V současné době se zvyšuje potřeba rozvoje agilních výrobních postupů, které lze snadno přizpůsobit neustálému zavádění nových produktů na trh. Jednobodové inkrementální tváření je nový, inovativní a proveditelný tvářecí proces s jednoduchým uspořádáním. Proces se provádí při pokojové teplotě (tváření za studena) a vyžaduje CNC stroj, nástroj s kulovou hlavou a jednoduché příslušenství pro uchycení obrobku plechu. V samotném procesu jde o přírůstkové formování, řízené CNC programem. Plastická deformace je lokalizována pod formovacím nástrojem takže plech je tvářen souhrnem pohybů lokální plastické zóny. Tento proces je zdlouhavý a proto se hodí pouze pro prototypovou výrobu nebo pro malé výrobní dávky. Na druhé straně umožňuje vyšší tvářitelnost ve srovnání s konvenčními procesy tváření, umožňuje použití levných nástrojů a také je charakterizován krátkou dobou od návrhu po výrobu produktu. Tato práce je výsledkem mezinárodní spolupráce Danmarks Tekniske Universitet v Lyngby a Instituto Superior Técnico v Lisabonu. Práce začíná krátkým hodnocením dílčích tvářecích procesů, pokračuje představováním jednobodového inkrementálního tváření a identifikací jeho praktických aplikací. Teoretická část obsahuje přehled nového rámce pro jednobodové inkrementální tváření, který je vytvořen na základě analýzy styku třecích sil. Praktická část projektu poskytuje úplný popis experimentálních technik použitých pro charakterizaci materiálů a stanovení limitů tvářitelnosti, dále se analyzuje vliv různých vstupních parametrů procesu (poloměru nástroje, tepelné zpracování materiálu obrobku, druh maziva,...). Tato část také obsahuje přehled experimentálního uspořádaní procesu jednobodového inkrementálního tváření i krátký popis CAD / CAM vývoje tří testovacích modelů. Poté jsou popsány v samostatné kapitole výsledky pozorování a analýzy hlavních parametrů procesů, které ovlivňují tvařitelnostní limity v jednobodovém inkrementálním tváření v souvislosti s aplikovaným teoretickým rámcem. Výsledky experimentů z časti objasňují probíhající mezinárodní diskusi kolem tvářitelnosti mechanismu jednobodového inkrementálního tváření vzhledem k tradičním metodám tváření. Jako logické pokračování prováděných experimentů, byla práce rozšířena na více-stupňové jednobodové inkrementální tváření, které umožňuje tváření součástek (kalíšku) se svislými stěnami ve více krocích. Za účelem objasnění procesů spojených s tímhle procesem byly navrženy a ve čtyřech krocích vyrobeny dva experimentální modely. Hlavním přínosem této práce k více-stupňovému jednobodovému inkrementálnímu tváření byla úspěšná výroba součásti s nekruhovým průřezem a kolmými stěnami. S cílem aplikovat celkové znalosti získáných v předchozích částí práce byla vyrobena prototypová součást. Popis designu a vývoje prototypu je součástí práce. V neposlední řadě jsou celkové závěry uvedené v poslední kapitole. Předpokládá se, že tato práce přizpívá k lepšímu pochopení mechanismu jednobodového inkrementálního tváření.

