83 research outputs found
Multi-classifier classification of spam email on an ubiquitous multi-core architecture
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
[[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
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
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
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
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
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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Performance analysis and improvement of InfiniBand networks. Modelling and effective Quality-of-Service mechanisms for interconnection networks in cluster computing systems.
The InfiniBand Architecture (IBA) network has been proposed as a new
industrial standard with high-bandwidth and low-latency suitable for constructing
high-performance interconnected cluster computing systems. This architecture
replaces the traditional bus-based interconnection with a switch-based network for
the server Input-Output (I/O) and inter-processor communications. The efficient
Quality-of-Service (QoS) mechanism is fundamental to ensure the import at QoS
metrics, such as maximum throughput and minimum latency, leaving aside other
aspects like guarantee to reduce the delay, blocking probability, and mean queue
length, etc.
Performance modelling and analysis has been and continues to be of great
theoretical and practical importance in the design and development of
communication networks. This thesis aims to investigate efficient and cost-effective
QoS mechanisms for performance analysis and improvement of InfiniBand
networks in cluster-based computing systems.
Firstly, a rate-based source-response link-by-link admission and congestion
control function with improved Explicit Congestion Notification (ECN) packet
marking scheme is developed. This function adopts the rate control to reduce
congestion of multiple-class traffic. Secondly, a credit-based flow control scheme is
presented to reduce the mean queue length, throughput and response time of the system. In order to evaluate the performance of this scheme, a new queueing
network model is developed. Theoretical analysis and simulation experiments show
that these two schemes are quite effective and suitable for InfiniBand networks.
Finally, to obtain a thorough and deep understanding of the performance attributes
of InfiniBand Architecture network, two efficient threshold function flow control
mechanisms are proposed to enhance the QoS of InfiniBand networks; one is Entry
Threshold that sets the threshold for each entry in the arbitration table, and other is
Arrival Job Threshold that sets the threshold based on the number of jobs in each
Virtual Lane. Furthermore, the principle of Maximum Entropy is adopted to analyse
these two new mechanisms with the Generalized Exponential (GE)-Type
distribution for modelling the inter-arrival times and service times of the input traffic.
Extensive simulation experiments are conducted to validate the accuracy of the
analytical models
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