Designing open and distributed systems that can dynamically adapt in a predictable way to unexpected events is a challenging issue still not solved. Achieving this objective is a very complex task since it implies rea...
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ISBN:
(纸本)1595934804
Designing open and distributed systems that can dynamically adapt in a predictable way to unexpected events is a challenging issue still not solved. Achieving this objective is a very complex task since it implies reasoning at run-time, explicitly and in a combined way, on a system's functional and non-functional characteristics. This paper proposes a service-oriented architectural model allowing the dynamic enforcement of formally expressed metadata-based resilience policies. It also describes preliminary dynamic resilience experiments acting as proof of concept. Copyright 2007 ACM.
Negaid is posed as a plugin of a legal expert system shell, eGanges, which provides negotiation support for conflict prevention applications. A cohabitation contract application that uses an ontology of potential conf...
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ISBN:
(纸本)1595936807
Negaid is posed as a plugin of a legal expert system shell, eGanges, which provides negotiation support for conflict prevention applications. A cohabitation contract application that uses an ontology of potential conflict demonstrates the negotiation logic of the expert system as seamless with the Negaid algorithm, a revised version of the Family Winner algorithm. The new negotiation algorithm incorporates the use and reuse of the cohabitation contract application until a list of differences can be identified for resolution as a matter of compromise. The list is then subjected to the Negaid algorithm, which assists in the negotiation process by suggesting trade-offs. Copyright 2007 ACM.
With the development of Natural Language Processing (NLP), more and more systems want to adopt NLP in User Interface Module to process user input, in order to communicate with user in a natural way. However, this rais...
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ISBN:
(纸本)9781601320254
With the development of Natural Language Processing (NLP), more and more systems want to adopt NLP in User Interface Module to process user input, in order to communicate with user in a natural way. However, this raises a speed problem. That is, if NLP module can not process sentences in durable time delay, users will never use the system. As a result, systems which are strict with processing time, such as dialogue systems, web search systems, automatic customer service systems, especially real-time systems, have to abandon NLP module in order to get a faster system response. This paper aims to solve the speed problem. In this paper, at first, the construction of a syntactic parser which is based on corpus machine learning and statistics model is introduced, and then a speed problem analysis is performed on the parser and its algorithms. Based on the analysis, two accelerating methods, Compressed POS Set and Syntactic Patterns Pruning, are proposed, which can effectively improve the time efficiency of parsing in NLP module. To evaluate different parameters in the accelerating algorithms, two new factors, PT and RT, are introduced and explained in detail. Experiments are also completed to prove and test these methods, which will surely contribute to the application of NLP.
We consider a parallel method for solving generalized eigen-value problems that arise from molecular orbital computations. We use a moment-based method that finds several eigenvalues and their corresponding eigenvecto...
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Today there is a large movement towards creating social and cognitive robots. Today there is research aiming at using robots as care support as well as social agents introduced in geriatric care and home care. Much of...
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Today there is a large movement towards creating social and cognitive robots. Today there is research aiming at using robots as care support as well as social agents introduced in geriatric care and home care. Much of the research is aimed at the development of cognitive and social agents, since robot agents are considered to need ways of interacting with the people in the surrounding areas. In this perspective it is necessary to start thinking of robots not only in terms of social, cognitive or sociable, but also of socially acceptable. What are the requirements for a socially acceptable robot, and which properties in a robot provide for making it more or less acceptable as part of a social environment? In this paper a set of tentative acceptance properties is presented, together with the results from a pilot study trying to assess the importance of some of these properties for the social acceptance of domestic service robots.
A proper behaviour of a robot is probably of importance when we consider the possibility of having it accepted by people. For example, it has been shown that erratic or unexplained behaviour tends to be a cause of dis...
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A proper behaviour of a robot is probably of importance when we consider the possibility of having it accepted by people. For example, it has been shown that erratic or unexplained behaviour tends to be a cause of distrust in the robot. There are several other, more non-technical issues that need to be fulfilled by the robot in order to make it acceptable in society. Even for cognitive, intelligent and largely autonomous robots their tasks need to be modelled. One such task modelling method, task patterns, has been proposed earlier as a language for describing robot activities. In this article it is suggested that the task pattern language can be extended through a framework based on the ideas behind Design Patterns, to also incorporate modelling of task properties that are important to the acceptance of a robot in a social environment.
Decision trees (DTs) provide an attractive classification scheme because clinicians responsible for making reliable decisions can easily interpret them. Bayesian averaging over DTs allows clinicians to evaluate the cl...
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Decision trees (DTs) provide an attractive classification scheme because clinicians responsible for making reliable decisions can easily interpret them. Bayesian averaging over DTs allows clinicians to evaluate the class posterior distribution and therefore to estimate the risk of making misleading decisions. The use of Markov chain Monte Carlo (MCMC) methodology of stochastic sampling makes the Bayesian DT technique feasible to perform. The Reversible Jump (RJ) extension of MCMC allows sampling from DTs of different sizes. However, the RJ MCMC process may become stuck in a particular DT far away from the region with maximal posterior. This negative effect can be mitigated by averaging the DTs obtained in different starts. In this paper we describe a new approach based on an adaptive sampling scheme. The performances of Bayesian DT techniques with the restarting and adaptive strategies are compared on a synthetic dataset as well as on some medical datasets. By quantitatively evaluating the classification uncertainty, we found that the adaptive strategy is superior to the restarting strategy.
Regular wireless sensor networks gain more and more attention because they can help to save energy and achieve longer network lifetime. In this paper, the popular hexagonal sensor network is focused and some new energ...
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Regular wireless sensor networks gain more and more attention because they can help to save energy and achieve longer network lifetime. In this paper, the popular hexagonal sensor network is focused and some new energy efficient routing algorithms are proposed based on a new addressing scheme. Performance of the new algorithms is compared by simulation. The results show the tree based routing algorithm achieves the best performance since it can distribute the traffic more evenly in the whole networks.
Teachers working in robotics classes face a major problem: how to keep track on individual students' or even small groups' progress in a class of 30-40 students. A multi-agent environment to help teachers with...
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Teachers working in robotics classes face a major problem: how to keep track on individual students' or even small groups' progress in a class of 30-40 students. A multi-agent environment to help teachers with this problem is based on having pedagogical agents to monitor students' interaction, robots' movements, and the construction and programming process of robots. Mobile interaction agents move in local area network delivering other agents' observations to teacher's visualization agent. The implemented prototype system has revealed the strengths and the weakness of the proposed architecture.
The mechanics of seventy-two different Java refactorings are described fully in Fowler's text. In the same text, Fowler describes seven categories of refactoring, into which each of the seventy-two refactorings ca...
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The mechanics of seventy-two different Java refactorings are described fully in Fowler's text. In the same text, Fowler describes seven categories of refactoring, into which each of the seventy-two refactorings can be placed. A current research problem in the refactoring and XP community is assessing the likely time and testing effort for each refactoring, since any single refactoring may use any number of other refactorings as part of its mechanics and, in turn, can be used by many other refactorings. In this paper, we draw on a dependency analysis carried out as part of our research in which we identify the 'Use' and 'Used By' relationships of refactorings in all seven categories. We offer reasons why refactorings in the 'Dealing with Generalisation' category seem to embrace two distinct refactoring sub-categories and how refactorings in the 'Moving Features between Objects' category also exhibit specific characteristics. In a wider sense, our meta-analysis provides a developer with concrete guidelines on which refactorings, due to their explicit dependencies, will prove problematic from an effort and testing perspective.
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