28 resultados para Network topology

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The new complex [Cu(NCS)(2)(pn)] (1) (pn = 1,3-propanediamine) has been synthesized and characterized by elemental analysis, infrared and electronic spectroscopy. Single crystal X-ray diffraction studies revealed that complex 1 is made up of neutral [Cu(NCS)(2)(pn)] units which are connected by mu-1,3,3-thiocyanato groups to yield a 2D metal-organic framework with a brick-wall network topology. Intermolecular hydrogen bonds of the type NH...SCN and NH...NCS are also responsible for the stabilization of the crystal structure. (c) 2007 Elsevier B.V. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This paper presents a mathematical model and a methodology to solve the transmission network expansion planning problem with security constraints in full competitive market, assuming that all generation programming plans present in the system operation are known. The methodology let us find an optimal transmission network expansion plan that allows the power system to operate adequately in each one of the generation programming plans specified in the full competitive market case, including a single contingency situation with generation rescheduling using the security (n-1) criterion. In this context, the centralized expansion planning with security constraints and the expansion planning in full competitive market are subsets of the proposal presented in this paper. The model provides a solution using a genetic algorithm designed to efficiently solve the reliable expansion planning in full competitive market. The results obtained for several known systems from the literature show the excellent performance of the proposed methodology.

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This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering uncertainty in demand and generation. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The model presented results in an optimization problem that is solved using a specialized genetic algorithm. The results obtained for known systems from the literature show that cheaper plans can be found satisfying the uncertainty in demand and generation. ©2008 IEEE.

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This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering open access. The methodology finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with multiples generation scenarios. The model presented is solved using a specialized genetic algorithm. The methodology is tested in a system from the literature. ©2008 IEEE.

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We consider the two-level network design problem with intermediate facilities. This problem consists of designing a minimum cost network respecting some requirements, usually described in terms of the network topology or in terms of a desired flow of commodities between source and destination vertices. Each selected link must receive one of two types of edge facilities and the connection of different edge facilities requires a costly and capacitated vertex facility. We propose a hybrid decomposition approach which heuristically obtains tentative solutions for the vertex facilities number and location and use these solutions to limit the computational burden of a branch-and-cut algorithm. We test our method on instances of the power system secondary distribution network design problem. The results show that the method is efficient both in terms of solution quality and computational times. © 2010 Elsevier Ltd.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Teaching a course of special electric loads in a continuing education program to power engineers is a difficult task because they are not familiarized with switching topology circuits. Normally, in a typical program, many hours are dedicated to explain the thyristors switching sequence and to draw the converter currents and terminal voltages waveforms for different operative conditions. This work presents teaching support software in order to optimize the time spent in this task and, mainly to benefit the assimilation of the proposed subjects, studying the static converter under different non-ideal operative conditions.

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This paper presents the analysis of a dc-ac converter using a zero-voltage-switching (ZVS) commutation cell. First, we show the cell applied to the buck converter. The stages of operation are presented along with the main current and voltage equations. Next, we adapt the converter to the regenerative-operation mode. Hence, the full-bridge converter at low-frequency operation is connected in the dc-dc output stage (at high frequency). The main switches commute at zero voltage. The converter operated at constant frequency with pulse-width modulation (PWM), and neither overvoltage nor additional current stress was observed by digital simulation. A design example and experimental results obtained by prototype, rated at 275 V and 1 kW, are also presented. © 1997 IEEE.

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The design of a Gilbert Cell Mixer and a low noise amplifier (LNA), using GaAs PHEMT technology is presented. The compatibility is shown for co-integration of both block on the same chip, to form a high performance 1.9 GHz receiver front-end. The designed LNA shows 9.23 dB gain and 2.01 dB noise figure (NF). The mixer is designed to operate at RF=1.9 GHz, LO=2.0 GHz and IF=100 MHz with a gain of 14.3 dB and single sideband noise figure (SSB NF) of 9.6 dB. The mixer presents a bandwith of 8 GHz.

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This work presents a new high power factor three-phase rectifier based on a Y-connected differential autotransformer with reduced kVA and 18-pulse input current followed by three DC-DC boost converters. The topology provides a regulated output voltage and natural three-phase input power factor correction. The lowest input current harmonic components are the 17th and the 19th. Three boost converters, with constant input currents and regulated parallel connected output voltages are used to process 4kW each one. Analytical results from Fourier analyses of winding currents and the vector diagram of winding voltages are presented. Simulation results to verify the proposed concept and experimental results are shown in the paper.