We studied the ultrafast response in metal-semiconductor-metal ultraviolet photodiodes fabricated on GaN. The best performance of a device with 1-/spl mu/m finger width and spacing showed a 3.5-ps response. The pulse ...
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ISBN:
(纸本)1557527776
We studied the ultrafast response in metal-semiconductor-metal ultraviolet photodiodes fabricated on GaN. The best performance of a device with 1-/spl mu/m finger width and spacing showed a 3.5-ps response. The pulse width broadened significantly as the optical energy increased.
In this work, we present and analyze the use of a reconfigurable job scheduling simulator called RJSSim as an aid tool for parallel processing learning. This software is a functional and performance Java-based simulat...
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Dynamic programming (DP) is a principled way to design optimal controllers for certain classes of nonlinear systems;unfortunately, DP is computationally very expensive. The Reinforcement Learning methods known as Adap...
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Dynamic programming (DP) is a principled way to design optimal controllers for certain classes of nonlinear systems;unfortunately, DP is computationally very expensive. The Reinforcement Learning methods known as Adaptive Critics (AC) provide computationally feasible means for performing approximate Dynamic programming (ADP). The term 'adaptive ' in A C refers to the critic 's improved estimations of the Value Function used by DP. To apply DP, the user must craft a Utility function that embodies all the problem-specific design specifications/criteria. Model Reference Adaptive Control methods have been successfully used in the control community to effect on-line redesign of a controller in response to variations in plant parameters, with the idea that the resulting closed loop system dynamics will mimic those of a Reference Model. The work reported here 1) uses a reference model in ADP as the key information input to the Utility function, and 2) uses ADP off-line to design the desired controller. Future work will extend this to on-line application. This method is demonstrated for a hypersonic shaped airplane called LoFL YTE®;its handling characteristics are natively a little "hotter" than a pilot would desire. A control augmentation subsystem is designed using ADP to make the plane "feel like " a better behaved one, as specified by a Reference Model. The number of inputs to the successfully designed controller are among the largest seen in the literature to date.
We present a functional and structural didactic simulator of Cache Memory Systems developed at the Pontifical Catholic University of Minas Gerais, Brazil. The development occurred during the undergraduate computer Arc...
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In this paper, we present LiQuID, a tool for clustering lighting simulation data. Photographs are useful vehicles for both describing and making assessments of architectural lighting systems. A significant barrier to ...
In this paper, we present LiQuID, a tool for clustering lighting simulation data. Photographs are useful vehicles for both describing and making assessments of architectural lighting systems. A significant barrier to using photographs during the design process relates to the sheer volume of renderings that needs to be analyzed. Although there have been efforts to produce novel visualization systems to manage large sets of photographs, this research aims to reduce the complexity by classifying data into representative prototypes. A hypothetical case study is discussed.
In this paper, we attempt to improve the performance in congested parts (CP) of an asymmetric network using network controls and routing mechanisms. Typically, an asymmetric network is characterized by non-uniform lin...
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In this paper, we attempt to improve the performance in congested parts (CP) of an asymmetric network using network controls and routing mechanisms. Typically, an asymmetric network is characterized by non-uniform link capacities or uneven traffic load or both. In such a network, certain service classes can experience poor performance in parts of the network, even when the average performance is very close to the expected performance level. We studied a network derived from an actual service provider network with asymmetric concentration of traffic. We have developed two metrics in order to capture the congested part behavior in a network. In order to understand the generality of our conclusions, we used three variations of our network and show that controls like service class based multi-link dynamic capacity reservation (SMDCR) with a properly chosen reservation factor, significantly reduce variability in the performance over all parts of the network.
The use of intelligent systems and machine learning methods, capable of automatic decision making based on already solved cases, and data mining, are getting more and more popular. Here we are faced not only with tech...
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The use of intelligent systems and machine learning methods, capable of automatic decision making based on already solved cases, and data mining, are getting more and more popular. Here we are faced not only with technical problems, but also with limited confidence in machine learning techniques. In some cases methods that may explicitly show the deduction process are not powerful enough. One of the possibilities is to modify/improve the methods so that the users could easily follow the process of decision making. To solve this problem, a few years ago we started to develop a platform, which enables us to develop, test and use different kinds of hybrid methods. These are meant to combine the advantages of the integrated methods-e.g., power and knowledge representation-that contribute to the quality of the acquired knowledge. In this paper we present a way of using the developed platform in order to obtain new knowledge, based on results from neurophysiological measurements We are every pleased with the performance of our intelligent platform. The first results we obtained already show some improvement in comparison to classic machine learning approaches.
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