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Auswahl der wissenschaftlichen Literatur zum Thema „Phase-Based Algorithms“
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Zeitschriftenartikel zum Thema "Phase-Based Algorithms"
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Hu, Xiao-Xiao, and Kit Ian Kou. "Phase-based edge detection algorithms." Mathematical Methods in the Applied Sciences 41, no. 11 (2017): 4148–69. http://dx.doi.org/10.1002/mma.4567.
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Li, Fanxing, Wei Yan, Fupin Peng, Simo Wang, and Jialin Du. "Enhanced Phase Retrieval Method Based on Random Phase Modulation." Applied Sciences 10, no. 3 (2020): 1184. http://dx.doi.org/10.3390/app10031184.
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The phase retrieval method based on random phase modulation can wipe out any ambiguity and stagnation problem in reconstruction. However, the two existing reconstruction algorithms for the random phase modulation method are suffering from problems. The serial algorithm from the spread-spectrum phase retrieval method can realize rapid convergence but has poor noise immunity. Although there is a parallel framework that can suppress noise, the convergence speed is slow. Here, we propose a random phase modulation phase retrieval method based on a serial–parallel cascaded reconstruction framework to simultaneously achieve quality imaging and rapid convergence. The proposed serial–parallel cascaded method uses the phased result from the serial algorithm to serve as the initialization of the subsequent parallel process. Simulations and experiments demonstrate that the superiorities of both serial and parallel algorithms are fetched by the proposed serial–parallel cascaded method. In the end, we analyze the effect of iteration numbers from the serial process on the reconstruction performance to find the optimal allocation scope of iteration numbers.
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Yugov, Vsevolod, and Itsuo Kumazawa. "Online Boosting Algorithm Based on Two-Phase SVM Training." ISRN Signal Processing 2012 (August 14, 2012): 1–8. http://dx.doi.org/10.5402/2012/740761.
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We describe and analyze a simple and effective two-step online boosting algorithm that allows us to utilize highly effective gradient descent-based methods developed for online SVM training without the need to fine-tune the kernel parameters, and we show its efficiency by several experiments. Our method is similar to AdaBoost in that it trains additional classifiers according to the weights provided by previously trained classifiers, but unlike AdaBoost, we utilize hinge-loss rather than exponential loss and modify algorithm for the online setting, allowing for varying number of classifiers. We show that our theoretical convergence bounds are similar to those of earlier algorithms, while allowing for greater flexibility. Our approach may also easily incorporate additional nonlinearity in form of Mercer kernels, although our experiments show that this is not necessary for most situations. The pre-training of the additional classifiers in our algorithms allows for greater accuracy while reducing the times associated with usual kernel-based approaches. We compare our algorithm to other online training algorithms, and we show, that for most cases with unknown kernel parameters, our algorithm outperforms other algorithms both in runtime and convergence speed.
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Ahmadi, Hamed, and Chen-Fu Chiang. "Quantum phase estimation with arbitrary constant-precision phase shift operators." Quantum Information and Computation 12, no. 9&10 (2012): 864–75. http://dx.doi.org/10.26421/qic12.9-10-9.
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While Quantum phase estimation (QPE) is at the core of many quantum algorithms known to date, its physical implementation (algorithms based on quantum Fourier transform (QFT) ) is highly constrained by the requirement of high-precision controlled phase shift operators, which remain difficult to realize. In this paper, we introduce an alternative approach to approximately implement QPE with arbitrary constant-precision controlled phase shift operators. The new quantum algorithm bridges the gap between QPE algorithms based on QFT and Kitaev's original approach. For approximating the eigenphase precise to the nth bit, Kitaev's original approach does not require any controlled phase shift operator. In contrast, QPE algorithms based on QFT or approximate QFT require controlled phase shift operators with precision of at least Pi/2n. The new approach fills the gap and requires only arbitrary constant-precision controlled phase shift operators. From a physical implementation viewpoint, the new algorithm outperforms Kitaev's approach.
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Naimipour, Naveed, Shahin Khobahi, Mojtaba Soltanalian, Haleh Safavi, and Harry C. Shaw. "Unfolded Algorithms for Deep Phase Retrieval." Algorithms 17, no. 12 (2024): 587. https://doi.org/10.3390/a17120587.
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Exploring the idea of phase retrieval has been intriguing researchers for decades due to its appearance in a wide range of applications. The task of a phase retrieval algorithm is typically to recover a signal from linear phase-less measurements. In this paper, we approach the problem by proposing a hybrid model-based, data-driven deep architecture referred to as Unfolded Phase Retrieval (UPR), which exhibits significant potential in improving the performance of state-of-the-art data-driven and model-based phase retrieval algorithms. The proposed method benefits from the versatility and interpretability of well-established model-based algorithms while simultaneously benefiting from the expressive power of deep neural networks. In particular, our proposed model-based deep architecture is applied to the conventional phase retrieval problem (via the incremental reshaped Wirtinger flow algorithm) and the sparse phase retrieval problem (via the sparse truncated amplitude flow algorithm), showing immense promise in both cases. Furthermore, we consider a joint design of the sensing matrix and the signal processing algorithm and utilize the deep unfolding technique in the process. Our numerical results illustrate the effectiveness of such hybrid model-based and data-driven frameworks and showcase the untapped potential of data-aided methodologies to enhance existing phase retrieval algorithms.
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Choi, Seong Woo. "Scheduling Algorithm for Reentrant Flexible Flow Shop with the Objective Function of Minimizing Orders’ Total Flow Time." Korean Production and Operations Management Society 34, no. 1 (2023): 129–43. http://dx.doi.org/10.32956/kopoms.2023.34.1.129.
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This study focuses on a scheduling problem in a flexible flow shop, where there are serial stages, each with identical parallel machines. We suggest heuristic algorithms for the problem to minimize the total flow time of a given set of orders. Each order is composed of multiple lots and is processed on any parallel machines at each stage. This shop has reentrant flows since products for specific orders should visit the processing stages twice. We suggest algorithms of two types. The algorithms of the first type are three-phase algorithms, and the second type's algorithm is one-phase. In the first phase of three-phase algorithms, an initial sequence is obtained using priority dispatching rules, and then a construction algorithm is used to obtain sequences for each stage in the second phase. Finally, in the third phase, lots that visit the stages for the second time are scheduled using priority dispatching rules. Computational experiments are performed on randomly generated test problems to evaluate the performance of the suggested algorithms. Results show that the order-based algorithms perform better than the lot-based algorithms and an algorithm used in practice.
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Wu, Ting, Yuling Yang, Hao Wang, et al. "Investigation of an Improved Angular Spectrum Method Based on Holography." Photonics 11, no. 1 (2023): 16. http://dx.doi.org/10.3390/photonics11010016.
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Digital holography (DH) is a novel, real-time, non-destructive, and quantitative phase-contrast imaging method that is particularly suitable for label-free live biological cell imaging and real-time dynamic monitoring. It is currently a research hotspot in the interdisciplinary field of optics and biomedical sciences, both domestically and internationally. This article proposes an improved angle spectrum algorithm based on holographic technology, which reconstructs a cellular hologram based on phase information. Optical images and chromosome cell images, reconstructed using holographic technology at different diffraction distances under the improved angle spectrum algorithm, were analyzed and compared. The optimal diffraction distance for reconstructing chromosome cell images was selected, and chromosome cell images reproduced using traditional angle spectrum algorithms, angle spectrum algorithms combined with GS, and improved angle spectrum algorithms were compared. Comparative experiments with the different models show that the proposed algorithm is superior to traditional angle spectrum algorithms in reconstructing cell images based on phase information. Furthermore, experiments have shown that images reconstructed using the improved algorithm can resolve high signal-to-noise ratio information. This algorithmic improvement provides new applications for cellular detection in clinical diagnostics and is more suitable for cell phase reconstruction in practical applications.
