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Novel PM-Assisted Model of the Two-Layer Sub-Harmonic Synchronous Machines

Novel PM-Assisted Model of the Two-Layer Sub-Harmonic Synchr...

引用

2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023

作者： Sajjad Hossain Rafin, S.M. Ali, Qasim Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Dept. of Electrical and Computer Engineering MiamiFL United States Sukkur Iba University Dept. of Electrical Engineering Sukkur Pakistan

ISBN: (纸本)9781733509633

In this paper, a new pm-assisted model has been developed for the already introduced two-layer sub-harmonic synchronous machine. This work aims to increase the torque-producing capability of the brushless wound rotor machines while keeping the use of rare earth magnets to a minimum. A 2D finite element analysis has been performed to validate the proposed model and compare the performance with the reference model. The results in the paper demonstrate that the proposed machine's average torque has increased. © 2023 ACES.

关键词： Rare earths

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REINFORCEMENT LEARNING FOR UNRELATED PARALLEL MACHINE SCHEDULING WITH RELEASE DATES, SETUP TIMES, AND MACHINE ELIGIBILITY

REINFORCEMENT LEARNING FOR UNRELATED PARALLEL MACHINE SCHEDU...

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2024 Winter Simulation Conference, WSC 2024

作者： Cho, Sang-Hyun Kim, Hyun-Jung Mönch, Lars Dept. of Industrial and Systems Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Dept. of Mathematics and Computer Science University of Hagen Universitätsstraße 1 Hagen58097 Germany

ISBN: (纸本)9798331534202

This paper presents a novel approach for solving unrelated parallel machine scheduling problems through reinforcement learning. Notably, we consider three main constraints: release date, machine eligibility, and sequence- and machine-dependent setup time to minimize total weighted tardiness. Our work presents a new graph representation for solving the problem and utilizes graph neural networks combined with reinforcement learning. Experimental results show that our proposed method outperforms traditional dispatching rules and an apparent tardiness cost-based algorithm. Furthermore, since we represent and solve the problem using graphs, our method can be used regardless of the number of jobs or machines once trained. © 2024 IEEE.

关键词： Adversarial machine learning

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Reliability-Based Design of Time-Varying Electricity Tariff 31

Reliability-Based Design of Time-Varying Electricity Tariff

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31st International Conference on Electrical engineering, ICEE 2023

作者： Rastegar, Mohammad Sarajpoor, Nima School of Electrical and Computer Engineering Shiraz University Shiraz Iran University of Calgary Dept. of Electrical and Software Eng. Calgary Canada

ISBN: (纸本)9798350312560

Implementing price-based energy management programs to change the consumption pattern of residential consumers has become an indispensable solution to the operational challenges of smart distribution power systems. However, practical methods to design efficient time-varying prices to improve the reliability and operation of distribution systems have remained scarce. This paper proposes a bi-objective optimization problem to design time-differentiated electricity tariff for residential energy management, where a new reliability evaluation method is employed to evaluate the reliability enhancement caused by load shifting. A set of numerical studies and sensitivity analysis are conducted to investigate the effectiveness of the proposed pricing method. © 2023 IEEE.

关键词： Energy management

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Angle of Arrival Estimation Using SRS in 5G NR Uplink Scenarios

Angle of Arrival Estimation Using SRS in 5G NR Uplink Scenar...

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2024 Work-in-Progress in Hardware and software for Location Computation, WIPHAL 2024

作者： Spanos, Thodoris Fabra, Fran López-Salcedo, José A. Seco-Granados, Gonzalo Kanistras, Nikos Lapin, Ivan Paliouras, Vassilis Dept. of Electrical and Computer Engineering University of Patras Greece Loctio Greece Spain Radio Navigation Systems and Techniques Section European Space Agency Netherlands

This paper presents a comprehensive exploration of Angle of Arrival (AoA) estimation techniques in 5G environments, using the Sounding Reference Signal (SRS) in Uplink scenarios both in simulations and with actual measurements. Leveraging 5G capabilities, we investigate AoA algorithms for single-base station positioning. The study includes simulations and practical tests on a developed dedicated testbed featuring a base station equipped with a three-element Uniform Linear Array (ULA), considering Line of Sight conditions in an open environment. The testbed, employing Ettus E312 as the transmitter and Ettus N310 as the receiver, details waveform structures and reception processes. Additionally, our study examines the performance of Angle of Arrival (AoA) estimation algorithms, such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariant Techniques (ESPRIT), and Joint Angle and Delay Estimation (JADE) ESPRIT. A MATLAB ray tracing propagation model of the environment where the measurements are conducted, has been constructed. Simulation results using this model are presented, along with the actual measurements. The obtained results affirm the effectiveness of our implementation. © 2024 Copyright for this paper by its authors.

