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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

PREDICTING GENERAL VAGAL NERVE ACTIVITY VIA THE DEVELOPMENT OF BIOPHYSICAL ARTIFICIAL INTELLIGENCE

LeRayah Michelle Neely-Brown (17593539) 11 December 2023 (has links)
<p dir="ltr">The vagus nerve (VN) is the tenth cranial nerve that mediates most of the parasympathetic functions of the autonomic nervous system. The axons of the human VN comprise a mix of unmyelinated and myelinated axons, where ~80% of the axons are unmyelinated C fibers (Havton et al., 2021). Understanding that most VN axons are unmyelinated, there is a need to map the pathways of these axons to and from organs to understand their function(s) and whether C fiber morphology or signaling characteristics yield insights into their functions. Developing a machine learning model that detects and predicts the morphology of VN single fiber action potentials based on select fiber characteristics, e.g., diameter, myelination, and position within the VN, allows us to more readily categorize the nerve fibers with respect to their function(s). Additionally, the features of this machine learning model could help inform peripheral neuromodulation devices that aim to restore, replace, or augment one or more specific functions of the VN that have been lost due to injury, disease, or developmental abnormalities.</p><p dir="ltr">We designed and trained four types of Multi-layer Perceptron Artificial Deep Neural Networks (MLP-ANN) with 10,000 rat abdominal vagal C-fibers simulated via the peripheral neural interface model ViNERS. We analyze the accuracy of each MLP-ANN’s SFAP predictions by conducting normalized cross-correlation and morphology analyses with the ViNERS C-fiber SFAP counterparts. Our results showed that our best MLP predicted over 94% of the C-fiber SFAPs with strong normalized cross-correlation coefficients of 0.7 through 1 with the ViNERS SFAPs. Overall, this novel tool can use a C-fiber’s biophysical characteristics (i.e., fiber diameter size, fiber position on the x/y axis, etc.) to predict C-fiber SFAP morphology.</p>
12

Aplicação do algoritmo bioinspirado Novel Bat Algorithm na parametrização dos controladores suplementares de amortecimento e dispositivo FACTS GUPFC /

Miotto, Ednei Luiz January 2018 (has links)
Orientador: Percival Bueno de Araujo / Resumo: Este trabalho apresenta o Novel Bat Algorithm com uma nova técnica para realizar o ajuste coordenado dos parâmetros de controladores suplementares de amortecimento (Estabilizadores de Sistemas de Potência e do conjunto Generalized Unified Power Flow Controller – Power Oscillation Damping) em sistemas elétricos de potência multimáquinas. O objetivo principal é inserir amortecimento adicional aos modos oscilatórios de baixa frequência e, consequentemente, garantir a estabilidade do sistema elétrico frente a pequenas perturbações. Para representar o sistema elétrico de potência será utilizado o Modelo de Sensibilidade de Potência. Desse modo, todos os seus dispositivos e componentes foram modelados por injeções de potência. Análises estáticas e dinâmicas foram realizadas em dois sistemas teste, sendo: o Sistema Simétrico de Duas Áreas e o Sistema New England. A eficiência do dispositivo FACTS Generalized Unified Power Flow Controller atuando em conjunto com uma estrutura de controle baseada em controladores Proporcional – Integral foi criteriosamente avaliada para o controle de fluxos de potências ativa e reativa, para a melhoria do perfil de tensão do sistema elétrico e na redução das perdas no sistema de transmissão. O desempenho do Novel Bat Algorithm, no que concerne ao ajuste dos parâmetros dos controladores, foi comparado a outros quatro algoritmos bio-inspirados bastante difundidos na literatura: Particle Swarm Optimization, Bacterial Foragim Optimization, Bat Algorithm e... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: This work presents the Novel Bat Algorithm as a new technique for the to perform the coordinated tuning of the parameters of the supplementary damping controllers (Power Systems Stabilizers and Generalized Unified Power Flow Controller - Power Oscillation Damping) in multi-machine electric power systems. The main objective is to insert damping to low-frequency oscillations and thus ensure the stability of the electrical system against minor disturbances. The Power Sensitivity Model is used to represent the system. Thus, all devices and their components are modeled by power injection. Static and dynamic analyzes were performed in the two systems: the two-areas symmetric, and the New England. The performance of the proposed methodology (Novel Bat Algorithm), for tuning of the parameters of the controllers was compared to four other algorithms, presented in the literature: The Particle Swarm Optimization method, Bacterial Foraging Optimization method, Bat Algorithm method and a Genetic Algorithm with elitism. The results demonstrated that the Novel Bat Algorithm was more effective than the other techniques presented, generating robust solutions when variations on the scenarios of loads were considered, and therefore accredited it as a tool in the analysis of the study of small-signal stability. / Doutor
13