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Zou, Feng, Lei Wang, Xinhong Hei, Debao Chen, Qiaoyong Jiang, and Hongye Li. "Bare-Bones Teaching-Learning-Based Optimization." Scientific World Journal 2014 (2014): 1–17. http://dx.doi.org/10.1155/2014/136920.
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Teaching-learning-based optimization (TLBO) algorithm which simulates the teaching-learning process of the class room is one of the recently proposed swarm intelligent (SI) algorithms. In this paper, a new TLBO variant called bare-bones teaching-learning-based optimization (BBTLBO) is presented to solve the global optimization problems. In this method, each learner of teacher phase employs an interactive learning strategy, which is the hybridization of the learning strategy of teacher phase in the standard TLBO and Gaussian sampling learning based on neighborhood search, and each learner of learner phase employs the learning strategy of learner phase in the standard TLBO or the new neighborhood search strategy. To verify the performance of our approaches, 20 benchmark functions and two real-world problems are utilized. Conducted experiments can been observed that the BBTLBO performs significantly better than, or at least comparable to, TLBO and some existing bare-bones algorithms. The results indicate that the proposed algorithm is competitive to some other optimization algorithms.
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Pan, Jeng-Shyang, Li-Fa Liu, Shu-Chuan Chu, Pei-Cheng Song, and Geng-Geng Liu. "A New Gaining-Sharing Knowledge Based Algorithm with Parallel Opposition-Based Learning for Internet of Vehicles." Mathematics 11, no. 13 (2023): 2953. http://dx.doi.org/10.3390/math11132953.
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Heuristic optimization algorithms have been proved to be powerful in solving nonlinear and complex optimization problems; therefore, many effective optimization algorithms have been applied to solve optimization problems in real-world scenarios. This paper presents a modification of the recently proposed Gaining–Sharing Knowledge (GSK)-based algorithm and applies it to optimize resource scheduling in the Internet of Vehicles (IoV). The GSK algorithm simulates different phases of human life in gaining and sharing knowledge, which is mainly divided into the senior phase and the junior phase. The individual is initially in the junior phase in all dimensions and gradually moves into the senior phase as the individual interacts with the surrounding environment. The main idea used to improve the GSK algorithm is to divide the initial population into different groups, each searching independently and communicating according to two main strategies. Opposite-based learning is introduced to correct the direction of convergence and improve the speed of convergence. This paper proposes an improved algorithm, named parallel opposition-based Gaining–Sharing Knowledge-based algorithm (POGSK). The improved algorithm is tested with the original algorithm and several classical algorithms under the CEC2017 test suite. The results show that the improved algorithm significantly improves the performance of the original algorithm. When POGSK was applied to optimize resource scheduling in IoV, the results also showed that POGSK is more competitive.
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Doria-Cerezo, Arnau, Victor Repecho, and Domingo Biel. "Three-Phase Phase-Locked Loop Algorithms Based on Sliding Modes." IEEE Transactions on Power Electronics 36, no. 9 (2021): 10842–51. http://dx.doi.org/10.1109/tpel.2021.3064674.
Der volle Inhalt der QuelleDissertationen zum Thema "Phase-Based Algorithms"
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Pereira, Frances Elizabeth. "Duality-based algorithms for the global solution of fluid phase equilibria with general equations of state." Thesis, Imperial College London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526380.
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Cao, Yufei [Verfasser]. "Robust Numerical Algorithms Based on Corrected Operator Splitting for Two-Phase Flow in Porous Media / Yufei Cao." Aachen : Shaker, 2010. http://d-nb.info/110118406X/34.
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Choi, Won-Suk. "Phase-only and amplitude-only adaptive algorithms based on a D(3)LS method for smart antenna systems and airborne radar applications." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2005. http://wwwlib.umi.com/cr/syr/main.
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Mahamdi, Célia. "Multi-Consensus distribué : agrégation et révocabilité." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS426.
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Cette thèse présente deux contributions dans le domaine des systèmes distribués : OMAHA et le Consensus f-Révocable. OMAHA (Opportunistic Message Aggregation for pHase-based Algorithms) est un mécanisme d'agrégation de messages conçu pour les algorithmes à phases. Dans les environnements Cloud, où plusieurs applications partagent la même infrastructure, la bande passante est une ressource critique. Dans les datacenters, une partie importante du trafic est consacrée aux petits messages. Chaque message possède un en-tête, ainsi, l'accumulation de ces petits messages pose un véritable problème et entraîne une consommation non négligeable de bande passante. Plusieurs mécanismes ont été proposés pour adresser ce défi, mais peu d'entre eux prennent en compte les caractéristiques applicatives. Ils reposent principalement sur une agrégation des messages au niveau de la couche réseau. OMAHA exploite les spécificités des algorithmes à phases pour agréger intelligemment et de manière opportuniste les messages. Bien que gourmands en messages, de très nombreuses applications reposent sur des algorithmes à phases (Google Spanner, Zookeeper, etc.). Cependant, ils possèdent un avantage majeur : des communications prévisibles. En anticipant les futures communications, OMAHA retarde les messages en les regroupant avec d'autres destinés au même processus. Cela permet de réduire le nombre de messages envoyés sur le réseau et donc une économie de bande passante. Nos expériences montrent des économies de bande passante allant jusqu'à 30%, tout en limitant la dégradation de la latence à 5% pour le célèbre algorithme de Paxos. Dans les systèmes distribués, atteindre un consensus sur une action ou une valeur est un défi complexe, surtout lorsque les processus sont soumis à des contraintes. De nombreux systèmes, tels que les systèmes multi-agents (véhicules autonomes, gestion d'agenda, robotique, etc.) ou encore les systèmes d'allocation de ressources, doivent respecter des contraintes tout en atteignant un objectif global commun. Cependant, les algorithmes de consensus traditionnels ne prennent pas en compte ces contraintes, la décision se basant uniquement sur les valeurs proposées par les processus. Une solution triviale consisterait à recueillir toutes les contraintes, mais en raison de l'asynchronisme et des pannes, cela est impossible. Pour tolérer les pannes, certains algorithmes définissent un nombre maximal de fautes qu'ils peuvent supporter. Cela permet à l'algorithme de progresser sans attendre la réponse de tous les processus. En conséquence, la valeur décidée est souvent imposée par un sous-ensemble de processus, la majorité. Les contraintes de la minorité sont ainsi ignorées. Pour répondre à ce problème, nous avons introduit le Consensus f-Révocable. Ce consensus revisité permet de choisir une valeur qui respecte les contraintes des processus tout en offrant la possibilité de révoquer une décision prise par la majorité si celle-ci viole les contraintes d'un processus de la minorité. La convergence est assurée car le nombre de révocations est borné par le nombre de processus appartenant à la minorité. Nous avons développé deux adaptations de l'algorithme Paxos pour mettre en pratique ce nouveau consensus<br>This thesis presents two contributions to the field of distributed systems: OMAHA and the f-Revoke Consensus.OMAHA (Opportunistic Message Aggregation for pHase-based Algorithms) is a message aggregation mechanism designed for phase-based algorithms. In cloud environments, multiple applications share the same infrastructure, making bandwidth a critical resource. A significant portion of traffic in data centers consists of small messages. Each message includes a header, leading to substantial bandwidth consumption. Several mechanisms have been proposed to address this issue, but few consider application-specific characteristics. Most rely on aggregation at the network layer. OMAHA leverages the features of phase-based algorithms to intelligently and opportunistically aggregate messages. Many applications, such as Google Spanner and Zookeeper, depend on phase-based algorithms. They are often message-intensive but offer a key advantage: predictable communications. By anticipating future communications, OMAHA delays messages and groups them with others intended for the same process. This approach reduces the number of messages sent over the network, resulting in bandwidth savings. Our experiments show bandwidth saving of up to 30%, while limiting latency degradation to 5% for the well-known Paxos algorithm. In distributed systems, achieving consensus on an action or value is complex, especially when processes face constraints. Many systems, including multi-agent systems (like autonomous vehicles and robotics) and resource allocation systems, need to respect these constraints while working towards a common goal. Unfortunately, traditional consensus algorithms often overlook these constraints, focusing only on the values proposed by the processes. A straightforward solution would be to gather all constraints, but due to asynchrony and potential failures, this is impossible. To handle failures, some algorithms set a limit on the number of faults they can tolerate. This allows them to move forward without waiting for responses from every process. As a result, the final decision is made by a subset of processes known as the majority. This leads to the exclusion of constraints from the minority. To tackle this problem, we introduced the f-Revoke Consensus. This new approach enables the selection of a value that considers processes' constraints. It also allows for the revocation of a majority decision if it violates the constraints of a minority process. Importantly, convergence is ensured because the number of revocations is limited by the size of the minority. We developed two adaptations of the Paxos algorithm to implement this new consensus
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Maciel, Lucas da Silva. "A novel swarm-based algorithm for phase unwrapping." reponame:Repositório Institucional da UFSC, 2014. https://repositorio.ufsc.br/xmlui/handle/123456789/129595.