L'intelligence artificielle est la discipline de recherche d'imitation ou de remplacement de fonctions cognitives humaines. À ce titre, l'une de ses branches s'inscrit dans l'automatisation progressive du processus de programmation. Il s'agit alors de transférer de l'intelligence ou, à défaut de définition, de transférer de la charge cognitive depuis l'humain vers le système, qu'il soit autonome ou guidé par l'utilisateur. Dans le cadre de cette thèse, nous considérons les conditions de l'évolution depuis un système guidé par son utilisateur vers un système autonome, en nous appuyant sur une autre branche de l'intelligence artificielle : l'apprentissage artificiel. Notre cadre applicatif est celui de la conception d'un assistant opérationnel incrémental, c'est-à-dire d'un système capable de réagir à des requêtes formulées par l'utilisateur en adoptant les actions appropriées, et capable d'apprendre à le faire. Pour nos travaux, les requêtes sont exprimées en français, et les actions sont désignées par les commandes correspondantes dans un langage de programmation (ici, R ou bash). L'apprentissage du système est effectué à l'aide d'un ensemble d'exemples constitué par les utilisateurs eux-mêmes lors de leurs interactions. Ce sont donc ces derniers qui définissent, progressivement, les actions qui sont appropriées pour chaque requête, afin de rendre le système de plus en plus autonome. Nous avons collecté plusieurs ensembles d'exemples pour l'évaluation des méthodes d'apprentissage, en analysant et réduisant progressivement les biais induits. Le protocole que nous proposons est fondé sur l'amorçage incrémental des connaissances du système à partir d'un ensemble vide ou très restreint. Cela présente l'avantage de constituer une base de connaissances très représentative des besoins des utilisateurs, mais aussi l'inconvénient de n'aquérir qu'un nombre très limité d'exemples. Nous utilisons donc, après examen des performances d'une méthode naïve, une méthode de raisonnement à partir de cas : le raisonnement par analogie formelle. Nous montrons que cette méthode permet une précision très élevée dans les réponses du système, mais également une couverture relativement faible. L'extension de la base d'exemples par analogie est explorée afin d'augmenter la couverture des réponses données. Dans une autre perspective, nous explorons également la piste de rendre l'analogie plus tolérante au bruit et aux faibles différences en entrée en autorisant les approximations, ce qui a également pour effet la production de réponses incorrectes plus nombreuses. La durée d'exécution de l'approche par analogie, déjà de l'ordre de la seconde, souffre beaucoup de l'extension de la base et de l'approximation. Nous avons exploré plusieurs méthodes de segmentation des séquences en entrée afin de réduire cette durée, mais elle reste encore le principal obstacle à contourner pour l'utilisation de l'analogie formelle dans le traitement automatique de la langue. Enfin, l'assistant opérationnel incrémental fondé sur le raisonnement analogique a été testé en condition incrémentale simulée, afin d'étudier la progression de l'apprentissage du système au cours du temps. On en retient que le modèle permet d'atteindre un taux de réponse stable après une dizaine d'exemples vus en moyenne pour chaque type de commande. Bien que la performance effective varie selon le nombre total de commandes considérées, cette propriété ouvre sur des applications intéressantes dans le cadre incrémental du transfert depuis un domaine riche (la langue naturelle) vers un domaine moins riche (le langage de programmation). / Artificial Intelligence is the field of research aiming at mimicking or replacing human cognitive abilities. As such, one of its subfields is focused on the progressive automation of the programming process. In other words, the goal is to transfer cognitive load from the human to the system, whether it be autonomous or guided by the user. In this thesis, we investigate the conditions for making a user-guided system autonomous using another subfield of Artificial Intelligence : Machine Learning. As an implementation framework, we chose the design of an incremental operational assistant, that is a system able to react to natural language requests from the user with relevant actions. The system must also be able to learn the correct reactions, incrementally. In our work, the requests are in written French, and the associated actions are represented by corresponding instructions in a programming language (here R and bash). The learning is performed using a set of examples composed by the users themselves while interacting. Thus they progressively define the most relevant actions for each request, making the system more autonomous. We collected several example sets for evaluation of the learning methods, analyzing and reducing the inherent collection biases. The proposed protocol is based on incremental bootstrapping of the system, starting from an empty or limited knowledge base. As a result of this choice, the obtained knowledge base reflects the user needs, the downside being that the overall number of examples is limited. To avoid this problem, after assessing a baseline method, we apply a case base reasoning approach to the request to command transfer problem: formal analogical reasoning. We show that this method yields answers with a very high precision, but also a relatively low coverage. We explore the analogical extension of the example base in order to increase the coverage of the provided answers. We also assess the relaxation of analogical constraints for an increased tolerance of analogical reasoning to noise in the examples. The running delay of the simple analogical approach is already around 1 second, and is badly influenced by both the automatic extension of the base and the relaxation of the constraints. We explored several segmentation strategies on the input examples in order to reduce reduce this time. The delay however remains the main obstacle to using analogical reasoning for natural language processing with usual volumes of data. Finally, the incremental operational assistant based on analogical reasoning was tested in simulated incremental condition in order to assess the learning behavior over time. The system reaches a stable correct answer rate after a dozen examples given in average for each command type. Although the effective performance depends on the total number of accounted commands, this observation opens interesting applicative tracks for the considered task of transferring from a rich source domain (natural language) to a less rich target domain (programming language).