Aplicação do algoritmo bioinspirado Novel Bat Algorithm na parametrização dos controladores suplementares de amortecimento e dispositivo FACTS GUPFC / Application of the bio-inspired technique Novel Bat Algorithm in the parameterization of the additional damping controllers and FACTS GUPFC device

Miotto, Ednei Luiz 18 October 2018 (has links)
Submitted by Ednei Luiz Miotto (edneimiotto@utfpr.edu.br) on 2018-11-05T12:58:43Z No. of bitstreams: 1 TESE EDNEI LUIZ MIOTTO.pdf: 5057627 bytes, checksum: 74b7d6f2bd477e7e02941873ca291fa3 (MD5) / Approved for entry into archive by Cristina Alexandra de Godoy null (cristina@adm.feis.unesp.br) on 2018-11-08T19:07:02Z (GMT) No. of bitstreams: 1 miotto_el_dr_ilha.pdf: 5057627 bytes, checksum: 74b7d6f2bd477e7e02941873ca291fa3 (MD5) / Made available in DSpace on 2018-11-08T19:07:02Z (GMT). No. of bitstreams: 1 miotto_el_dr_ilha.pdf: 5057627 bytes, checksum: 74b7d6f2bd477e7e02941873ca291fa3 (MD5) Previous issue date: 2018-10-18 / Este trabalho apresenta o Novel Bat Algorithm com uma nova técnica para realizar o ajuste coordenado dos parâmetros de controladores suplementares de amortecimento (Estabilizadores de Sistemas de Potência e do conjunto Generalized Unified Power Flow Controller – Power Oscillation Damping) em sistemas elétricos de potência multimáquinas. O objetivo principal é inserir amortecimento adicional aos modos oscilatórios de baixa frequência e, consequentemente, garantir a estabilidade do sistema elétrico frente a pequenas perturbações. Para representar o sistema elétrico de potência será utilizado o Modelo de Sensibilidade de Potência. Desse modo, todos os seus dispositivos e componentes foram modelados por injeções de potência. Análises estáticas e dinâmicas foram realizadas em dois sistemas teste, sendo: o Sistema Simétrico de Duas Áreas e o Sistema New England. A eficiência do dispositivo FACTS Generalized Unified Power Flow Controller atuando em conjunto com uma estrutura de controle baseada em controladores Proporcional – Integral foi criteriosamente avaliada para o controle de fluxos de potências ativa e reativa, para a melhoria do perfil de tensão do sistema elétrico e na redução das perdas no sistema de transmissão. O desempenho do Novel Bat Algorithm, no que concerne ao ajuste dos parâmetros dos controladores, foi comparado a outros quatro algoritmos bio-inspirados bastante difundidos na literatura: Particle Swarm Optimization, Bacterial Foragim Optimization, Bat Algorithm e o Algoritmo Genético com Elitismo. Os resultados demonstraram que o Novel Bat Algorithm foi mais eficiente que as demais técnicas avaliadas, obtendo soluções com amortecimento satisfatório, mesmo quando variações nos cenários de carregamento do sistema são consideradas, sendo, portanto, credenciado como ferramenta promissora para a análise da estabilidade a pequenas perturbações em sistemas elétricos de potência multimáquinas. / This work presents the Novel Bat Algorithm as a new technique for the to perform the coordinated tuning of the parameters of the supplementary damping controllers (Power Systems Stabilizers and Generalized Unified Power Flow Controller - Power Oscillation Damping) in multi-machine electric power systems. The main objective is to insert damping to low-frequency oscillations and thus ensure the stability of the electrical system against minor disturbances. The Power Sensitivity Model is used to represent the system. Thus, all devices and their components are modeled by power injection. Static and dynamic analyzes were performed in the two systems: the two-areas symmetric, and the New England. The performance of the proposed methodology (Novel Bat Algorithm), for tuning of the parameters of the controllers was compared to four other algorithms, presented in the literature: The Particle Swarm Optimization method, Bacterial Foraging Optimization method, Bat Algorithm method and a Genetic Algorithm with elitism. The results demonstrated that the Novel Bat Algorithm was more effective than the other techniques presented, generating robust solutions when variations on the scenarios of loads were considered, and therefore accredited it as a tool in the analysis of the study of small-signal stability.
14