关键词： Multiple signal classification

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Multi-Task Bias-Variance Trade-Off Through Functional Constraints 48

Multi-Task Bias-Variance Trade-Off Through Functional Constr...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Cervino, Juan Bazerque, Juan Andrés Calvo-Fullana, Miguel Ribeiro, Alejandro University of Pennsylvania Dept. of Electrical and Systems Engineering Philadelphia United States University of Pittsburgh Dept. of Electrical and Computer Engineering Pittsburgh United States Universitat Pompeu Fabra Dept. of Information and Communication Technologies Barcelona Spain

ISBN: (纸本)9781728163277

Multi-task learning aims to acquire a set of functions, either regressors or classifiers, that perform well for diverse tasks. At its core, the idea behind multi-task learning is to exploit the intrinsic similarity across data sources to aid in the learning process for each individual domain. In this paper we draw intuition from the two extreme learning scenarios - a single function for all tasks, and a task-specific function that ignores the other tasks dependencies - to propose a bias-variance trade-off. To control the relationship between the variance (given by the number of i.i.d. samples), and the bias (coming from data from other task), we introduce a constrained learning formulation that enforces domain specific solutions to be close to a central function. This problem is solved in the dual domain, for which we propose a stochastic primal-dual algorithm. Experimental results for a multi-domain classification problem with real data show that the proposed procedure outperforms both the task specific, as well as the single classifiers. © 2023 IEEE.

关键词： Constrained Learning Multi-task Learning

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Optimizing 3D Flight Paths for Multiple UAVs with Connectivity Management in Urban Delivery systems 19

Optimizing 3D Flight Paths for Multiple UAVs with Connectivi...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Lee, Yeongmin Syahran, Raihan Muhammad Spangenberger, Mael Yang, Huigyu Oh, Jiyong Choo, Hyunseung Dept. of Artificial Intelligence Sungkyunkwan University Suwon Korea Republic of Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of Convergence Research Institute Sungkyunkwan University Suwon Korea Republic of Dept. of AI Systems Engineering Sungkyunkwan University Suwon Korea Republic of Dept. of Informatics Télécom SudParis Évry France

ISBN: (纸本)9798331507817

The dynamic deployment of aerial vehicles in urban delivery scenarios demands precise route planning, reliable data links, and efficient use of network infrastructure. Although prior efforts have explored various aspects of unmanned navigation or communication optimization, existing approaches often overlook the combined impact of three-dimensional path selection and robust connectivity maintenance. To address this gap, this paper proposes a deep reinforcement learning framework employing Independent Proximal Policy Optimization (IPPO) to steer the flight paths of unmanned vehicles while curtailing needless interactions with base stations (BSs). By incorporating communication-specific metrics, Reference Signal Received Power (RSRP), the proposed system adapts to urban conditions and upholds resilient network links. Comprehensive performance evaluations reveal the potential of the framework to reduce excessive BS connections by up to 82.24%, preserve RSRP levels above -80 dBm, and balance handover frequencies across flight trajectories. These findings affirm the scalability and effectiveness of the method for achieving efficient aerial navigation and consistent communication in urban delivery services. © 2025 IEEE.

关键词： Deep reinforcement learning

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Robust Phishing URL Classification Using FastText Character Embeddings and Hybrid Deep Learning 3

Robust Phishing URL Classification Using FastText Character ...

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3rd IEEE International Conference on Robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Al-Sakib, Abdullah Limon, Zishad Hossain Sakib, Anamul Pranto, Md Nuruzzaman Islam, Md Ariful Sultana, Shayma Ahmed, Md. Redwan Rahman, Shafiur Westcliff University Dept. of Information Technology CA92614 United States Westcliff University Dept. of Computer Science CA92614 United States International American University Dept. of Business Administration CA90010 United States International American University Dept. of Management Information System CA90010 United States East West University Dept. of Computer Science and Engineering Dhaka1212 Bangladesh Daffodil International University Dept. of Software Engineering Dhaka1216 Bangladesh

ISBN: (纸本)9798331534400

Phishing attacks are a major cybersecurity threat that resulted in over 1.2 million incidents in the first half of 2020. These attacks caused substantial financial losses and posed risks to individuals and organizations. Being able to identify fraudulent websites is crucial in order to effectively address these potential risks. This study introduces a novel method for detecting phishing URLs by using word and character embeddings to capture complex URL patterns. We used a dataset of 80,000 URLs, including 50,000 legitimate ones and 30,000 phishing instances, and applied thorough preprocessing techniques. We utilized word embeddings in FastText to handle unseen words, with the added advantage of n-gram representations. Additionally, we captured character-level features through dense character embeddings. We trained several machine learning and deep learning models, and one model, the Convolutional Bidirectional LSTM (CBiLSTM), stood out with an accuracy of 99.01% and an F1-score of 99.08%. Furthermore, we made a thorough comparison with the most advanced techniques available, and our findings demonstrated clear superiority over previous research. This study presents an effective approach for classifying phishing URLs, providing a valuable tool to combat fraud and protect against identity theft, thereby helping to minimize the financial and emotional harm experienced by victims. © 2024 IEEE.

