Centralized approaches to Network Management have demonstrated a clear inadequacy for efficient management of large and heterogeneous computer networks. Considerable research is being carried out on decentralized appr...
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We report an observation of essentially full spatial coherence in a high average power soft-x-ray laser. Rapid coherence buildup due to strong refractive antiguiding in a long plasma column is experimentally demonstra...
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We report an observation of essentially full spatial coherence in a high average power soft-x-ray laser. Rapid coherence buildup due to strong refractive antiguiding in a long plasma column is experimentally demonstrated. This allows the generation of fully coherent, milliwatt-level average power soft-x-ray radiation by a tabletop device. The peak brightness of this laser reaches 2×1025photonss−1mm−2mrad−2 within 0.01% spectral bandwidth, making it one of the brightest soft-x-ray sources available.
We present the fuzzy Bayes predictor (FBP), a hybrid system for the task of monthly electric load forecasting. The FBP is a modification we introduce in the naive Bayes classifier in order to enable it to predict nume...
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ISBN:
(纸本)0780370449
We present the fuzzy Bayes predictor (FBP), a hybrid system for the task of monthly electric load forecasting. The FBP is a modification we introduce in the naive Bayes classifier in order to enable it to predict numerical values. We consider three versions of the FBP, each one with a different dependence among the input data: independence, first-order and second-order dependence. For verifying the efficiency of the FBP's prediction, we compare it with two fuzzy systems and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.
We have proposed for the task of hourly electric load forecasting a hybrid neural system combining unsupervised and supervised learning. The system consists of a recurrent neural gas (RNG) network and many Elman neura...
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We have proposed for the task of hourly electric load forecasting a hybrid neural system combining unsupervised and supervised learning. The system consists of a recurrent neural gas (RNG) network and many Elman neural networks (ENs). RNG is a modification we introduced in the neural gas (NG) network in order to enable it to do clustering using a sequence of input data. For verifying the RNG's performance, many architectures are compared in the learning of global and local models. In a global model only one supervised network is trained and in a local model the training examples are grouped by a clustering algorithm and each one of these groups is sent to different supervised networks. These architectures use different clustering algorithms (NG and RNG) or different supervised networks for prediction (ENs that are trained by backpropagation or backpropagation through time, and feedforward networks).
The objectives of Human Engineering (HE) are generally viewed as increasing human performance, reducing human error, enhancing personnel and equipment safety, and reducing training and related personnel costs. There a...
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The objectives of Human Engineering (HE) are generally viewed as increasing human performance, reducing human error, enhancing personnel and equipment safety, and reducing training and related personnel costs. There are other benefits that are thoroughly consistent with the direction of the Navy of the future, chief among these is reduction of required numbers of personnel to operate and maintain Navy ships. The Naval Research Advisory Committee (NRAC) report on Man-Machine Technology in the Navy estimated that one of the benefits from increased application of man-machine technology to Navy ship design is personnel reduction as well as improving system availability, effectiveness, and safety The objective of this paper is to discuss aspects of the human engineering design of ships and systems that affect manning requirements, and impact human-performance and safety The paper will also discuss how the application of human engineering leads to improved performance, and crew safety, and reduced workload, all of which influence manning levels. Finally, the paper presents a discussion of tools and case studies of good human engineering design practices which reduce manning.
作者:
FAIRHEAD, DLHALL, CCSince graduating from Cleveland State University in 1965 with a Bachelor of Science degree in Mathematics
he has worked for the Navy at Annapolis participating in several different automation efforts ranging from design aids to surface ship bridge control. Mr. Fairhead has completed graduate work in Computer Science at the University of Maryland has a certificate in Computer Programming holds a patent and is a member of the Association for Computing Machinery (ACM). Upon graduation from Morgan State in 1962
Mr. Hall was employed as a physicist at the Naval Surface Warfare Center Carderock Division Annapolis until 1994. During that time period he served as program technical manager for propulsion technology and as senior project scientist for several automation projects including the Automated Ships Bridge project. Mr. Hall also served as a member of the initial Technical Director's Technology Application Team and of the Autonomic Ship Innovation Center Team. Mr. Hall is a member of the American Institute of Physics and Sigma Pi Sigma (National Physics Honor Society).
