Feature Selection for Text and Image Data Using Differential Evolution with SVM and Naïve Bayes Classifiers

Classification problems are increasing in various important applications such as text categorization, images, medical imaging diagnosis and bimolecular analysis etc. due to large amount of attribute set. Feature extraction methods in case of large dataset play an important role to reduce the irrelevant feature and thereby increases the performance of classifier algorithm. There exist various methods based on machine learning for text and image classification. These approaches are utilized for dimensionality reduction which aims to filter less informative and outlier data. Therefore, these approaches provide compact representation and computationally better tractable accuracy. At the same time, these methods can be challenging if the search space is doubled multiple time. To optimize such challenges, a hybrid approach is suggested in this paper. The proposed approach uses differential evolution (DE) for feature selection with naïve bayes (NB) and support vector machine (SVM) classifiers to enhance the performance of selected classifier. The results are verified using text and image data which reflects improved accuracy compared with other conventional techniques. A 25 benchmark datasets (UCI) from different domains are considered to test the proposed algorithms.  A comparative study between proposed hybrid classification algorithms are presented in this work. Finally, the experimental result shows that the differential evolution with NB classifier outperforms and produces better estimation of probability terms. The proposed technique in terms of computational time is also feasible

Advances in Optimization and Nonlinear Analysis

The present book focuses on that part of calculus of variations, optimization, nonlinear analysis and related applications which combines tools and methods from partial differential equations with geometrical techniques. More precisely, this work is devoted to nonlinear problems coming from different areas, with particular reference to those introducing new techniques capable of solving a wide range of problems. The book is a valuable guide for researchers, engineers and students in the field of mathematics, operations research, optimal control science, artificial intelligence, management science and economics

Computational Architecture: development, design and optimization. Case study of a glass and steel roof for the Scuola Normale Superiore's courtyard in Pisa

This thesis is built around the conception, development and optimization of complex architecture, also known as free form. The project consists in a steel and glass roof over the inner courtyard of the Scuola Normale Superiore, with the aim to make the living space accessible at every moment of day life. The shape was conceived such that it would suit well the architecture of the Scuola Normale and the spirit it emobdies, with a special regard to energetics and fabrication, true weakness of architectures of this kind. The structure was modelled entirely on Grasshopper, a Rhino3D plug-in which allows to parametrically design objects. This programming environment allowed to interface add-ons, both proprietary and made on purpose by the author. With those tools, the author was able to develop algorithms for structural and geometric optimization. The former consisted in the process at the end of which the best structural performance is found, at constant weight: in the case studym genetic algorithms and iterative processes were used. Geometric optimization consisted in seeking the fabricability of the architecture, in the reduction of overall panel curvatures and eventually in the panelization of the surface. Finally, thanks to the code so created, it was possible to easily export all data and run required analysis exploiting the software more suited for each needing