Linked Data describes an extensive set of structured but heterogeneous datasources where entities are connected by formal semantic descriptions. In thevision of the Semantic Web, these semantic links are extended towards theWorld Wide Web to provide as much machine-readable data as possible forsearch queries. The resulting connections allow an automatic evaluation to findnew insights into the data. Identifying these semantic connections betweentwo data sources with automatic approaches is called link discovery. We derivecommon requirements and a generic link discovery workflow based on similaritiesbetween entity properties and associated properties of ontology concepts. Mostof the existing link discovery approaches disregard the fact that in times ofBig Data, an increasing volume of data sources poses new demands on linkdiscovery. In particular, the problem of complex and time-consuming linkdetermination escalates with an increasing number of intersecting data sources.To overcome the restriction of pairwise linking of entities, holistic clusteringapproaches are needed to link equivalent entities of multiple data sources toconstruct integrated knowledge bases. In this context, the focus on efficiencyand scalability is essential. For example, reusing existing links or backgroundinformation can help to avoid redundant calculations. However, when dealingwith multiple data sources, additional data quality problems must also be dealtwith. This dissertation addresses these comprehensive challenges by designingholistic linking and clustering approaches that enable reuse of existing links.Unlike previous systems, we execute the complete data integration workflowvia a distributed processing system. At first, the LinkLion portal will beintroduced to provide existing links for new applications. These links act asa basis for a physical data integration process to create a unified representationfor equivalent entities from many data sources. We then propose a holisticclustering approach to form consolidated clusters for same real-world entitiesfrom many different sources. At the same time, we exploit the semantic typeof entities to improve the quality of the result. The process identifies errorsin existing links and can find numerous additional links. Additionally, theentity clustering has to react to the high dynamics of the data. In particular,this requires scalable approaches for continuously growing data sources withmany entities as well as additional new sources. Previous entity clusteringapproaches are mostly static, focusing on the one-time linking and clustering ofentities from few sources. Therefore, we propose and evaluate new approaches for incremental entity clustering that supports the continuous addition of newentities and data sources. To cope with the ever-increasing number of LinkedData sources, efficient and scalable methods based on distributed processingsystems are required. Thus we propose distributed holistic approaches to linkmany data sources based on a clustering of entities that represent the samereal-world object. The implementation is realized on Apache Flink. In contrastto previous approaches, we utilize efficiency-enhancing optimizations for bothdistributed static and dynamic clustering. An extensive comparative evaluationof the proposed approaches with various distributed clustering strategies showshigh effectiveness for datasets from multiple domains as well as scalability on amulti-machine Apache Flink cluster.

This thesis concerns the design, implementation and evaluation of a specification based testing architecture for reactive systems using the paradigm of learning-based testing. As part of this work we have designed, verified and implemented new incremental learning algorithms for DFA and Kripke structures.These have been integrated with the NuSMV model checker to give a new learning-based testing architecture. We have evaluated our architecture on case studies and shown that the method is effective. / QC 20110822

No description available.

