This Master’s thesis studies different ways of exploiting the signal strength measurements from wireless interfaces for position determination. Difficulties include handling the fluctuating observations and their sensitivity to obstruction. We list important factors to take into account before describing a new system based on location fingerprinting and capable of integrating observations from multiple wireless interfaces. Compared to typical fingerprinting solutions, the training time is an order of magnitude shorter, but the location resolution is limited to locations of particular interest. In an office environment, the proposed solution determines the location correctly 80 percent of the time with sufficient precision for being used with context-aware services. In an open space environment, an incorrect location is reported 42 percent of the time. / Det här exjobbet studerar olika sätt att använda signalstyrka från trådlösa gränssnitt för positionsbestämning. Några av svårigheterna ligger i att hantera observationernas fluktuationer och deras känslighet för obstruktion. De viktigaste faktorerna att ta hänsyn till tas upp innan ett nytt system beskrivs. Det är baserat på positionsigenkänning (location fingerprinting) och kan dra nytta av observationer från flera olika trådlösa gränssnitt. Jämfört med vanliga metoder för positionsigenkänning är träningstiden en storleksordning kortare, men positionsupplösningen är begränsad till ett visst antal positioner av särskilt värde. I en kontorsmiljö klarar den föreslagna lösningen att korrekt bestämma positionen i 80 procent av fallen med tillräckligt hög noggrannhet för att användas till kontextmedvetna tjänster (context-aware services). I en öppen rumslösning ger lösningen en felaktig position i 42 procent av fallen.

Exploiting context-aware environments, where sensors scattered in a environment update presence servers to indicate the environmental changes can be used to enable new services. Such systems have become feasible both in terms of technical di±culties and their cost. A current focus in this area of research is how a context-aware system should be designed so that it reduces both the cost and complexity of the infrastructure, but still provides the desired services. One of the key components of many context-aware systems is location sensing, because a user's location is one of the most used elements of information in context-aware services. In this paper, we address cost e®ective location services by utilizing measurements of WLAN signal strength. We derive from these measurements an estimate of a device's location, and make this location information available via a SIP Presence User Agent, thus making location information readily available to services that might wish to use this information - while hiding details of how this information is acquired from these services. / Genom att utnyttja kontextmedvetna miljöer, där sensorer i en miljö uppdaterar närvarande servrar med information omändringar i omgivningen, så kan man öppna upp vägar för nya tjänster. Sådana system har blivit utförbara bade när det gäller tekniska svarigheter och deras kostnader. Inom forskning som rör sådana här system ägnas mycket uppmärksamhetåt hur en kontextmedveten miljö borde designas för att minimera både kostnaden och komplexiteten av infrastrukturen, men fortfarande tillhandahålla den önskade tjänsten. En av huvudkomponenterna i många kontextmedvetna system är platsuppfattning, eftersom en användares position är en av de mest använda elementen av information i kontextmedvetna tjänster. I den här uppsatsen ägnar vi oss åt kostnadseffektiva platstjänster genom att mäta signalstyrkan av ett WLAN. Genom dessa mätningar uppskattar vi en enhets position och gör denna information tillgänglig via en SIP Presence User Agent, och gör på så vis platsinformationen tillgänglig för tjänster som kan vilja ha den { utan att avslöja detaljer om hur informationen har skaffats.

Background. Code reviewing is a commonly used practice in software development. It refers to the process of reviewing new code changes, commonly before they aremerged with the code base. However, in order to perform the review, developers need to be assigned to that task. The problems with a manual assignment includes a time-consuming selection process; limited pool of known candidates; risk of high reuse of the same reviewers (high workload). Objectives. This thesis aims to attempt to address the above issues with a recommendation system. The idea is to receive feedback from experienced developers in order to expand upon identified reviewer factors; which can be used to determinethe suitability of developers as reviewers for a given change. Also, to develop and implement a solution that uses some of the most promising reviewer factors. The solution can later be deployed and validated through user and reviewer feedback in a real large-scale project. The developed recommendation system is named Carrot. Methods. An improvement case study was conducted at Ericsson. The identification of reviewer factors is found through literature review and semi-structured interviews. Validation of Carrot’s usability was conducted through static analysis,user feedback, and static validation. Results. The results show that Carrot can help identify adequate non-obvious reviewers and be of great assistance to new developers. There are mixed opinions on Carrot’s ability to assist with workload balancing and decrease of review lead time. The recommendations can be performed in a production environment in less than a quarter of a second. Conclusions. The implemented and validated approach indicates possible usefulness in performing recommendations, but could benefit significantly from further improvements. Many of the problems seen with the recommendations seem to be a result of corner-cases that are not handled by the calculations. The problems would benefit considerably from further analysis and testing.