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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Mecânica, Florianópolis, 2014.<br>Made available in DSpace on 2015-02-05T21:16:46Z (GMT). No. of bitstreams: 1
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Previous issue date: 2014<br>O correto funcionamento de tubulações subterrâneas para o transporte de gás e petróleo depende de um monitoramento frequente e correto dos estados de tensões. Avanços recentes na medição de tensões residuais têm aplicado métodos ópticos em conjunto com o alívio de tensões de maneira a avaliar o campo de tensões no componente. Estes métodos requerem uma etapa de remoção do salto de fase para interpretar corretamente os dados adquiridos. Esta remoção do salto de fase tem sido um desafio para diversas aplicações metrológicas. Este trabalho tem por objetivo propor uma abordagem original para a solução deste problema. Neste trabalho é apresentado o algoritmo proposto assim como diversos resultados com diferentes imagens comparados com métodos consagrados.A luz, comportando-se como onda, obedece ao princípio de superposição que por sua vez dá lugar ao fenômeno de interferência. Este fenômeno pode ser utilizado de diversas maneiras para a medição de superfícies e formas geométricas. No entanto, várias dessas aplicações, como interferometria speckle e shearografia, fornecem os valores de interesse restringidos a um intervalo de ?p a p. Assim, faz-se necessária uma operação para retomar os valores reais que produziram o resultado obtido. Esta operação é chamada de remoção do salto de fase.Por décadas tem-se estudado diversas técnicas para realizar a remoção do salto de fase. Elas podem ser divididas em duas categorias principais: métodos que seguem caminhos e métodos independente de caminhos. Métodos que seguem caminhos aplicam uma simples equação de comparação e adição de múltiplos de 2p por toda a imagem. Elas diferem nos caminhos de pixels escolhidos. Para que o resultado seja confiável, é necessário que esse caminho evite pixels de baixa qualidade ou corrompidos. As técnicas de branch-cut identificam esses pixels através da teoria de resíduos e conectando resíduos de sinais opostos, ela é capaz de traçar caminhos confiáveis para a remoção do salto de fase. Técnicas baseadas em qualidade atribuem notas relativas a diferentes critérios de qualidade para cada pixel, excluindo da análise aqueles que se encontram abaixo de um limiar arbitrário.Técnicas independentes de caminhos, como os métodos de norma mínima, assemelham-se a métodos de otimização. Estes são iterativos e procuram por um mínimo na diferença entre as derivadas da solução proposta e as derivadas da imagem original. Estes métodos são considerados bastante robustos e confiáveis. No entanto, estes tambémdemandam maior tempo de processamento para encontrar a resposta correta.Em paralelo aos desenvolvimentos na área de remoção do salto de fase, cientistas têm desenvolvido técnicas computacionais baseadas no comportamento de animais sociais. O campo de Inteligência de Enxame é inspirado por insetos como formigas, abelhas e cupins e outros animais como peixes e pássaros. Estes animais têm em comum o fato de criarem sistemas organizados embora compostos de elementos simples e a ausência de uma liderança clara. O comportamento de formigas e abelhas na busca por comida e os movimentos em grupo de peixes e pássaros são os exemplos mais claros do conceito de comportamento emergente: um comportamento que, embora não explícito na descrição de seus elementos individuais, surge com a interação entre diversos desses elementos. Este comportamento emergente pode ser explicado em termos de agentes simples e independentes, regras simples e um comportamento descentralizado.Este fenômeno tem inspirado as ciências da computação por décadas. Diversas soluções computacionais para problemas matemáticos ou operacionais têm sido propostas a partir das soluções elegantes encontradas na natureza. Exemplos dessas soluções são os algoritmos de otimização baseados no comportamento de formigas e abelhas. No entanto, pouco deste conceito tem sido aplicado na área de processamento de imagem. Quanto ao problema de remoção do salto de fase, mais especificamente, não foi encontrado nenhum trabalho que propusesse uma solução baseada em Inteligência de Enxame.Assim, o presente trabalho propõe uma solução baseada nestes conceitos. Por causa da natureza imprevisível do comportamento emergente, o desenvolvimento do algoritmo proposto foi pouco convencional. Em primeiro lugar, foi necessário o desenvolvimento de um ambiente de testes onde o enxame pudesse ser observado em tempo real durante a sua operação. Em segundo lugar, a criação do algoritmo se deu de maneira iterativa até que fosse encontrado um conjunto de regras satisfatório.Uma primeira solução foi encontrada modelando os agentes como máquinas de estados finitos. Este modelo de agente foi implementado com dinâmicas de comunicação indireta através de estigmergia e comunicação direta em casos de necessidade. Este método, apesar de ter apresentado bons resultados em termos de qualidade da remoção do salto de fase, necessitava ainda de um critério de parada independente do usuário. Na criação deste critério de parada, novas regras deram espaço para a criação de um algoritmo completamente diferente.Esta segunda solução modela o agente a partir de cinco regras simples que permitem, entre outras coisas, a criação e desativação de novos agentes. Uma vez que todos os agentes são desativados, o programa chega ao fim e retorna a imagem com o salto de fase removido. A primeira destas regras afirma que se há um ou mais pixels que podem ter seu salto removido na vizinhança do agente, um deles será escolhido aleatoriamente para a operação. O agente então se move para o pixel escolhido e ganha um ponto de energia. Se não há pixels aptos a serem trabalhados, um pixel já trabalhado na vizinhança é escolhido aleatoriamente, de acordo com a segunda regra. O agente se move para o pixel escolhido e perde um ponto de energia. A terceira regra faz com que agentes que encontram dois pixels vizinhos já trabalhados mas inconsistentes entre si, marcarem estes pixels como defeituosos e desativarem-se. As duas últimas regras fazem com que agentes com energia excedente repliquem-se e aqueles sem energia desativem-se.O comportamento esperado é que os agentes de distribuam pela imagem de maneira eficiente, aproveitando ao máximo os ciclos de processamento. Além disso, a regra de marcação de remoções duvidosas faz com que problemas de ambiguidade na remoção do salto de fase não sejam propagados por grandes regiões da imagem. Este algoritmo foi testado em diversas condições e comparado com outros métodos estabelecidos.Os primeiros resultados foram gerados aplicando-se o enxame em imagens sintéticas sem quaisquer erros. Assim, foi possível avaliar a influência de diferentes parâmetros escolhidos pelo usuário no comportamento do enxame e qualidade dos