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Canadian Conference on Electrical and computer engineering (CCECE)

作者： Ahmed Khalid Rana Asif Rehman Byung-Seo Kim Department of Computer Science National University of Computer & Emerging Sciences Pakistan Dept. of Software and Communications Engineering Hongik University Sejong-si South Korea

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

Underwater wireless sensor network (UWSN) is a communication paradigm that works in underwater environment such as in oceans, rivers, lakes, and seas. Multiple sensors are deployed in underwater that collect information according to user demand and forwards the data towards the Underwater Autonomous Vehicle (UAV) that send the data towards the ship or user. UWSN is based on Internet Protocol (IP). There are several limitations in existing IP based architecture such as data redundancy, location dependency, mobility. Therefore, there is need for a new network that enhance the network efficiently. Named Data Network (NDN) is a new communication paradigm that provides several built-in benefits such as in-network caching, mobility, avoid data duplication, and fast content retrieval time. In case of NDN based UWSN (NUWSN), network traffic increases due to bandwidth and large propagation delay. Due to dynamic nature of water the ratio of traffic load, packet duplication, packet retransmission increases. When delay is large then more packets can loss and more number of packet retrans-mission, and data duplication occurs. Therefore, there is need for efficient forwarding mechanism in NUWSN that minimize data duplication and packet retransmission. In this paper, we proposed a forwarding mechanism named as Reliable Forwarding Strategy in NDN based UWSN (RFSNU). RFSNU improves the forwarding process in underwater environment using depth based forwarding. Our scheme improves packets retransmission rate, and packet duplication that are main problems in NUWSN.

关键词： Wireless communication Wireless sensor networks Protocols Redundancy Telecommunication traffic Sensors Rivers

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Fed-Sophia: A Communication-Efficient Second-Order Federated Learning Algorithm

arXiv

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arXiv 2024年

作者： Elbakary, Ahmed Issaid, Chaouki Ben Shehab, Mohammad Seddik, Karim ElBatt, Tamer Bennis, Mehdi University of Oulu Finland Department of Electronics and Communications Engineering American University Cairo Egypt Department of Computer Science and Engineering American University Cairo Egypt Department of Electronics and Communications Engineering Cairo University Egypt

Federated learning is a machine learning approach where multiple devices collaboratively learn with the help of a parameter server by sharing only their local updates. While gradient-based optimization techniques are widely adopted in this domain, the curvature information that second-order methods exhibit is crucial to guide and speed up the convergence. This paper introduces a scalable second-order method, allowing the adoption of curvature information in federated large models. Our method, coined Fed-Sophia, combines a weighted moving average of the gradient with a clipping operation to find the descent direction. In addition to that, a lightweight estimation of the Hessian's diagonal is used to incorporate the curvature information. Numerical evaluation shows the superiority, robustness, and scalability of the proposed Fed-Sophia scheme compared to first and second-order baselines. © 2024, CC BY.

关键词： Deep neural networks

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Fed-Sophia: A Communication-Efficient Second-Order Federated Learning Algorithm

Fed-Sophia: A Communication-Efficient Second-Order Federated...

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IEEE International Conference on communications (ICC)

作者： Ahmed Elbakary Chaouki Ben Issaid Mohammad Shehab Karim Seddik Tamer ElBatt Mehdi Bennis Centre for Wireless Communications (CWC) University of Oulu Finland Department of Electronics and Communications Engineering American University in Cairo Egypt Department of Computer Science and Engineering American University in Cairo Egypt Department of Electronics and Communications Engineering Cairo University Egypt

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

关键词： Federated learning Scalability Estimation Robustness Numerical models Servers Task analysis

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Feasibility Study of a Hybrid Renewable Energy System for a Remote Rural Community Using HOMER Pro 9

Feasibility Study of a Hybrid Renewable Energy System for a ...

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9th IEEE International Conference on Power and Energy, PECon 2022

作者： Yap, Christine Monique F. Bismark, Kent Marc Kobe C. Caballa, Lorenzo Gabriel C. Pena, Robert Alfie S. Parocha, Raymark C. Macabebe, Erees Queen B. School of Science and Engineering Ateneo de Manila University Ateneo Energy Research Lab Department of Electronics Computer and Communications Engineering Quezon City1108 Philippines

