Loss Modelling of Three-Level Inverters controlled with Space Vector Modulation Technique

The objective of this master’s thesis is to investigate the loss behavior of three-level ANPC inverter and compare it with conventional NPC inverter. The both inverters are controlled with mature space vector modulation strategy. In order to provide the comparison both accurate and detailed enough NPC and ANPC simulation models should be obtained. The similar control model of SVM is utilized for both NPC and ANPC inverter models. The principles of control algorithms, the structure and description of models are clarified. The power loss calculation model is based on practical calculation approaches with certain assumptions. The comparison between NPC and ANPC topologies is presented based on results obtained for each semiconductor device, their switching and conduction losses and efficiency of the inverters. Alternative switching states of ANPC topology allow distributing losses among the switches more evenly, than in NPC inverter. Obviously, the losses of a switching device depend on its position in the topology. Losses distribution among the components in ANPC topology allows reducing the stress on certain switches, thus losses are equally distributed among the semiconductors, however the efficiency of the inverters is the same. As a new contribution to earlier studies, the obtained models of SVM control, NPC and ANPC inverters have been built. Thus, this thesis can be used in further more complicated modelling of full-power converters for modern multi-megawatt wind energy conversion systems.

Impacts and Detection of Design Smells

Les changements sont faits de façon continue dans le code source des logiciels pour prendre en compte les besoins des clients et corriger les fautes. Les changements continus peuvent conduire aux défauts de code et de conception. Les défauts de conception sont des mauvaises solutions à des problèmes récurrents de conception ou d’implémentation, généralement dans le développement orienté objet. Au cours des activités de compréhension et de changement et en raison du temps d’accès au marché, du manque de compréhension, et de leur expérience, les développeurs ne peuvent pas toujours suivre les normes de conception et les techniques de codage comme les patrons de conception. Par conséquent, ils introduisent des défauts de conception dans leurs systèmes. Dans la littérature, plusieurs auteurs ont fait valoir que les défauts de conception rendent les systèmes orientés objet plus difficile à comprendre, plus sujets aux fautes, et plus difficiles à changer que les systèmes sans les défauts de conception. Pourtant, seulement quelques-uns de ces auteurs ont fait une étude empirique sur l’impact des défauts de conception sur la compréhension et aucun d’entre eux n’a étudié l’impact des défauts de conception sur l’effort des développeurs pour corriger les fautes. Dans cette thèse, nous proposons trois principales contributions. La première contribution est une étude empirique pour apporter des preuves de l’impact des défauts de conception sur la compréhension et le changement. Nous concevons et effectuons deux expériences avec 59 sujets, afin d’évaluer l’impact de la composition de deux occurrences de Blob ou deux occurrences de spaghetti code sur la performance des développeurs effectuant des tâches de compréhension et de changement. Nous mesurons la performance des développeurs en utilisant: (1) l’indice de charge de travail de la NASA pour leurs efforts, (2) le temps qu’ils ont passé dans l’accomplissement de leurs tâches, et (3) les pourcentages de bonnes réponses. Les résultats des deux expériences ont montré que deux occurrences de Blob ou de spaghetti code sont un obstacle significatif pour la performance des développeurs lors de tâches de compréhension et de changement. Les résultats obtenus justifient les recherches antérieures sur la spécification et la détection des défauts de conception. Les équipes de développement de logiciels doivent mettre en garde les développeurs contre le nombre élevé d’occurrences de défauts de conception et recommander des refactorisations à chaque étape du processus de développement pour supprimer ces défauts de conception quand c’est possible. Dans la deuxième contribution, nous étudions la relation entre les défauts de conception et les fautes. Nous étudions l’impact de la présence des défauts de conception sur l’effort nécessaire pour corriger les fautes. Nous mesurons l’effort pour corriger les fautes à l’aide de trois indicateurs: (1) la durée de la période de correction, (2) le nombre de champs et méthodes touchés par la correction des fautes et (3) l’entropie des corrections de fautes dans le code-source. Nous menons une étude empirique avec 12 défauts de conception détectés dans 54 versions de quatre systèmes: ArgoUML, Eclipse, Mylyn, et Rhino. Nos résultats ont montré que la durée de la période de correction est plus longue pour les fautes impliquant des classes avec des défauts de conception. En outre, la correction des fautes dans les classes avec des défauts de conception fait changer plus de fichiers, plus les champs et des méthodes. Nous avons également observé que, après la correction d’une faute, le nombre d’occurrences de défauts de conception dans les classes impliquées dans la correction de la faute diminue. Comprendre l’impact des défauts de conception sur l’effort des développeurs pour corriger les fautes est important afin d’aider les équipes de développement pour mieux évaluer et prévoir l’impact de leurs décisions de conception et donc canaliser leurs efforts pour améliorer la qualité de leurs systèmes. Les équipes de développement doivent contrôler et supprimer les défauts de conception de leurs systèmes car ils sont susceptibles d’augmenter les efforts de changement. La troisième contribution concerne la détection des défauts de conception. Pendant les activités de maintenance, il est important de disposer d’un outil capable de détecter les défauts de conception de façon incrémentale et itérative. Ce processus de détection incrémentale et itérative pourrait réduire les coûts, les efforts et les ressources en permettant aux praticiens d’identifier et de prendre en compte les occurrences de défauts de conception comme ils les trouvent lors de la compréhension et des changements. Les chercheurs ont proposé des approches pour détecter les occurrences de défauts de conception, mais ces approches ont actuellement quatre limites: (1) elles nécessitent une connaissance approfondie des défauts de conception, (2) elles ont une précision et un rappel limités, (3) elles ne sont pas itératives et incrémentales et (4) elles ne peuvent pas être appliquées sur des sous-ensembles de systèmes. Pour surmonter ces limitations, nous introduisons SMURF, une nouvelle approche pour détecter les défauts de conception, basé sur une technique d’apprentissage automatique — machines à vecteur de support — et prenant en compte les retours des praticiens. Grâce à une étude empirique portant sur trois systèmes et quatre défauts de conception, nous avons montré que la précision et le rappel de SMURF sont supérieurs à ceux de DETEX et BDTEX lors de la détection des occurrences de défauts de conception. Nous avons également montré que SMURF peut être appliqué à la fois dans les configurations intra-système et inter-système. Enfin, nous avons montré que la précision et le rappel de SMURF sont améliorés quand on prend en compte les retours des praticiens.