resultados. Foi possível observar o impacto dos parâmetros de energia na densidade do enxame que, por sua vez, é importante para a correção de ambiguidades propagadas.Em seguida, foram testadas imagens sintéticas com erros artificiais. Os resultados foram comparados com um algoritmo baseado em qualidade e um algoritmo de norma mínima. Foi observado que o algoritmo proposto foi extremamente capaz de contornar as dificuldades das imagens de maneira, produzindo resultados confiáveis. Para certas condições, os resultados foram ainda melhores que os obtidos pelo outro algoritmo baseado em qualidade.Foram testadas ainda imagens provenientes de aplicações metrológicas reais: projeção de franjas, interferometria speckle e shearografia. Os resultados obtidos pelo algoritmo baseado em Inteligência de Enxame foram bastante satisfatórios, comparáveis aos métodos mais robustos. Ainda, o algoritmo proposto apresentou melhoresresultados para imagens muito ruidosas quando comparado com o outro algoritmo baseado em qualidade testado. Estes resultados atestam do potencial do método proposto em obter resultados rápidos e confiáveis.Por fim, este trabalho foi concluído com um breve resumo destes resultados e a validação dos objetivos originais, afirmando assim o sucesso do método proposto. Foram listadas ainda algumas sugestões para avanços futuros como os testes com imagens e parâmetros de qualidade novos, a implementação de processamento paralelo e a criação de novas abordagens baseadas em Inteligência de Enxame para a solução deste problema e outros semelhantes.<br><br>Abstract : The proper functioning of underground oil and gas pipelines depend on the frequent and correct monitoring of stress states. Recent developments on residual stress measurement techniques have employed optical methods allied with stress relief in order to assess the underlying stress field. These optical methods require a phase unwrapping step to interpret the acquired data correctly. Phase unwrapping has posed a challenge for many optical metrology applications for decades and saw the development of many different solutions. For the past decades, the field of Swarm Intelligence, based on the behavior observed among ants, bees and other social insects, has been studied and many algorithms have been designed to perform a variety of computational tasks. Swarm Intelligence is commonly regarded as robust and fast, which are desirable features in a phase unwrapping algorithm. This work proposes a novel approach to phase unwrapping based on Swarm Intelligence, assessing its applicability, comparing it to existing methods and evaluating its potential to future developments. The proposed algorithm is thoroughly explained and the results for several different images are presented. These results show a great potential of the proposed method, performing better than some established techniques in specific situations. This potential is assessed and suggestion for future advancements are given.
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Bakkar, Mostafa. "Sag effects on protection system in distributed generation grids." Doctoral thesis, Universitat Politècnica de Catalunya, 2022. http://hdl.handle.net/10803/673721.
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Distributed Generators (DGs) are sensible to voltage sags, so the protection devices must trip fast to disconnect the faulted part of the grid. The DG disconnection will not be desirable in the near future with a large penetration, so it will be necessary to lay down new requirements that should be based on avoiding unnecessary disconnections. Therefore, to prevent unnecessary tripping when inverter-based DGs are connected to the Medium Voltage (MV) grid, reliable and effective protection strategies need to be developed, considering the limited short-circuit current contribution of DG.
The initial goal of this study is to employ different possible control strategies for a grid-connected inverter according to the Spanish grid code and to analyze the output voltage behavior during symmetrical and unsymmetrical voltage sags. The analytical development of the proposed strategies shows the impacts of the sag on currents, voltages, active and reactive powers.
Another goal of this research is to propose a protection strategy based on Artificial Intelligence for a radial or ring distribution system with high DG penetration. The protection strategy is based on three different algorithms to develop a more secure, redundant, and reliable protection system to ensure supply continuity during disturbances in ring and radial grids without compromising system stability. In order to classify, locate and distinguish between permanent or transient faults, new protection algorithms based on artificial intelligence are proposed in this research, allowing network availability improvement disconnecting only the faulted part of the system. This research introduces the innovative use of directional relay based on a communication system and Artificial Neural Network (ANN). The first algorithm, Centralize algorithm (CE), collects the data from all the PDs in the grid in the centralized controller. This algorithm detects the power flow direction and calculates the positive-sequence current of all the PDs in the grid. Significant benefits of this system are that it consolidates the entire systems security into a single device, which can facilitate system security control. However, the CE will not pinpoint the exact location of the fault if there is any loss of information due to poor communication. Therefore, the systems redundancy can be improved by cooperating with a second algorithm, the Zone algorithm (ZO). ZO algorithm is based on zone control using peer-to-peer connectivity in the same line. The faulty line in that zone may be identified by combining the two PDs data on the same line. The most relevant advantage of this algorithm is its flexibility to adapt to any grid modification or disturbance, even if they are just temporary, unlike the CE, which is fixed to the existing grid configuration. The third protection algorithm, Local algorithm (LO), has been proposed without depending on the communication between the PDs; then, the protection system can work properly in case of a total loss of communication. Each PD should be able to detect if the fault is located in the protected line or another line by using only the local information of the PD. According to the type of fault and based on local measurements at each PD of abc voltages and currents, different algorithms will be applied depending on the calculation of the sequence components. The main advantage of this algorithm is the separate decision of each PD, and avoiding communication problems.
In case of radial grids, both mechanical breakers and Solid State Relays (SSRs) are used to verify the protection strategies, and in the case of ring grids, mechanical breakers are used, due to the limitations in required voltage difference of SSR.