关键词： Phishing

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CDP: Selective Influential Nodes Based on Cliques in the Diffusion Process in Social Networks 9

CDP: Selective Influential Nodes Based on Cliques in the Dif...

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9th International Conference on Web Research, ICWR 2023

作者： Yazdanifar, Fatemeh Beni, Hamid Ahmadi Salimi, Nikoo Bouyer, Asgarali Amirkabir University of Technology Dept. of Mathematics and Computer Science Tehran Iran Madani University Dept. Software Engineering Azarbijan Shahid Tabriz Iran University of Genoa Dept. of the Elec. Electronics Electronics and Telecommunication Eng. and Naval Architecture Genoa Italy Azarbaijan Shahid Madani University Dept. of Computer Engineering Tabriz Iran

ISBN: (纸本)9798350399691

Influence maximization techniques emphasize selecting a set of influential nodes in order to maximize influence. Because the algorithms presented in this field ignore the topology of cliques for diffusion, there are two major challenges in influence maximization algorithms: optimal diffusion and computational overhead reduction. As a result, the CDP algorithm is presented in this article to address these issues. This algorithm first selects suitable cliques for diffusion based on their position and strategy in social networks. Furthermore, for each clique, a score is calculated based on the topological criteria of the clique, and suitable cliques are selected for diffusion by applying a threshold limit. The seed nodes are chosen from the cliques in the second step. To avoid the rich club phenomenon, only a few nodes from each clique are chosen as seed candidate nodes. Finally, the seed nodes are chosen based on the node's topology and the strength of the node's level one neighbor. In the experiment section, the CDP algorithm significantly outperforms the best algorithms presented in recent years in terms of influence spread rate and execution time. © 2023 IEEE.

关键词： Diffusion

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Movement-Based Interaction: An Approach to Visual and Auditory Stimulus and Memory 6

Movement-Based Interaction: An Approach to Visual and Audito...

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6th Experiment at International Conference, exp.at 2023

作者： Nogueira, Maria Rita Menezes, Paulo Institute of Systems and Robotics University of Coimbra Coimbra Portugal University of Coimbra Dept. of Electrical and Computer Engineering Coimbra Portugal

ISBN: (纸本)9798350314403

Movement-based interaction design is an innovative field that leverages the body's natural movements to create intuitive and engaging interfaces. This approach takes a sensorial approach to visual and auditory memory, seeking to enhance user engagement and create more meaningful experiences. The use of movement-based interfaces has significant implications for senior citizens, who may have mobility limitations or cognitive impairments. Using movement-based interfaces, seniors can engage in physical activity and maintain cognitive function, essential aspects for healthy aging. Movement-based interfaces can also help children develop physical coordination, cognitive skills, and social interaction. Furthermore, movement-based interaction design can benefit everyone's physical well-being by promoting physical activity and reducing sedentary behavior. Studies have demonstrated that movement-based interfaces can enhance posture, physical activity levels, and general health. By combining movement with sensory experiences, movement-based interaction design can create a more engaging and enjoyable experience for users, which can motivate them to maintain physical and cognitive health. In this article, we present two case studies that research the effectiveness of movement-based interaction design in enhancing visual and auditory memory. Overall, the results of these case studies suggest that movement-based interaction design is an effective approach to enhancing visual and auditory memory. The introduction of movement-based interfaces can give participants a more enjoyable and memorable experience, improving user engagement and information retention. © 2023 IEEE.

关键词： Machine learning

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An Introduction to Power Electronics Design Methodology

An Introduction to Power Electronics Design Methodology

引用

2023 IEEE Design Methodologies Conference, DMC 2023

作者： Rafin, Sm Sajjad Hossain Hussein, Hossam Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Dept. of Electrical and Computer Engineering MiamiFL United States

ISBN: (纸本)9798350315547

The development of effective and dependable electronic systems for a variety of applications, from renewable energy systems and electric vehicles to industrial automation and consumer electronics, depends heavily on power electronics design techniques. Moreover, the power electronics design technique offers a methodical way to create high-performance, dependable, and efficient electronic systems, which helps scholars and engineers address the unique requirements of varied applications while taking thermal management, electromagnetic interference, and safety considerations by integrating theoretical analysis, simulation tools, prototyping, and testing. The effectiveness of this methodology is further increased by the ongoing development of power semiconductor and design methodologies, which makes it possible to realize cutting-edge and environmentally friendly power electronic solutions for the modern world. Considering above mentioned importance, this paper is written as an initial guideline for scholars and engineers to design power electronic systems. © 2023 IEEE.

关键词： Design

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