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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Abolfazl Ghaffari Alireza Askarzadeh Roohollah Fadaeinedjad Gerry Moschopoulos Department of Electrical and Computer Engineering Graduate University of Advanced Technology Kerman Iran Department of Energy Management and Optimization Institute of Science and High Technology and Environmental Sciences Graduate University of Advanced Technology Kerman Iran Department of Electrical and Computer Engineering Western University London Ontario Canada

The use of wind energy as an energy resource in distribution networks is increasing. A disadvantage to using wind energy, however, is the emission of flicker in an electrical distribution network (EDN), which may adversely affect power quality during system operation. An effective way to improve power quality is to include the allocation of wind turbines (WTs) in the planning phase. The location and size of WTs can significantly improve the network power quality and electrical performance in an EDN. This paper considers modeling for flicker emission by using a mixed integer non-linear programming (MINLP) model to determine the optimal location and size of WTs. The optimal design of the network associated with WTs generation profile patterns and the variation of load demand during the planning horizon 24-h is also determined. The proposed model is implemented in GAMS and tested on a standard IEEE 33-bus system.

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Energy Efficient Transmission Parameters Selection Method Using Reinforcement Learning in Distributed LoRa Networks

Energy Efficient Transmission Parameters Selection Method Us...

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IEEE Conference on Wireless Communications and Networking

作者： Ryotai Airiyoshi Mikio Hasegawa Tomoaki Ohtsuki Aohan Li Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan Department of Electrical Engineering Tokyo University of Science Tokyo Japan Department of Information and Computer Science Keio University Yokohama Japan

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

With the increase in demand for Internet of Things (IoT) applications, the number of IoT devices has drastically grown, making spectrum resources seriously insufficient. Transmission collisions and retransmissions increase power consumption. Therefore, even in long-range (LoRa) networks, selecting appropriate transmission parameters, such as channel and transmission power, is essential to improve energy efficiency. However, due to the limited computational ability and memory, traditional transmission parameter selection methods for LoRa networks are challenging to implement on LoRa devices. To solve this problem, a distributed reinforcement learning-based channel and transmission power selection method is proposed, which can be implemented on the LoRa devices to improve energy efficiency in this paper. Specifically, the channel and transmission power selection problem in LoRa networks is first mapped to the multi-armed-bandit (MAB) problem. Then, an MAB-based method is introduced to solve the formulated transmission parameter selection problem based on the acknowledgment (ACK) packet and the power consumption for data transmission of the LoRa device. The performance of the proposed method is evaluated by the constructed actual LoRa network. Experimental results show that the proposed method performs better than fixed assignment, adaptive data rate low-complexity (ADR-Lite), and e-greedy-based methods in terms of both transmission success rate and energy efficiency.

关键词： Performance evaluation Power demand LoRa Reinforcement learning Energy efficiency Internet of Things

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Optimization of the Healthcare Infrastructure Planning in Guanajuato: A Comprehensive Primary Healthcare Units Planning Model

Optimization of the Healthcare Infrastructure Planning in Gu...

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IISE Annual Conference and Expo 2024

作者： Jinwoo, Park Michael Mendoza-Gómez, Rodolfo Ríos-Mercado, Roger Z. School of Engineering and Science Eugenio Garza Sada SN Cerro Gordo Guanajuato León37190 Mexico Universidad Autónoma de Nuevo León Graduate Program in Electrical Engineering Av. Universidad SN Cd. Universitaria Nuevo León San Nicolás de los Garza66455 Mexico

ISBN: (纸本)9781713877851

The planning of primary healthcare infrastructure is essential for improving population access to healthcare services, especially in developing countries where access to healthcare is limited. In this work, we propose the use of a bi-objective optimization model to support the decision-making process related to the strategic decisions of locating new Primary Healthcare Units (PHUs), upgrading the installed capacity in the PHUs network, and allocating demand points to PHUs. We present a case study based on the State of Guanajuato, Mexico;a federal entity with more than 6 million inhabitants in 2020, where more than 21% of the population lacks formal healthcare insurance and the other 35% is affiliated to a public healthcare institution. The problem addressed was solved for each of the state's eight regions, with instances between 650 and 1398 demand points, generating the Pareto set for five different budget scenarios. The problem minimizes the weighted total travel distance from demand points to PHUs for general medical consultation while maximizing the demand coverage for complementary services such as nutrition counseling, dental care, mental health, clinical analysis, and imaging. An augmented version of the Ε-constraint method is used to find the Pareto sets, and the Cplex solver is employed to solve all the generated instances. The model's usefulness is shown through its application in the case study. © IISE Annual Conference and Expo *** rights reserved.