The proposed protection algorithms are compared with conventional protections (Overcurrent and Differential) protections to validate the contribution of the proposed algorithms, especially in reconfigurable smart grids.<br>El objetivo inicial de este estudio es emplear diferentes estrategias de control posibles para un inversor conectado a la red segun el código de red español y analizar el comportamiento de la tensión de salida durante caídas de tensión simétricas y asimétricas. El desarrollo analítico de las estrategias propuestas muestra los impactos de los huecos de tensión en las corrientes, tensiones, potencias activas y reactivas. Otro objetivo de esta investigación es proponer una estrategia de protecclón basada en lnteligencia Artificial para una red del Sistema de Distribución, radial o en anillo, con elevada penetración de Generación Distribuida. La estrategia de protección se basa en tres algoritmos diferentes para desarrollar un sistema de protección más seguro, redundante, y fiable, que asegure la continuidad de suministro durante perturbaciones en redes radiales o en anillo sin comprometer la estabilidad del sistema. Para clasificar, localizar y distinguir entre faltas permanentes o transitorias, se proponen en este trabajo nuevos algoritmos de protección basados en inteligencia artificial, permitiendo la mejora de la disponibilidad de la red, al desconectar sólo la parte del sistema en falta. Esta investigación introduce la innovación del uso del rele direccional basado en un sistema de comunicación y Redes Neuronales Artificiales (ANN). El primer algoritmo, Algoritmo Central (CE), recibe los datos de todos los PDs de la red en un control central. Este algoritmo detecta la dirección de flujo de cargas y calcula la corriente de secuencia positiva de todos los PDs de la red. El entrenamiento de ANNs incluye variaciones en la corriente de cortocircuito y la dirección del flujo de potencia en cada PD. Los beneficios mas significativos de este sistema son que concentra la seguridad total del sistema en un único dispositivo, lo que puede facilitar el control de la seguridad del sistema. Sin embargo, el CE no determinara con precisión la localización exacta de la falta si hay alguna perdida de información debida a una pobre comunicación. Por lo tanto, la redundancia del sistema se puede mejorar cooperando con un segundo algoritmo, el algoritmo de Zona (ZO). El algoritmo ZO se basa en un control de zona usando la conectividad entre dispositivos de protección de una misma línea. La línea en falta en esa zona puede identificarse combinando los datos de los dos PDs de la misma línea.. La ventaja mas relevante de este algoritmo es su flexibilidad para adaptarse a cualquier modificación de la red o perturbación, incluso si sólo son temporales, a diferencia del CE, que se ha adaptado para la configuración de la red existente. El tercer algoritmo de protección, algoritmo Local (LO), ha sido propuesto sin dependencia de la comunicación entre PDs; por lo tanto, el sistema de protección puede operar correctamente en el caso de una pérdida total de comunicación. Cada PD debe poder detectar si la falta esta ubicada en la línea protegida o en otra línea, utilizando sóIo la información local del PD. Según el tipo de falta, y en base a medidas locales en cada PD, de tensiones y corrientes abc, se aplican diferentes algoritmos en función del cálculo de las componentes simétricas. La principal ventaja de este algoritmo es la actuación por separado de cada PD, evitando los problemas de comunicación. En el caso de las redes radiales, se utilizan tanto interruptores mecánicos como réles de estado sóIido (SSR) para verificar las estrategias de protección, y en el caso de las redes en anillo se utilizan interruptores mecánicos, debido a las limitaciones de tensión para su conexión. Los algoritmos de protección propuestos se comparan con protecciones convencionales (Sobrecorriente y Diferencial) para validar la contribución de los algoritmos propuestos, especialmente en redes inteligentes reconfigurables.<br>Enginyeria Elèctrica
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Jattiem, Mogamad Shaheed. "An improved algorithm for phase-based voltage dip classification." Master's thesis, University of Cape Town, 2007. http://hdl.handle.net/11427/5201.
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Word processed copy.<br>Includes bibliographical references (leaves 71-72)<br>In this thesis, a new phase-based algorithm is developed, which overcomes the shortcomings of the Bollen algorithms. The new algorithm computes the dip type based on the difference in phase angle between the measured voltages.
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Xia, Tao. "Frequency Monitoring Network (FNET) Algorithm Improvements and Application Development." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/77296.
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The Internet Based real-time GPS synchronized wide-area Frequency Monitoring Network (FNET) is an extremely low cost and quickly deployable wide-area frequency measurement system with high dynamic accuracy which consists of Frequency Disturbance Recorder (FDR) distributed to more than 100 places around North America and an Information Management System situated at Virginia Tech. Since its first FDR deployment in 2003, the FNET system has been proved to be able to reliably receive phasor data accurately measured at and instantaneously sent via the Internet from different locations of interest, and efficiently run the analyzing program to detect and record significant system disturbances and subsequently estimate the location of disturbance center, namely the event location, in the electric grid based on the information gathered. The excellent performance of the FNET system so far has made power grid situation awareness and monitoring based on distribution level frequency measurements a reality, and thus advances our understanding of power system dynamics to a higher level and in a broader dimensionality.
Chapter 1 and Chapter 2 of this dissertation briefly introduce the genesis and the architecture of the FNET system, followed by a summary of its concrete implementations. Chapter 3 and Chapter 4 outline FNET frequency estimation algorithm and phase angle estimation algorithm, including their attributes and the new methodologies to enhance them. In Chapter 5, the report discusses the algorithms developed at FNET to detect the frequency disturbance and estimate the disturbance location by the triangulation procedure using real-time frequency data and geographic topology of the FNET units in the power grid where the disturbance occurs. Then, the dissertation proceeds to introduce the FNET angle-based power system oscillation detection and present some research about Matrix Pencil Modal Analysis of FNET phase angle oscillation data in the following two chapters. Lastly, the content of this report is summarized and the future work envisioned in Chapter 8.<br>Ph. D.
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Maciel, Luiz Alexandre Hiane da Silva. "A timestamp-based two phase commit protocol for web services." Instituto Tecnológico de Aeronáutica, 2011. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=1974.
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Service Oriented Architecture (SOA) allows the development of software with requirements of interoperability and loose coupling. New services can be offered through the composition of existing services in order to address new business requirements. Business-to-business collaborative web applications demand a loosely coupled, coarse-grained interaction model. Thus, the traditional transaction architectures based on the ACID must be re-visited to support long-running web services. For such web services, it is not advisable to lock resources because they become blocked to other transactions. The two most adopted SOA architecture styles are the WS-* and REST (Representational State Transfer). WS-* is a set of specifications for the development of services based on SOAP and WSDL. The WS-* specifications support the implementation of non-functional requirements among them the transaction control. Two of the WS-* drawbacks are the implementation complexity and the strong dependency on SOAP and WSDL. REST, however, as an architectural style, does not provide "official" standards to address the non-functional requirements of services. We investigate the means by which a web service application can support transactions implementation using timestamp. We propose a protocol based in timestamp and two phase commit protocol in order to support the transactional control implementation in the web service domain. A protocol extension to improve the satisfaction of business rules is also proposed. The extension takes into account the application domain business rules which guide the web services behavior. In order to show the feasibility of the protocols, examples of an application are described. We also describe how the proposed protocols must be used to deal with host and connection failures.
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Arslan, Omer Cagri. "Implementation And Performance Evaluation Of A Three Antenna Direction Finding System." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12611215/index.pdf.
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State of the art direction finding (DF) systems usually have several antennas in order to increase accuracy and robustness to certain factors. In this thesis, a three antenna DF system is built and evaluated. While more antennas give better DF performance, a three antenna system is useful for system simplicity and many of the problems in DF systems can be observed and evaluated easily. This system can be used for both azimuth and elevation direction of arrival (DOA) estimation. The system is composed of three monopole antennas, an RF front end, A/D converters and digital signal processing (DSP) units. A number of algorithms are considered, such as, three channel interferometer, correlative interferometer, LSE (least square error) based correlative interferometer and MUSIC (multiple signal classification) algorithms. Different problems in DF systems are investigated. These are gain/phase mismatch of the receiver channels, mutual coupling between antennas, multipath signals and multiple sources. The advantages and disadvantages of different algorithms are outlined.
Bücher zum Thema "Phase-Based Algorithms"
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Bogumil, Veniamin, and Sarango Duke. Telematics on urban passenger transport. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1819882.