Antenas fotônicas compactas compatíveis com a tecnologia CMOS

Orientador: Lucas Heitzmann GabrielliTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: A área das antenas fotônicas desenvolveu-se muito nos últimos anos, com aplicações diretas em detecção de luz e avaliação de distância (LIDAR), microscopia, fotovoltaica, holografia, e as comunicações inter-chip e intra-chip ¿ entre outras. Da ampla variedade de antenas relatadas na literatura, as antenas fotônicas compatíveis com a tecnologia de semicondutores de óxido metálico complementar (CMOS) são candidatas promissoras para resolver o gargalo das comunicações em nível de chip, e também prometem levar a tecnologia LIDAR para aplicações comerciais viáveis de última geração como os carros autônomos. Dentre as antenas propostas na literatura a antena do tipo grade é a mais utilizada devido a sua facilidade de projeção e fabricação, e a seu desempenho. Embora a antena de tipo grade seja adequada para várias aplicações, esta ainda tem várias desvantagens. Entre estas, sua forte dependência da polarização e do comprimento de onda, sua direção de radiação máxima inclinada, e seu desempenho ineficiente quando projetada com uma área efetiva próxima a um comprimento de onda operacional. Nesta tese, apresentamos o projeto de antenas com desenhos não-intuitivos utilizando algoritmos de otimização do estado da arte, para aplicações em acoplamento da fibra para o chip, e também para seu uso em arranjos. Por um lado, produzimos conhecimento local na área de fabricação e caracterização de antenas de silício sobre isolante (SOI), desenvolvendo receitas de fabricação com alta repetibilidade em cada etapa do processo. Por outro lado, mostramos que as antenas otimizadas podem superar algumas limitações das antenas tipo grade. As simulações mostram que nosso projeto de antena para acoplamento atinge uma eficiência de acoplamento vertical de?6.3 dB e uma largura de banda operacional de 3 dB de 60 nm. Sendo esta a menor antena para acoplamento com esse nível de desempenho na literatura, ela ocupa apenas 15 % do espaço de uma antena convencional tipo grade para acoplamento, o que possibilita seu uso para acoplamento em fibras com múltiplos núcleos. Também mostramos experimentalmente pela primeira vez uma antena com radiação totalmente vertical para utilização em arranjos com um tamanho compacto, perto do comprimento de onda, com uma área de 1.78 µm × 1.78 µm, e uma largura de banda operacional maior do que 100 nm. Finalmente, mostramos um arranjo de antenas passivo integrado de 8 elementos distribuídos seguindo o desenho aperiódico da espiral de Fermat apresentando um nível de lóbulo lateral (SLL) cerca de 1 dB menor que o equivalente periódico do mesmo tamanho num comprimento de onda de 1550 nm. Além disso, também se usou um modulador espacial de luz (SLM) a um comprimento de onda visível para emular arranjos de antenas maiores, mostrando que a distribuição dos elementos seguindo a espiral Fermat é capaz de reduzir o SLL para arranjos de até 64 elementos espaçados até 581'lambda'Abstract: The field of photonic antennas has become an area of intensive study in recent years, with direct applications in light detection and ranging (LIDAR), microscopy, sensors, photovoltaics, holography, and inter- and intra-chip communications ¿ among several others. Of the great variety of antennas reported in the literature, the photonic antennas compatible with the well-established complementary metal¿oxide¿semiconductor (CMOS) technology are promising candidates to solve the chip-level communication bottleneck, and also promise to make the LIDAR technology a viable commercial application for autonomous vehicles. Among the antennas proposed in the literature we find that the grating-type antenna is the most widely used due to its straightforward design and manufacture, and its performance. However, even if grating antennas are suitable for several applications, they still present several drawbacks. In particular, their radiation properties are strongly dependent on polarization and wavelength, their direction of maximum radiation does not occur at broadside direction, and they are power inefficient when designed with an effective area close to the operating wavelength. In this thesis, we present the design of antennas with counterintuitive designs obtained by means of state-of-the-art optimization algorithms for applications in fiber coupling to the chip, and also for use as radiation element in large-scale arrays. We produced, on the one hand, local knowledge in the manufacturing and characterization of silicon-on-insulator (SOI) antennas, developing manufacturing recipes with high repeatabil-ity at each step of the process. On the other hand, we show that optimized antennas can overcome some limitations of grating-type antennas. Simulations show that our antenna designed for coupling achieves an efficiency in the vertical direction of ?6.3 dB and an operating 3 dB bandwidth of 60 nm. This represents the smallest antenna designed for coupling at this performance level in the literature, it occupies only 15 % of the footprint of a conventional grating antenna, which in turn enables its use in multicore fibers. We also demonstrated experimentally for the first time an antenna with vertical radiation anda compact footprint for use in arrays. Its dimensions are close to the operation wavelength, and it has an area 1.78 µm × 1.78 µm and an operational bandwidth exceeding 100 nm. Finally, we show that a passive integrated 8-element array antenna distributed following the aperiodic design of the Fermat spiral shows a side lobe level (SLL) approximately 1 dB lower than a periodic array of the same size, both operating at a wavelength of 1550 nm. In addition, we also use a spatial ligth modulator (SLM) at visible wavelength to emulate larger arrays, showing that the Fermat spiral successfully reduces the SLL in for arrays with up to 64-elements spaced by 581'lambda'DoutoradoTelecomunicações e TelemáticaDoutor em Engenharia ElétricaCAPE

