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A New Comparative Approach Based on Features of Subcomponents and Machine Learning Algorithms to Detect and Classify Power Quality Disturbances

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Electric Power Components and Systems 2024年第8期52卷 1269-1292页

作者： Akkaya, Sıtkı Yüksek, Emre Akgün, Hasan Metehan Department of Electrical and Electronics Engineering of Faculty of Engineering and Natural Sciences Sivas University of Science and Technology Sivas Turkey Department of Computer Engineering of Faculty of Engineering and Natural Sciences Sivas University of Science and Technology Sivas Turkey Department of Aircraft Technology of Sivas Vocational School Sivas University of Science and Technology Sivas Turkey

Current measurement systems based on the IEEE-1159 standard have some limitations and robustness problems under noisy and fast-changing conditions. Besides, applying different methods for each Power Quality Disturbance (PQD) to every window is required but time-consuming and not feasible. Therefore, different kinds of two-stage methods, Detection and Classification (D&C), have been improved in many studies. Then, the required measurement can be performed to define disturbance. For this purpose, a new approach based on features of subcomponents with Machine Learning Algorithms (MLAs) to detect and classify PQDs is proposed. 21-class dataset including single and multiple PQDs under different noisy conditions was prepared randomly. Of this dataset, determined features were extracted and some of these were selected. Then, selected features were trained and tested with some MLAs in a workstation. Results obtained from comparative MLAs and the other classification methods show that the best MLA with related features is Random Forest with 96.97% while LightGBM, k-Nearest Neighbors, and XGBoost 96.85%, 96.73%, and 92.82% accuracy, respectively. Because the selected features, optimized parameters, and the related MLA were obtained by investigating for features provided from the PQDs in the whole parameter space, this approach brings the advantages of high accuracy, low D&C complexity, and computing load. © 2023 Taylor & Francis Group, LLC.

关键词： Power quality

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Stochastic Optimization on Parking Lots for Smart Parking Using Reinforcement Learning Methods 14

Stochastic Optimization on Parking Lots for Smart Parking Us...

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2024 IEEE 14th Annual Computing and Communication Workshop and Conference, CCWC 2024

作者： Khatermohammadi, Davoud Ghalari, Seyed Amir Ebadollahi, Saeed Gil, Bob Iran University of Science and Technology Department of Electrical Engineering Iran British Columbia Institute of Technology Department of Electrical and Computer Engineering Technology Canada

ISBN: (纸本)9798350360134

Various sciences have always considered the maximum use of limited resources and planning to optimize their use. Parking in urban spaces is regarded as a finite resource. This paper investigates the idea of introducing learning algorithms for parking guidance and information systems that employ a central server. Each driver engages in a systematic search during a cycle to identify the parking space with the highest perceived reward among all available options, the optimal parking is determined based on predefined tunings signifying the pursuit of identifying the best parking places to select. To provide estimated optimal parking searching strategies to travelers there are two options linear programming and dynamic programming. Several scenarios will be argued from basic linear programming to Reinforcement Learning methods. The main contribution of this paper lies in the identification of optimal parking spaces for drivers by considering various factors associated with the parking spaces, employing the MAB approach. The multi-armed bandit (MAB) model has been widely adopted for studying many practical optimization problems (network resource allocation, ad placement, crowdsourcing, etc.) with unknown parameters, as one of the reinforcement learning implementations used in this investigation. Each driver who played this MAB gained its reward with their probabilities. The reinforcement learning methodology is utilized for which both Greedy and ϵ-Greedy simulations are run considering stationary and nonstationary scenarios, meanwhile, each parking selection can change the environment, and regarding this change, scenario assumptions change which is a new scenario in the area of parking problems finally results of these conditions are analyzed while aspects of each scenario are discussed and compared to their efficiency. © 2024 IEEE.