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The monograph discusses the application of telematics in dispatch control systems in urban passenger transport. The role of telematics as a technological basis in automating the solution of control tasks, accounting and analysis of the volume and quality of transport work in modern dispatch control systems on urban passenger transport is shown. Analytical models have been developed to estimate the capacity of a high-speed bus transportation system on a dedicated line. Mathematical models and algorithms for predicting passenger vehicle interior filling at critical stages of urban passenger transport routes are presented. The issues of application of the concept of the phase space of states introduced by the authors to assess the quality of the passenger transportation process on the route of urban passenger transport are described. The developed classification of service levels and their application in order to inform passengers at stopping points about the degree of filling of the passenger compartment of the arriving vehicle is described. The material is based on the results of theoretical research and practical work on the creation and implementation of automated control systems for urban passenger transport in Russian cities. The material of M.H. Duque Sarango's dissertation submitted for the degree of Candidate of Technical Sciences in the specialty 05.22.10 "Operation of motor transport" was used.
 It will be useful to specialists in the field of telematics on urban passenger transport.
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Damodaran, A. Managing Arts in Times of Pandemics and Beyond. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192856449.001.0001.
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The work seeks to provide a management perspective about museums, theatres, and related organizations (like auction houses) from the angles of philosophy, policy, organizational design, economics, and technology. The work seeks to examine the unprecedented crisis engendered by the COVID-19 pandemic on arts organizations across the world and the management strategies adopted to handle the pandemic. The work delves into the immense significance of digital technologies such as streaming technologies, algorithm-driven sales, and information storing digital ledgers like blockchains in guiding the fortunes of the arts organization both during and beyond the phase of pandemics. The key message of the book is that art organizations will not be the same even after the COVID-19 pandemic. Arts organizations that have for long relied on the real world of exhibitions and performances will be tempted to straddle in both the real and virtual models. Their revenue earnings models will also be more diversified than at present, so would their reach to their customers. Further the advent of Non-Fungible Tokens (NFTs) based on blockchain platform Ethereum, it is argued, will turn democratize the world of creation, collection, and consumption thus nudging extant institutions to change their prevalent methods of doing business in arts works.
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Nolan, Jerry P. Advanced life support. Edited by Neil Soni and Jonathan G. Hardman. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0091.
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Anaesthetists have a central role in cardiopulmonary resuscitation (CPR). The incidence of treated out-of-hospital cardiopulmonary arrest is 40 per 100 000 population and is associated with a survival rate to hospital discharge of 8–10%. The incidence of in-hospital cardiac arrest (IHCA) is 1–5 per 1000 admissions and is associated with a survival rate to hospital discharge of 13–17%. The most effective strategy for reducing mortality from IHCA is to prevent it occurring by detecting and treating those at risk or to identify in advance those with no chance of survival and to make a decision not to attempt resuscitation. The European Resuscitation Council and the Resuscitation Council (UK) publish guidelines for CPR every 5 years and the evidence supporting these is described in the international consensus on CPR science. The advanced life support algorithm forms the core of the guidelines but the precise interventions depend on the circumstances of the cardiac arrest and the skills of the healthcare providers. High-quality CPR with minimal interruptions will optimize survival rates. Shockable rhythms are treated with defibrillation while minimizing the pause in chest compressions. Although adrenaline (epinephrine) is used in most cardiac arrests, no studies have shown that it improves long-term outcome. The post-cardiac arrest syndrome is common and requires multiple organ support in an intensive care unit. Therapy in this phase is aimed at improving neurological (e.g. targeted temperature management) and myocardial (e.g. percutaneous coronary intervention) outcomes. Based on standard outcome measurements (e.g. cerebral performance category), 75–80% of survivors will have a ‘good’ neurological outcome, but many of these will have subtle neurocognitive deficits.
Buchteile zum Thema "Phase-Based Algorithms"
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Dolly, Bably, and Deepa Raj. "Image Retrieval Based on Texture Using Local Binary Pattern and Local Phase Quantization." In Algorithms for Intelligent Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6307-6_7.
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Guo, Yahong, Jinbao Li, Longjiang Guo, Jinghua Zhu, and Xu Liu. "A Cache Based Multi-join Query Method with Two-Phase Processing in MANET." In Wireless Algorithms, Systems, and Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31869-6_39.
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Kojima, Kaname, Naoki Nariai, Takahiro Mimori, et al. "HapMonster: A Statistically Unified Approach for Variant Calling and Haplotyping Based on Phase-Informative Reads." In Algorithms for Computational Biology. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07953-0_9.
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Baumeister, Tom, Paul Eichler, Swen Jacobs, Mouhammad Sakr, and Marcus Völp. "Parameterized Verification of Round-Based Distributed Algorithms via Extended Threshold Automata." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-71162-6_33.
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AbstractThreshold automata are a computational model that has proven to be versatile in modeling threshold-based distributed algorithms and enabling their completely automatic parameterized verification. We present novel techniques for the verification of threshold automata, based on well-structured transition systems, that allow us to extend the expressiveness of both the computational model and the specifications that can be verified. In particular, we extend the model to allow decrements and resets of shared variables, possibly on cycles, and the specifications to general coverability. While these extensions of the model in general lead to undecidability, our algorithms provide a semi-decision procedure. We demonstrate the benefit of our extensions by showing that we can model complex round-based algorithms such as the phase king consensus algorithm and the Red Belly Blockchain protocol (published in 2019), and verify them fully automatically for the first time.
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Kapoor, Gaurav, Vikas Soni, and Jitendra Yadvendra. "Fast Walsh–Hadamard Transform-Based Artificial Intelligent Technique for Transmission Line Fault Detection and Faulty Phase Recognition." In Algorithms for Intelligent Systems. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1059-5_17.
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Wang, Jianrong, Haoran Sun, and Tianyi Xu. "Blockchain-Based Secure and Efficient Federated Learning with Three-phase Consensus and Unknown Device Selection." In Wireless Algorithms, Systems, and Applications. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19208-1_37.
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Scott, Jennifer, and Miroslav Tůma. "Sparse Matrix Ordering Algorithms." In Nečas Center Series. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-25820-6_8.
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AbstractSo far, our focus has been on the theoretical and algorithmic principles involved in sparse Gaussian elimination-based factorizations. To limit the storage and the work involved in the computation of the factors and in their use during the solve phase it is generally necessary to reorder (permute) the matrix before the factorization commences. The complexity of the most critical steps in the factorization is highly dependent on the amount of fill-in, as can be seen from the following observation.
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Jiang, Jian-guo, Shang Jiang, Bo-bai Zhao, Si-ye Wang, Meng-nan Cai, and Yan-fang Zhang. "CS-Dict: Accurate Indoor Localization with CSI Selective Amplitude and Phase Based Regularized Dictionary Learning." In Algorithms and Architectures for Parallel Processing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60239-0_46.
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Ouedrhiri, Oumayma, Oumayma Banouar, Salah El Hadaj, and Said Raghay. "A New Approach for Quantum Phase Estimation Based Algorithms for Machine Learning." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54376-0_13.
