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共 7021 条记录，以下是91-100 订阅

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Optimizing Mobility IoT Device Networks with Dynamic RIS in mMIMO-Cooperative NOMA 6G Systems 1

Optimizing Mobility IoT Device Networks with Dynamic RIS in ...

引用

1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Hassan, Khalil Hassan, Mohamed Hamid, Khalid Hassan, Elmuntaser Mokhtar, Rania A. Saeed, Mamoon M. Dept. of Comm. Systems Uni. of Science & Technology Omdurman Sudan Dept. of Electrical Eng. Omdurman Islamic Uni. Omdurman Sudan Dept. of Computer Science Al-Neelain University Khartoum Sudan Department of Computer Engineering Taif University Taif Saudi Arabia Yemen

ISBN: (纸本)9798331533557

Advanced technologies like reconfigurable intelligent surfaces (RISs), massive multiple-input multiple-output (mMIMO), and non-orthogonal multiple access (NOMA) are crucial for the upcoming 6G communications landscape, particularly for IoT applications. This study uniquely explores the effects of RIS dynamics on the performance of mMIMO downlink (DL) cooperative NOMA systems in dense IoT environments. It introduces a novel methodology for modeling dynamic traffic distribution and integrating RIS, focusing on key performance metrics such as network capacity, spectral efficiency (SE), latency, and energy efficiency (EE). Various scenarios are evaluated, considering different distributions of IoT devices and signal-to-noise ratios (SNRs). Using simulation software, the research analyzes performance under unstable channel conditions with varying device distances, speeds, and power locations, employing 256-QAM modulation and successive interference cancellation (SIC). The results demonstrate that dynamic RIS significantly enhances capacity, spectrum efficiency, latency, and EE, paving the way for optimized IoT network architecture in future wireless systems. © 2024 IEEE.

关键词： Quadrature amplitude modulation

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Study on Improving the Durability of Shaded Pole Induction Motors Used for Refrigerator Fans

Study on Improving the Durability of Shaded Pole Induction M...

引用

2024 International Conference on Electronics, Information, and Communication, ICEIC 2024

作者： Yeo, Jae-Hyeon Lee, Dong-Kyu Kim, Bong-Jik Kim, Gyu-Sik SPG Co. Ltd. Dept. of R&D Korea Republic of Univ. of Seoul Dept. of Electrical and Computer Eng. Korea Republic of

ISBN: (纸本)9798350371888

The shaded pole induction motor is simply a selfstarting single-phase induction motor whose one of the poles is shaded by the copper ring. Even though it has poor efficiency and the starting torque is very low, it is widely used, because of low cost and easy starting. The shaded pole induction motors used in cooling fans in refrigerators are generally well used, but in areas where the power supply is unstable, it sometimes leads to the faults such as motor coil disconnection. In this paper, the fan load tests and the locked rotor tests were performed in order to determine the operation status of the motor in overvoltage conditions. Through some experimental studies, it was found that the durability of the motor would be improved if the coil diameter became reduced and the coil leng.hened even in overvoltage conditions. © 2024 IEEE.

关键词： Poles

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Towards Sustainable Economic Zones with UAV-assisted Real-time Energy Replenishment in Wireless Rechargeable Sensor Networks 17

Towards Sustainable Economic Zones with UAV-assisted Real-ti...

引用

17th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2023

作者： Goyal, Riya Tomar, Abhinav Singal, Gaurav Netaji Subhas University of Technology Dept. of Computer Science and Eng. New Delhi Dwarka India

ISBN: (纸本)9798350307672

An economic zone is bound to have continuous monitoring and control by an autonomous surveillance system for better production competency and security. Wireless Rechargeable Sensor Networks (WRSNs) have gained popularity to provide reliable and sustainable energy supply for continual network operations. In economic zones, numerous sensor nodes are deployed for diverse activities that require continuous energy supply. However, the integration of WRSNs with UAVs has increased the efficiency of recharging the sensor nodes deployed in areas that are difficult to reach by mobile chargers. Nevertheless, UAVs' limited battery life limits their performance and range which requires efficient deployment of charging stations. This paper proposes an integration of the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithms to address the charging scheduling problem through efficient deployment of charging stations and finding the optimal charging scheduling path for UAVs. Simulation results demonstrate that the proposed scheme produces a shorter planning path, leading to a longer network lifespan than alternative approaches. © 2023 IEEE.

关键词： Ant colony optimization

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Replicability Study: Corpora For Understanding Simulink Models & Projects 17

Replicability Study: Corpora For Understanding Simulink Mode...

