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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Dai, Jiongyu Mahboob, Shadab Wang, Haining Liu, Lingjia Virginia Tech Bradley Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798331517786

The increased number of connected devices and diverse quality of service demands in cellular networks present formidable challenges for efficient traffic management. In this paper, we present a handover control approach to tackle these challenges in 5G networks, integrating the Proximal Policy Optimization (PPO) framework with Reservoir Computing (RC). Our approach, aligned with the O-RAN architecture, offers a near-real-time solution for intelligent handover management, improving cell performance, and enhancing user experience. This renders our solution O-RAN compliant and deployable as an 'xApp' on the RAN Intelligent Controller (RIC). The introduced algorithm features a sequential state design including user-specific and cell-specific metrics. Harnessing the power of reservoir computing, our solution captures dynamic changes in state sequences while reducing training overhead and enhancing online training efficiency. The efficacy of our algorithm is demonstrated through evaluations on the ns3 platform, proving its superiority in system-level simulations. The experimental results affirm the effectiveness of the introduced algorithm in addressing the dynamic challenges of handover in cellular networks. © 2024 IEEE.

关键词： Deep reinforcement learning

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Influence of Rise Time on the Aging of Electric Machine Windings

Influence of Rise Time on the Aging of Electric Machine Wind...

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2024 IEEE Conference on electrical Insulation and Dielectric Phenomena, CEIDP 2024

作者： Arafat, Easir Rahman, Md Asifur Islam, Farzana Ghassemi, Mona Laboratory Department of Electrical and Computer Engineering RichardsonTX United States

ISBN: (纸本)9798350366679

This study examines how fast rise times, which are common in modern power electronics and drive systems, affect the aging of electric machine windings. It focuses on how to ensure these windings can last longer and work reliably in electrical systems. A twisted pair magnet wire with insulation commonly used in wound machines was used to get experimental data to understand how different voltage waveforms can influence endurance testing of motor insulation systems powered by inverters. Unlike past studies that looked at comparatively slower rise times and fewer repetitions, this research specifically addresses the challenges posed by next-generation wide bandgap (WBG)-based conversion systems. These systems operate at very high speeds, up to 100 kV/μs, and switch frequencies up to 500 kHz, where both frequency and rise time are crucial factors affecting insulation aging over time. © 2024 IEEE.

关键词： Machine windings

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Blockchain Breakthrough: A Review of its Role in Modern Technology 2

Blockchain Breakthrough: A Review of its Role in Modern Tech...

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Asthana, Sameer Chaturvedi, Ravi Prakash Mishra, Annu Nayyar, Poorva Shaliyar, Md. Greater Noida Institute of Technology Department of Computer Science and Engineering Greater Noida India Sharda School of Engineering and Technology Department of Computer Science and Applications Greater Noida India Sharda School of Engineering and Technology Department of Computer Science and Engineering Greater Noida India

ISBN: (纸本)9798350368109

This article summarizes the Blockchain technology along with the artificial intelligence. The cutting edge technology is described in a elaborated manner along with its advantages, disadvantages and its impact with the artificial intelligence. There are various sectors in which it is used and the outcomes are discussed. The proficiency of blockchain has proved its reliability and threshold in different domains. © 2024 IEEE.

关键词： artificial intelligence blockchain ledger security

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Cultivating Cluster Enactment in Wireless Sensor Networks Through Hybrid Metaheuristics Intended for Energy Optimization

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SN computer science 2025年第3期6卷 1-12页

作者： Kushwaha, Ajay Goswami, Anjali Sharada, K. Sharma, Manmohan Berar, Gagandeep Edara, Deepak Chowdary Department of Computer Science and Engineering Rungta College of Engineering and Technology R1 CG Bhilai India Department of Mathematics and Statistics College of Science and Theoretical Studies Saudi Electronic University Riyadh 13323 Saudi Arabia Department of Computer Science and Engineering GITAM (Deemed to be University) AP Visakhapatnam India Department of Computer Science and Engineering Manipal University Jaipur Rajasthan Jaipur India Department of Computer Science and Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Department of CSE Vignan’s Foundation for Science Technology and Research Vadlamudi AP Guntur India