ISBN: (数字)9781665409902

ISBN: (纸本)9781665409902

As the Philippines strives towards energy security, there remains the concern for reliable and stable electricity in rural areas due to the lack of access to the main grid and the high cost of expansion. Standalone energy systems in rural areas can increase energy security from local renewable sources such as solar, wind, and water resources. This study modeled and designed a hybrid renewable energy system (HRES) in a remote rural community using HOMER Pro simulations. The goal is to assess the feasibility of integrating solar and wind energy resources with the existing micro-hydro power plant to provide 24/7 electricity in the community. A techno-economic assessment and an implementation strategy of the HRES are presented in this paper. Results show that the optimal HRES configuration has an additional cost of energy of PHP 3.98 per kW and includes 84-kW solar PV panels, 84 batteries, and a 27-kW converter. These can be integrated into the existing 10-kW micro-hydro power system. Together with the hardware technical specifications and system configuration, this contribution provides cost calculations, and has identified approaches to add to the overall system's long-term sustainability. © 2022 IEEE.

关键词： Distributed power generation

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A simple method for generating wideband dual-chirp microwave waveforms based on monolithic integrated laser

A simple method for generating wideband dual-chirp microwave...

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2023 International Topical Meeting on Microwave Photonics, MWP 2023

作者： Chen, Shilin Pu, Tao Wang, Li Zheng, Jilin Wu, Gengze Li, Jin Zhang, Xin Zhao, Jiaqi Army Engineering University of PLA College of Communications Engineering Nanjing China Nanjing Vocational College of Information Technology Communication Department Nanjing China College of Communications Engineering Army Engineering University of PLA Nanjing China Nanjing University of Science and Technology ZiJin College Computer Department Nanjing China College of Information and Communication National University of Defense Technology Wuhan China

ISBN: (纸本)9798350342215

A method of generating broadband dual-linear frequency modulation signal microwave waveforms (DCMWs) based on monolithic integrated laser is proposed and verified by simulation. In this scheme, under the appropriate bias current, the integrated mutual injection semiconductor laser enters the P1 state, and then the linear frequency modulation signal is directly modulated to the front-end laser. In the simulation experiment demonstration, three kinds of DCMWs in the frequency range of 5~9 GHz are obtained, and the time bandwidth product (TBWP) reaches 800. The full width at half maximum (FWHM) of the three kinds of DCMWs are all less than 0.34 ns, and the peak sidelobe ratio (PSR) is higher than 15.1 dB. The scheme has the advantages of high integration, simple structure and easy regulation. © 2023 IEEE.

关键词： Microwave photonics

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Data-Aided Channel Estimation for Time Diversity in Helicopter Satellite communications 15

Data-Aided Channel Estimation for Time Diversity in Helicopt...

引用

15th International Conference on Advanced Technologies for communications, ATC 2022

作者： Kojima, Toshiharu Azuma, Riki Graduate School of Informatics and Engineering The University of Electro-Communications Department of Computer and Network Engineering 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan

ISBN: (数字)9781665451888

ISBN: (纸本)9781665451888

The periodic blockage of the transmission channel is the most important issue in helicopter satellite communications. Time diversity is a practical solution to overcome it, requiring channel estimation to implement maximal ratio combining (MRC). This paper proposes a channel estimation method for helicopter satellite communications employing time diversity. The proposed method estimates the channel gain by removing modulation from the received signal using the provisional demodulated data. The estimation is rapid and accurate. In addition, signal processing is simple. computer simulation shows that the degradation of bit error rate performance of MRC due to channel estimation error is under 0.1 dB. © 2022 IEEE.

关键词： Channel estimation

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Optimization Ensemble Weights Model for Wind Forecasting System

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computers, Materials & Continua 2022年第11期73卷 2619-2635页

作者： Amel Ali Alhussan El-Sayed M.El-kenawy Hussah Nasser AlEisa M.El-SAID Sayed A.Ward Doaa Sami Khafaga Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Electrical Engineering Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Delta Higher Institute of Engineering and Technology(DHIET) Mansoura35111Egypt Department of Electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairo11629Egypt Faculty of Engineering Delta University for Science and TechnologyGamasaMansoura11152Egypt

Effective technology for wind direction forecasting can be realized using the recent advances in machine ***,the stability and safety of power systems are expected to be significantly ***,the unstable and unpredictable qualities of the wind predict the wind direction a challenging *** paper proposes a practical forecasting approach based on the weighted ensemble of machine learning *** weighted ensemble is optimized using a whale optimization algorithm guided by particle swarm optimization(PSO-Guided WOA).The proposed optimized weighted ensemble predicts the wind direction given a set of input *** conducted experiments employed the wind power forecasting dataset,freely available on Kaggle and developed to predict the regular power generation at seven wind farms over forty-eight *** recorded results of the conducted experiments emphasize the effectiveness of the proposed ensemble in achieving accurate predictions of the wind *** addition,a comparison is established between the proposed optimized ensemble and other competing optimized ensembles to prove its ***,statistical analysis using one-way analysis of variance(ANOVA)and Wilcoxon’s rank-sum are provided based on the recorded results to confirm the excellent accuracy achieved by the proposed optimized weighted ensemble.

