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2024 IEEE PES/IAS PowerAfrica, PowerAfrica 2024

作者： Gelchu, Milky Ali Ehnberg, Jimmy School of Electrical and Computer Engineering Addis Ababa University Addis Ababa Ethiopia Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden

ISBN: (纸本)9798350389388

To provide electricity to rural areas in sub-Saharan Africa that currently lack access, mini-grids have been considered a solution. However, the deployment of mini-grids is challenging in rural areas of sub-Saharan Africa, due to the low demand, discounted tariffs set by the public power authority, and the limited paying capacity of rural populations. As a result, many mini-grid proj ects in these areas heavily rely on financial aid from donors or government subsidies. While studies have explored ways to improve the bankability of installed mini-grids by incorporating productive uses, each with different load characteristics, there has been limited research on fixed-capacity mini-grids. This study aims to investigate how future load compositions can impact the bankability of rural mini-grids with a fixed capacity. The results indicate that the future load composition, specifically the integration of productive uses such as small bars and millers with the existing household load, can enhance the bankability of the mini-grid. © 2024 IEEE.

关键词： bankability load Composition mini-grid

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ADMM-Based Hybrid-Field Uplink Channel Estimation for Extremely Large-Scale MIMO Systems

ADMM-Based Hybrid-Field Uplink Channel Estimation for Extrem...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Li, Yiqing Jiang, Miao Guangdong University of Technology School of Computer Science and Technology Guangzhou510006 China Guangdong University of Technology School of Information Engineering Guangzhou510006 China

ISBN: (纸本)9798350345384

Extremely large-scale multiple-input multiple-output (XL-MIMO) is considered as a promising technique for upcoming sixth-generation (6G) mobile communication systems in improving the performance of current systems. However, XL-MIMO may face channel estimation challenges due to its high-dimensional channel. To reduce the pilot overhead for channel estimation, we exploit the channel sparsity in the uplink hybrid-field XL-MIMO system in 6G by utilizing both the far-field angle-domain dictionary and near-field polar-domain dictionary. Consequently, the channel estimation problem is formulated as an optimization problem with two 0-norm constraints. Due to the non-convexity of the resulting problem, we relax the 0-norm to 1-norm and propose an alternating direction method of multiplier (ADMM)-based algorithm. Finally, simulation results demonstrate that the proposed ADMM-based method achieves more than 2 dB performance gain over existing schemes based on orthogonal matching pursuit. © 2023 IEEE.

关键词： Channel estimation

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A comprehensive survey on 6G-security: physical connection and service layers

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Discover Internet of Things 2025年第1期5卷 1-30页

作者： Saeed, Mamoon M. Saeed, Rashid A. Hasan, Mohammad Kamrul Ali, Elmustafa Sayed Mazha, Tehseen Shahzad, Tariq Khan, Sunawar Hamam, Habib Sana00967 Yemen Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif21944 Saudi Arabia Department of Electronics Engineering College of Electronics Engineering Sudan University of Science and Technology Omdurman Sudan Bangi43600 Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Red Sea University Port Sudan33312 Sudan School of Computer Science National College of Business Administration and Economics Lahore54000 Pakistan Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal57000 Pakistan Department of Computer Science and Software Engineering International Islamic University Islamabad44000 Pakistan School of Electrical Engineering University of Johannesburg Johannesburg2006 South Africa BP 1989 Av. Grandes Ecoles Libreville Gabon Bridges for Academic Excellence-Spectrum Tunis Tunisia Department of Computer Science School Education Department Government of Punjab Layyah31200 Pakistan Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura140401 India

After adopting 5G technology, businesses and academia have started working on sixth-generation wireless networking (6G) technologies. Mobile communications options are expected to expand in areas where previous generations could not do so. 6G networks are anticipated to be constructed using various diverse technologies. These encompass diverse cutting-edge advancements, such as distributed ledger systems like blockchain, visible light communications (VLC), post-quantum cryptography, edge computing, molecular communication, THz, and other advances. These advances necessitate a reassessment of previous security strategies from a security perspective. In the future, networks must adhere to stricter criteria for authentication, encryption, access control, connectivity, and detection of harmful activities. Ensuring privacy and dependability necessitates the implementation of supplementary security protocols. The essay explores the primary concerns and challenges related to the security of the 6G network. This paper describes the improvements in security in communications from 1G through 6G. This paper divides security in the sixth generation into three layers: physical, connection, and service. Each layer-by-layer discusses the standard technologies and security issues for each technology proposed in each sixth-generation security layer. All proposed solutions for each of the three layers are discussed in Sixth Generation Security. It also reviews all proposed solutions for each layer, indicating the proposed solution and its limitations. © The Author(s) 2025.

关键词： 5G mobile communication systems

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Study of Ocean Pattern's and Ocean Bed Using Applications of IOT 2

Study of Ocean Pattern's and Ocean Bed Using Applications of...