Though traditional search methods shine when faced with local goals and a plethora of decision factors, they could struggle when faced with engineering design limitations. On the other hand, metaheuristic approaches promise to find global optima in real-world optimization problems, even in nonlinear and multimodal settings. In order to improve cluster head selection in Wireless Sensor Networks (WSNs), this research presents a new metaheuristic method that combines the principles of Cuckoo Search method (CSA) and Selection by Optimization (SBO). When choosing a Chief Cluster Head (CCH), the CSA algorithm takes hop count into account, whereas SBO finds the best cluster heads by considering communication range. By comparing the suggested approach to both stand-alone SBO and CSA methods, we can see how well it performs in terms of throughput, latency, energy usage, delivery ratio, and packet overhead. The combined SBO-CSA method improves cluster performance, simplifies cluster head selection in WSNs, and increases network efficiency overall, according to the results. To prove its efficacy in enhancing network performance, the suggested solution outperforms standalone SBO and CSA approaches across a range of performance parameters, such as throughput, latency, energy consumption, and packet overhead. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： CCH CH CSA Metaheuristic methods SBO

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Deep Learning Approaches for Multi-target Weather Patterns Forecasting in Bangladesh 5th

Deep Learning Approaches for Multi-target Weather Patterns F...

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5th International Conference on electrical and Electronics engineering, ICEEE 2024

作者： Mumu, Sumaiya Siddiqua Sultana, Syeda Samia Adnan, Imranul Islam Waughfa, Mohammed Z. Department of Computer Science and Engineering Ahsanullah University of Science and Technology Dhaka Bangladesh

ISBN: (纸本)9789819791118

Weather forecasting in countries like Bangladesh poses unique challenges, given its diverse geographical features. The region experiences varying weather patterns influenced by factors such as monsoons, river systems, and coastal influences. The intricacies of high temperatures, sudden atmospheric changes, and complex circulations demand advanced forecasting methods. The research aimed to address the challenges in weather prediction for 8 cities in Bangladesh. The research used 3 deep learning models: CNN(Conv1D), LSTM, and GRU. Comparing these models to get the best results for temperature, rainfall, and humidity prediction. The performance of the models was evaluated using standard techniques, including the Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). In individual forecasts for Maximum Temperature and Rainfall, GRU shows the lowest RMSE for Rainfall, while LSTM excels in Maximum Temperature prediction. Conv1D proves highly effective in Humidity forecasting. Our investigation emphasizes GRU’s superior performance across eight cities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mean square error

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A Modified Code Design for Punctured Polar Codes 15

A Modified Code Design for Punctured Polar Codes

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Lee, Sang-Yoon Ju, Hyosang Park, Jisang Kim, Sang-Hyo Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350364637

In this paper, we suggest modified code design for punctured polar codes. To apply polar codes in practical wireless communication environments, rate matching is crucial. However, the polarization weight (PW) algorithm, a representative channel-agnostic code design method, does not fully account for the punctured polar codes scenario. We introduce a penalty function into the existing PW. This modification evaluates the reliability of source bits more accurately and prevents almost incapable bits to be left as information bits. The simulation results demonstrate that the proposed code design outperforms the conventional PW-based code design in various puncturing scenarios. © 2024 IEEE.

关键词： Codes (symbols)

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A Comprehensive Study of Sequential Model Predictive Control Methods for Multilevel Inverters 50

A Comprehensive Study of Sequential Model Predictive Control...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Le, Hoang Dekka, Apparao Department of Electrical and Computer Engineering Lakehead University Thunder Bay Canada

ISBN: (纸本)9781665464543

Due to the low computational burden, sequential model predictive control (SMPC) methods have emerged as promising solutions for multilevel inverters (MLIs). Over the years, several SMPC approaches focusing on either load current or load voltage as the primary objective have been explored for MLIs. These methods have adopted philosophies such as cost function with weighting factors, offline switching vector selection or inherent strategies to minimize common-mode voltage (CMV). However, the literature lacks a comprehensive analysis of SMPC methods with CMV minimization and their pros and cons on system performance. To fill the research gap, this paper presents the philosophies behind various SMPC methods for four-level inverters (FLIs), along with the mathematical models utilized in SMPC implementation and case studies to highlight their performances. Finally, a comparative analysis of SMPC methods is provided, aiding researchers in selecting suitable methods for their applications. © 2024 IEEE.

关键词： Predictive control systems

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Ophthalmic Diseases Detection using CNN: A Comparative Analysis of ResNet and VGG Architectures 16

Ophthalmic Diseases Detection using CNN: A Comparative Analy...

