检索结果-内蒙古大学图书馆

From light sensing to adaptive learning:hafnium diselenide reconfigurable memcapacitive devices in neuromorphic computing

引用

Light(Science & Applications) 2025年第1期14卷 215-226页

作者： Bashayr Alqahtani Hanrui Li Abdul Momin Syed Nazek El-Atab Electrical and Computer Engineering Program Computer Electrical Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)ThuwalSaudi Arabia Electrical Engineering Department College of EngineeringPrincess Nourah Bint Abdulrahman University(PNU)RiyadhSaudi Arabia

Advancements in neuromorphic computing have given an impetus to the development of systems with adaptive behavior,dynamic responses,and energy efficiency *** charge-based or emerging memory technologies such as memristors have been developed to emulate synaptic plasticity,replicating the key functionality of neurons—integrating diverse presynaptic inputs to fire electrical impulses—has remained *** this study,we developed reconfigurable metal-oxide-semiconductor capacitors(MOSCaps)based on hafnium diselenide(HfSe2).The proposed devices exhibit(1)optoelectronic synaptic features and perform separate stimulus-associated learning,indicating considerable adaptive neuron emulation,(2)dual light-enabled charge-trapping and memcapacitive behavior within the same MOSCap device,whose threshold voltage and capacitance vary based on the light intensity across the visible spectrum,(3)memcapacitor volatility tuning based on the biasing conditions,enabling the transition from volatile light sensing to non-volatile optical data *** reconfigurability and multifunctionality of MOSCap were used to integrate the device into a leaky integrate-and-fire neuron model within a spiking neural network to dynamically adjust firing patterns based on light stimuli and detect exoplanets through variations in light intensity.

关键词： integrate volatile integrating

来源：评论

学校读者我要写书评

暂无评论

Intelligent integrated sensing and communication:a survey

引用

Science China(Information Sciences) 2025年第3期68卷 5-46页

作者： Jifa ZHANG Weidang LU Chengwen XING Nan ZHAO Naofal AL-DHAHIR George K.KARAGIANNIDIS Xiaoniu YANG School of Information and Communication Engineering Dalian University of Technology College of Information Engineering Zhejiang University of Technology School of Information and Electronics Beijing Institute of Technology Department of Electrical and Computer Engineering The University of Texas at Dallas Department of Electrical and Computer Engineering Aristotle University of Thessaloniki

Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.

关键词： artificial intelligence deep learning deep reinforcement learning federated learning generative artificial intelligence integrated sensing and communication machine learning transfer learning

来源：评论

学校读者我要写书评

暂无评论

New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond Communications

引用

computer Modeling in engineering & Sciences 2024年第3期138卷 2749-2767页

作者： Shimaa M.Amer Ashraf A.M.Khalaf Amr H.Hussein Salman A.Alqahtani Mostafa H.Dahshan Hossam M.Kassem Electronics and Communications Engineering Department Higher Institute of Engineering and TechnologyKafr ElsheikhEgypt Electronics and Electrical Communications Engineering Department Faculty of EngineeringMinia UniversityMiniaEgypt Electronics and Electrical Communications Engineering Department Faculty of EngineeringTanta UniversityTantaEgypt Electronics and Electrical Communications Engineering Department Faculty of EngineeringHorus University EgyptNew DamiettaEgypt Department of Computer Engineering College of computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia School of Computing Mathematics and EngineeringCharles Sturt UniversityBathurstNSW2795Australia

Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to ***,it improves the array gain and directivity,increasing the detection range and angular resolution of radar *** study proposes two highly efficient SLL reduction *** techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,*** convolution process determines the element’s excitations while the GA optimizes the element *** M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,*** the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher *** the increased HPBWof the odd and even excitations,the element spacing is optimized using the ***,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the ***,for extreme SLL reduction,the DConv/GA is *** this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation *** provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.

关键词： Array synthesis convolution process genetic algorithm(GA) half power beamwidth(HPBW) linear antenna array(LAA) side lobe level(SLL) quality of service(QOS)

来源：评论

学校读者我要写书评

暂无评论

Impact of Different Integration Times on Distributions of Rain Rates for Predictions of Rain Attenuation

引用

Progress in Electromagnetics Research C 2025年 154卷 229-238页

作者： Hassan, Mohammad Rofiqul Rafiqul, Islam Md. Habaebi, Mohamed Hadi Suriza, Ahmad Zabidi Badron, Khairayu Budalal, Asma Ali Mahfuz, Md. Mahmudul Hasan Department of Electrical and Computer Engineering Faculty of Engineering International Islamic University Malaysia Jalan Gombak Kuala Lumpur53100 Malaysia College of Electrical and Electronics Technology Benghazi Libya Department of Electrical and Computer Engineering Concordia University Canada