付記する学位プログラム名: デザイン学大学院連携プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21217号 / 情博第670号 / 新制||情||115(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 五十嵐 淳, 教授 石田 亨, 教授 山本 章博 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

The purpose of this thesis was to utilize existing technologies to create a development environment suitable for creating context-aware applications and systems specific to home and family living conditions. After outlining the history of context-aware applications and the challenges that face family-centric systems in this field, a development environment was implemented that solves the unique challenges that face application development for family-centric, context-aware applications. In particular, research cited in this document indicates that a browser-based user interface is the most appropriate interface for a family environment. The flexibility of the interface, as well as the familiarity of the application structure allows family members of varying levels of comprehension to use a given application. The use of a browser interface for a context-aware system creates unique challenges such as the ability to integrate with external applications and external devices. In addition to overcoming the restrictions of web browsers, the development environment was designed to support the unique user environment presented by a family structure. This includes mechanisms for the long-term adaptability of the system to the changing lifestyles of the family members, as well as the infrequent, but necessary ability to adjust the structure of the family unit due to the addition or prolonged absence of family members. Another problem that the development environment was required to solve was the varying levels of computer comprehension that exist among different family members. An application that targets an entire family unit must meet the usability needs of all levels of comprehension. The development environment was created to account for this wide array of usability requirements. The resulting development environment was implemented on a Windows XP Professional environment, utilizing existing technologies and software that were mostly cross-browser compatible. Although a new technology was not designed and created, existing technologies were combined to solve the aforementioned problems that are unique to developing systems and applications for a family-centric, context-aware environment. Recommendations are made for future research and development in the area of family-assistive application development.

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Tesis por compendio / [EN] Multi-Agent Systems (MAS), Argumentation and Automated Planning are three lines of investigations within the field of Artificial Intelligence (AI) that have been extensively studied over the last years. A MAS is a system composed of multiple intelligent agents that interact with each other and it is used to solve problems whose solution requires the presence of various functional and autonomous entities. Multi-agent systems can be used to solve problems that are difficult or impossible to resolve for an individual agent. On the other hand, Argumentation refers to the construction and subsequent exchange (iteratively) of arguments between a group of agents, with the aim of arguing for or against a particular proposal. Regarding Automated Planning, given an initial state of the world, a goal to achieve, and a set of possible actions, the goal is to build programs that can automatically calculate a plan to reach the final state from the initial state. The main objective of this thesis is to propose a model that combines and integrates these three research lines. More specifically, we consider a MAS as a team of agents with planning and argumentation capabilities. In that sense, given a planning problem with a set of objectives, (cooperative) agents jointly construct a plan to satisfy the objectives of the problem while they defeasibly reason about the environmental conditions so as to provide a stronger guarantee of success of the plan at execution time. Therefore, the goal is to use the planning knowledge to build a plan while agents beliefs about the impact of unexpected environmental conditions is used to select the plan which is less likely to fail at execution time. Thus, the system is intended to return collaborative plans that are more robust and adapted to the circumstances of the execution environment. In this thesis, we designed, built and evaluated a model of argumentation based on defeasible reasoning for planning cooperative multi-agent system. The designed system is independent of the domain, thus demonstrating the ability to solve problems in different application contexts. Specifically, the system has been tested in context sensitive domains such as Ambient Intelligence as well as with problems used in the International Planning Competitions. / [ES] Dentro de la Inteligencia Artificial (IA), existen tres ramas que han sido ampliamente estudiadas en los últimos años: Sistemas Multi-Agente (SMA), Argumentación y Planificación Automática. Un SMA es un sistema compuesto por múltiples agentes inteligentes que interactúan entre sí y se utilizan para resolver problemas cuya solución requiere la presencia de diversas entidades funcionales y autónomas. Los sistemas multiagente pueden ser utilizados para resolver problemas que son difíciles o imposibles de resolver para un agente individual. Por otra parte, la Argumentación consiste en la construcción y posterior intercambio (iterativamente) de argumentos entre un conjunto de agentes, con el objetivo de razonar a favor o en contra de una determinada propuesta. Con respecto a la Planificación Automática, dado un estado inicial del mundo, un objetivo a alcanzar, y un conjunto de acciones posibles, el objetivo es construir programas capaces de calcular de forma automática un plan que permita alcanzar el estado final a partir del estado inicial. El principal objetivo de esta tesis es proponer un modelo que combine e integre las tres líneas anteriores. Más específicamente, nosotros consideramos un SMA como un equipo de agentes con capacidades de planificación y argumentación. En ese sentido, dado un problema de planificación con un conjunto de objetivos, los agentes (cooperativos) construyen conjuntamente un plan para resolver los objetivos del problema y, al mismo tiempo, razonan sobre la viabilidad de los planes, utilizando como herramienta de diálogo la Argumentación. Por tanto, el objetivo no es sólo obtener automáticamente un plan solución generado de forma colaborativa entre los agentes, sino también utilizar las creencias de los agentes sobre la información del contexto para razonar acerca de la viabilidad de los planes en su futura etapa de ejecución. De esta forma, se pretende que el sistema sea capaz de devolver planes colaborativos más robustos y adaptados a las circunstancias del entorno de ejecución. En esta tesis se diseña, construye y evalúa un modelo de argumentación basado en razonamiento defeasible para un sistema de planificación cooperativa multiagente. El sistema diseñado es independiente del dominio, demostrando así la capacidad de resolver problemas en diferentes contextos de aplicación. Concretamente el sistema se ha evaluado en dominios sensibles al contexto como es la Inteligencia Ambiental y en problemas de las competiciones internacionales de planificación. / [CA] Dins de la intel·ligència artificial (IA), hi han tres branques que han sigut àmpliament estudiades en els últims anys: Sistemes Multi-Agent (SMA), Argumentació i Planificació Automàtica. Un SMA es un sistema compost per múltiples agents intel·ligents que interactúen entre si i s'utilitzen per a resoldre problemas la solución dels quals requereix la presència de diverses entitats funcionals i autònomes. Els sistemes multiagente poden ser utilitzats per a resoldre problemes que són difícils o impossibles de resoldre per a un agent individual. D'altra banda, l'Argumentació consistiex en la construcció i posterior intercanvi (iterativament) d'arguments entre un conjunt d'agents, amb l'objectiu de raonar a favor o en contra d'una determinada proposta. Respecte a la Planificació Automàtica, donat un estat inicial del món, un objectiu a aconseguir, i un conjunt d'accions possibles, l'objectiu és construir programes capaços de calcular de forma automàtica un pla que permeta aconseguir l'estat final a partir de l'estat inicial. El principal objectiu d'aquesta tesi és proposar un model que combine i integre les tres línies anteriors. Més específicament, nosaltres considerem un SMA com un equip d'agents amb capacitats de planificació i argumentació. En aquest sentit, donat un problema de planificació amb un conjunt d'objectius, els agents (cooperatius) construeixen conjuntament un pla per a resoldre els objectius del problema i, al mateix temps, raonen sobre la viabilitat dels plans, utilitzant com a ferramenta de diàleg l'Argumentació. Per tant, l'objectiu no és només obtindre automàticament un pla solució generat de forma col·laborativa entre els agents, sinó també utilitzar les creences dels agents sobre la informació del context per a raonar sobre la viabilitat dels plans en la seua futura etapa d'execució. D'aquesta manera, es pretén que el sistema siga capaç de tornar plans col·laboratius més robustos i adaptats a les circumstàncies de l'entorn d'execució. En aquesta tesi es dissenya, construeix i avalua un model d'argumentació basat en raonament defeasible per a un sistema de planificació cooperativa multiagent. El sistema dissenyat és independent del domini, demostrant així la capacitat de resoldre problemes en diferents contextos d'aplicació. Concretament el sistema s'ha avaluat en dominis sensibles al context com és la inte·ligència Ambiental i en problemes de les competicions internacionals de planificació. / Pajares Ferrando, S. (2016). Defeasible Argumentation for Cooperative Multi-Agent Planning [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/60159 / Compendio

