83 research outputs found

    Multi-classifier classification of spam email on an ubiquitous multi-core architecture

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    This paper presents an innovative fusion based multi-classifier email classification on a ubiquitous multi-core architecture. Many approaches use text-based single classifiers or multiple weakly trained classifiers to identify spam messages from a large email corpus. We build upon our previous work on multi-core by apply our ubiquitous multi-core framework to run our fusion based multi-classifier architecture. By running each classifier process in parallel within their dedicated core, we greatly improve the performance of our proposed multi-classifier based filtering system. Our proposed architecture also provides a safeguard of user mailbox from different malicious attacks. Our experimental results show that we achieved an average of 30% speedup at the average cost of 1.4 ms. We also reduced the instance of false positive, which is one of the key challenges in spam filtering system, and increases email classification accuracy substantially compared with single classification techniques.<br /

    Output Effect Evaluation Based on Input Features in Neural Incremental Attribute Learning for Better Classification Performance

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    [[abstract]]Machine learning is a very important approach to pattern classification. This paper provides a better insight into Incremental Attribute Learning (IAL) with further analysis as to why it can exhibit better performance than conventional batch training. IAL is a novel supervised machine learning strategy, which gradually trains features in one or more chunks. Previous research showed that IAL can obtain lower classification error rates than a conventional batch training approach. Yet the reason for that is still not very clear. In this study, the feasibility of IAL is verified by mathematical approaches. Moreover, experimental results derived by IAL neural networks on benchmarks also confirm the mathematical validation.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]電子

    RFID ownership transfer with positive secrecy capacity channels

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    RFID ownership transfer protocols (OTPs) transfer tag ownership rights. Recently, there has been considerable interest in such protocols, however, guaranteeing privacy for symmetric-key settings without trusted third parties (TTPs) is a challenge still unresolved. In this paper, we address this issue and show that it can be solved by using channels with positive secrecy capacity. We implement these channels with noisy tags and provide practical values, thus proving that perfect secrecy is theoretically possible. We then define a communication model that captures spatiotemporal events and describe a first example of symmetric-key based OTP that: (i) is formally secure in the proposed communication model and (ii) achieves privacy with a noisy tag wiretap channel without TTPs

    Performance of management solutions and cooperation approaches for vehicular delay-tolerant networks