In a broader sense the main research objective of this thesis (and ongoing research work) is distributed knowledge management for mobile dynamic systems. But the primary focus and presented work focuses on communication/interoperability of heterogeneous entities in an infrastructure less paradigm, a distributed resource manipulation infrastructure and distributed learning in the absence of global knowledge. The research objectives achieved discover the design aspects of heterogeneous distributed knowledge systems towards establishing a seamless integration. This thesis doesn’t cover all aspects in this work; rather focuses on interoperability and distributed learning. Firstly a discussion on the issues in knowledge management for swarm of heterogeneous entities is presented. This is done in a broader and rather abstract fashion to provide an insight of motivation for interoperability and distributed learning towards knowledge management. Moreover this will also serve the reader to understand the ongoing work and research activities in much broader perspective. Primary focus of this thesis is communication/interoperability of heterogeneous entities in an infrastructure less paradigm, a distributed resource manipulation infrastructure and distributed learning in the absence of global knowledge. In dynamic environments for mobile autonomous systems such as robot swarms or mobile software agents there is a need for autonomic publishing and discovery of resources and just-in-time integration for on-the-fly service consumption without any a priori knowledge. SOA (Service-Oriented Architecture) serves the purpose of resource reuse and sharing of services different entities. Web services (a SOA manifestation) achieves these objectives but its exploitation in dynamic environments, where the communication infrastructure is lacking, requires a considerable research. Generally Web services are exploited in stable client-server paradigms, which is a pressing assumption when dynamic distributed systems are considered. UDDI (Universal Description Discovery and Integration) is the main pediment in the exploitation of Web services in distributed control and dynamic natured systems. UDDI can be considered as a directory for publication and discovery of categorized Web services but assumes a centralized registry; even if distributed registries and associated mechanism are employed problems of collaborative communication in infrastructure less paradigms are ignored. Towards interoperability main contribution this thesis is a mediator-based distributed Web services discovery and invocation middleware, which provides a collaborative and decentralized services discovery and management middleware for infrastructure-less mobile dynamic systems with heterogeneous communication capabilities. Heterogeneity of communication capabilities is abstracted in middleware by a conceptual classification of computing entities on the basis of their communication capabilities and communication issues are resolved via conceptual overlay formation for query propagation in system. The proposed and developed middleware has not only been evaluated extensively using Player Stage simulator but also been applied in physical robot swarms. Experimental validations analyze the results in different communication modes i. active and ii. passive mode of communication with and without shared resource conflict resolution. I analyze discoverable Web services with respect to time, services available in complete view of cluster and the impact and resultant improvements in distributed Web services discovery by using caching and semantics. Second part of this thesis focuses on distributed learning in the absence of global information. This thesis takes the argument of defeasibility (common-sense inference) as the basis of intelligence in human-beings, in which conclusions/inferences are drawn and refuted at the same time as more information becomes available. The ability of common-sense reasoning to adapt to dynamic environments and reasoning with uncertainty in the absence of global information seems to be best fit for distributed learning for dynamic systems. This thesis, thus, overviews epistemic cognition in human beings, which motivates the need of a similar epistemic cognitive solution in fabricated systems and considers formal concept analysis as a case for incremental and distributed learning of formal concepts. Thesis also presents a representational schema for underlying logic formalism and formal concepts. An algorithm for incremental learning and its use-case for robotic navigation, in which robots incrementally learn formal concepts and perform common-sense reasoning for their intelligent navigation, is also presented. Moreover elaboration of the logic formalism employed and details of implementation of developed defeasible reasoning engine is given in the latter half of this thesis. In summary, the research results and achievements described in this thesis focus on interoperability and distributed learning for heterogeneous distributed knowledge systems which contributes towards establishing a seamless integration in mobile dynamic systems. / QC 20100614 / ROBOSWARM EU FP6

User inertia is a real innovation adoption problem that cannot be seen or grasped. How to overcome user inertia while introducing innovation has become a key factor in today's society. Based on the background of requirements engineering, the goal of this thesis is to study and understand the relationship between user inertia and innovation adoption, including whether the type of innovation has an impact on user adoption and how to use strategies to reduce this impact. Through an online survey of 60 users and a systematic literature review of a series of articles, we have concluded the following points: RI has a greater impact on user inertia, while II has almost no impact; neither RI nor II has a significant impact on user satisfaction. Not only that, but through literature review, we have also concluded a comprehensive strategy to deal with the adoption problem caused by user inertia.

Incremental idle clickers is a genre of games where gameplay revolves aroundsimple interactions like clicking the screen repeatedly to accumulatecurrency. The clicking action is often automatized by the game. This thesisinvestigates qualities that make interactions in incremental idle clickerscompulsive and motivating. The incremental idle clickers genre adoptsmechanics and interactions that were experienced as compelling, motivatingand anxiety-inducing. The “idle” mechanic allows the game to run withoutplayer interaction and proved to be central in relation to the playerexperience. Through a user-centered design-process, the compulsive andmotivating nature can be suggested to emerge from three major experiencesof the genre, “Monotony”, “Intrusive omnipresence” and “Demanding”. Theresult includes a discovery of the ambiguous tension and balance betweeninteractivity and interpassivity in the genre. Finding this balance may provebeneficial to the player experience. I identified ethical challenges concerningthe game depriving players of satisfying gameplay.