关键词： Guided Whale Optimization Algorithm(Guided WOA) forecasting machine learning weighted ensemble model wind direction

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MIRA: A Method of Federated MultI-Task Learning for LaRge LAnguage Models

arXiv

引用

arXiv 2024年

作者： Elbakary, Ahmed Issaid, Chaouki Ben ElBatt, Tamer Seddik, Karim Bennis, Mehdi University of Oulu Finland Department of Electronics and Communications Engineering American University in Cairo Egypt Department of Computer Science and Engineering American University in Cairo Egypt Department of Electronics and Communications Engineering Cairo University Egypt

In this paper, we introduce a method for fine-tuning Large Language Models (LLMs), inspired by Multi-Task learning in a federated manner. Our approach leverages the structure of each client’s model and enables a learning scheme that considers other clients’ tasks and data distribution. To mitigate the extensive computational and communication overhead often associated with LLMs, we utilize a parameter-efficient fine-tuning method, specifically Low-Rank Adaptation (LoRA), reducing the number of trainable parameters. Experimental results, with different datasets and models, demonstrate the proposed method’s effectiveness compared to existing frameworks for federated finetuning of LLMs in terms of average and local performances. The proposed scheme outperforms existing baselines by achieving lower local loss for each client while maintaining comparable global performance. © 2024, CC BY.

关键词： Federated learning

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MECG-E: Mamba-based ECG Enhancer for Baseline Wander Removal

MECG-E: Mamba-based ECG Enhancer for Baseline Wander Removal

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Hung, Kuo-Hsuan Wang, Kuan-Chen Liu, Kai-Chun Chen, Wei-Lun Lu, Xugang Tsao, Yu Lin, Chii-Wann National Taiwan University Department of Biomedical Engineering Taiwan Research Center for Information Technology Innovation Academic Sinica Taiwan University of Massachusetts Amherst College of Information and Computer Sciences United States National Institute of Information and Communications Technology Japan

ISBN: (纸本)9798350362480

Electrocardiogram (ECG) is an important non-invasive method for diagnosing cardiovascular disease. However, ECG signals are susceptible to noise contamination, such as electrical interference or signal wandering, which reduces diagnostic accuracy. Various ECG denoising methods have been proposed, but most existing methods yield suboptimal performance under very noisy conditions or require several steps during inference, leading to latency during online processing. In this paper, we propose a novel ECG denoising model, namely Mamba-based ECG Enhancer (MECG-E), which leverages the Mamba architecture known for its fast inference and outstanding nonlinear mapping capabilities. Experimental results indicate that MECG-E surpasses several well-known existing models across multiple metrics under different noise conditions. Additionally, MECG-E requires less inference time than state-of-the-art diffusion-based ECG denoisers, demonstrating the model's functionality and efficiency. © 2024 IEEE.

关键词： Electrocardiograms

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Contrast enhancement of optical videoscope images

引用

Iran Journal of computer Science 2023年第3期6卷 261-275页

作者： Ammar, Reda Aboshosha, Sahar El-Hag, Noha A. Saifeldeen, Reda El-Shafai, Walid El-Banby, Ghada M. Ashiba, Huda I. Khalaf, Ashraf A. M. Elazm, Atef Abou El-Rabaie, El-Sayed M. Abd El-Samie, Fathi E. El-Safrawey, Amir Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Comm. Faculty of Engineering Minia University Minya Egypt Department of Management of Information Systems Higher Institute of Commercial Science El-Mahala El-Kobra Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Department of Electronics and Electrical Communications Engineering Bilbis Higher Institute of Engineering Sharqia Bilbis Egypt Security Engineering Laboratory Computer Science Department Prince Sultan University Riyadh 11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia

The videoscope (VS) images have poor quality and low contrast. Hence, in this paper, three proposed frameworks to improve the quality of VS images are presented. The first framework depends on contrast-limited adaptive histogram equalization (CLAHE) with adaptive gamma correction. The second framework depends on homomorphic processing. The third framework is based on the homomorphic enhancement with histogram equalization. The first one is superior from the entropy perspective, while the third one is superior from the contrast perspective. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Fuzzy enhancement Histogram equalization Homomorphic enhancement Spectral entropy

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