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IEEE Conference on Electromagnetic Field Computation

作者： Leandro dos Santos Coelho Carlos Richter Viviana Cocco Mariani Alireza Askarzadeh Industrial and Systems Eng. Grad. Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba PR Brazil Department of Electrical Engineering Federal University of Parana Curitiba PR Brazil Pontifical Catholic University of Parana (PUCPR) Mechanical Engineering Graduate Program (PPGEM) Curitiba PR Brazil Department of Energy Management and Optimization University of Advanced Technology Kerman Iran

ISBN: (纸本)9781509010332

Recently, an optimization metaheuristic paradigm based intelligent behavior of crows called crow search algorithm (CSA) has been proposed. To enhance the performance of the standard CSA algorithm, this paper proposes to tune the control parameters using population diversity information and Gaussian distribution. Loney's solenoid benchmark problem is used to examine the effectiveness of the conventional CSA and the proposed modified CSA.

关键词： Optimization Solenoids Electromagnetics Sociology Statistics Gaussian distribution Benchmark testing

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Mean-variance and Safety-first Portfolio Selection Strategy for High-volume/Highvalue Traded Stocks in Philippine Stock Exchange (PSE)

Mean-variance and Safety-first Portfolio Selection Strategy ...

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IEEE International Conference on industrial engineering and engineering Management

作者： T. C. De Guzman M. N. Young Y. T. Prasetyo S. F. Persada R. Nadilfatin School of Graduate Studies Mapua University Manila Philippines School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This research evaluates the effectiveness of Mean-Variance (MV) and Safety-First (SF) portfolio selection strategies for high-volume/high-value traded stocks on the Philippine Stock Exchange (PSE). Analyzing data from 288 stocks over 7,670 trading days (30 years), we estimated stock returns, assigned probability weights, and conducted optimization models. The results show that the Mean-Variance (MV0.5) strategy achieved the best balance between risk and return, boasting the highest mean and cumulative returns with moderate volatility. The Safety-First (SF) strategy, however, yielded negative cumulative returns, indicating potential issues. The Market strategy had the lowest mean return but also the least risk, appealing to risk-averse investors. The Portfolio Mean-Variance (PMV) strategy provided a reasonable balance of returns and risk. Statistical analysis revealed that only the MV0.5 strategy outperformed market returns. These findings offer crucial insights into risk assessment and portfolio management for investors evaluating these strategies against market performance.

关键词： Statistical analysis Optimization models Oils Safety Risk management Stock markets Portfolios Standards Monitoring Investment

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Non-hermitian fabry-perot resonances in a PT-symmetric system

arXiv

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arXiv 2020年

作者： Shobe, Ken Kuramoto, Keiichi Imura, Ken-Ichiro Hatano, Naomichi Department of Semiconductor Electronics and Integration Science AdSM Hiroshima University 739-8530 Japan Program of Electronic Devices and Systems School of Engineering Hiroshima University 739-8527 Japan Graduate School of Advanced Science and Engineering Hiroshima University 739-8530 Japan Institute of Industrial Science The University of Tokyo 277-8574 Japan

In non-Hermitian scattering problems the behavior of the transmission probability is very different from its Hermitian counterpart;it can exceed unity or even be divergent, since the non-Hermiticity can add or remove the probability to and from the scattering system. In the present paper, we consider the scattering problem of a PT-symmetric potential and find a counter-intuitive behavior. In the usual PT-symmetric non-Hermitian system, we would typically find stationary semi-Hermitian dynamics in a regime of weak non-Hermiticity but observe instability once the non-Hermiticity goes beyond an exceptional point. Here, in contrast, the behavior of the transmission probability is strongly non-Hermitian in the regime of weak non-Hermiticity with divergent peaks, while it is superficially Hermitian in the regime of strong non-Hermiticity, recovering the conventional Fabry-Perot-type peak structure. We show that the unitarity of the S-matrix is generally broken in both of the regimes, but is recovered in the limit of infinitely strong non-Hermiticity. Copyright © 2020, The Authors. All rights reserved.

关键词： Transmissions

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Deep Learning-Based Residual Useful Lifetime Prediction for Assets with Uncertain Failure Modes

arXiv

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arXiv 2024年

作者： Su, Yuqi Fang, Xiaolei Operations Research Graduate Program North Carolina State University 915 Partners Way RaleighNC27607 United States Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University 915 Partners Way RaleighNC27607 United States

industrial prognostics focuses on utilizing degradation signals to forecast and continually update the residual useful life of complex engineering systems. However, existing prognostic models for systems with multiple failure modes face several challenges in real-world applications, including overlapping degradation signals from multiple components, the presence of unlabeled historical data, and the similarity of signals across different failure modes. To tackle these issues, this research introduces two prognostic models that integrate the mixture (log)-location-scale distribution with deep learning. This integration facilitates the modeling of overlapping degradation signals, eliminates the need for explicit failure mode identification, and utilizes deep learning to capture complex nonlinear relationships between degradation signals and residual useful lifetimes. Numerical studies validate the superior performance of these proposed models compared to existing methods. © 2024, CC BY.