Incremental damage assessment is a tool used to assess the justification for expensive modifications of inadequate dams. The input data to incremental damage assessment are the output from the breach analysis and flood routing. For this reason, flood routing should be conducted carefully. Distorted results from the flood routing technique or unstable modeling of the problem will distort the results of an incremental damage assessment, because an error in the estimated incremental stage will cause a certain error in the estimated incremental damages. The objectives of this study were (1) to perform a comprehensive survey of the available dam break flood-routing techniques, (2) to evaluate the performance of commonly used flood-routing techniques for predicting failure and no-failure stage, incremental stage, average velocities, and travel times, and (3) to develop a set of recommendations upon which future applications of dam break models can be based. Flood-routing techniques that are evaluated cover dynamic routing as contained in DAMBRK, and kinematic, Muskingum-Cunge, and normal depth storage routing as contained in the Hydrological Engineering Center (HEC 1). These techniques were evaluated against the more accurate two-dimensional flood-routing technique contained in the diffusion hydrodynamic model (DHM). Results and errors from different techniques for different downstream conditions were calculated and conclusions were drawn. The effect of the errors on the incremental stage and the errors in the incremental stage were estimated. Overall, the performance of one-dimensional techniques in predicting peak stages, and assessing a two-feet criterion showed that DAMBRK did best, and normal depth storage and outflow did worst. This overall ranking matches the degree of simplification in representing the true flood-routing situation. However, in some circumstances DAMBRK performed worst, and normal depth storage and outflow outperformed either the Muskingum-Cunge or kinematic techniques. Thus, it is important to understand the specific performance characteristics of all the methods when selecting one for a flood-routing application.

Cette thèse porte sur la conception et la réalisation de convertisseurs analogique/numérique (ADC) haute résolution dans le domaine de l’imagerie spatiale en technologie 0.18 μm.Un imageur CMOS est un système destiné à acquérir des informations lumineuses et les convertir en données numériques afin que cellesci soient traitées. Ce système est composé d’une matrice de pixels, d’ADC, de registres et de blocs de signaux de commande afin de rendre toutes ces données disponibles. Avec la taille grandissante de la matrice de pixels et la cadence d’image par seconde croissante, l’ADC doit réaliser de plus en plus de conversions en moins de temps et est donc devenu l’un des « bottleneck » les plus importants dans les systèmes d’imagerie. Une solution adaptée a donc été le développement d’ADC colonne situé en bout de colonnes de pixels afin de réaliser des conversions en parallèles et c’est ce sujet qui va m’intéresser.Dans une première partie, n’ayant pas de contraintes sur l’architecture d’ADC à utiliser, une étude de l’état de l’art des ADC pour l’imagerie est réalisée ainsi que les spécifications visées pour notre application. Une architecture sigma-delta incrémental à deux étapes semble la plus prometteuse et va être développée. Ensuite, une étude théorique de l’ADC choisi, et plus particulièrement du modulateur sigma-delta à utiliser est effectuée, afin notamment de déterminer l’ordre de ce modulateur, mais également le nombre de cycles de cette conversions. Une fois les paramètres de modélisation définis, un schéma transistor est réalisé au niveau transistor, avec une particularité au niveau de l’amplificateur utilisé. En effet, afin de gagner en surface qui est l’un des points importants dans les systèmes d’imagerie, un inverseur est utilisé. Une étude de cette inverseur, afin de choisir le plus adapté à notre besoin est effectuée avec des simulations montecarlo et aux « corners ». Pour finir, un routage global de l’ADC est réalisé afin de pouvoir comparer ces performances à l’état de l’art. / This thesis deals with the conception and design of high resolution analog-to-digital converters (ADC) for CMOS image sensor (CIS) applications with the 0.18 μm technology. A CIS is a system able to convert light to digital data to be processed. This system includes a pixel array, ADCs, registers and a set of clocks to acquire and transport the data. At the beginning, a single ADC was used for the whole matrix of pixels, converting the pixel value in a sequential way. With the growing size of the pixel array and the increasing frame rate, the ADC became one of the bottleneck of these system. A solution was found to use column ADC, located at the bottom of each column in order to parallelize the conversions. These column ADC are going to be my point of interest in this thesis.First of all, a state of the art of the ADC for CIS is realized in order to determine the best architecture to use. A two-step incremental sigma-delta is chosen and investigated. A theoretical analysis is done, especially on the modulator in order to determine the order of this modulator and the oversampling ratio of the conversion. Then a schematic is realized, with a special feature on the amplifier. Indeed, an inverter is used as amplifier in order to reduce the size of the ADC. A montecarlo and corner studies are then realized on the ADC, a layout is proposed and the ADC is compared to the state of the art of the ADC for CIS.