Evolutionary Robot Swarms Under Real-World Constraints

Tese de doutoramento em Engenharia Electrotécnica e de Computadores, na especialidade de Automação e Robótica, apresentada ao Departamento de Engenharia Electrotécnica e de Computadores da Faculdade de Ciências e Tecnologia da Universidade de CoimbraNas últimas décadas, vários cientistas e engenheiros têm vindo a estudar as estratégias provenientes da natureza. Dentro das arquiteturas biológicas, as sociedades que vivem em enxames revelam que agentes simplistas, tais como formigas ou pássaros, são capazes de realizar tarefas complexas usufruindo de mecanismos de cooperação. Estes sistemas abrangem todas as condições necessárias para a sobrevivência, incorporando comportamentos de cooperação, competição e adaptação. Na “batalha” sem fim em prol do progresso dos mecanismos artificiais desenvolvidos pelo homem, a ciência conseguiu simular o primeiro comportamento em enxame no final dos anos oitenta. Desde então, muitas outras áreas, entre as quais a robótica, beneficiaram de mecanismos de tolerância a falhas inerentes da inteligência coletiva de enxames. A área de investigação deste estudo incide na robótica de enxame, consistindo num domínio particular dos sistemas robóticos cooperativos que incorpora os mecanismos de inteligência coletiva de enxames na robótica. Mais especificamente, propõe-se uma solução completa de robótica de enxames a ser aplicada em contexto real. Nesta ótica, as operações de busca e salvamento foram consideradas como o caso de estudo principal devido ao nível de complexidade associado às mesmas. Tais operações ocorrem tipicamente em cenários dinâmicos de elevadas dimensões, com condições adversas que colocam em causa a aplicabilidade dos sistemas robóticos cooperativos. Este estudo centra-se nestes problemas, procurando novos desafios que não podem ser ultrapassados através da simples adaptação da literatura da especialidade em algoritmos de enxame, planeamento, controlo e técnicas de tomada de decisão. As contribuições deste trabalho sustentam-se em torno da extensão do método Particle Swarm Optimization (PSO) aplicado a sistemas robóticos cooperativos, denominado de Robotic Darwinian Particle Swarm Optimization (RDPSO). O RDPSO consiste numa arquitetura robótica de enxame distribuída que beneficia do particionamento dinâmico da população de robôs utilizando mecanismos evolucionários de exclusão social baseados na sobrevivência do mais forte de Darwin. No entanto, apesar de estar assente no caso de estudo do RDPSO, a aplicabilidade dos conceitos aqui propostos não se encontra restrita ao mesmo, visto que todos os algoritmos parametrizáveis de enxame de robôs podem beneficiar de uma abordagem idêntica. Os fundamentos em torno do RDPSO são introduzidos, focando-se na dinâmica dos robôs, nos constrangimentos introduzidos pelos obstáculos e pela comunicação, e nas suas propriedades evolucionárias. Considerando a colocação inicial dos robôs no ambiente como algo fundamental para aplicar sistemas de enxames em aplicações reais, é assim introduzida uma estratégia de colocação de robôs realista. Para tal, a população de robôs é dividida de forma hierárquica, em que são utilizadas plataformas mais robustas para colocar as plataformas de enxame no cenário de forma autónoma. Após a colocação dos robôs no cenário, é apresentada uma estratégia para permitir a criação e manutenção de uma rede de comunicação móvel ad hoc com tolerância a falhas. Esta estratégia não considera somente a distância entre robôs, mas também a qualidade do nível de sinal rádio frequência, redefinindo assim a sua aplicabilidade em cenários reais. Os aspetos anteriormente mencionados estão sujeitos a uma análise detalhada do sistema de comunicação inerente ao algoritmo, para atingir uma implementação mais escalável do RDPSO a cenários de elevada complexidade. Esta elevada complexidade inerente à dinâmica dos cenários motivaram a ultimar o desenvolvimento do RDPSO, integrando para o efeito um mecanismo adaptativo baseado em informação contextual (e.g., nível de atividade do grupo). Face a estas considerações, o presente estudo pode contribuir para expandir o estado-da-arte em robótica de enxame com algoritmos inovadores aplicados em contexto real. Neste sentido, todos os métodos propostos foram extensivamente validados e comparados com alternativas, tanto em simulação como com robôs reais. Para além disso, e dadas as limitações destes (e.g., número limitado de robôs, cenários de dimensões limitadas, constrangimentos reais limitados), este trabalho contribui ainda para um maior aprofundamento do estado-da-arte, onde se propõe um modelo macroscópico capaz de capturar a dinâmica inerente ao RDPSO e, até certo ponto, estimar analiticamente o desempenho coletivo dos robôs perante determinada tarefa. Em suma, esta investigação pode ter aplicabilidade prática ao colmatar