Syntactic Based Machine Translation from English to Malayalam

Due to the emergence of multiple language support on the Internet, machine translation (MT) technologies are indispensable to the communication between speakers using different languages. Recent research works have started to explore tree-based machine translation systems with syntactical and morphological information. This work aims the development of Syntactic Based Machine Translation from English to Malayalam by adding different case information during translation. The system identifies general rules for various sentence patterns in English. These rules are generated using the Parts Of Speech (POS) tag information of the texts. Word Reordering based on the Syntax Tree is used to improve the translation quality of the system. The system used Bilingual English –Malayalam dictionary for translation.

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

Vector Fields

Exercises and solutions about vector fields. Diagrams for the questions are all together in the support.zip file, as .eps files

Modelling capability and affordance as properties of human/machine resource systems

Understanding how and why the capability of one set of business resources, its structural arrangements and mechanisms compared to another works can provide competitive advantage in terms of new business processes and product and service development. However, most business models of capability are descriptive and lack formal modelling language to qualitatively and quantifiably compare capabilities, Gibson’s theory of affordance, the potential for action, provides a formal basis for a more robust and quantitative model, but most formal affordance models are complex and abstract and lack support for real-world applications. We aim to understand the ‘how’ and ‘why’ of business capability, by developing a quantitative and qualitative model that underpins earlier work on Capability-Affordance Modelling – CAM. This paper integrates an affordance based capability model and the formalism of Coloured Petri Nets to develop a simulation model. Using the model, we show how capability depends on the space time path of interacting resources, the mechanism of transition and specific critical affordance factors relating to the values of the variables for resources, people and physical objects. We show how the model can identify the capabilities of resources to enable the capability to inject a drug and anaesthetise a patient.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

Comparing machine learning classifiers in potential distribution modelling

Species` potential distribution modelling consists of building a representation of the fundamental ecological requirements of a species from biotic and abiotic conditions where the species is known to occur. Such models can be valuable tools to understand the biogeography of species and to support the prediction of its presence/absence considering a particular environment scenario. This paper investigates the use of different supervised machine learning techniques to model the potential distribution of 35 plant species from Latin America. Each technique was able to extract a different representation of the relations between the environmental conditions and the distribution profile of the species. The experimental results highlight the good performance of random trees classifiers, indicating this particular technique as a promising candidate for modelling species` potential distribution. (C) 2010 Elsevier Ltd. All rights reserved.

Bounded solutions of fermions in the background of mixed vector-scalar inversely linear potentials

The problem of a fermion subject to a general mixing of vector and scalar potentials in a two-dimensional world is mapped into a Sturm-Liouville problem. Isolated bounded solutions are also searched. For the specific case of an inversely linear potential, which gives rise to an effective Kratzer potential in the Sturm-Liouville problem, exact bounded solutions are found in closed form. The case of a pure scalar potential with their isolated zero-energy solutions, already analyzed in a previous work, is obtained as a particular case. The behavior of the upper and lower components of the Dirac spinor is discussed in detail and some unusual results are revealed. The nonrelativistic limit of our results adds a new support to the conclusion that even-parity solutions to the nonrelativistic one-dimensional hydrogen atom do not exist. (c) 2004 Elsevier B.V. All rights reserved.

Klein-Gordon particles in mixed vector-scalar inversely linear potentials

The problem of a spinless particle subject to a general mixing of vector and scalar inversely linear potentials in a two-dimensional world is analyzed. Exact bounded solutions are found in closed form by imposing boundary conditions on the eigenfunctions which ensure that the effective Hamiltonian is Hermitian for all the points of the space. The nonrelativistic limit of our results adds a new support to the conclusion that even-parity solutions to the nonrelativistic one-dimensional hydrogen atom do not exist. (c) 2005 Elsevier B.V. All rights reserved.

