In this paper, the study of thermal CVD grown CNT field emitters in a triode amplifier configuration is reported. The DC characteristics of the CNT triode are investigated, including I/sub a/ vs. V/sub a/ for differen...
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In this paper, the study of thermal CVD grown CNT field emitters in a triode amplifier configuration is reported. The DC characteristics of the CNT triode are investigated, including I/sub a/ vs. V/sub a/ for different V/sub g/. Moreover, DC parameters such as transconductance, amplification factor and anode resistance of the triode amplifier are determined. It was shown that a higher amplification factor can be achieved with optimum gate-anode-cathode spacing such that the cathode is effectively shielded from the anode by the gate but the anode still collects all electrons emitted from the cathode. High emission current at low gate voltage is key to achieving high transconductance. This can be obtained by optimum configuration of high-density CNTs array in a triode structure with a common gate.
We start from a case study of an architecture company and move on to a framework of agents to identify and inform conceptual design. The processes and problems exhibited by the company involved are quite common and ca...
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We start from a case study of an architecture company and move on to a framework of agents to identify and inform conceptual design. The processes and problems exhibited by the company involved are quite common and can be found in other similar companies. Our intent is to instrument the current process using agent technology, in an effort to improve global awareness during the conceptual design phase, allowing the designers to design so as to facilitate later steps and optimize the process as a whole.
Many new services have emerged to realize ubiquitous computing environments, owing to the increasing supply of mobile devices and more widespread Internet and wireless network facilities. We introduce the U-Campus (ub...
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ISBN:
(纸本)0769521231
Many new services have emerged to realize ubiquitous computing environments, owing to the increasing supply of mobile devices and more widespread Internet and wireless network facilities. We introduce the U-Campus (ubiquitous computing for campus) service. This study has been conducted through interdisciplinary research by four participating departments. The U-campus project is part of the UTOPIA project (Ubiquitous computing TOwn Project: Intelligent context Awareness), which covers town- and city-wide environments. Currently, a test bed for U-campus has been constructed to support various services suck as U-profile, U-messaging and U-campus tour guide services. Students, professors, school staffs, and campus visitors can easily access the various available campus services by using image-based sensors and mobile devices such as CDMA cellular phones or WiFi smart phones. The major purpose of this research is to provide a context-aware U-campus environment to users by utilizing sensors and mobile devices currently available in the public sector and the marketplace.
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 undergraduatecomputer Arc...
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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 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).
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.
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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