de DSC foram 94,65 % para massa branca, 91.03% para massa cinzenta e 76.89 % para o líquido cérebroespinal. Na abordagem 3D ,os valores de DSC encontrados foram 93.81 % % para massa branca, 89.69 % para massa cinzenta e 74.68 % para o líquido cérebroespinal. Os resultados utilizando as imagens humanas, foram 91.59% para massa branca e 84,58% para massa cinzenta.This work is part of the SIGMA project with the reference FCT-ANR/NEU-OSD/0258/2012, co-financed by the French public funding agency ANR (Agence Nationale pour la Recherche, APP Blanc International II 2012), the Portuguese FCT (Fundação para a Ciência e Tecnologia) and the Portuguese North Regional Operational Program (ON.2 – O Novo Norte) under the National Strategic Reference Framework (QREN), through the European Regional Development Fund (FEDER) as well as the Projecto Estratégico co-funded by FCT (PEst-C/SAU/LA0026-/2013) and the European Regional Development Fund COMPETE (FCOMP-01-0124-FEDER-037298).This work was also supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT within the Project Scope: UID/CEC/00319/2013

Cognitive engineering in aerospace application: Pilot interaction with cockpit automation

Because of recent incidents involving glass-cockpit aircraft, there is growing concern with cockpit automation and its potential effects on pilot performance. However, little is known about the nature and causes of problems that arise in pilot-automation interaction. The results of two studies that provide converging, complementary data on pilots' difficulties with understanding and operating one of the core systems of cockpit automation, the Flight Management System (FMS) is reported. A survey asking pilots to describe specific incidents with the FMS and observations of pilots undergoing transition training to a glass cockpit aircraft served as vehicles to gather a corpus on the nature and variety of FMS-related problems. The results of both studies indicate that pilots become proficient in standard FMS operations through ground training and subsequent line experience. But even with considerable line experience, they still have difficulties tracking FMS status and behavior in certain flight contexts, and they show gaps in their understanding of the functional structure of the system. The results suggest that design-related factors such as opaque interfaces contribute to these difficulties which can affect pilots' situation awareness. The results of this research are relevant for both the design of cockpit automation and the development of training curricula specifically tailored to the needs of glass cockpits

Affect Analysis in Video

Ph.DDOCTOR OF PHILOSOPH

Knowledge trading : computational support for individual and collaborative sense-making activities

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2004.Includes bibliographical references (leaves 127-132).(cont.) outlined. 2. Demonstration that computer systems can use the discovered relations among data items to help users search for relevant information, prioritize the data exchange between collaborating users, and visualize data in various ways. This investigation looks at how a human's increasing knowledge about a problem space is influential in the subsequent accumulation of new data. The findings are converted into computational equivalents that can support individual and collaborative sense-making processes.This dissertation explores the potential for computational systems to analyze and support individual and collaborative human sense-making activities. In this context human sense-making refers to the act of mentally and physically relating pieces of information so as to develop an understanding of a particular situation. Human sense-making activities such as brainstorming, decision-making, and problem solving sessions often produce a lot of data such as notes, sketches, and documents. The participants of sense-making activities usually develop a good understanding of the relations among these individual data items. These relations define the context. Because the relations remain within the minds of the participants they are neither accessible to outsiders and computational systems nor can they be recorded or backed up. This dissertation outlines a first set of computational mechanisms that construct relations from the spatial arrangement, use, and storage of data items. A second set of computational mechanisms takes advantage of these relations by helping users to keep track of, search for, exchange, arrange, and visualize data items. The computational mechanisms are both adaptive and evocative, meaning that the computational mechanisms dynamically adapt to users and changing circumstances while also trying to influence the human sense-making process. Contributions: 1. Demonstration that computer systems can discover probable relations among data items from their spatial arrangement and use by users. This work identifies and analyzes various human mental processes involved in the determination of possible relations among data items such as documents on a work desk or files in a computer system. A computational equivalent is proposed for every mental processby Paul Erich Keel.Ph.D

Computational models and approaches for lung cancer diagnosis

The success of treatment of patients with cancer depends on establishing an accurate diagnosis. To this end, the aim of this study is to developed novel lung cancer diagnostic models. New algorithms are proposed to analyse the biological data and extract knowledge that assists in achieving accurate diagnosis results

Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design

Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design

Animating the evolution of software

The use and development of open source software has increased significantly in the last decade. The high frequency of changes and releases across a distributed environment requires good project management tools in order to control the process adequately. However, even with these tools in place, the nature of the development and the fact that developers will often work on many other projects simultaneously, means that the developers are unlikely to have a clear picture of the current state of the project at any time. Furthermore, the poor documentation associated with many projects has a detrimental effect when encouraging new developers to contribute to the software. A typical version control repository contains a mine of information that is not always obvious and not easy to comprehend in its raw form. However, presenting this historical data in a suitable format by using software visualisation techniques allows the evolution of the software over a number of releases to be shown. This allows the changes that have been made to the software to be identified clearly, thus ensuring that the effect of those changes will also be emphasised. This then enables both managers and developers to gain a more detailed view of the current state of the project. The visualisation of evolving software introduces a number of new issues. This thesis investigates some of these issues in detail, and recommends a number of solutions in order to alleviate the problems that may otherwise arise. The solutions are then demonstrated in the definition of two new visualisations. These use historical data contained within version control repositories to show the evolution of the software at a number of levels of granularity. Additionally, animation is used as an integral part of both visualisations - not only to show the evolution by representing the progression of time, but also to highlight the changes that have occurred. Previously, the use of animation within software visualisation has been primarily restricted to small-scale, hand generated visualisations. However, this thesis shows the viability of using animation within software visualisation with automated visualisations on a large scale. In addition, evaluation of the visualisations has shown that they are suitable for showing the changes that have occurred in the software over a period of time, and subsequently how the software has evolved. These visualisations are therefore suitable for use by developers and managers involved with open source software. In addition, they also provide a basis for future research in evolutionary visualisations, software evolution and open source development

The urban real-time traffic control (URTC) system : a study of designing the controller and its simulation

The growth of the number of automobiles on the roads in China has put higher demands on the traffic control system that needs to efficiently reduce the level of congestion occurrence, which increases travel delay, fuel consumption, and air pollution. The traffic control system, urban real-time traffic control system based on multi-agent (MA-URTC) is presented in this thesis. According to the present situation and the traffic's future development in China, the researches on intelligent traffic control strategy and simulation based on agent lays a foundation for the realization of the system. The thesis is organized as follows: The first part focuses on the intersection' real-time signal control strategy. It contains the limitations of current traffic control systems, application of artificial intelligence in the research, how to bring the dynamic traffic flow forecast into effect by combining the neural network with the genetic arithmetic, and traffic signal real-time control strategy based on fuzzy control. The author uses sorne simple simulation results to testify its superiority. We adopt the latest agent technology in designing the logical structure of the MA-URTC system. By exchanging traffic flows information among the relative agents, MA-URTC provides a new concept in urban traffic control. With a global coordination and cooperation on autonomy-based view of the traffic in cities, MA-URTC anticipates the congestion and control traffic flows. It is designed to support the real-time dynamic selection of intelligent traffic control strategy and the real-time communication requirements, together with a sufficient level of fault-tolerance. Due to the complexity and levity of urban traffic, none strategy can be universally applicable. The agent can independently choose the best scheme according to the real-time situation. To develop an advanced traffic simulation system it can be helpful for us to find the best scheme and the best switch-point of different schemes. Thus we can better deal with the different real-time traffic situations. The second part discusses the architecture and function of the intelligent traffic control simulation based on agent. Meanwhile the author discusses the design model of the vehicle-agent, road agent in traffic network and the intersection-agent so that we can better simulate the real-time environment. The vehicle-agent carries out the intelligent simulation based on the characteristics of the drivers in the actual traffic condition to avoid the disadvantage of the traditional traffic simulation system, simple-functioned algorithm of the vehicles model and unfeasible forecasting hypothesis. It improves the practicability of the whole simulation system greatly. The road agent's significance lies in its guidance of the traffic participants. It avoids the urban traffic control that depends on only the traffic signal control at intersection. It gives the traffic participants the most comfortable and direct guidance in traveling. It can also make a real-time and dynamic adjustment on the urban traffic flow, thus greatly lighten the pressure of signal control in intersection area. To sorne extent, the road agent is equal to the pre-caution mechanism. In the future, the construction of urban roads tends to be more intelligent. Therefore, the research on road agent is very important. All kinds of agents in MA-URTC are interconnected through a computer network. In the end, the author discusses the direction of future research. As the whole system is a multi-agent system, the intersection, the road and the vehicle belongs to multi-agent system respectively. So the emphasis should be put on the structure design and communication of all kinds of traffic agents in the system. Meanwhile, as an open and flexible real-time traffic control system, it is also concerned with how to collaborate with other related systems effectively, how to conform the resources and how to make the traffic participants anywhere throughout the city be in the best traffic guidance at all times and places. To actualize the genuine ITS will be our final goal. \ud ______________________________________________________________________________ \ud MOTS-CLÉS DE L’AUTEUR : Artificial Intelligence, Computer simulation, Fuzzy control, Genetic Algorithm, Intelligent traffic control, ITS, Multi-agent, Neural Network, Real-time