a lacuna que se faz sentir no âmbito das estratégias de enxames de robôs em contexto real e, em particular, em cenários de busca e salvamento.Over the past decades, many scientists and engineers have been studying nature’s best and time-tested patterns and strategies. Within the existing biological architectures, swarm societies revealed that relatively unsophisticated agents with limited capabilities, such as ants or birds, were able to cooperatively accomplish complex tasks necessary for their survival. Those simplistic systems embrace all the conditions necessary to survive, thus embodying cooperative, competitive and adaptive behaviours. In the never-ending battle to advance artificial manmade mechanisms, computer scientists simulated the first swarm behaviour designed to mimic the flocking behaviour of birds in the late eighties. Ever since, many other fields, such as robotics, have benefited from the fault-tolerant mechanism inherent to swarm intelligence. The area of research presented in this Ph.D. Thesis focuses on swarm robotics, which is a particular domain of multi-robot systems (MRS) that embodies the mechanisms of swarm intelligence into robotics. More specifically, this Thesis proposes a complete swarm robotic solution that can be applied to real-world missions. Although the proposed methods do not depend on any particular application, search and rescue (SaR) operations were considered as the main case study due to their inherent level of complexity. Such operations often occur in highly dynamic and large scenarios, with harsh and faulty conditions, that pose several problems to MRS applicability. This Thesis focuses on these problems raising new challenges that cannot be handled appropriately by simple adaptation of state-of-the-art swarm algorithms, planning, control and decision-making techniques. The contributions of this Thesis revolve around an extension of the Particle Swarm Optimization (PSO) to MRS, denoted as Robotic Darwinian Particle Swarm Optimization (RDPSO). The RDPSO is a distributed swarm robotic architecture that benefits from the dynamical partitioning of the whole swarm of robots by means of an evolutionary social exclusion mechanism based on Darwin’s survival-of-the-fittest. Nevertheless, although currently applied solely to the RDPSO case study, the applicability of all concepts herein proposed is not restricted to it, since all parameterized swarm robotic algorithms may benefit from a similar approach The RDPSO is then proposed and used to devise the applicability of novel approaches. The fundamentals around the RDPSO are introduced by focusing on robots’ dynamics, obstacle avoidance, communication constraints and its evolutionary properties. Afterwards, taking the initial deployment of robots within the environment as a basis for applying swarm robotics systems into real-world applications, the development of a realistic deployment strategy is proposed. For that end, the population of robots is hierarchically divided, wherein larger support platforms autonomously deploy smaller exploring platforms in the scenario, while considering communication constraints and obstacles. After the deployment, a way of ensuring a fault-tolerant multi-hop mobile ad hoc communication network (MANET) is introduced to explicitly exchange information needed in a collaborative realworld task execution. Such strategy not only considers the maximum communication range between robots, but also the minimum signal quality, thus refining the applicability to real-world context. This is naturally followed by a deep analysis of the RDPSO communication system, describing the dynamics of the communication data packet structure shared between teammates. Such procedure is a first step to achieving a more scalable implementation by optimizing the communication procedure between robots. The highly dynamic characteristics of real-world applications motivated us to ultimate the RDPSO development with an adaptive strategy based on a set of context-based evaluation metrics. This thesis contributes to the state-of-the-art in swarm robotics with novel algorithms for realworld applications. All of the proposed approaches have been extensively validated in benchmarking tasks, in simulation, and with real robots. On top of that, and due to the limitations inherent to those (e.g., number of robots, scenario dimensions, real-world constraints), this Thesis further contributes to the state-of-the-art by proposing a macroscopic model able to capture the RDPSO dynamics and, to some extent, analytically estimate the collective performance of robots under a certain task. It is the author’s expectation that this Ph.D. Thesis may shed some light into bridging the reality gap inherent to the applicability of swarm strategies to real-world scenarios, and in particular to SaR operations.FCT - SFRH/BD /73382/201