关键词： Decision making

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Prospective evaluation of data-driven models to predict daily risk of Clostridioides difficile infection at 2 large academic health centers (vol 2, pg 1, 2022)

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INFECTION CONTROL & HOSPITAL EPIDEMIOLOGY 2023年第10期44卷 1705-1705页

作者： Kamineni, Meghana Otles, Erkin Oh, Jeeheh Rao, Krishna Young, Vincent B. Li, Benjamin Y. West, Lauren R. Hooper, David C. Shenoy, Erica S. Guttag, John G. Wiens, Jenna Makar, Maggie Electrical Engineering and Computer Science Department Massachusetts Institute of Technology Cambridge Massachusetts Medical Scientist Training Program University of Michigan Medical School Ann Arbor Michigan Department of Industrial and Operations Engineering University of Michigan College of Engineering Ann Arbor Michigan Division of Computer Science and Engineering University of Michigan College of Engineering Ann Arbor Michigan Department of Internal Medicine Division of Infectious Diseases University of Michigan Medical School Ann Arbor Michigan Infection Control Unit Massachusetts General Hospital Boston Massachusetts Division of Infectious Diseases Massachusetts General Hospital Boston Massachusetts Harvard Medical School Boston Massachusetts

Many data-driven patient risk stratification models have not been evaluated prospectively. We performed and compared the prospective and retrospective evaluations of 2 Clostridioides difficile infection (CDI) risk-prediction models at 2 large academic health centers, and we discuss the models’ robustness to data-set shifts.

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A 3D Dual-band electrically Small Monopole Antenna for Internet of Sea Applications

A 3D Dual-band Electrically Small Monopole Antenna for Inter...

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2021 IEEE International Symposium on Antennas and Propagation and North American Radio science Meeting, APS/URSI 2021

作者： Liao, Hanguang Bilal, Rana Muhammad Shamim, Atif Electrical and Computer Engineering Program King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (纸本)9781728146706

Sensing and retrieving data from ocean to land are challenging and expensive tasks, while the Internet of Sea (IoS) concept can help to monitor ocean environment in a low-cost way. In this paper, an electrically Small (ES) dual-band monopole antenna is proposed for the IoS application. Dual-band operation (GSM-900, LoRa, and BLE bands) and vertical polarization are maintained in a very compact size. The proposed antenna operates as a folded monopole antenna at 900MHz, and as a simple monopole antenna at 2.4 GHz, by combining the top-loaded folded monopole antenna and the 2-layer monopole feeding structure. The proposed antenna has ka of 0.45 at the LB, with a decent polarization purity and radiation efficiency of 54%. The proposed antenna is designed with a low-cost additive manufacturing material system. © 2021 IEEE.

关键词： Monopole antennas

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Analytical reference compensation for tracking dynamic target signals with linear robust MPC strategies

Analytical reference compensation for tracking dynamic targe...

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American Control Conference (ACC)

作者： Tito L. M. Santos Bruno S. S. Pereira Department of Electrical and Computer Engineering Federal University of Bahia Salvador Bahia Brazil Graduate Program on Electrical and Engineering Federal University of Bahia Salvador Bahia Brazil Department of Robotics SENAI-CIMATEC Salvador Bahia Brazil

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper proposes an analytical target modifi-cation for linear robust model predictive control strategies in order to deal with time-varying references defined by dynamic signal targets. The new approach can be directly integrated to linear robust model predictive control algorithms that achieve piecewise constant reference tracking if recursive feasibility is ensured for any set-point. The main contribution is to present a direct analytical approach that provides a potentially improved steady-state tracking error performance with the same computation complexity of the original MPC for tracking piecewise constant reference. A simulation case study based on the trajectory tracking control of a quadrotor is used to illustrate the usefulness of the new analytical target modification layer.

关键词： Sufficient conditions Target tracking Trajectory tracking Heuristic algorithms Prediction algorithms Steady-state Computational complexity

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Content-Aware Opportunistic Packet Scheduling with Dynamic Routing Algorithm for Multi-path Video Streaming over Mesh Networks*

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Chinese Journal of Electronics 2023年第2期21卷 270-276页

作者： Yongfer Zhang Yunsheng Zhang Chun Yuan Shiyin Qin Zhihai He Digital Media Laboratory School of Computer Science and Engineering Beihang University Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China The Graduate School at Shenzhen Tsinghua University Shenzhen China Department of Electrical and Computer Engineering University of Missouri Columbia MO U.S.A

Multi-path video streaming over networks emerges as an important application in multimedia communication. Since the efficiency of multi-path video streaming is closely tied to the packet scheduling strategies, in this paper, we develop a content-aware opportunistic packet scheduling scheme with dynamic routing algorithm, which aims to maximize the reconstructed video quality by considering the content diversity of each video packet. To handle the problem of increased reordering delay, a sliding-window-based policy is then developed to find a balance between the reconstructed video quality and the reordering delay, throughout and packet loss. Our extensive experimental results demonstrate that the proposed packet scheduling scheme significantly outperforms EDPF and achieves a good tradeoff between the reconstructed video quality and the reordering time at the receiver side.