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16th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Al Razi, Alif Khan, Zarif Ul Sami, Zawwad Khan, Mohammad Monirujjaman North South University Department of Electrical and Computer Engineering Dhaka Bangladesh

ISBN: (纸本)9798331505264

Ocular illnesses present a considerable risk to worldwide public health, frequently resulting in visual impairment or blindness if not identified and addressed appropriately. This study focuses on the essential task of automated identification of eye diseases via convolutional neural network (CNN) models. With the increasing availability of digital retinal imaging data, there is a critical need for precise and efficient diagnostic tools to aid healthcare personnel in identifying common eye diseases, including diabetic retinopathy, cataracts, glaucoma, and normal eye conditions. The majority of eye disease diagnoses now occur through manual examination by ophthalmologists, which can be laborious and prone to inter-observer variability. By leveraging CNN architectures like VGG19, VGG16, ResNet18, and ResNet50, we propose a robust framework for automated eye disease detection. Our methods involve preprocessing retinal images, training CNN models on labeled datasets, and evaluating their performance on unseen data. Our results showcase high classification accuracy, sensitivity, and specificity across all disease categories. Specifically, our models achieved an accuracy of 92% for VGG19, 91% for VGG16, 87% for ResNet18, and 85% for ResNet50. The findings offer a promising solution to streamline the diagnostic process and improve access to timely eye care services. Integrating this CNN-based system into clinical workflows can expedite diagnosis, enable early intervention, and prevent vision loss, contributing to advancements in computer-aided diagnosis systems and enhancing efficiency in medical imaging analysis. © 2024 IEEE.

关键词： Ophthalmology

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Introduction to Reinforcement Learning for Torpedo Guidance with Obstacle Avoidance 15

Introduction to Reinforcement Learning for Torpedo Guidance ...

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Lee, Hyunsoo Kim, Joongheon Korea University Department of Electrical and Computer Engineering Seoul Korea Republic of

ISBN: (纸本)9798350364637

This paper explores the application of reinforcement learning (RL) to torpedo guidance with a focus on obstacle avoidance and target acquisition in dynamic environments. By employing a dual-actor network approach and a regularization technique for the critic network, the proposed method demonstrates robust performance in scenarios with random obstacle placements and target directions. Our results show that the system effectively navigates toward the target while avoiding obstacles, leveraging reinforcement learning to optimize torpedo trajectories. The study addresses the challenges of overestimation and underestimation biases common in reinforcement learning methods, such as deep deterministic policy gradient (DDPG), by utilizing the double actors and regularized critics (DARC) algorithm. This approach has potential implications for enhancing the autonomy and efficiency of military applications in complex and uncertain settings. © 2024 IEEE.

关键词： Torpedoes

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Efficient Implementation of High-Fidelity Models of IPMSM Drive Systems in Offline and Real-Time Simulators 3

Efficient Implementation of High-Fidelity Models of IPMSM Dr...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Tahim, Ekamjot Singh Kaushik, Abhay Rahman, Shadman Saqlain Ramesh, Rahul Raman Jatskevich, Juri University of British Columbia Department of Electrical and Computer Engineering Vancouver Canada

ISBN: (纸本)9798331540319

Interior permanent magnet synchronous machines (IPMSMs) are widely used in industrial applications, electric propulsion and precision applications. Accurate and efficient simulations of IPMSM drives are essential for the design and tuning of such systems. Field-oriented control (FOC) is commonly used to achieve precise control by decoupling the stator currents into flux- and torque-controlling components. The FOC-based controllers, however, require addressing the nonlinear flux-current relationships in IPMSMs caused by saliency, magnetic saturation, and cross-coupling effects. Different methods, such as parameter estimation and look-up tables (LUTs) techniques, are used to model these nonlinearities, with LUTs offering accuracy but demanding substantial memory allocation. Alternatively, memory-compact models such as polynomial-based models are used when systems impose constraints on memory allocation. This paper presents the efficient implementation of both the LUT-based and polynomial-based IPMSM drive system models for offline and real-time simulators. The accuracy of the models is verified through offline studies performed in MATLAB/Simulink and OPAL-RT's OP5700 real-time simulator. The obtained results demonstrate the difference in system resource utilization, such as memory requirement and computational efficiency, when using LUT-based and polynomial-based IPMSM models. © 2024 IEEE.

关键词： MATLAB

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