Predicting multibody assembly of proteins

textThis thesis addresses the multi-body assembly (MBA) problem in the context of protein assemblies. [...] In this thesis, we chose the protein assembly domain because accurate and reliable computational modeling, simulation and prediction of such assemblies would clearly accelerate discoveries in understanding of the complexities of metabolic pathways, identifying the molecular basis for normal health and diseases, and in the designing of new drugs and other therapeutics. [...] [We developed] F²Dock (Fast Fourier Docking) which includes a multi-term function which includes both a statistical thermodynamic approximation of molecular free energy as well as several of knowledge-based terms. Parameters of the scoring model were learned based on a large set of positive/negative examples, and when tested on 176 protein complexes of various types, showed excellent accuracy in ranking correct configurations higher (F² Dock ranks the correcti solution as the top ranked one in 22/176 cases, which is better than other unsupervised prediction software on the same benchmark). Most of the protein-protein interaction scoring terms can be expressed as integrals over the occupied volume, boundary, or a set of discrete points (atom locations), of distance dependent decaying kernels. We developed a dynamic adaptive grid (DAG) data structure which computes smooth surface and volumetric representations of a protein complex in O(m log m) time, where m is the number of atoms assuming that the smallest feature size h is [theta](r[subscript max]) where r[subscript max] is the radius of the largest atom; updates in O(log m) time; and uses O(m)memory. We also developed the dynamic packing grids (DPG) data structure which supports quasi-constant time updates (O(log w)) and spherical neighborhood queries (O(log log w)), where w is the word-size in the RAM. DPG and DAG together results in O(k) time approximation of scoring terms where k << m is the size of the contact region between proteins. [...] [W]e consider the symmetric spherical shell assembly case, where multiple copies of identical proteins tile the surface of a sphere. Though this is a restricted subclass of MBA, it is an important one since it would accelerate development of drugs and antibodies to prevent viruses from forming capsids, which have such spherical symmetry in nature. We proved that it is possible to characterize the space of possible symmetric spherical layouts using a small number of representative local arrangements (called tiles), and their global configurations (tiling). We further show that the tilings, and the mapping of proteins to tilings on arbitrary sized shells is parameterized by 3 discrete parameters and 6 continuous degrees of freedom; and the 3 discrete DOF can be restricted to a constant number of cases if the size of the shell is known (in terms of the number of protein n). We also consider the case where a coarse model of the whole complex of proteins are available. We show that even when such coarse models do not show atomic positions, they can be sufficient to identify a general location for each protein and its neighbors, and thereby restricts the configurational space. We developed an iterative refinement search protocol that leverages such multi-resolution structural data to predict accurate high resolution model of protein complexes, and successfully applied the protocol to model gp120, a protein on the spike of HIV and currently the most feasible target for anti-HIV drug design.Computer Science

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios