Les usages dans le domaine des systèmes multi-agents ont évolué de manière à intégrer davantage les utilisateurs humains dans les applications. La manipulation d'informations privées par des agents autonomes appelle alors à une protection adaptée des données personnelles. Les présents travaux examinent d'abord le contexte légal de la protection de la vie privée, ainsi que<br />les divers moyens informatiques destinés à la protection des données personnelles. Il en ressort un besoin de solutions fondées sur les méthodes d'IA, autorisant à la fois un raisonnement sur les réglementations et l'adaptation du comportement d'un agent à ces réglementations. Dans cette perspective, nous proposons le modèle d'agent PAw (Privacy-Aware) et la logique DLP (Deontic Logic for Privacy), conçue pour traiter des réglementations provenant d'autorités multiples. Le composant de raisonnement normatif de l'agent analyse son contexte hétérogène et fournit une politique cohérente pour le traitement des données personnelles. L'agent PAw contrôle alors automatiquement sa propre utilisation des données en regard de cette politique. Afin d'appliquer cette politique de manière distante, nous étudions les différentes architectures d'applications distribuées orientées vers la protection de la vie privée, notamment celles fondées sur les principes du Trusted Computing. Nous en proposons une complémentaire, illustrant la possibilité d'utiliser différemment cette technologie. L'implémentation de l'agent PAw permet la démonstration de ses principes sur trois scénarios, montrant ainsi l'adaptabilité de l'agent à son contexte normatif et l'influence des réglementations sur le comportement de l'application.

<p>In this work, an existing generator for layout of Static Random Access Memory (SRAM) is improved. The tool is completed with a block decoder, which was missing when the thesis started. A feature of generating schematic files is also added. The schematics are important to get a better overview, to test parts properly, and enable Layout versus Schematics (LVS) checks.</p><p>The main focus of this thesis work is to implement and evaluate a new SRAM cell, called Zero Aware Asymmetric SRAM cell. This cell saves major power when zeros are stored. Furthermore the pull-up circuit is modified to be less power consuming. Other parts are also modified to fit the new memory cell.</p><p>Several minor flaws are corrected in the layout generator. It does still not produce a complete memory without manual interventions, but it does at least create all parts with one command. Several tests, including Design Rule Checks (DRC) and LVS checks, are carried out both on minor and larger parts. Development of documentation that makes it easier for users and developers to use and understand the tool is initiated.</p>

<p>The purpose of the study is to explore the context, from the users’ perspective, in order to find relevant context parameters that can be useful in the development of the future context-aware technology. The goal is to find some of the context parameters relevant to the situated activity and investigate to what extent and in which way they influence the user in everyday planning activities.</p><p>The method used in the study was based on scenario descriptions. A total of 41 participants reported how they would have acted in the different situations and they also rated how important they believed the different context factors were in the situations. Analyses were made to reveal relationships between context factors and service properties used by the participants in the scenarios.</p><p>In the study several interesting relationships between context factors and the use of services were discovered. The level of urgency was in several situations considered to be important, and it was also found to have an impact on how the participants chose to communicate. The cost was introduced by the participants during the study. It seemed to be important; however, in situations with high urgency it became less important. The study revealed a potential relationship between the risk of disturbing the people in the vicinity and the effort to communicate quietly. Another interesting finding was the relationship between privacy and the choice of modality when communicating: voice-based services were avoided. Further, the importance of privacy and disturbance also appeared to have greater influence in non-anonymous situations than in anonymous.</p> / <p>Syftet med studien är att undersöka kontexten, utifrån användarens perspektiv, för att kunna hitta relevanta kontextfaktorer som kan vara användbara i utvecklingen av kontextmedveten teknologi. Målet är att finna kontextfaktorer som är relevanta för den pågående aktiviteten och undersöka i vilken utsträckning och på vilka sätt dessa faktorer påverkar användaren i de dagliga planeringsaktiviteterna.</p><p>Metoden som användes i studien baserades på scenariobeskrivningar. 41 stycken försöksdeltagare fick beskriva hur de skulle ha handlat i de olika situationerna och de fick också skatta hur viktiga de olika kontextfaktorerena var i situationerna. Analyser genomfördes för att finna samband mellan kontextfaktorer och egenskaper hos de tjänster som försöksdeltagarna använde sig av i scenarierna.</p><p>I studien upptäcktes en rad intressanta relationer mellan kontextfaktorer och användningen av tjänster. Exempelvis ansågs nivån av brådska vara betydelsefull i flera situationer och den verkade också ha inverkan på hur försöksdeltagarna valde att kommunicera. Försöksdeltagarna introducerade under studien kontextfaktorn kostnad. Kostnaden påverkade valet av tjänster men blev mindre betydande i situationer med stor brådska. Studien visade också på potentiella samband mellan risken att störa människor i sin omgivning och viljan att kommunicera tyst. En annan intressant upptäckt var sambandet mellan avskildhet och kommunikationssätt: röstbaserade tjänster undveks när andra människor fanns i närheten. Dessutom verkade det som om det var viktigare att värna om sin avskildhet och att inte störa andra i ickeanonyma situationer än i situationer där man var helt anonym.</p>