From mobile to cloud : Using bio-inspired algorithms for collaborative application offloading / Du mobile au cloud : Utilisation d'algorithmes bio-inspirés pour le déploiement d'applications collaboratives

Golchay, Roya 26 January 2016 (has links)
Actuellement les smartphones possèdent un grand éventail de fonctionnalités. Ces objets tout en un, sont constamment connectés. Il est l'appareil favori plébiscité par les utilisateurs parmi tous les dispositifs de communication existants. Les applications actuelles développées pour les smartphones doivent donc faire face à une forte augmentation de la demande en termes de fonctionnalités tandis que - dans un même temps - les smartphones doivent répondre à des critères de compacité et de conception qui les limitent en énergie et à un environnement d'exécution pauvre en ressources. Utiliser un système riche en ressource est une solution classique introduite en informatique dans les nuages mobiles (Mobile Cloud Computing), celle-ci permet de contourner les limites des appareils mobiles en exécutant à distance, toutes ou certaines parties des applications dans ces environnements de nuage. Certaines architectures émergent, mais peu d'algorithmes existent pour traiter les propriétés dynamiques de ces environnements. Dans cette thèse, nous focalisons notre intérêt sur la conception d'ACOMMA (Ant-inspired Collaborative Offloading Middleware for Mobile Applications), un interlogiciel d'exécution déportée collaborative inspirée par le comportement des fourmis, pour les applications mobiles. C'est une architecture orientée service permettant de décharger dynamiquement des partitions d'applications, de manière simultanée, sur plusieurs clouds éloignés ou sur un cloud local créé spontanément, incluant les appareils du voisinage. Les principales contributions de cette thèse sont doubles. Si beaucoup d'intergiciels traitent un ou plusieurs défis relatifs à l'éxecution déportée, peu proposent une architecture ouverte basée sur des services qui serait facile à utiliser sur n'importe quel support mobile sans aucun exigence particulière. Parmi les principaux défis il y a les questions de quoi et quand décharger dans cet environnement très dynamique. A cette fin, nous développons des algorithmes de prises de décisions bio-inspirées : un processus de prise de décision bi-objectif dynamique avec apprentissage et un processus de prise de décision en collaboration avec les autres dispositifs mobiles du voisinage. Nous définissons un mécanisme de dépôt d'exécution avec une méthode de partitionnement grain fin de son graphe d'appel. Nous utilisons les algorithmes des colonies de fourmis pour optimiser bi-objectivement la consommation du CPU et le temps total d'exécution, en incluant la latence du réseau. Nous montrons que les algorithmes des fourmis sont plus facilement re-adaptables face aux modifications du contexte, peuvent être très efficaces en ajoutant des algorithmes de cache par comparaison de chaîne (string matching caching) et autorisent facilement la dissémination du profil de l'application afin de créer une exécution déportée collaborative dans le voisinage. / Not bounded by time and place, and having now a wide range of capabilities, smartphones are all-in-one always connected devices - the favorite devices selected by users as the most effective, convenient and neces- sary communication tools. Current applications developed for smartphones have to face a growing demand in functionalities - from users, in data collecting and storage - from IoT device in vicinity, in computing resources - for data analysis and user profiling; while - at the same time - they have to fit into a compact and constrained design, limited energy savings, and a relatively resource-poor execution environment. Using resource- rich systems is the classic solution introduced in Mobile Cloud Computing to overcome these mobile device limitations by remotely executing all or part of applications to cloud environments. The technique is known as application offloading. Offloading to a cloud - implemented as geographically-distant data center - however introduces a great network latency that is not acceptable to smartphone users. Hence, massive offloading to a centralized architecture creates a bottleneck that prevents scalability required by the expanding market of IoT devices. Fog Computing has been introduced to bring back the storage and computation capabilities in the user vicinity or close to a needed location. Some architectures are emerging, but few algorithms exist to deal with the dynamic properties of these environments. In this thesis, we focus our interest on designing ACOMMA, an Ant-inspired Collaborative Offloading Middleware for Mobile Applications that allowing to dynamically offload application partitions - at the same time - to several remote clouds or to spontaneously-created local clouds including devices in the vicinity. The main contributions of this thesis are twofold. If many middlewares dealt with one or more of offloading challenges, few proposed an open architecture based on services which is easy to use for any mobile device without any special requirement. Among the main challenges are the issues of what and when to offload in a dynamically changing environment where mobile device profile, context, and server properties play a considerable role in effectiveness. To this end, we develop bio-inspired decision-making algorithms: a dynamic bi-objective decision-making process with learning, and a decision-making process in collaboration with other mobile devices in the vicinity. We define an offloading mechanism with a fine-grained method-level application partitioning on its call graph. We use ant colony algorithms to optimize bi-objectively the CPU consumption and the total execution time - including the network latency.
15