关键词： Dynamic programming

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Neurocognitive assessment under various human-robot teaming environments 46

Neurocognitive assessment under various human-robot teaming ...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Packy, Anna L. Jayahankar, Jayesh Teymourlouei, Arya Stone, Joshua Oh, Hyuk Katz, Garrett E. Reggia, James A. Gentili, Rodolphe J. University of Maryland Neuroscience and Cognitive Science Program College Park United States University of Maryland Department of Computer Science College Park United States University of Maryland Department of Electrical & Computer Engineering College Park United States University of Maryland Department of Kinesiology College Park United States Syracuse University Department of Electrical Engineering & Computer Science Syracuse United States

ISBN: (纸本)9798350371499

Human-robot teaming has become increasingly important with the advent of intelligent machines. Prior efforts suggest that performance, mental workload, and trust are critical elements of human-robot dynamics that can be altered by the robot's behavior. Most prior human-robot teaming studies used behavioral analyses, but a limited number used neural markers, without the use of physical robots and complex tasks. Here we combine behavioral and EEG cortical dynamics to examine cognitive-motor processes when individuals complete a complex task under various team environments with a robot. The results revealed that altering the robot quality affected both behavioral and EEG dynamics. Task completion with an experienced robot led to greater team performance and human trust along with lower mental workload compared to an inexperienced teammate or when individuals performed alone. EEG changes suggest that different attentional processes were engaged when humans worked with the robot and performed alone, and that visual processing was more prominent when teaming with an inexperienced teammate. This work can inform human cognitive-motor processes and the design of robotic controllers in human-robot teams. © 2024 IEEE.

关键词： Man machine systems

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Modelling and simulation of energy management of power-split hybrid electric vehicles using the discrete EVent system specification

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International Journal of Vehicle Systems Modelling and Testing 2024年第1期18卷 33-61页

作者： Maatoug, Abdelfettah Kharoubi, Sahraoui Maaskri, Moustafa Belalem, Ghalem Mahmoudi, Said Faculty of Applied Sciences Science and Technology Department University of Tiaret Tiaret14000 Algeria Faculty of Mathematics and Computer Science Computer Science Department University of Tiaret Tiaret14000 Algeria Faculty of Applied Sciences Electrical Engineering Department University of Tiaret Tiaret14000 Algeria Faculty of Exact and Applied Sciences Computer Science Department University of Oran 1 Ahmed Ben Bella Oran31000 Algeria Faculty of Engineering Computer Science Department University of Mons Mons7000 Belgium

This work provides a basis for studying energy management optimisation in power-split hybrid electric vehicles (PSHEVs) to reduce fuel consumption and increase powertrain efficiency by enforcing a strategy related to battery level and vehicle speed. Three modes were used to operate the vehicle to meet different situations related to available energy and desired speed. These are particularly abundance mode, ascetic mode and optimal mode. For this, a system was designed based on several sub-models written in the discrete EVent system (DEVS) specification. The vehicle's power train and control strategy models were created in the DEVSimPy environment, and a joint simulation was carried out from the composite sub models until the overall model is reached. Simulation results under several driving cycles showed that the proposed system improves the energy consumption of the vehicle in different operating modes of the engines and gives more opportunities to adopt electric motors in vehicle transmission. © 2024 Inderscience Enterprises Ltd.

关键词： Energy management

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Adaptive iterated local search algorithm for dynamic patient admission scheduling problems

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Soft Computing 2025年第7期29卷 1-11页

作者： Turky, Ayad Sabar, Nasser R. Song, Andy Hussain, Abir Liatsis, Panos Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Information Technology La Trobe University MelbourneVIC3086 Australia School of Computing Technologies RMIT University Melbourne Australia Department of Electrical Engineering University of Sharjah Sharjah United Arab Emirates Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates

Healthcare resource management is essential for ensuring the quality of patient care. However, it can be a complex and costly task. This work addresses the patient admission scheduling (PAS) problem, a complex aspect of healthcare resource management. PAS aims to allocate patients to hospital beds within a planning horizon, subject to a variety of healthcare constraints. The goal is to maximize management efficiency and patient comfort to improve medical treatment. In this work, we consider a practical variant of PAS known as dynamic PAS (DPAS). DPAS considers several factors and constraints, such as the daily registration of new patients, urgent patients, uncertainties in stay lengths, operating theatre resources, and the surgery scheduling process. An effective and efficient adaptive iterated local search (AILS) algorithm is proposed to solve DPAS. To enable the search to explore the search space efficiently, the proposed AILS adaptively integrates a number of components. Two adaptive perturbation strategies are devised to locate unexplored areas in the search space. To exploit the newly discovered areas effectively, we propose an adaptive local search mechanism as an intensification strategy to find a high-quality solution. The proposed AILS algorithm is compared to benchmark problems used by existing algorithms. The experimental results demonstrate the effectiveness and efficiency of the proposed approach. Specifically, out of 30 tested instances, AILS obtains 17 of the best-known results using less computational time. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Resource allocation

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High resolution and high sensitivity imaging magnetometer with magnetic nanoparticle and optical heterodyne detection

High resolution and high sensitivity imaging magnetometer wi...

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2024 Laser science, LS 2024

作者： Bartos, Jan Ba Tis, Taleb Park, Wounjhang Huang, Shu-Wei Department of Electrical Computer and Energy Engineering University of Colorado Boulder80309 United States Material Science and Engineering Program University of Colorado Boulder80309 United States

We present progress towards an imaging magnetometer using a magneto-optical polymer nanocomposite thin film, experimentally demonstrating 29nT/√Hz sensitivity with © 2024 The Author(s). © Optica Publishing ... 详细信息

关键词： Heterodyne detection

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Diffusion Posterior Sampling is Computationally Intractable 41

Diffusion Posterior Sampling is Computationally Intractable

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41st International Conference on Machine Learning, ICML 2024

作者： Gupta, Shivam Jalal, Ajil Parulekar, Aditya Price, Eric Xun, Zhiyang Department of Computer Science University of Texas Austin United States Department of Electrical Engineering and Computer Science University of California Berkeley United States

Diffusion models are a remarkably effective way of learning and sampling from a distribution p(x). In posterior sampling, one is also given a measurement model p(y | x) and a measurement y, and would like to sample from p(x | y). Posterior sampling is useful for tasks such as inpainting, super-resolution, and MRI reconstruction, so a number of recent works have given algorithms to heuristically approximate it;but none are known to converge to the correct distribution in polynomial time. In this paper we show that posterior sampling is computationally intractable: under the most basic assumption in cryptography-that one-way functions exist-there are instances for which every algorithm takes superpolynomial time, even though unconditional sampling is provably fast. We also show that the exponential-time rejection sampling algorithm is essentially optimal under the stronger plausible assumption that there are one-way functions that take exponential time to invert. Copyright 2024 by the author(s)

关键词： Heuristic algorithms

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Classification of Parkinson's Disease Using MRMR and ICA Prediction Models - A Comparative Study

Classification of Parkinson's Disease Using MRMR and ICA Pre...

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2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Olawoye, Prisca O. Adebiyi, Marion O. Harry, Sotonye Vydah Arowolo, Micheal O. Landmark University Department of Computer Science Omu-Aran Nigeria University of Missouri Department of Electrical Engineering and Computer Science Columbia United States