A speech controlled animation system is both a useful application program as well as a laboratory in which to investigate context aware applications as well as controlling errors. The user need not have prior knowledge or experience in animation and is yet able to create interesting and meaningful animation naturally and fluently. The system can be used in a number of applications ranging from PowerPoint presentations to simulations to children’s storytelling tools. / Singapore-MIT Alliance (SMA)

Driven by the need for faster devices and higher transistor densities, technology trends have pushed transistor dimensions into the deep sub-micron regime. This continued scaling, however, has led to many challenges facing digital integrated circuits today. One important challenge is the increased variations in the underlying process and environmental parameters, and the significant impact of this variability on circuit timing and leakage power, making it increasingly difficult to design circuits that achieve a required specification. Given these challenges, there is a need for computer-aided design (CAD) techniques that can predict and analyze circuit performance (timing and leakage) accurately and efficiently in the presence of variability. This thesis presents new techniques for variation-aware timing and leakage analysis that address different aspects of the problem. First, on the timing front, a pre-placement statistical static timing analysis technique is presented. This technique can be applied at an early stage of design, when within-die correlations are still unknown. Next, a general parameterized static timing analysis framework is proposed, which supports a general class of nonlinear delay models and handles both random (process) parameters with arbitrary distributions and non-random (environmental) parameters. Following this, a parameterized static timing analysis technique is presented, which can capture circuit delay exactly at any point in the parameter space. This is enabled by identifying all potentially critical paths in the circuit through novel and efficient pruning algorithms that improve on the state of art both in theoretical complexity and runtime. Also on the timing front, a novel distance-based metric for robustness is proposed. This metric can be used to quantify the susceptibility of parameterized timing quantities to failure, thus enabling designers to fix the nodes with smallest robustness values in order to improve the overall design robustness. Finally, on the leakage front, a statistical technique for early-mode and late-mode leakage estimation is presented. The novelty lies in the random gate concept, which allows for efficient and accurate full-chip leakage estimation. In its simplest form, the leakage estimation reduces to finding the area under a scaled version of the within-die channel length auto-correlation function, which can be done in constant time.

As computing becomes ubiquitous and intelligent, it is possible for systems to adapt their behavior based on information sensed from the situational context. However, determining the context space has been taken for granted in most ubiquitous applications, and so that context-adaptive systems often miss the situational factors that are most relevant to users. The mismatch between a system's computational model and users' mental model of the context may frustrate and disorient users. This thesis describes the CCM (cognitive context model)-based approach for eliciting individual cognitive views of a context-aware task and selecting an appropriate context space for context-aware computing. It captures the situational and cognitive context for each task, using a structural architecture in which individual participants use a context view to describe their situational perspective of the task. Clustering and optimization techniques are applied to analyze and integrate context views in CCM. Developers can use the optimization output to identify an appropriate context space, specify context-aware adaptation policies and resolve run-time policy conflicts. This approach simplifies the task of context elicitation, emphasizes individual variance in context-aware activity, and helps avoid user requirements misunderstanding.

Driven by the need for faster devices and higher transistor densities, technology trends have pushed transistor dimensions into the deep sub-micron regime. This continued scaling, however, has led to many challenges facing digital integrated circuits today. One important challenge is the increased variations in the underlying process and environmental parameters, and the significant impact of this variability on circuit timing and leakage power, making it increasingly difficult to design circuits that achieve a required specification. Given these challenges, there is a need for computer-aided design (CAD) techniques that can predict and analyze circuit performance (timing and leakage) accurately and efficiently in the presence of variability. This thesis presents new techniques for variation-aware timing and leakage analysis that address different aspects of the problem. First, on the timing front, a pre-placement statistical static timing analysis technique is presented. This technique can be applied at an early stage of design, when within-die correlations are still unknown. Next, a general parameterized static timing analysis framework is proposed, which supports a general class of nonlinear delay models and handles both random (process) parameters with arbitrary distributions and non-random (environmental) parameters. Following this, a parameterized static timing analysis technique is presented, which can capture circuit delay exactly at any point in the parameter space. This is enabled by identifying all potentially critical paths in the circuit through novel and efficient pruning algorithms that improve on the state of art both in theoretical complexity and runtime. Also on the timing front, a novel distance-based metric for robustness is proposed. This metric can be used to quantify the susceptibility of parameterized timing quantities to failure, thus enabling designers to fix the nodes with smallest robustness values in order to improve the overall design robustness. Finally, on the leakage front, a statistical technique for early-mode and late-mode leakage estimation is presented. The novelty lies in the random gate concept, which allows for efficient and accurate full-chip leakage estimation. In its simplest form, the leakage estimation reduces to finding the area under a scaled version of the within-die channel length auto-correlation function, which can be done in constant time.

As computing becomes ubiquitous and intelligent, it is possible for systems to adapt their behavior based on information sensed from the situational context. However, determining the context space has been taken for granted in most ubiquitous applications, and so that context-adaptive systems often miss the situational factors that are most relevant to users. The mismatch between a system's computational model and users' mental model of the context may frustrate and disorient users. This thesis describes the CCM (cognitive context model)-based approach for eliciting individual cognitive views of a context-aware task and selecting an appropriate context space for context-aware computing. It captures the situational and cognitive context for each task, using a structural architecture in which individual participants use a context view to describe their situational perspective of the task. Clustering and optimization techniques are applied to analyze and integrate context views in CCM. Developers can use the optimization output to identify an appropriate context space, specify context-aware adaptation policies and resolve run-time policy conflicts. This approach simplifies the task of context elicitation, emphasizes individual variance in context-aware activity, and helps avoid user requirements misunderstanding.

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Context information brings new opportunities for efficient and effective applications and services on mobile devices. Many existing work exploit the context dependency of mobile usage for specific applications, and show significant, quantified, performance gains by utilizing context. In order to be practical, such works often pay careful attention to the energy and processing costs of context awareness while attempting to maintain reasonable accuracy. These works also have to deal with the challenges of multiple sources of context, which can lead to a sparse training data set. Even with the abundance of such work, quantifying context-dependency and the relationship between context-dependency and performance achievements remains an open problem, and solutions to manage the and challenges of context awareness remain ad-hoc. To this end, this dissertation methodologically quantifies and measures the context dependency of three principal types of mobile usage in a methodological, application agnostic yet practical manner. The three usages are the websites the user visits, the phone numbers they call, and the apps they use, either built-in or obtained by the user from the App Store . While this dissertation measures the context dependency of these three principal types of mobile usage, its methodology can be readily extended to other context-dependent mobile usage and system resources. This dissertation further presents SmartContext, a framework to systematically optimize the energy cost of context awareness by selecting among different context sources, while satisfying the system designer’s cost-accuracy tradeoffs. Finally, this thesis investigates the collective effect of social context on mobile usage, by separating and comparing LiveLab users based on their socioeconomic groups. The analysis and findings are based on usage and context traces collected in real-life settings from 24 iPhone users over a period of one year. This dissertation presents findings regarding the context dependency of three principal types of mobile usage; visited websites, phone calls, and app usage. The methodology and lessons presented here can be readily extended to other forms of context and context-dependent usage and resources. They guide the development of context aware systems, and highlight the challenges and expectations regarding the context dependency of mobile usage.