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2nd International Conference on Emerging Trends in Information technology and engineering, ic-ETITE 2024

作者： Vishwanath, K. Reddy, Rachit Roy, Sritama Vellore Institute of Technology Department of Computer Science Chennai600127 India School of Electronics Engineering Vellore Institute of Technology Chennai600127 India

ISBN: (纸本)9798350328202

The ocean plays an integral role for influencing Earth's climate and sustaining diverse ecosystems as oceans covers almost 70 % of the earth's surface. It is important to monitor and control the ocean biodiversity through the advanced IoT technologies. The internet of Underwater things (IoUT) is an emerging technology which can connect the underwater objects as well as environment. IoUT is directly related with the navigation, disaster prediction, smart monitoring and intelligent system. Understanding the dynamics of the ocean is crucial for various applications, including weather forecasting, maritime operations, and environmental conservation. This research paper presents an in-depth analysis of an Ocean buoy Monitoring System that utilizes temperature, humidity, and geolocation data collected from buoys to predict ocean patterns, tides, and marine life. The system combines real-time sensor measurements with advanced data analysis techniques to provide valuable insights into oceanographic phenomena. © 2024 IEEE.

关键词： Buoys

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Model Uncertainty Estimation Based on a Dual-Module Neural Network Architecture 23

Model Uncertainty Estimation Based on a Dual-Module Neural N...

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23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Guo, Weiqing Zhang, Tianlun Peng, Dunlu Wang, Debby D. School of Science and Technology Hong Kong Metropolitan Universit Hong Kong Hong Kong School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China

ISBN: (纸本)9798331528041

In recent years, deep learning has achieved remarkable success in various fields, including biology and medicine. However, the interpretability and robustness still face challenges, as erroneous predictions can lead to serious consequences in critical applications. This paper introduces a new framework for estimating model uncertainty that can enhance the decision-making process. Compared to existing uncertainty estimation methods like Bayesian neural networks and Monte Carlo dropout, this paper provides a more direct way to model uncertainty by directly estimating the output variance through a dual-module neural network architecture. Without the need for multiple forward passes or complex Bayesian inference, it can reduce computational intensity. In specific, this framework consists of a prediction module for input processing and an uncertainty module for estimating prediction uncertainty. We demonstrate the efficiency of our method through applications in medical image segmentation and protein-ligand binding affinity prediction. By incorporating model uncertainty estimation, the proposed framework not only improves the accuracy of deep learning models, but also significantly reduces the computational burden which is especially beneficial for processing large datasets. © 2024 IEEE.

关键词： Prediction models

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A Novel Technique to Secure Telemedicine Using Blockchain and Visual Cryptography 1

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International Conference on. Cryptology and Network Security with Machine Learning, ICCNSML 2023

作者： Mittal, Poonam Vashista, Hariom Srivastava, Atul Department of Computer engineering J.C. Bose University of Science and Technology YMCA Faridabad India Amity School of Engineering and Technology AUUP Uttar Pradesh Lucknow India

ISBN: (数字)9789819706419

ISBN: (纸本)9789819706402

Medical facilities in the different regions of the world are not available as per requirement. More significantly, remote and rural areas have lots of scarcity of quality doctors and diagnosis facilities. Today, the whole world is connected via the Internet which can be used to facilitate medical prescription and diagnosis at distant places. Everything about these facilities is defined by a hypernym that is telemedicine. Medical data of the patients is very confidential and can be misused if someone is able to access the network and retrieve the data. Security mechanisms, such as digital watermarking and other primitive cryptographic technologies, are in use, but these technologies have their limitations. Therefore, there is a need to propose a security mechanism that can provide confidentiality, integrity, and authentication. The research proposes a security mechanism based on blockchain. The security features provided by blockchain, along with cryptographic primitives, can be used to safeguard the information. Most of the medical data is in an image format. The pixels of the data are arranged along with the patient's personal information, and a corresponding hash value is generated. Every terminal in the blockchain network is updated with the basic agreement and a hash value. It is protected with a proof-of-work mechanism which is very complex even to brute force. Along with this, elliptic curve digital signature algorithm and partial homomorphic encryption algorithm are also implemented to further ensure confidentiality, integrity, and authenticity of the data. The paper also presents a use case where we have used visual cryptography as a means to secure the medical images. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Telemedicine

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Wearable and interactive multicolored photochromic fiber display

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Light(Science & Applications) 2024年第3期13卷 454-465页

作者： Pan Li Yuwei Wang Xiaoxian He Yuyang Cui Jingyu Ouyang Ju Ouyang Zicheng He Jiayu Hu Xiaojuan Liu Hang Wei Yu Wang Xiaoling Lu Qian Ji Xinyuan Cai Li Liu Chong Hou Ning Zhou Shaowu Pan Xiangru Wang Huamin Zhou Cheng-Wei Qiu Yan-Qing Lu Guangming Tao State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and Engineering and Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Vascular Aging(HUST) Ministry of EducationWuhan 430030China School of Optoelectronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and ManipulationCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China School of Performing Arts Wuhan Conservatory of MusicWuhan 430060China School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Architecture and Urban Planning Huazhong University of Science and TechnologyWuhan 430074China School of Fashion Beijing Institute of Fashion TechnologyBeijing 100029China School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Tongji Medical College Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua UniversityShanghai 201620China

Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent,wearable interactive ***,significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight ***,we introduce a mass-produced,wearable,and interactive photochromic fiber that provides uniform multicolored light *** designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the *** impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission *** addition,we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single *** prepared fibers on mass-produced kilometer-long using the thermal drawing *** fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as *** work provides a new perspective and inspiration to the existing field of fiber display interaction,paving the way for future human–machine integration.

关键词： fiber interactive colored

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Unlocking New Opportunities for Crop Management Through Hyper Spectral Image Analysis 5th

Unlocking New Opportunities for Crop Management Through Hype...

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5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023

作者： Kumar, R. M. Sunil Agarwal, Trapty Mehta, Deepak Singh, Arjun School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bangalore India Department of Electronic and Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

Hyper spectral imaging has emerged as a reliable and accurate method of crop management. The era involves the usage of a couple of sensors of varying bandwidths to collect records throughout the complete electromagnetic spectrum. By using collecting data in dozens or maybe masses of spectral bands, hyper spectral imaging allows for the extraction of a mess of particular characteristics, making an allowance for extra precise analysis and insights. This technology lets in for stepped forward measurement and yields, permitting higher crop identity and classifications, in addition to stepped forward crop overall performance and yields. It is able to also potentially help to discover undesirable characteristics of a crop, such as disorder, nutrient deficiencies, or pest infestations. The analysis of hyper spectra also can be useful for assessing in-season stress elements, together with water deficiency, high temperatures, or competition with weeds. The use of hyper spectral imaging to research crops offers a huge range of potential packages, from monitoring growers’ fields to developing irrigation recommendation. By way of capitalizing on this effective new era, growers can gain extraordinary perception into crop health, permitting them to make informed decisions on how excellent to optimize their management techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： First Keyword Second Keyword Third Keyword

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An Analysis of the Use of Machine Learning to Enhance Online Digital Learning 8

An Analysis of the Use of Machine Learning to Enhance Online...

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8th International Conference on Electronics, Communication and Aerospace technology, ICECA 2024

作者： Acharjya, Pinaki Pratim Majumdar, Jayeeta Bera, Mihir Baran Barman, Subhabrata Sinha, Jayashri Deb Das, Moumita Haldia Institute of Technology Computer Science and Engineering Haldia India Haldia Institute of Technology School of Applied Science Haldia India Haldia India

ISBN: (纸本)9798350367904

Academic institutions' interest in online learning is rising at an exponential rate due to the rapid advancement of expertise. The Learning Management System (LMS) is a key component of the online learning architecture and is also used to mine student data. This study reviews and analyses the literature on machine learning (ML) in online education and machine learning integrated learning management systems (LMS). The goal of this study is to comprehend the different efforts made to employ different ML techniques to lessen the difficulties associated with online learning environments, or online LMSs. Increasing student performance by projecting future grades is just one of several obstacles. Other issues that can be resolved using machine learning include student retention and behavior analysis for performance enhancement. The paper presents the research that different authors have done in the relevant topic. The chosen time frame for the project remains close to the Covid19 years. © 2024 IEEE.

关键词： Federated learning

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High-Dimensional Multi-Label Data Stream Classification With Concept Drifting Detection

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IEEE Transactions on Knowledge and Data engineering 2023年第8期35卷 8085-8099页

作者： Li, Peipei Zhang, Haixiang Hu, Xuegang Wu, Xindong Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei230601 China Hefei University of Technology School of Computer Science and Information Engineering Hefei230601 China Second People's Hospital of Hefei Anhui Hefei230011 China Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of Education of China School of Computer Science and Information Engineering Anhui Hefei230002 China

Multi-label data streams such as Web texts and images have been popular on the Web. These data present the characteristics of multiple label, high dimensionality, high volume, high velocity and especial concept drift etc. Thus, multi-label data stream classification is a very challenging and significant task especially in the handling of high-dimensional data with concept drifts. However, this challenge has received little attention from the research community. Therefore, we propose the max-relevance and min-redundancy based algorithm adaptation approach for the efficient and effective classification on multi-label data streams with high-dimensional attributes and concept drifts. In order to reduce the impact from the high-dimensional data with noisy attributes, we first refine the minimal-redundancy-maximal-relevance criterion based on mutual information to select qualified features in multi-label data streams. Second, we propose the data distribution based concept drifting detection approach to distinguish concept drifts hidden in data streams. Finally, we build an incremental ensemble classification model for efficiently classifying multi-label data streams. Extensive studies show that our approach can get optimal subsets of features while maintaining a good performance in the multi-label classification, as compared to several state-of-the-art multi-label feature selection algorithms using two efficient multi-label classification methods as base classifiers. Meanwhile, our approach is superior to three well-known multi-label data stream classification approaches in the effectiveness and efficiency. © 1989-2012 IEEE.

关键词： Classification (of information)

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