关键词： Failure modes

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Capacity management and patient scheduling in an outpatient clinic using discrete event simulation 13

Capacity management and patient scheduling in an outpatient ...

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Simulation Winter Conference

作者： Gokce Akin Julie S. Ivy Todd R. Huschka Thomas R. Rohleder Yariv N. Marmor Graduate Program in Operations Research North Carolina State University Raleigh NC USA Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University Raleigh NC USA Department of Health Care Policy and Research Mayo Clinic Rochester MN USA

ISBN: (纸本)9781479920778

Capacity management and scheduling decisions are important for managing an outpatient clinic in which multiple classes of patients are treated. After an appointment is scheduled, it can be rescheduled, cancelled, or a patient may not show-up on their appointment day. This study simulates the behavior of patients with regard to the time to appointment, examining different demand rates and service times for each patient class (new external patients, internal patients, established patients and subsequent visit patients); we also consider different delay-dependent reschedule, cancellation, and no-show rates. A discrete event simulation model is developed to analyze the effects of allowing different appointment windows, i.e., the maximum time between the appointment request date and the actual appointment date, for different patient classes. Capacity utilization, patient access, and financial rewards are used as the performance indicators.

关键词： Analytical models Delays Medical services Calendars Mathematical model Data models Data analysis

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Deep Reinforcement Learning Applied to a Sparse-Reward Trading Environment with Intraday Data

SSRN

引用

SSRN 2023年

作者： Takara, Lucas de Azevedo Alves Portela Santos, André Mariani, Viviana Cocco dos Santos Coelho, Leandro Department of Electrical Engineering PPGEE Federal University of Parana UFPR Avenida Coronel Francisco Herácito dos Santos Parana Curitiba81530–000 Brazil CUNEF Universidad Calle Almansa 101 Madrid28040 Spain Mechanical Engineering Graduate Program PPGEM Pontifical Catholic University of Parana PUCPR Imaculada Conceição Parana Curitiba80215–901 Brazil Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Parana PUCPR Imaculada Conceição Parana Curitiba80215–901 Brazil

Deep reinforcement learning (DRL) achieved significant progress in several areas enabling computers to perform complex decision-making tasks. Applied to quantitative trading, DRL trading agents can optimize their decisions during distinct market scenarios to reach a profitable strategy by learning from previous experiences. This work proposes a trading system containing a variant of the Deep Q-Network (DQN) algorithm as its main component called Extended Trading DQN (ETDQN). It can adapt its learning to trade across numerous market-behavior moments, receiving feedback only when a trade is liquidaded, differently from recent approaches that provide constant feedback. Based on distributional learning and other independent extensions suggested by the DRL community, the algorithm optimizes its decision-making process by replaying prioritized experiences containing different sub-goals, assisting the agent in collecting the maximum value of profits and removing the need for fine-tuning rewards. ETDQN learned to trade on three distinct financial time series signals, identifying trading opportunities during volatile price moments. The algorithm showed more aggressive behavior regarding the volatility of its annual returns than the Trading DQN benchmark, achieving a 1.46 and 7.13 better performance with respect to average daily cumulative returns in Western Digital Corporation and Cosmos cryptocurrency historical market data. © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Portfolio Selection Using Mean Variance Theory Based on the 30-year Historical Returns of Selected Subsectors of the Philippine industrial Sector

Portfolio Selection Using Mean Variance Theory Based on the ...

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IEEE International Conference on industrial engineering and engineering Management

作者： A. D. Yamanaka M.N. Young T.N. Chuahay Y. Pratseyo S. Persada R. Nadlifatin School of Graduate Studies Mapua University Manila Philippines School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Finance Chung Yuan University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

Portfolio selection is an important part of investment management that aims to select the right combination of assets to achieve an optimal risk-return ratio. This study integrates the Mean-Variance Theory utilizing the 30-year historical returns of the Philippine Stock Exchange. Three subsectors of the industrial Sector were used as the investment pool. The back-test results showed that the MeanVariance portfolios of selected subsectors can outperform the industrial sector and not the market. Stakeholders must be cautious when investing in these three subsectors, considering the values obtained from the simulations. There are recommended portfolio selections wherein companies have a specific allocation that investors and financial managers can use whenever they decide to invest in these subsectors. Overall, this study offers a framework for investors to use as a guide in diversifying their stakes in the Philippine Stock Exchange.