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17th ACM/IEEE International Symposium on Empirical Software eng.neering and Measurement, ESEM 2023

作者： Shrestha, Sohil Lal Chowdhury, Shafiul Azam Csallner, Christoph University of Texas at Arlington Computer Science & Eng. Dept. ArlingtonTX76019 United States

ISBN: (纸本)9781665452236

Background: Empirical studies on widely used model-based development tools such as MATLAB/Simulink are limited despite the tools' importance in various industries. Aims: The aim of this paper is to investigate the reproducibility of previous empirical studies that used Simulink model corpora and to evaluate the generalizability of their results to a newer and larger corpus, including a comparison with proprietary models. Method: The study reviews methodologies and data sources employed in prior Simulink model studies and replicates the previous analysis using SLNET. In addition, we propose a heuristic for determining code-generating Simulink models and assess the open-source models' similarity to proprietary models. Results: Our analysis of SLNET confirms and contradicts earlier findings and highlights its potential as a valuable resource for model-based development research. We found that open-source Simulink models follow good modeling practices and contain models comparable in size and properties to proprietary models. We also collected and distribute 208 git repositories with over 9k commits, facilitating studies on model evolution. Conclusions: The replication study offers actionable insights and lessons learned from the reproduction process, including valuable information on the generalizability of research findings based on earlier open-source corpora to the newer and larger SLNET corpus. The study sheds light on noteworthy attributes of SLNET, which is self-contained and redistributable. © 2023 IEEE.

关键词： Simulink

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Proof of Equation: A Novel Consensus Algorithm for Dynamic Spectrum Access 16

Proof of Equation: A Novel Consensus Algorithm for Dynamic S...

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16th IEEE AFRICON, AFRICON 2023

作者： Silva, Thiwanka Bamunuge, Madhushika Dissanayake, Dilusha Seneviratne, Chatura Gamage, Tharindu Liyanage, Madhusanka University of Ruhuna Faculty of Engineering Dept. of Electrical and Information Eng. Sri Lanka School of Computer Science University College of Dublin Ireland

ISBN: (纸本)9798350336214

The future of communication technology is moving from 5G to 6G with new innovations. Blockchain (BC) is a such immersive technology that significantly impacts the betterment of communication technology. BC-based spectrum-sharing solutions can be used in Dynamic Spectrum Access (DSA) systems to fulfill the need for secure and efficient communication. With the invention of cognitive radio networks, DSA became a popular topic for the scientific community. Spectrum misuse/violations can occur due to the rapid growth of spectrum sharing. As the system is open to malicious attacks, licensed spectrum owners must be identified and verified. However, the existing BC-based DSA solutions are more expensive, non-optimized, and lack spectrum misuse detection. This paper proposes a novel consensus algorithm called 'Proof of Equation' for spectrum misuse detection. The core of the proposed algorithm is a consensus score calculation based on a numerical equation with three parameters rather than using cryptographic calculations. The performance of the proposed algorithm is studied using Python simulations, and simulation results show that the proposed algorithm outperforms the Proof of Work (PoW) and Proof of Stake (PoS) consensus algorithms in terms of block production time. © 2023 IEEE.

关键词： Smart contract

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A 24-28 GHz Frequency Synthesizer for Millimeter Wave Radar Application

A 24-28 GHz Frequency Synthesizer for Millimeter Wave Radar ...

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2024 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2024

作者： Chen, Jheng.Long Peng. Kang-Chun Ins. Eng. Science and Technology National Kaohsiung Univ. Science and Technology Kaohsiung Taiwan Dept. Computer and Comm. Eng. National Kaohsiung Univ. Science and Technology Kaohsiung Taiwan

ISBN: (纸本)9798350389210

This paper presents the developed 24-28 GHz frequency synthesizer for millimeter-wave radar applications, incorporating a phase noise filter (PNF) at the input stage of the phase-frequency detector (PFD) to enhance in-band phase noise suppression. Measurement results show that the PNF effectively reduces phase noise from -88.6 dBc/Hz to -97 dBc/Hz at a 10 kHz frequency offset with a locking time of less than 68 us. © 2024 IEEE.

关键词： Frequency synthesizers

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Unmasking Harmful Comments: An Approach to Text Toxicity Classification Using Machine Learning in Native Language

Unmasking Harmful Comments: An Approach to Text Toxicity Cla...

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2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2024

作者： Ahsan, Afia Islam, Mohammad Manzurul Chowdhury, Abdullahi Ali, Md Sawkat Jabid, Taskeed Islam, Maheen Dept. of Computer Science and Eng. East West University Dhaka Bangladesh UniSA Online University of South Australia Adelaide Australia

ISBN: (纸本)9798331533137

In the modern digital era, social media plays a central role in our everyday lives, bringing both advantages and obstacles. While it facilitates global communication and trade, it also brings significant negative impacts, such as the spread of toxic comments that can lead to severe consequences, including mental distress and, in extreme cases, suicide. This study centers on classifying toxic comments by utilizing three different machine learning models: the Stochastic Gradient Descent (SGD) Classifier, the baseline Support Vector Machine (SVM), and an Optimized SVM model. A dataset comprising text comments in both Bangla and eng.ish, collected from various social media platforms, was used to train these models. The initial SVM model, while powerful, showed limitations, particularly in handling class imbalance, leading to suboptimal performance. The SGD Classifier provided a balanced approach but fell short in recall for non-harmful comments. To address these challeng.s, an Optimized SVM model was developed by fine-tuning key hyperparameters, significantly enhancing the model’s performance. The optimized model achieved superior accuracy, precision, recall, and F1-scores across both harmful and non-harmful comment classifications. Our results demonstrate that the Optimized SVM model is the most reliable and effective among the three, making it the preferred choice for deployment in real-world scenarios where accurate classification of toxic comments is critical. ©2024 IEEE.