Sintese sonora auto-organizavel atraves da aplicação de algoritmos bio-inspirados / Self-organizing sound synthesis by means of the application of bio-inspired algorithms

Caetano, Marcelo Freitas 20 April 2006 (has links)
Orientadores: Fernando Jose Von Zuben, Jonatas Manzolli / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-06T18:10:14Z (GMT). No. of bitstreams: 1 Caetano_MarceloFreitas_M.pdf: 11758987 bytes, checksum: 2521dc99ef68d0b0a4e06b9ea4751fc5 (MD5) Previous issue date: 2006 / Resumo: Não há limitações teóricas para o uso do computador como fonte de sons musicais. O computador digital permite a produção de qualquer som concebivel dada a seqüência correta de números (amostras digitais). No entanto, produzir uma dada seqüência de números que corresponda a um som musical que possua determinadas características perceptivas desejadas é uma tarefa de difícil resolução. Grande parte dos métodos e sistemas de síntese sonora digital utiliza modelos e/ou incorpora técnicas que não levam em conta a natureza dinâmica dos sons musicais ou que não foram originalmente desenvolvidas para manipulação musical. Neste trabalho, é apresentada uma abordagem populacional para síntese sonora no domínio temporal. Foi estudado um espaço sonoro e um conjunto de atratores, isto é, um conjunto de formas de onda com qualidades sonoras desejadas e definidas a priori, e foi possível obter sons que possuem características associadas a um ou mais atratores, representando variantes dos mesmos. Este método de síntese de sons musicais pode ser interpretado como um processo de busca no espaço vetorial que contém todas as possibilidades sonoras decorrentes da representação adotada, e tem por objetivo a criação de formas de onda digítalizadas com características emergentes e potencial para serem utilizadas em diversas aplicações musicais. Os resultados representam variantes e/ou possuem íntersecções das características próprias dos atratores, responsáveis por indicar as regiões de interesse do espaço de busca. A proposta de pesquisa envolveu a utilização de algoritmos bioinspirados - os quais expressam propriedades de sistemas auto-organizados e adaptativos - como definidores de processos de geração e estruturação dos elementos sonoros, entendidos aqui como problemas de otimização. A auto-organização e os mecanismos de manutenção de diversidade e de adaptação, intrínsecos aos sistemas bio-inspirados, fundamentam a proposta no sentido de viabilizarem a emergência temporal de estruturas estáveis sem um elemento organizador externo / Abstract: There are no theoretical limitations to the use of the computer as a source of musical sounds. The digital computer allows for the production of any conceivable sound given the carrect sequence af numbers (digital samples). Nevertheless, producing the correct sequence of numbers that correspond to a musical sound expressing predefined perceptual characteristics is a very difficult task. Most sound synthesis methods and systems utilize models and/or incorporate techniques which do not take into account the dynamic nature of musical sounds or were not originally developed for the manipulation of musical tones. In this work we are proposing a populational sound synthesis approach in the time domain. A soundspace and a set of attractors, i.e. waveforms containing a priari desired features or qualities, and a population of agents communicating by means of local interaction were studied, and it was possible to attain sounds which share some qualities from more than one of the attractors, resulting exclusively from low-Ievel rules followed by these agents. This sound synthesis method can be regarded as a search in the vector space that contains ali the possible sounds resulting from the adopted representation, and its objective is to synthesize digital waveforms that possess emergent properties and the potential to be used in musical applications. The resulting sounds are variants or hybrids that share some of the intrinsic features of the attractors, which are responsible for indicating the regions of interest in the search space. This proposal involved the use of bio-inspired algorithms, which express features of adaptive, self-organizing systems, as definers of generating and structuring processes of sound elements, regarded herein as optimization processes. Self-organization and diversity maintenance and adaptation mechanisms, intrinsic to bio-inspired systems, lay the foundations of this proposal so as to make viable the temporal emergence of stable structures without an externa I organizing element / Mestrado / Engenharia de Computação / Mestre em Engenharia Elétrica

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