关键词： Scheduling algorithms Heuristic algorithms Packet loss Receivers Streaming media Routing Dynamic scheduling

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White rice stem borer pest detection system using image-based convolution neural network

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Procedia computer science 2024年 245卷 518-527页

作者： Akhmad Saufi Suharjito Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480

Preventing agricultural resource loss caused by pests remains a crucial issue. While technological advancements are being achieved, the current agricultural management methods and equipment have yet to meet the required level for precise pest control, a huge portion of the pest population analysis process is still conducted manually. As a solution to this issue, the development of a White Rice Stem Borer pest detection system has been conducted by applying Convolutional Neural Network (CNN) technology to calculate the pest population count at the research location. This system has been specifically designed to detect the White Rice Stem Borer using available traps. The method involves training data from a direct dataset obtained from the field, categorized into two positive and negative classes of the White Stem Borer pests. Six models have been trained from this dataset, utilizing two different architectures. Out of the six trained models, four showed potential overfitting, one exhibited underfitting, and one model demonstrated optimal results. The highest accuracy in image detection achieved by the most optimal CNN model was 97.35%, with a training accuracy of 98.54%. This best-performing model utilized an architecture with three Convolution layers, 50 Epochs, and an automatic data split with an 80:20 training-validation data ratio. From the research findings, it is concluded that this study can assist in automatically analyzing the quantity of White Stem Borer pests in a specific area without directly counting the number of pests from existing traps. However, the study still encounters a limitation—the detection process still requires substantial server resources and cannot be directly processed on the Raspberry PI device installed in the trap. Consequently, the detection relies on transmitting image data from the field device to the server before the detection process can occur.

关键词： White Rice Stem Borer Stem Borer White Stem Borer Detection Pest Detection Convolutional Neural Network (CNN)

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A Preliminary Study on Analysing Mandarin Tone Values of Romance L2 Mandarin Learners

A Preliminary Study on Analysing Mandarin Tone Values of Rom...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Wu-Hao Li Te-hsin Liu Chen-Yu Chiang College of Electrical Engineering and Computer Science National Taipei University Taiwan Graduate Program of Teaching Chinese as the Second Language National Taiwan University Dept. of Communication Engineering National Taipei University New Taipei City Taiwan

ISBN: (数字)9798350367331

ISBN: (纸本)9798350367348

The 5-level tone value labeling system helps characterize pitch contours of syllables for L2 Mandarin learners and teachers to facilitate tone acquisition and tone error analysis, respectively. In the past, linguistic experts did the tone value labeling and initially used it to represent or analyze the pitch contours of monosyllables. Some L2 Mandarin teachers also used the tone value labeling system to analyze pitch contours of continuous speech and illustrate pitch realizations for L2 Mandarin learners. However, the pitch contours of the labeled tone values of continuous speech were rarely objectively measured or analyzed. This paper presents a preliminary analysis of tone values of a continuous read speech corpus uttered by six Romance L2 Mandarin learners. The pitch contours of the tone value classes were explored, and some experiments related to the automatic recognition of tone and tone value classes were reported. We expect the results reported by this study to shed light on the development of an automatic tone value classification mechanism, which will be used in computer-assisted pronunciation training for L2 learners in the future.

关键词： Training Error analysis Asia Information processing Linguistics Labeling

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High Resolution of City-Level Climate Simulation by GPU with Multi-physical Phenomena 18th

High Resolution of City-Level Climate Simulation by GPU with...

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18th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2021

作者： Watanabe, Koei Kikuchi, Kohei Boku, Taisuke Sato, Takuto Kusaka, Hiroyuki Master’s Program in Computer Science Graduate School of Systems and Information Engineering University of Tsukuba Tsukubashi Japan Center for Computational Sciences University of Tsukuba Tsukubashi Tennodi Japan

ISBN: (纸本)9783030935702

In this paper, we describe the Graphics Processing Unit (GPU) implementation of our City-LES code on detailed large eddy simulations, including the multi-physical phenomena on fluid dynamics, heat absorption and reflection by surface and building materials, cloud effects, and even sunlight effect. Because a detailed simulation involving these phenomena is required for analyses at the street level and several meters of resolution, the computation amount is enormous, and ordinary CPU computation cannot provide sufficient performance. Therefore, we implemented the entire code on GPU clusters with large-scale computing. We applied OpenACC coding to incrementally implement relatively easy programming and eliminate data transfers between the CPU and GPU memories. Based on this research, we determined that the elimination of data transfers is effective, even in the case where a part of the code execution on the GPU is slower than the CPU, owing to the absence of spatial parallelism. The objective of this study is to perform a complete climate simulation on a few square-kilometers field around the Tokyo Station, considering the finest resolution of the original highlighted area of the Marathon race in the Olympic Games Tokyo 2020. We successfully transferred the entire code to the GPU to provide approximately eight times the performance of CPU-only computation on multi-GPU per node with a large scale cluster. © 2022, IFIP International Federation for Information Processing.

关键词： Graphics processing unit

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