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Li, Shengqing, Haotian Feng, and Xi Deng. "Short-Term Wind Speed Prediction Based on Phase Space Reconstruction and Elman Network-Grey Wolf Optimization." In Smart Communications, Intelligent Algorithms and Interactive Methods. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5164-9_29.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Phase-Based Algorithms"
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Wang, Zheng, Hua Zhang, Jie Guo, Lihai Fan, Jinyu Chen, and Xia Chen. "Research and application of initial phase angle calibration technology for smart grids based on cloud platform." In International Conference on Algorithms, High Performance Computing and Artificial Intelligence, edited by Pavel Loskot and Liang Hu. SPIE, 2024. http://dx.doi.org/10.1117/12.3051454.
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Kumar, Siripurapu Pavan Dinesh, Bhagwan K. Murthy, and Aratipamula Bhanuchandar. "Implementation of Predictive Current Control Technique for a 1-Phase 5-Level Switched Capacitor-Based Grid-Connected Inverter." In 2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS). IEEE, 2024. http://dx.doi.org/10.1109/iacis61494.2024.10721969.
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Stanescu, Sorin Laurentiu, and Omonigho Benedict Otanocha. "Phase-based neuron training using evolutionary algorithms." In 2014 International Symposium on Fundamentals of Electrical Engineering (ISFEE). IEEE, 2014. http://dx.doi.org/10.1109/isfee.2014.7050633.
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Langer, M., P. Cloetens, J. P. Guigay, S. Valton, and F. Peyrin. "QUANTITATIVE EVALUATION OF PHASE RETRIEVAL ALGORITHMS IN PROPAGATION BASED PHASE TOMOGRAPHY." In 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro. IEEE, 2007. http://dx.doi.org/10.1109/isbi.2007.356911.
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Gómez-Pedrero, José A., D. Crespo, and Juan A. Quiroga. "Fourier-based design of asynchronous phase detection algorithms." In Optical Metrology, edited by Wolfgang Osten, Christophe Gorecki, and Erik L. Novak. SPIE, 2007. http://dx.doi.org/10.1117/12.725668.
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Vogel, Curtis R., Tony F. Chan, and Robert J. Plemmons. "Fast algorithms for phase-diversity-based blind deconvolution." In Astronomical Telescopes & Instrumentation, edited by Domenico Bonaccini and Robert K. Tyson. SPIE, 1998. http://dx.doi.org/10.1117/12.321720.
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Mahamdi, Célia, Jonathan Lejeune, Julien Sopena, Pierre Sens, and Mesaac Makpangou. "OMAHA: Opportunistic Message Aggregation for pHase-based Algorithms." In 2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC). IEEE, 2023. http://dx.doi.org/10.1109/prdc59308.2023.00027.
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Ouedrhiri, Oumayma, Oumayma Banouar, Salah El Hadaj, and Said Raghay. "Quantum phase estimation based algorithms for machine learning." In 2021 2nd International Informatics and Software Engineering Conference (IISEC). IEEE, 2021. http://dx.doi.org/10.1109/iisec54230.2021.9672406.
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Garren, David A. "Effects of region of interest selection on phase history based SAR moving target autofocus." In Algorithms for Synthetic Aperture Radar Imagery XXVI, edited by Edmund Zelnio and Frederick D. Garber. SPIE, 2019. http://dx.doi.org/10.1117/12.2518435.
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Jdanov, Vladimir, and Tatiana Sestacova. "Microprocessor Protection Relay Based on Amplitude-Phase Measurements of Signals." In 12th International Conference on Electronics, Communications and Computing. Technical University of Moldova, 2022. http://dx.doi.org/10.52326/ic-ecco.2022/el.05.
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Microprocessor-based relay protection devices enable efficient operation of the electrical infrastructure of high voltage power lines and substations under emergency conditions. This is achieved by using high-speed fault detection algorithms and advanced electronic components. The paper deals with the elaboration of a such algorithm which novelty lies in the fact that it is based on amplitude-phase measurements of asymmetrical components of current and voltage signals, which detects accidents with symmetrical and asymmetric overloads significantly faster. The algorithm is implemented in microprocessor protection in the LIRA device.
Berichte der Organisationen zum Thema "Phase-Based Algorithms"
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Cordeiro de Amorim, Renato. A survey on feature weighting based K-Means algorithms. Web of Open Science, 2020. http://dx.doi.org/10.37686/ser.v1i2.79.
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In a real-world data set there is always the possibility, rather high in our opinion, that different features may have different degrees of relevance. Most machine learning algorithms deal with this fact by either selecting or deselecting features in the data preprocessing phase. However, we maintain that even among relevant features there may be different degrees of relevance, and this should be taken into account during the clustering process. With over 50 years of history, K-Means is arguably the most popular partitional clustering algorithm there is. The first K-Means based clustering algorithm to compute feature weights was designed just over 30 years ago. Various such algorithms have been designed since but there has not been, to our knowledge, a survey integrating empirical evidence of cluster recovery ability, common flaws, and possible directions for future research. This paper elaborates on the concept of feature weighting and addresses these issues by critically analysing some of the most popular, or innovative, feature weighting mechanisms based in K-Means
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Borkman, Steve, Marlo Verdesca, and Jon Watkins. Algorithms for Ground Soldier Based Simulations and Decision Support Applications. Phase 1. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada560713.
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Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan, and Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010891.
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A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform lighting conditions. In the second part of the framework, the context-based segmentation is developed to eliminate regions from imagery that are not considered to be a threat to the pipeline. Context based segmentation makes use of a cascade of pre-trained classifiers to search for regions that are not threats. The context based segmentation algorithm accelerates threat identification and improves object detection rates. The last phase of the framework is an efficient object detection model. Efficient object detection �follows a three-stage approach which includes extraction of the local phase in the image and the use of local phase characteristics to locate machinery threats. The local phase is an image feature extraction technique which partially removes the lighting variance and preserves the edge information of the object. Multiple orientations of the same object are matched and the correct orientation is selected using feature matching by histogram of local phase in a multi-scale framework. The classifier outputs locations of threats to pipeline.�The advanced automatic image analysis system is intended to be capable of detecting construction equipment along the ROW of pipelines with a very high degree of accuracy in comparison with manual threat identification by a human analyst. �
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Blundell, S. User guide : the DEM Breakline and Differencing Analysis Tool—gridded elevation model analysis with a convenient graphical user interface. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45040.
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Gridded elevation models of the earth’s surface derived from airborne lidar data or other sources can provide qualitative and quantitative information about the terrain and its surface features through analysis of the local spatial variation in elevation. The DEM Breakline and Differencing Analysis Tool was developed to extract and display micro-terrain features and vegetative cover based on the numerical modeling of elevation discontinuities or breaklines (breaks-in-slope), slope, terrain ruggedness, local surface optima, and the local elevation difference between first surface and bare earth input models. Using numerical algorithms developed in-house at the U.S. Army Engineer Research and Development Center, Geospatial Research Laboratory, various parameters are calculated for each cell in the model matrix in an initial processing phase. The results are combined and thresholded by the user in different ways for display and analysis. A graphical user interface provides control of input models, processing, and display as color-mapped overlays. Output displays can be saved as images, and the overlay data can be saved as raster layers for input into geographic information systems for further analysis.
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Desa, Hazry, and Muhammad Azizi Azizan. OPTIMIZING STOCKPILE MANAGEMENT THROUGH DRONE MAPPING FOR VOLUMETRIC CALCULATION. Penerbit Universiti Malaysia Perlis, 2023. http://dx.doi.org/10.58915/techrpt2023.004.
