This thesis presents design, modeling, and fabrication of an RF MEMS adjustable impedance matching network. The device employs the basic triple stub matching technique for impedance matching. It has three adjustable length stubs which are implemented using capacitively loaded coplanar waveguides. The capacitive loading of the stubs are realized using the MEMS switches which are evenly distributed over the stubs. There are 40 MEMS bridges on each stub whichare separated with &amp / #955 / /40 spacing making a total of 120 MEMS switches in the structure. The variability of the stub length is accomplished by closing the MEMS switch nearest to the required stub length, and making a virtual short circuit to ground. The device is theoretically capable of doing matching to every point on the Smith chart. The device is built on coplanar waveguide transmission lines. It has a center operating frequency of 10GHz, but because of its adjustability property it is expected to work in 1-40GHz range. It has dimensions of 8950 &times / 5720&micro / m2. This work is the continuation of the first national work on fabrication of RF MEMS devices. The device in this work is fabricated using the surface micromachining technology in the microelectronic facilities of Middle East Technical University.

Cette thèse propose l’utilisation de l’alignement d'ontologies pour contribuer à l'interopérabilité d’une fédération d’entreprises en se basant sur l'interopérabilité des données au niveau sémantique. Une approche d'alignement basée sur des modèles d’ontologie utilisant les mots noyaux est proposée en réponse aux problèmes et aux défis existants, visant ainsi à améliorer la capacité d'adaptation et la précision dans la mise en correspondance de concepts. De plus une étape d'agrégation des « matchers » analytique, qui permet de combiner automatiquement plusieurs adaptateurs et d'améliorer les résultats combinés, vient compléter l’approche. Un système prototype a été mis en œuvre à l’issue des travaux conceptuels pour la validation de l’approche proposée. Les expériences démontrent que l’approche proposée a obtenu des résultats prometteurs et a atteint les objectifs escomptés sur la définition de proximité des concepts. L'approche d'alignement d’ontologies proposée et le système de prototype mis en œuvre ont enfin été appliqués à une architecture dirigée par les ontologies et axée sur l'interrogation des données de plusieurs bases de données relationnelles. / This thesis brings ontology alignment to contribute to federated enterprise interoperability focusing on data interoperability at the semantic level. In response to existing problems and challenges, aiming at improving the matching ability and precision, a pattern-based core word ontology alignment approach is proposed, as well as an analytic matcher aggregation approach, which allows combining the multiple matchers automatically and improve the combined results. A prototype system is implemented for validation and further application based on the proposed approaches. The experiments suggest that the proposed approaches obtained promising results and reached expected goals. The proposed ontology alignment approach and implemented prototype system are applied to an ontology-driven architecture for querying data from multiple relational databases.

L’utilisation de réseaux de neurones artificiels pour divers types de traitements d’information bio-inspirés est une technique de plus en plus répandue dans le domaine de l’intelligence artificielle. Leur fonctionnement diffère avantageusement de celui des ordinateurs conventionnels en permettant une plus grande parallélisation des calculs, ce qui explique pourquoi autant d’efforts sont déployés afin de réaliser une plate-forme matérielle dédiée à leur simulation. Pour ce projet, une architecture matérielle flexible simulant efficacement un réseau de neurones à décharges est présentée. Celle-ci se distingue des architectures existantes notamment parce qu’elle utilise une approche de simulation à événements discrets et parce qu’elle permet une détection efficace des événements simultanés. Ces caractéristiques en font une plate-forme de choix pour la simulation de réseaux de neurones à décharges de plus de 100 000 neurones où un niveau important de synchronie des décharges neuronales est atteint. Afin d’en démontrer les performances, une application en traitement d’images utilisant cette architecture a été réalisée sur FPGA. Cette application a permis de démontrer que la structure proposée pouvait simuler jusqu’à 2[indice supérieur 17] neurones et traiter des dizaines de millions d’événements par secondes lorsque cadencé à 100 MHz.

The aim of this thesis is to create a mobile application for Android, which allows users to create high-quality photos of planar objects. User can create multiple photographs of a selected planar object. These photographs are then aligned and combined into one final image. Various shortcomings that can be present in the photographs are filtered.

In the field of speech recognition, an algorithm must learn to tell the difference between "a nice rock" and "a gneiss rock". These identical-sounding phrases are called oronyms. Word frequency dictionaries are often used by speech recognition systems to help resolve phonetic sequences with more than one possible orthographic phrase interpretation, by looking up which oronym of the root phonetic sequence contains the most-common words.Our paper demonstrates a technique used to validate word frequency dictionary values. We chose to use frequency values from the UNISYN dictionary, which tallies each word on a per-occurance basis, using a proprietary text corpus, to calculate word frequency.In the first phase of our user study, we generated oronym strings for the phrase "a nice cold hour", and had over a dozen people make 62 of the most-common oronyms for that phrase. In the second phase, we selected 15 of the phase one recordings, and had 74 different people transcribe each one, for a total of 953 transcriptions overall. If the frequency dictionary values for our test phrases accurately reflected the real-world expectations of actual listeners, we would expect that the most-commonly transcribed phrases in our user study would roughly correspond with our metric for the most likely oronym interpretation of the root phrase. During the course of our study, we found that using per-occurance frequency values, like those found in the UNISYN dictionary, when computing our overall-phrase-frequency metric caused the end result to be thrown off by excessively common words, such as "the", "is", and "a" These super-common words had such high per-occurance tallies that they overpowered any effect that any regular word had on a frequency metric. When we used frequency values from the COCA dictionary, which has word frequency values tallied on a document-count basis instead of a UNISYN-like per-occurance basis, we found that this effect was mitigated. As a result, we do not recommend using the UNISYN dictionary for word frequency purposes.

This work deals with the text-dependent speaker recognition in systems, where just a few training samples exist. For the purpose of this recognition, the voice imprint based on different features (e.g. MFCC, PLP, ACW etc.) is proposed. At the beginning, there is described the way, how the speech signal is produced. Some speech characteristics important for speaker recognition are also mentioned. The next part of work deals with the speech signal analysis. There is mentioned the preprocessing and also the feature extraction methods. The following part describes the process of speaker recognition and mentions the evaluation of the used methods: speaker identification and verification. Last theoretically based part of work deals with the classifiers which are suitable for the text-dependent recognition. The classifiers based on fractional distances, dynamic time warping, dispersion matching and vector quantization are mentioned. This work continues by design and realization of system, which evaluates all described classifiers for voice imprint based on different features.