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    A wide range of daily-life applications supported by vehicular networks attracted the interest, not only from the research community, but also from governments and the automotive industry. For example, they can be used to enable services that assist drivers on the roads (e.g., road safety, traffic monitoring), to spread commercial and entertainment contents (e.g., publicity), or to enable communications on remote or rural regions where it is not possible to have a common network infrastructure. Nonetheless, the unique properties of vehicular networks raise several challenges that greatly impact the deployment of these networks. Most of the challenges faced by vehicular networks arise from the highly dynamic network topology, which leads to short and sporadic contact opportunities, disruption, variable node density, and intermittent connectivity. This situation makes data dissemination an interesting research topic within the vehicular networking area, which is addressed by this study. The work described along this thesis is motivated by the need to propose new solutions to deal with data dissemination problems in vehicular networking focusing on vehicular delay-tolerant networks (VDTNs). To guarantee the success of data dissemination in vehicular networks scenarios it is important to ensure that network nodes cooperate with each other. However, it is not possible to ensure a fully cooperative scenario. This situation makes vehicular networks suitable to the presence of selfish and misbehavior nodes, which may result in a significant decrease of the overall network performance. Thus, cooperative nodes may suffer from the overwhelming load of services from other nodes, which comprises their performance. Trying to solve some of these problems, this thesis presents several proposals and studies on the impact of cooperation, monitoring, and management strategies on the network performance of the VDTN architecture. The main goal of these proposals is to enhance the network performance. In particular, cooperation and management approaches are exploited to improve and optimize the use of network resources. It is demonstrated the performance gains attainable in a VDTN through both types of approaches, not only in terms of bundle delivery probability, but also in terms of wasted resources. The results and achievements observed on this research work are intended to contribute to the advance of the state-of-the-art on methods and strategies for overcome the challenges that arise from the unique characteristics and conceptual design of vehicular networks.O vasto número de aplicações e cenários suportados pelas redes veiculares faz com que estas atraiam o interesse não só da comunidade científica, mas também dos governos e da indústria automóvel. A título de exemplo, estas podem ser usadas para a implementação de serviços e aplicações que podem ajudar os condutores dos veículos a tomar decisões nas estradas, para a disseminação de conteúdos publicitários, ou ainda, para permitir que existam comunicações em zonas rurais ou remotas onde não é possível ter uma infraestrutura de rede convencional. Contudo, as propriedades únicas das redes veiculares fazem com que seja necessário ultrapassar um conjunto de desafios que têm grande impacto na sua aplicabilidade. A maioria dos desafios que as redes veiculares enfrentam advêm da grande mobilidade dos veículos e da topologia de rede que está em constante mutação. Esta situação faz com que este tipo de rede seja suscetível de disrupção, que as oportunidades de contacto sejam escassas e de curta duração, e que a ligação seja intermitente. Fruto destas adversidades, a disseminação dos dados torna-se um tópico de investigação bastante promissor na área das redes veiculares e por esta mesma razão é abordada neste trabalho de investigação. O trabalho descrito nesta tese é motivado pela necessidade de propor novas abordagens para lidar com os problemas inerentes à disseminação dos dados em ambientes veiculares. Para garantir o sucesso da disseminação dos dados em ambientes veiculares é importante que este tipo de redes garanta a cooperação entre os nós da rede. Contudo, neste tipo de ambientes não é possível garantir um cenário totalmente cooperativo. Este cenário faz com que as redes veiculares sejam suscetíveis à presença de nós não cooperativos que comprometem seriamente o desempenho global da rede. Por outro lado, os nós cooperativos podem ver o seu desempenho comprometido por causa da sobrecarga de serviços que poderão suportar. Para tentar resolver alguns destes problemas, esta tese apresenta várias propostas e estudos sobre o impacto de estratégias de cooperação, monitorização e gestão de rede no desempenho das redes veiculares com ligações intermitentes (Vehicular Delay-Tolerant Networks - VDTNs). O objetivo das propostas apresentadas nesta tese é melhorar o desempenho global da rede. Em particular, as estratégias de cooperação e gestão de rede são exploradas para melhorar e optimizar o uso dos recursos da rede. Ficou demonstrado que o uso deste tipo de estratégias e metodologias contribui para um aumento significativo do desempenho da rede, não só em termos de agregados de pacotes (“bundles”) entregues, mas também na diminuição do volume de recursos desperdiçados. Os resultados observados neste trabalho procuram contribuir para o avanço do estado da arte em métodos e estratégias que visam ultrapassar alguns dos desafios que advêm das propriedades e desenho conceptual das redes veiculares

    A framework for active software engineering ontology

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    The passive structure of ontologies results in the ineffectiveness to access and manage the knowledge captured in them. This research has developed a framework for active Software Engineering Ontology based on a multi-agent system. It assists software development teams to effectively access, manage and share software engineering knowledge as well as project information to enable effective and efficient communication and coordination among teams. The framework has been evaluated through the prototype system as proof-of-concept experiments

    Evolutionary Computation 2020

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    Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms

    Emerging Converter Topologies and Control for Grid Connected Photovoltaic Systems

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    Continuous cost reduction of photovoltaic (PV) systems and the rise of power auctions resulted in the establishment of PV power not only as a green energy source but also as a cost-effective solution to the electricity generation market. Various commercial solutions for grid-connected PV systems are available at any power level, ranging from multi-megawatt utility-scale solar farms to sub-kilowatt residential PV installations. Compared to utility-scale systems, the feasibility of small-scale residential PV installations is still limited by existing technologies that have not yet properly address issues like operation in weak grids, opaque and partial shading, etc. New market drivers such as warranty improvement to match the PV module lifespan, operation voltage range extension for application flexibility, and embedded energy storage for load shifting have again put small-scale PV systems in the spotlight. This Special Issue collects the latest developments in the field of power electronic converter topologies, control, design, and optimization for better energy yield, power conversion efficiency, reliability, and longer lifetime of the small-scale PV systems. This Special Issue will serve as a reference and update for academics, researchers, and practicing engineers to inspire new research and developments that pave the way for next-generation PV systems for residential and small commercial applications
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