This paper describes a multiple-view meta-modeling approach for managing variability in software product lines using the Unified Modeling Language notation (UML). A multiple-view meta-model for software product lines ...
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THEMIS (Threat Evaluation Metamodel for Information Systems) is a description logic-based framework to apply state, federal, and international law to reason about the intent of computer network attacks with respect to...
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Concurrent accesses to a file frequently occur in a distributed computing environment where a few number of network-attached servers are designated as a data storage pool and the clients are physically connected to th...
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Experimental studies have observed synaptic potentiation when a presynaptic neuron fires shortly before a postsynaptic neuron, and synaptic depression when the presynaptic neuron fires shortly after. The dependence of...
Experimental studies have observed synaptic potentiation when a presynaptic neuron fires shortly before a postsynaptic neuron, and synaptic depression when the presynaptic neuron fires shortly after. The dependence of synaptic modulation on the precise timing of the two action potentials is known as spike-timing dependent plasticity or STDP. We derive STDP from a simple computational principle: synapses adapt so as to minimize the postsynaptic neuron's variability to a given presynaptic input, causing the neuron's output to become more reliable in the face of noise. Using an entropy-minimization objective function and the biophysically realistic spike-response model of Gerstner (2001), we simulate neurophysiological experiments and obtain the characteristic STDP curve along with other phenomena including the reduction in synaptic plasticity as synaptic efficacy increases. We compare our account to other efforts to derive STDP from computational principles, and argue that our account provides the most comprehensive coverage of the phenomena. Thus, reliability of neural response in the face of noise may be a key goal of cortical adaptation.
We present a comparison of four optical flow methods and three spatio-temporal filters for mobile robot navigation in corridor-like environments. Previous comparisons of optical flow methods have evaluated performance...
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We present a comparison of four optical flow methods and three spatio-temporal filters for mobile robot navigation in corridor-like environments. Previous comparisons of optical flow methods have evaluated performance only in terms of accuracy and/or efficiency, and typically in isolation. These comparisons are inadequate for addressing applicability to continuous, real-time operation as part of a robot control loop. We emphasise the need for comparisons that consider the context of a system, and that are confirmed by in-system results. To this end, we give results for on and off-board trials of two biologically inspired behaviours: corridor centring and visual odometry. Our results show the best in-system performances are achieved using Lucas and Kanade's gradient-based method in combination with a recursive temporal filter. Results for traditionally used Gaussian filters indicate that long latencies significantly impede performance for real-time tasks in the control loop.
UML is a good tool to represent ontologies. When using UML for Ontology development, one of the principal goals is to assure the quality of ontologies. UML class diagrams provide a static modeling capability that is w...
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ISBN:
(纸本)0769521185
UML is a good tool to represent ontologies. When using UML for Ontology development, one of the principal goals is to assure the quality of ontologies. UML class diagrams provide a static modeling capability that is well suited for representing ontologies, so the structural complexity of a UML class diagram is one of the most important measures to evaluate the quality of the ontologies. This paper uses weighted class dependence graphs to represent a given class diagrams, and then presents a structure complexity measure for the UML class diagrams based on entropy distance. It considers complexity of both classes and relationships between the classes, and presents rules for transforming complexity value of classes and different lands of relations into a weighted class dependence graphs. This method can measure the structure complexity of class diagrams objectively.
In this paper, we present an adaptive security model that aims at securing resources in heterogeneous networks. Traditional security model usually work according to a static decision-making approach. However, we may e...
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This paper makes two contributions to the study of configuring real-time aspects into quality of service (QoS)-enabled component middleware for distributed real-time and embedded (DRE) systems. First, it compares and ...
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Recently, Web services have become a new technology trend for Enterprise Application Integration (EAI) and more and more applications based on Web services are emerging. One of the problems in using Web services in bu...
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ISBN:
(纸本)0769521673
Recently, Web services have become a new technology trend for Enterprise Application Integration (EAI) and more and more applications based on Web services are emerging. One of the problems in using Web services in business applications such as logistics is services composition automatically and efficiently. In this paper, we present a Dynamic, Demand-Driven Web services Engine called D3D-Serv to implement composite service functionality that is used to dynamically build composite services from existing services according to different business logics and requirements. In this D3D_Serv framework, the most challenging function to implement is dynamic selection of service providers at run time. The highly dynamic and distributed nature of Web services often makes some service providers overloaded at certain times while others idle. To solve this problem, we propose an efficient services selection and execution strategy that is based on the queuing theory and can provide guarantees for the QOS (Quality of Service) under provider's limited resources. Preliminary experimental results have shown that this algorithm is effective.
Artificial immune systems (AISs) are biologically inspired problem solvers that have been used successfully as intrusion detection systems (IDSs). In this paper we compare a genetic hacker with 12 evolutionary hackers...
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Artificial immune systems (AISs) are biologically inspired problem solvers that have been used successfully as intrusion detection systems (IDSs). In this paper we compare a genetic hacker with 12 evolutionary hackers based on particle swarm optimization (PSO) that have been effectively used as vulnerability analyzers (red teams) for AIS-based IDSs. Our results show that the PSO-based red teams that use Clerc's constriction coefficient outperform those that do not. Our results also show that the three types of red teams (genetic, basic PSO, and PSO with the constriction coefficient) have distinct search behaviors that are complimentary. This result suggests that red teams based on genetic swarms may hold the most promise.
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