关键词： Companies Benchmark testing industrial engineering Market research Stakeholders Resource management Stock markets Portfolios Optimization Investment

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A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and Automotive Radars

arXiv

引用

arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh Graduate Degree Program of Robotics National Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan

Existing radar sensors can be classified into automotive and scanning radars. While most radar odometry (RO) methods are only designed for a specific type of radar, our RO method adapts to both scanning and automotive radars. Our RO is simple yet effective, where the pipeline consists of thresholding, probabilistic submap building, and an NDT-based radar scan matching. The proposed RO has been tested on two public radar datasets: the Oxford Radar RobotCar dataset and the nuScenes dataset, which provide scanning and automotive radar data respectively. The results show that our approach surpasses state-of-the-art RO using either automotive or scanning radar by reducing translational error by 51% and 30%, respectively, and rotational error by 17% and 29%, respectively. Besides, we show that our RO achieves centimeter-level accuracy as lidar odometry, and automotive and scanning RO have similar accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

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Mean Variance Portfolio Selection Utilizing Services Subsector’s (Media, Telecommunications, and Information Technology) 30-Year Philippine Stock Exchange Trading Data

Mean Variance Portfolio Selection Utilizing Services Subsect...

引用

IEEE International Conference on industrial engineering and engineering Management

作者： E.D. Salazar M.N. Young T.N. Chuahay Y. Pratseyo S. Persada R. Nadilfatin Myra F. Contreras School of Industrial Engineering and Engineering Management Mapúa University Intramuros School of Graduate Studies Mapúa University Intramuros Department of Finance Chung Yuan Christian University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institur Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

The Philippine Stock Exchange (PSE), established in 1927, has significantly evolved, especially since the 1980s with major reforms and technological advancements. This paper analyzes the performance of portfolios in the Media, Telecommunications, and Information Technology sectors listed on the PSE over a 30year span. Using mean-variance analysis, it evaluates portfolio optimization by balancing risk and return. Drawing on data from 1993 to 2022, the study examines portfolios across various risk-return frontiers (RRFs) and compares the service sector’s performance. The results highlight varying portfolio metrics across RRFs, with some showing outperformance and higher RRFs leading to diminishing returns. The study also identifies key companies with significant stock allocations, providing strategic insights for portfolio construction. These findings offer investors guidance on optimizing portfolio strategies within the PSE for better decision-making and investment outcomes.

关键词： Measurement Decision making Companies Media Telecommunications Resource management Stock markets Portfolios Optimization Investment

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Methodology proposal for acquisition of biotelemetric data in a real time

Methodology proposal for acquisition of biotelemetric data i...

引用

International Conference on Computers & industrial engineering (CIE)

作者： Osiris Canciglieri M. Rudek Lucas A. Bodaczny Teófilo Miguel de Souza Pontificia Universidade Catolica do Parana Curitiba PR BR Department of Manufacturing Engineering Pontifical Catholic University of Paran Curitiba Parana Brazil Department of Manufacturing Engineering of Pontifical Catholic Industrial and Systems Engineering Graduate Program (PPGEPS) Curitiba PR Brazil Pontifical Catholic University of Paran Curitiba Parana Brazil Department of Electrical Engineering Sao Paulo State University (UNESP) Guaratingueta SP Brazil

This work presents a methodological proposal for acquisition of biometric data through telemetry basing its development on a research-action and a case study. Nowadays, the qualified professionals of physical evaluation have to use specific devices to obtain biometric signals and data. These devices in the most of the time are high cost and difficult to use and handling. Therefore, the methodological proposal was elaborate in order to develop, conceptually, a bio telemetric device which could acquire the desirable biometric signals: oxymetry, biometrics, corporal temperature and pedometry which are essential for the area of physical evaluation. It was researched the existent biometrics sensors, the possible ways for the remote transmission of signals and the computer systems available so that the acquisition of data could be possible. This methodological proposal of remote acquisition of biometrical signals is structured in four modules: Acquisitor of biometrics data; Converser and transmitter of biometric signals; Receiver and Processor of biometrics signals and Generator of Interpretative Graphs. The modules aim the obtention of interpretative graphics of human biometric signals. In order to validate this proposal a functional prototype was developed and it is presented in the development of this work.

关键词： Temperature sensors Proposals Bioinformatics Real time systems Product development Temperature measurement

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