The history of much of Industrial engineering has its roots in the Industrial Revolution where technologies helped mechanize what had been manual labor. However a lot has changed in the 100 plus years since the Indust...
The systems Architecting and engineering Graduate program at the University of Southern California began as a graduate educational program primarily focused on aerospace and defense. Founded by Eberhardt Rechtin in 19...
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Due to the changing global business environment, the operations of engineering companies in the U.S. are moving from self sufficient engineering operations toward the integration of various engineering operations, inc...
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This paper discusses the activities involved in improving systemsengineering (SE) on a large, mature program. It discusses the reasons for improving SE for a fielded product and then provides a description and discus...
The features of the Masters of Science in Telecommunication systemsprogram at the University of Oklahoma (OU)-Tulsa, are discussed. The program requires all student to complete a minimum of 32 credit hours, including...
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The features of the Masters of Science in Telecommunication systemsprogram at the University of Oklahoma (OU)-Tulsa, are discussed. The program requires all student to complete a minimum of 32 credit hours, including a professional project. The program was created, under the aegis of the School of Electrical and Computer engineering, to produce engineering graduates in telecommunication-related fields. In addition to the common core coursework, students are required to complete 12 hours of technical elective coursework with Telecommunication systems (TCOM) and computer engineering.
Reinforcement Learning is a branch of machine learning to learn control strategies that achieve a given objective through trial-And-error in the environment. Because this can be applicable even when the state transiti...
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Reinforcement Learning is a branch of machine learning to learn control strategies that achieve a given objective through trial-And-error in the environment. Because this can be applicable even when the state transition function of the control object is unknown or it is difficult to create its model properly, this can reduce the designer's burden. Reinforcement learning repeats evaluating a policy and improving it based on that evaluation. An algorithm called value function approximation is used in this evaluation. Value function approximation is a general term for algorithms of approximating a function called value function, which maps an arbitrary state to how much reward can be obtained in the future when acting according to a policy from that state. Value function approximation should have high approximation accuracy and hyperparameter easy to tune. Although various value function approximation methods have been proposed so far, some of them does not have convergent guarantee and the others' hyperparameter tuning is difficult. The purpose of this paper is to propose a value function approximation method that have convergence guarantee even with nonlinear function approximator and whose hyperparameter tuning is easy and to verify its performance through numerical experiments. To this end, we focused on GTD2 method, which is one of the value function approximation methods that has convergence guarantee even with a nonlinear function approximator. GTD2 method has the drawback that its hyperparameter is difficult to tune appropriately so that the approximation does not diverge during learning. Therefore, we firstly clarified the cause of the divergence of GTD2 method. Secondly, based on this cause, we proposed Normalized and Regularized GTD2 (NRGTD2) method, that incorporates a method for suppressing divergence into GTD2 method. Finally, through numerical experiments, it was clarified that the proposed method suppresses the divergence and can achieve better approxim
Effective development of virtual reality (VR) applications is heavily reliant on the evaluation of user experience (UX). However, traditional methods such as questionnaires have inherent limitations which hinder their...
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This paper presents a metaheuristic optimization-based approach for selecting a pre-determined number of measurement markers from the set of available markers that optimizes the performance of the recently introduced ...
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This study presents the design of a lunar navigation satellite constellation to provide global Positioning, Navigation, and Timing (PNT) services, beginning with coverage at the lunar South Pole and gradually expandin...
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This paper presents the design and the development of multi-string I-V curve tracer for photovoltaic (PV) strings. It uses a capacitive load and double pole relay to measure the I-V characteristics of a multiple PV st...
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