ISBN: (纸本)9798350358155

Parkinson's disease (PD) is a neurodegenerative disorder which impacts the central nervous system and characterized by neuronal loss, particularly in the substantia nigra area of the brain. PD rendered dopamine-producing neurons dead which ultimately leads to a reduction in a variety of motor activities. Patients can have their quality of life improved by receiving an accurate diagnosis and preventative therapy. The primary criteria for diagnosing Parkinson's disease (PD) are medical indicators, particularly motor symptoms. However, traditional diagnostic procedures for PD can be subjective and prone to misdiagnosis due to the difficulty in categorizing small movements accurately. By improving medical professionals' ability to classify Parkinson's disease (PD), this study hopes to expedite the treatment process for those who suffer from it. To select the superior machine learning method, we evaluate the strengths and weaknesses of Independent Component Analysis (ICA) and Minimum Redundancy Maximum Relevance (MRMR). To categorize data, this study employs three well-known methods: the Support Vector Machine (SVM), the K-Nearest Neighbors (KNN), and the Decision Tree. Research used datasets that contained both patients with and without Parkinson's disease for both the training and testing phases of the study. This research suggests significant implications for subtyping Parkinson's disease. A similar level of accuracy (83.05%) is reached by the ICA-SVM model as well as the ICA-KNN model. The ICA-Decision Tree model's classification accuracy of 81.36 percent is also quite good. These results provide new avenues for exploring how machine learning might be used to better categorize people with Parkinson's. Bringing attention to these cutting-edge models is important to us because of their potential to boost diagnostic accuracy and efficiency in Parkinson's disease. © 2024 IEEE.

关键词： Neurodegenerative diseases

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Nano-structured metamaterial absorber based on a plus-shaped resonator for optical wavelength applications

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Journal of engineering and Applied science 2024年第1期71卷 134页

作者： Islam, Istiaq Mohammad Tanvirul Islam, Sikder Sunbeam Islam, Md. Rashedul Karim, Abu Naser Md. Rezaul Azim, Rezaul Department of Electrical and Electronic Engineering International Islamic University Chittagong Chittagong Bangladesh Department of Computer Science and Engineering International Islamic University Chittagong Chittagong Bangladesh Department of Physics Chittagong University Chittagong Bangladesh

Metamaterial absorbers have sparked widespread interest due to their remarkable electromagnetic properties, which enable a wide range of applications in light absorption and manipulation. This study introduces a new three-layer nanomaterial absorber (NMA) unit cell composed of nickel (Ni), silicon dioxide (SiO2), and nickel (Ni) designed to operate across the entire visible spectrum (390–780 nm). We demonstrate the NMA’s exceptional absorption characteristics through rigorous numerical simulations using industry-standard software, achieving a mean absorption rate of 97.17% and a maximum absorption peak of 99.99% at 694.89 nm under standard angles. Furthermore, the NMA unit cell has good impedance matching, efficient coupling between capacitors and inductors, and significant plasmonic resonance properties. Fabrication feasibility and potential applications in solar energy harvesting, optical sensing, and light detection. © The Author(s) 2024.

关键词： Silica

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Distance Measurement of Tunnel Facilities for Monocular Camera-based Localization

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Journal of Institute of Control, Robotics and Systems 2023年第1期29卷 7-14页

作者： Kim, Jongkwang Kim, Hyoungrae Oh, Jangsub Li, Xingyou Jang, Kyeongjun Kim, Hakil Department of Electrical and Computer Engineering Inha University Korea Republic of Program in Future Vehicle Engineering Inha University Korea Republic of Department of Smart Mobility Engineering Inha University Korea Republic of

The GNSS signal used for vehicle localization exhibits a shaded area such as a tunnel. To accurately estimate the location in the shaded area, the accumulated position error must be compensated with information obtained from a separate sensor. When a monocular camera is selected as an additional sensor, the process of measuring the relative distance after detecting objects in a tunnel should be performed before using these data as an indicator. This paper presents a modified inverse perspective transformation model that projects image pixels to the plane parallel to the ground. The image pixels are projected to the plane accounting for the distance and the height of the facility in the tunnel. Then, through the transformation model, the distance of the facility in the tunnel can be measured using a single camera sensor. The Samsungsan Tunnel located on National Highway 110 in South Korea was chosen for the experiment. The estimated distance results by the proposed method were compared with the LiDAR measurements obtained real-time time by computing the position errors for the longitudinal and lateral directions, separately. This study demonstrates the possibility of estimating a distance with only a monocular camera for precise positioning even in a tunnel. © ICROS 2023.

关键词： Optical radar

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