A growing concern about the shrinking size of the U.S. Navy budget and the pool from which selections will be made to ''man'' U. S. Navy shipboard systems has led to investigations on achieving improve...
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A growing concern about the shrinking size of the U.S. Navy budget and the pool from which selections will be made to ''man'' U. S. Navy shipboard systems has led to investigations on achieving improvements in affordability and operational effectiveness. One such investigation has resulted in the development of the Standard Monitoring and Control System (SMCS), a modular, open architecture control system which includes the control system components for propulsion, electric plant, auxiliaries, and damage control. The first major technology upgrade to SMCS will entail the insertion of Artificial Intelligence (AI) technologies into HM&E monitoring and control applications. The Intelligent Machinery Control Integration Task (IMCI) was established to provide a structural approach for this major technology upgrade. As part of the first phase of IMCI, an identification of intelligent control requirements, an assessment of AI technologies, and a survey of intelligent control applications were performed. This paper lists those HM&E-related shipboard operational requirements from which intelligent machinery control requirements will be identified. Also, there is an initial assessment of AI-related reasoning and the following AI technologies, knowledge-based systems, fuzzy logic, neural nets, and genetic algorithms. The survey provided some insight into applying AI technologies to SMCS shipboard operational requirements.
作者:
NARAYANAN, VMANELA, MLADE, RKSARKAR, TKDepartment of Electrical and Computer Engineering
Syracuse University Syracuse New York 13244-1240 Viswanathan Narayanan was born in Bangalore
India on December 14 1965. He received the BE degree in Electronics and Communications from B.M.S. College of Engineering Bangalore in 1988. He joined the Department of Electrical Engineering at Syracuse University for his graduate studies in 1989 where he is currently a research assistant. His research interests are in microwave measurements numerical electromagnetics and signal processing. Biographies and photos are not available for M. Manela and R. K. Lade.Tapan K. Sarkar (Sf69-M'76-SM'X1) was born in Calcutta. India
on August 2 1948. He received the BTech degree from the Indian Institute of Technology Kharagpur India in 1969 the MScE degree from the University of New Brunswick Fredericton Canada in 1971. and the MS and PhD degrees from Syracuse University. Syracuse NY in 1975. From 1975-1976 he was with the TACO Division of the General Instruments Corporation. He was with the Rochester Institute of Technology (Rochester NY) from 1976-1985. He was a Research Fellow at the Gordon Mckay Laboratory Harvard University Cambridge MA from 1977 to 1978. He is now a Professor in the Department of Electrical and Computer Engineering Syracuse University. His current research interests deal with numerical solutions of operator equations arising in electromagnetics and signal processing with application to system design. He obtained one of the “ best solution” awards in May 1977 at the Rome Air Development Center (RADC) Spectral Estimation Workshop. He has authored or coauthored more than 154 journal articles and conference papers and has written chapters in eight books. Dr. Sarkar is a registered professional engineer in the state of New York. He received the Best Paper Award of the IEEE Transactions on Electromagnetic Compatibility in 1979. He was an Associate Editor for feature articles of the lEEE Antennas arid Propagation Sociefy Newsletter and was
Dynamic analysis of waveguide structures containing dielectric and metal strips is presented. The analysis utilizes a finite difference frequency domain procedure to reduce the problem to a symmetric matrix eigenvalue...
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Dynamic analysis of waveguide structures containing dielectric and metal strips is presented. The analysis utilizes a finite difference frequency domain procedure to reduce the problem to a symmetric matrix eigenvalue problem. Since the matrix is also sparse, the eigenvalue problem can be solved quickly and efficiently using the conjugate gradient method resulting in considerable savings in computer storage and time. Comparison is made with the analytical solution for the loaded dielectric waveguide case. For the microstrip case, we get both waveguide modes and quasi-TEM modes. The quasi-TEM modes in the limit of zero frequency are checked with the static analysis which also uses finite difference. Some of the quasi-TEM modes are spurious. This article describes their origin and discusses how to eliminate them. Numerical results are presented to illustrate the principles.
Herein, it is shown that by exploiting integral definitions of well known special functions, through generalizations and differentiations, broad classes of definite integrals can be solved in closed form or in terms o...
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