Augmented Reality (AR) transforms the entire 3D space around the user into a dynamic screen, surpassing the limitations of traditional displays and enabling efficient access to multiple pieces of information simultaneously, all day, every day. Recent developments in AR eyeglasses promise that AR could become the next generation of personal computing devices. To realize this vision of pervasive AR, the AR interface must address the challenges posed by constant and omnipresent virtual content. As the user's context changes, the virtual content in AR head-worn displays can occasionally become obtrusive, hindering the user's perception and awareness of their surroundings and their interaction with both the virtual and physical worlds. An intelligent interface is needed to adapt the presentation and interaction of AR content. This dissertation outlines a roadmap towards effective, efficient, and unobtrusive AR through intelligent AR (iAR) systems that automatically learn and adapt the interface to the user's context. To achieve this goal, we: %(1) Design multiple context-aware AR interfaces and explore their design and effectiveness in various contexts through four experiments; (1) Identify multiple AR design principles and guidelines that maintain efficiency while addressing challenges such as occlusion, social interaction, and content placement in AR. (2) Demonstrate the impact of context on AR effectiveness, validating the advantages of context-awareness and highlighting the complexities of implementing a context-aware approach in pervasive AR, particularly in scenarios involving context-switching. (3) Propose a design space for XR interfaces; (4) Develop a taxonomy of quantifiable contextual components and a framework for designing iAR interfaces. / Doctor of Philosophy / Augmented Reality (AR) integrates digital information with the real world in real-time, transforming the surrounding physical space into a dynamic, interactive screen. This technology can simultaneously provide hands-free access to unlimited virtual applications and information, facilitating fast and easy access. With recent advancements in AR eyeglasses, AR is anticipated to become the next generation of personal computing, potentially replacing mobile phones and computers. However, to be seamlessly integrated into daily life, AR must overcome challenges such as occluding important real-world objects, distraction, visual clutter, and information overload. This dissertation presents a roadmap for developing intelligent AR (iAR) systems that automatically adapt to the user's context. To achieve this goal, we identify the design space for adaptable AR elements and design and test various context-aware AR interfaces. We identify key AR design principles that ensure efficiency while addressing challenges like occlusion, social interaction, and content placement. We also highlight the impact of context on AR effectiveness and the complexities of implementing a context-aware approach, especially in context-switching scenarios. Additionally, we informed the design process of iAR interfaces by identifying the contextual components that influence their effectiveness and providing a framework and architecture for utilizing this information for automatic adaptations. These efforts aim to enhance AR effectiveness and efficiency while ensuring it remains unobtrusive in everyday use.