We obtain recombination rate distribution functions for all human chromosomes using an optimal quantization method. This nonparametric method allows us to control over-/under-fitting. The piece-wise constant recombina...
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We obtain recombination rate distribution functions for all human chromosomes using an optimal quantization method. This nonparametric method allows us to control over-/under-fitting. The piece-wise constant recombination rate distribution functions are convenient to store and retrieve. Our experimental results showed more abrupt distribution functions than two recently published results. In the previous results, the over-/under-fitting issues were not addressed explicitly. Our estimation had greater log likelihood over a previous result using Parzen window. It suggests that the optimal quantization technique might be of great advantage for estimation of other genomic feature distributions.
This paper proposes the development of a fuzzy predictive control. Genetic algorithms (GA's) are used to automatically tune the controller. A recurrent neural network is used to identify the process, and then prov...
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This paper proposes the development of a fuzzy predictive control. Genetic algorithms (GA's) are used to automatically tune the controller. A recurrent neural network is used to identify the process, and then provides predictions about the process behavior, based on control actions applied to the system. These predictions are used by the fuzzy controller, in order to accomplish a better control of an alcoholic fermentation process from chemical industry. This problem has been chosen due to its non-linearity and large accommodation time, that make it hard to control by standard controllers. Comparison of performance is made with non-predictive approaches(PID and Fuzzy-PD), and also with another predictive approach, GPC(Generalized Predictive Control).
In general, two types of resource reservations in computer networks can be distinguished: immediate reservations which are made in a just-in-time manner and advance reservations which allow to reserve resources a long...
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In general, two types of resource reservations in computer networks can be distinguished: immediate reservations which are made in a just-in-time manner and advance reservations which allow to reserve resources a long time before they are actually used. Advance reservations are especially useful for grid computing but also for a variety of other applications that require network quality-of-service, such as content distribution networks or even mobile clients, which need advance reservation to support handovers for streaming video. With the emerged MPLS standard, explicit routing can be implemented also in IP networks, thus overcoming the unpredictable routing behavior which so far prevented the implementation of advance reservation services. The impact of such advance reservation mechanisms on the performance of the network with respect to the amount of admitted requests and the allocated bandwidth has so far not been examined in detail. We show that advance reservations can lead to a reduced performance of the network with respect to both metrics. The analysis of the reasons shows a fragmentation of the network resources. In advance reservation environments, additional new services can be defined such as malleable reservations and can lead to an increased performance of the network. Four strategies for scheduling malleable reservations are presented and compared. The results of the comparisons show that some strategies increase the resource fragmentation and are therefore unsuitable in the considered environment while others lead to a significantly better performance of the network. Besides discussing the performance issue, the software architecture of a management system for advance reservations is presented.
Traditional security systems are not easily scalable and can become single points of failure or performance bottlenecks when used on a large-scale distributed system such as the Internet. This problem occurs also when...
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Traditional security systems are not easily scalable and can become single points of failure or performance bottlenecks when used on a large-scale distributed system such as the Internet. This problem occurs also when using a public key infrastructure (PKI) with a hierarchical thrust model. SDSI/SPKI is a PKI that adopts a more scalable trust paradigm, which is focused on the client and based on authorization chains. However, the task of locating the chain that links a client to a server is not completely addressed by SDSI/SPKI. Aiming to overcome this limitation, the paper proposes extensions to the SDSI/SPKI authorization and authentication model. The proposed approach introduces the concept of Federation Webs, which allows the client to build new authorization chains linking it to a server when a direct path does not exist. A prototype implementation of this proposal has shown promising results.
This work presents a methodology to develop autonomous agents for network management. There are two kinds of agents to develop: static or dynamic agents. The first one can be implemented;using heuristics obtained from...
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ISBN:
(纸本)0889863474
This work presents a methodology to develop autonomous agents for network management. There are two kinds of agents to develop: static or dynamic agents. The first one can be implemented;using heuristics obtained from an expert or the network administrator, through production rules or feed forward neural networks (NN). Using the network examples we can construct dynamic agents. The NN may be trained to solve a problem using some examples. Moreover, the behavior of the management must be considered, the network management may be reactive or proactive. Normally, we have the reactive behavior when the problem occurs and after we will search for a solution. We may see in diagnostic or troubleticket systems for Fault Management. On the contrary, the proactive behavior is a preventive control of the network. We divided the network management in the five functional areas proposed by OSI Model Reference. Thus, each area has a different intelligent solution.
The objective of this study is to propose a project management model which includes the unified process (UP) and UML language, for e-business software development in a physically distributed environment. The research ...
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The objective of this study is to propose a project management model which includes the unified process (UP) and UML language, for e-business software development in a physically distributed environment. The research is a qualitative study, aiming to develop methods and models. The main research method is the case study, according to Yin (1992). Initial results point towards a model, which includes the spiral life cycle type, the development process of object-oriented systems (using UML specification language and the unified process as proposed by RUP), and the incorporation of the procedural approach proposed by PMBOK (2000). The proposed model is divided into 6 phases, where each one of these phases contains a set of associated activities. In the future, the intention is to develop a support software for the model and apply this software into the environment in study. This extremely important study line demonstrates that the business world and business practices in the software development area are moving ahead of existent theories and conceptual models in this area. This study, yet in its initial phases, starts to bring significant results that contribute to meet market expectations nowadays.
High dimensional inputs coupled with scarcity of labeled data are among the greatest challenges for classification of hyperspectral data. These problems are exacerbated if the number of classes is large. High dimensio...
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High dimensional inputs coupled with scarcity of labeled data are among the greatest challenges for classification of hyperspectral data. These problems are exacerbated if the number of classes is large. High dimensional output classes can often be handled effectively by decomposition into multiple two-(meta)class problems, where each sub-problem is solved using a suitable binary classifier, and outputs of this collection of classifiers are combined in a suitable manner to obtain the answer to the original multi-class problem. This approach is taken by the binary hierarchical classifier (BHC). The advantages of the BHC for output decomposition can be further exploited for hyperspectral data analysis by integrating a feature selection methodology with the classifier. Building upon the previously developed best bases BHC algorithm with greedy feature selection, a new method is developed that selects a subset of band groups within metaclasses using reactive tabu search. Experimental results obtained from analysis of Hyperion data acquired over the Okavango Delta in Botswana are superior to those of the greedy feature selection approach and more robust than either the original BHC or the BHC with greedy feature selection.
In this paper we analyze the use of research activities as learning instrument in electrical engineering and computer science. This pedagogic approach was applied in undergraduate disciplines, undergraduate teaching a...
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In this paper we analyze the use of research activities as learning instrument in electrical engineering and computer science. This pedagogic approach was applied in undergraduate disciplines, undergraduate teaching assistance and undergraduate research projects. Our main goals are optimize the learning process using research and motivate the use of research activities as learning instrument.
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