关键词： Stochastic systems

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Multi-Objective Algorithms for Learning Open-Ended Robotic Problems 10

Multi-Objective Algorithms for Learning Open-Ended Robotic P...

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10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Robert, Martin Brodeur, Simon Ferland, Francois Universite De Sherbrooke Dept. of Math and Informatics Sherbrooke Canada Menya AI division Levio Sherbrooke Canada Universite De Sherbrooke Dept. of Electrical Eng. and Computer Eng Sherbrooke Canada

ISBN: (纸本)9798350373011

Quadrupedal locomotion is a complex, open-ended problem vital to expanding autonomous vehicle reach. Traditional reinforcement learning approaches often fall short due to training instability and sample inefficiency. We propose a novel method leveraging multi-objective evolutionary algorithms as an automatic curriculum learning mechanism, which we named Multi-Objective Learning (MOL). Our approach significantly enhances the learning process by projecting velocity commands into an objective space and optimizing for both performance and diversity. Tested within the MuJoCo physics simulator, our method demonstrates superior stability and adaptability compared to baseline approaches. As such, it achieved 19% and 44% fewer errors against our best baseline algorithm in difficult scenarios based on a uniform and tailored evaluation respectively. This work introduces a robust framework for training quadrupedal robots, promising significant advancements in robotic locomotion and open-ended robotic problems. © 2024 IEEE.

关键词： Contrastive Learning

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Studying Power Loss Minimization in Active Distribution Systems Using PMD

Studying Power Loss Minimization in Active Distribution Syst...

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2025 IEEE Texas Power and Energy Conference, TPEC 2025

作者： Ullah, Irfan Butler-Purryjs, Karen L. Bent, Russell Nagarajan, Harsha Barnes, Arthur Texas A&M University Electrical & Computer Eng. Dept. United States Los Alamos National Laboratory Los AlamosNM United States

ISBN: (纸本)9798331541125

This study investigates the minimization of power losses in active distribution systems through the integration of Distributed Energy Resources (DERs) into a modified 20-node section of the IEEE 123-node test feeder. Using the Distribution Optimal Power Flow (D-OPF) framework, implemented in Julia using the PowerModelsDistribution (PMD) package and the IPOPT solver, the analysis incorporates 5 photovoltaic distributed generators (DGs), spanning both single-phase and three-phase systems. The framework optimizes active and reac-tive power flows while ensuring voltage stability. Comparative results demonstrated that the proposed framework effectively reduces power losses, balances PV generation, and maintains voltage profiles within permissible limits. The approach was validated through a strong alignment with results from a previous study, with minor deviations attributed to differences in tool methodologies. This study underscores the potential of advanced optimization frameworks to enhance the efficiency and per-formance of power distribution networks, paving the way for the future integration of larger-scale DERs and more complex systems. © 2025 IEEE.

关键词： Distributed energy

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Enhancing Lymph Node Classification in Rectal Cancer MRI Images Through a Multi-Model Approach

Enhancing Lymph Node Classification in Rectal Cancer MRI Ima...

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2024 IEEE International Conferences of AI, science, eng.neering, and Technology, AIxSET 2024

作者： Gupta, Rishit Iwahori, Yuji Funahashi, Kenji Bhuyan, M.K. Bhatt, Manish Kijsirikul, Boonserm Wang, Aili Ouchi, Akira Shimizu, Yasuhiro Indian Institute of Technology Guwahati Dept. of Electronics & Electrical Eng. Assam Guwahati India Chubu University Dept. of Computer Science Kasugai Japan Nagoya Institute of Technology Dept. of Computer Science Nagoya Japan Chulalongkorn University Dept. of Computer Engineering Bangkok Thailand Harbin University of Science and Technology Higher Educational Key Laboratory Harbin China Aichi Cancer Center Hospital Dept. of Gastroenterological Surgery Nagoya Japan

ISBN: (纸本)9798350390995

Rectal cancer remains to be a major issue worldwide, necessitating accurate and precise methods for proper classification of lymph nodes in MRI scan images to guide treatment decisions. The use of deep learning based techniques can help with the task of classification. This research focuses on enhancing the process of lymph node classification in rectal cancer MRI images by using a multi-model approach. Firstly, we explore the use of diffusion models in data augmentation, to produce synthetic lymph node images to counter the issue of limited dataset size. Secondly, Real-ESRGAN and Swin2SR super-resolution techniques are examined for their ability to improve image quality and hence enhance the accuracy of lymph node classifications. Lastly, ConvNeXt is employed as an advanced technique used to improve overall performance at classifying lymph nodes for rectal cancer. Through a series of detailed experiments on the dataset consisting of T2-Weighted Axial MRI scans from 54 patients, we demonstrate the effectiveness of our approach in classification of lymph nodes. The metrics like accuracy and precision exhibit significant improvements, highlighting the superiority of our multi-model approach. © 2024 IEEE.

关键词： Magnetic resonance imaging

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