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Stockpile volumetric calculation is an important aspect in many industries, including construction, mining, and agriculture. Accurate calculation of stockpile volumes is essential for efficient inventory management, logistics planning, and quality control. Traditionally, stockpile volumetric calculation is done using ground-based survey methods, which can be time-consuming, labour-intensive, and often inaccurate. However, with the recent advancements in drone technology, it has become possible to use drones for stockpile volumetric calculation, providing a faster, safer, and more accurate solution. The duration of this project is one year, from May 1st, 2019, until April 30th, 2020, and is comprised of two primary research components: analyzing the properties and classification of limestone and conducting digital aerial mapping to calculate stockpile volumetrics. The scope of this technical report is specifically limited to the aerial mapping aspect of the project, which was carried out using drones. The project involved two phases, with drone flights taking place during each phase, spaced about six months apart. The first drone flight for data collection occurred on July 12th, 2019, while the second took place on December 15th, 2020. The project aims to utilize drone technology for stockpile volumetric calculation, providing a more efficient and cost-effective solution. The project will involve the use of advanced drone sensors and imaging technology to capture high-resolution data of the stockpile area. The data will then be processed using sophisticated software algorithms to generate accurate 3D models and volumetric calculations of the stockpile.
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Kanagavel, Rameshkumar, and Indragandhi Vairavasundaram. FPGA Implementation and Investigation of Hybrid Artificial Bee Colony Algorithm-based Single Phase Shunt Active Filter. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2020. http://dx.doi.org/10.7546/crabs.2020.05.13.
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Puestow. L52194 Detection of Third Party Encroachment Using Satellite Based Remote Sensing Technologies. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0011045.
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Building on past experience, it was the objective of this investigation to automate the satellite-based detection of encroachment events, to improve target detection and reduce false alarms using radar and optical imagery and to investigate the integration of one-call services into the process flow. Algorithm development for target detection using optical imagery was carried out with the intention to facilitate the future integration of unmanned airborne vehicle (UAV) technology into the process. The capacity of the multitemporal algorithm was extended to enable the detection of area changes in addition to vehicle targets. The integration of existing notification services in the satellite-based approach was examined. A satellite-based encroachment monitoring system is now in place to undertake large-scale field demonstrations over 100 to 200 miles of right-of-way for a period of several months, preceded by a pre-service calibration phase of several weeks to adjust the procedures to local conditions. A constant false alarm rate between 5 and 10% can be achieved after a service period of 8 to 10 months.
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Morkun, Vladimir S., Natalia V. Morkun, and Andrey V. Pikilnyak. Augmented reality as a tool for visualization of ultrasound propagation in heterogeneous media based on the k-space method. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3757.
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For programming the AR tools, interactive objects and creating the markers, the method of fiber spaces (k-space) for modeling of ultrasonic wave propagation in an inhomogeneous medium using coarse grids, with maintaining the required accuracy was used. The algorithm and tools of augmented reality were introduced into the adaptive control system of the pulp gas phase in the iron ore flotation process using a control action on the basis of high-energy ultrasound dynamic effects generated by ultrasonic phased arrays. The tools of augmented reality based on k-space methods allow to facilitate wider adoption of ultrasound technology and visualize the ultra-sound propagation in heterogeneous media by providing a specific correspondence between the ultrasound data acquired in real- time and a sufficiently detailed augmented 3D scene. The tools of augmented reality allow seeing the field of ultrasound propagation, its characteristics, as well as the effect of the dynamic effects of ultrasound on the change in the gas phase during the flotation process.
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Radvand, Tina, and Alireza Talebpour. A Quantum Optimization Algorithm for Optimal Electric Vehicle Charging Station Placement for Intercity Trips. Illinois Center for Transportation, 2024. https://doi.org/10.36501/0197-9191/24-028.
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Electric vehicles (EVs) play a significant role in enhancing the sustainability of transportation systems. However, their widespread adoption is hindered by inadequate public charging infrastructure, particularly to support long-distance travel. Identifying optimal charging station locations in large transportation networks presents a well-known NP-hard combinatorial optimization problem, as the search space grows exponentially with the number of potential charging station locations. This report introduces a quantum search-based optimization algorithm designed to enhance the efficiency of solving this NP-hard problem for both corridors and transportation networks. By leveraging quantum parallelism, amplitude amplification, and quantum phase estimation as a subroutine, the optimal solution is identified with a quadratic improvement in complexity compared to classical exact methods, such as branch and bound. The detailed design and complexity of a resource-efficient quantum circuit are discussed.
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Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7585193.bard.
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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are obtained by manual sampling of the filed in a grid pattern. Maps of various field attributes are then prepared from these samples by the "Inverse Distance" interpolation method or by Kriging. An improved interpolation method was developed which is based on minimizing the overall curvature of the resulting map. Such maps are the ground truth reference, used for training the algorithm that generates the predicted field maps from remote sensing imagery. Both the reference and the predicted maps are stratified into "Prototype Plots", e.g. 15xl5 blocks of 2m pixels whereby the block size is 30x30m. This averaging reduces the datasets to manageable size and significantly improves the typically poor repeatability of remote sensing imaging systems. In the first two years of the project we used the Normalized Difference Vegetation Index (NDVI), for generating predicted yield maps of sugar beets and com. The NDVI was computed from image cubes of three spectral bands, generated by an optically filtered three camera video imaging system. A two dimensional FFT based regression model Y=f(X), was used wherein Y was the reference map and X=NDVI was the predictor. The FFT regression method applies the "Wavelet Based", "Pixel Block" and "Image Rotation" transforms to the reference and remote images, prior to the Fast - Fourier Transform (FFT) Regression method with the "Phase Lock" option. A complex domain based map Yfft is derived by least squares minimization between the amplitude matrices of X and Y, via the 2D FFT. For one time predictions, the phase matrix of Y is combined with the amplitude matrix ofYfft, whereby an improved predicted map Yplock is formed. Usually, the residuals of Y plock versus Y are about half of the values of Yfft versus Y. For long term predictions, the phase matrix of a "field mask" is combined with the amplitude matrices of the reference image Y and the predicted image Yfft. The field mask is a binary image of a pre-selected region of interest in X and Y. The resultant maps Ypref and Ypred aremodified versions of Y and Yfft respectively. The residuals of Ypred versus Ypref are even lower than the residuals of Yplock versus Y. The maps, Ypref and Ypred represent a close consensus of two independent imaging methods which "view" the same target. In the last two years of the project our remote sensing capability was expanded by addition of a CASI II airborne hyperspectral imaging system and an ASD hyperspectral radiometer. Unfortunately, the cross-noice and poor repeatability problem we had in multi-spectral imaging was exasperated in hyperspectral imaging. We have been able to overcome this problem by over-flying each field twice in rapid succession and developing the Repeatability Index (RI). The RI quantifies the repeatability of each spectral band in the hyperspectral image cube. Thereby, it is possible to select the bands of higher repeatability for inclusion in the prediction model while bands of low repeatability are excluded. Further segregation of high and low repeatability bands takes place in the prediction model algorithm, which is based on a combination of a "Genetic Algorithm" and Partial Least Squares", (PLS-GA). In summary, modus operandi was developed, for deriving important plant growth attribute maps (yield, leaf nitrate, biomass and sugar percent in beets), from remote sensing imagery, with sufficient accuracy for precision cropping applications. This achievement is remarkable, given the inherently high cross-noice between the reference and remote imagery as well as the highly non-repeatable nature of remote sensing systems. The above methodologies may be readily adopted by commercial companies, which specialize in proving remotely sensed data to farmers.