TRIPLE-VECTOR-BOSON PROCESSES IN GAMMA-GAMMA COLLIDERS

We study the production of three gauge bosons (W(+)W(-)Z(0) and W(+)W(-)gamma) at the next generation of linear e(+)e(-) colliders operating in the yy mode. We analyze the total cross sections as well as several kinematical distributions of the final state particles. We find out that a linear e(+)e(-) machine operating in the rr mode will produce 5-10 times more three-gauge-boson states compared to the standard e(+)e(-) mode at high energies.

Line based camera calibration in machine vision dynamic applications

The problem of dynamic camera calibration considering moving objects in close range environments using straight lines as references is addressed. A mathematical model for the correspondence of a straight line in the object and image spaces is discussed. This model is based on the equivalence between the vector normal to the interpretation plane in the image space and the vector normal to the rotated interpretation plane in the object space. In order to solve the dynamic camera calibration, Kalman Filtering is applied; an iterative process based on the recursive property of the Kalman Filter is defined, using the sequentially estimated camera orientation parameters to feedback the feature extraction process in the image. For the dynamic case, e.g. an image sequence of a moving object, a state prediction and a covariance matrix for the next instant is obtained using the available estimates and the system model. Filtered state estimates can be computed from these predicted estimates using the Kalman Filtering approach and based on the system model parameters with good quality, for each instant of an image sequence. The proposed approach was tested with simulated and real data. Experiments with real data were carried out in a controlled environment, considering a sequence of images of a moving cube in a linear trajectory over a flat surface.

Tri-state Space Vector Modulation for Three-phase integrated inverters

The aim of this work is to present a modified Space Vector Modulation (SVM) suitable for Tri-state Three-phase inverters. A standard SVM algorithm and the Tri-state PWM (Pulse Width Modulation) are presented and their concept are mixed into the novel SVM. The proposed SVM is applied to a three-phase tri-state integrated Boost inverter, intended to Photovoltaic Energy Applications. The main features for this novel SVM are validated through simulations and also by experimental tests. The obtained results prove the feasibility of the proposal. © 2011 IEEE.

Amazonian malaria: Asymptomatic human reservoirs, diagnostic challenges, environmentally driven changes in mosquito vector populations, and the mandate for sustainable control strategies

Across the Americas and the Caribbean, nearly 561,000 slide-confirmed malaria infections were reported officially in 2008. The nine Amazonian countries accounted for 89% of these infections; Brazil and Peru alone contributed 56% and 7% of them, respectively. Local populations of the relatively neglected parasite Plasmodium vivax, which currently accounts for 77% of the regional malaria burden, are extremely diverse genetically and geographically structured. At a time when malaria elimination is placed on the public health agenda of several endemic countries, it remains unclear why malaria proved so difficult to control in areas of relatively low levels of transmission such as the Amazon Basin. We hypothesize that asymptomatic parasite carriage and massive environmental changes that affect vector abundance and behavior are major contributors to malaria transmission in epidemiologically diverse areas across the Amazon Basin. Here we review available data supporting this hypothesis and discuss their implications for current and future malaria intervention policies in the region. Given that locally generated scientific evidence is urgently required to support malaria control interventions in Amazonia, we briefly describe the aims of our current field-oriented malaria research in rural villages and gold-mining enclaves in Peru and a recently opened agricultural settlement in Brazil. (C) 2011 Elsevier B.V. All rights reserved.

Trypanosoma (Megatrypanum) melophagium in the Sheep Ked Melophagus ovinus from Organic Farms in Croatia: Phylogenetic Inferences Support Restriction to Sheep and Sheep Keds and Close Relationship with Trypanosomes from Other Ruminant Species

Trypanosoma (Megatrypanum) melophagium is a parasite of sheep transmitted by sheep keds, the sheep-restricted ectoparasite Melophagus ovinus (Diptera: Hippoboscidae). Sheep keds were 100% prevalent in sheep from five organic farms in Croatia, Southeastern Europe, whereas trypanosomes morphologically compatible with T. melophagium were 86% prevalent in the guts of the sheep keds. Multilocus phylogenetic analyses using sequences of small subunit rRNA, glycosomal glyceraldehyde-3-phosphate dehydrogenase, spliced leader, and internal transcribed spacer 1 of the rDNA distinguished T. melophagium from all allied trypanosomes from other ruminant species and placed the trypanosome in the subgenus Megatrypanum. Trypanosomes from sheep keds from Croatia and Scotland, the only available isolates for comparison, shared identical sequences. All biologic and phylogenetic inferences support the restriction of T. melophagium to sheep and, especially, to the sheep keds. The comparison of trypanosomes from sheep, cattle, and deer from the same country, which was never achieved before this work, strongly supported the host-restricted specificity of trypanosomes of the subgenus Megatrypanum. Our findings indicate that with the expansion of organic farms, both sheep keds and T. melophagium may re-emerge as parasitic infections of sheep.