All wireless communication systems are moving towards higher and higher frequencies day by day which are severely attenuated by rains in outdoor environment. To design a reliable RF system, an accurate prediction method of rain attenuation is established and used globally based on local rain intensity measurement. Required rain intensity used for attenuation prediction is generally measured at a point with 1-min integration time or converted from higher integration time to 1-min. Recent measurements of rain intensity with a 10-second integration time indicate that intensity is not uniform over a 1-minute duration. Consequently, the statistics of rain intensity distribution and attenuation predictions are influenced by measurements with integration times shorter than 1 minute. It has been established that an integration time of 0.01% provides the optimal fit for actual rain rate data. This paper presents the rain intensity distributions from data measured with 2-min, 1-min, 30-sec, 20-sec, and 10-sec integration times, and it has impact on rain rate distributions as well as rain attenuation predictions. © 2025, Electromagnetics Academy. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

引用

Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

来源：评论

学校读者我要写书评

暂无评论

LSTM-SAC reinforcement learning based resilient energy trading for networked microgrid system

AIMS Electronics and Electrical Engineering

引用

AIMS electronics and electrical engineering 2025年第2期9卷 165-191页

作者： Sharma, Desh Deepak Bansal, Ramesh C. Department of Electrical Engineering MJP Rohilkhnad University Bareilly India Electrical Engineering Department University of Sharjah Sharjah United Arab Emirates Department of Electrical Electronics & Computer Engineering University of Pretoria Pretoria South Africa

On the whole, the present microgrid constitutes numerous actors in highly decentralized environments and liberalized electricity markets. The networked microgrid system must be capable of detecting electricity price changes and unknown variations in the presence of rare and extreme events. The networked microgrid system comprised of interconnected microgrids must be adaptive and resilient to undesirable environmental conditions such as the occurrence of different kinds of faults and interruptions in the main grid supply. The uncertainties and stochasticity in the load and distributed generation are considered. In this study, we propose resilient energy trading incorporating DC-OPF, which takes generator failures and line outages (topology change) into account. This paper proposes a design of Long Short-Term Memory (LSTM) - soft actor-critic (SAC) reinforcement learning for the development of a platform to obtain resilient peer-to-peer energy trading in networked microgrid systems during extreme events. A Markov Decision Process (MDP) is used to develop the reinforcement learning-based resilient energy trade process that includes the state transition probability and a grid resilience factor for networked microgrid systems. LSTM-SAC continuously refines policies in real-time, thus ensuring optimal trading strategies in rapidly changing energy markets. The LSTM networks have been used to estimate the optimal Q-values in soft actor-critic reinforcement learning. This learning mechanism takes care of the out-of-range estimates of Q-values while reducing the gradient problems. The optimal actions are decided with maximized rewards for peer-to-peer resilient energy trading. The networked microgrid system is trained with the proposed learning mechanism for resilient energy trading. The proposed LSTM-SAC reinforcement learning is tested on a networked microgrid system comprised of IEEE 14 bus systems. ©2025 the Author(s), licensee AIMS Press.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Binary feature mask optimization for feature selection

引用

Neural Computing and Applications 2025年第6期37卷 5155-5167页

作者： Lorasdagi, Mehmet E. Turali, Mehmet Y. Kozat, Suleyman S. Department of Electrical and Electronics Engineering Bilkent University Ankara06800 Turkey Department of Electrical and Computer Engineering University of California Los Angeles Los Angeles United States

We investigate feature selection problem for generic machine learning models. We introduce a novel framework that selects features considering the outcomes of the model. Our framework introduces a novel feature masking approach to eliminate the features during the selection process, instead of completely removing them from the dataset. This allows us to use the same machine learning model during feature selection, unlike other feature selection methods where we need to train the machine learning model again as the dataset has different dimensions on each iteration. We obtain the mask operator using the predictions of the machine learning model, which offers a comprehensive view on the subsets of the features essential for the predictive performance of the model. A variety of approaches exist in the feature selection literature. However, to our knowledge, no study has introduced a training-free framework for a generic machine learning model to select features while considering the importance of the feature subsets as a whole, instead of focusing on the individual features. We demonstrate significant performance improvements on the real-life datasets under different settings using LightGBM and multilayer perceptron as our machine learning models. Our results show that our methods outperform traditional feature selection techniques. Specifically, in experiments with the residential building dataset, our general binary mask optimization algorithm has reduced the mean squared error by up to 49% compared to conventional methods, achieving a mean squared error of 0.0044. The high performance of our general binary mask optimization algorithm stems from its feature masking approach to select features and its flexibility in the number of selected features. The algorithm selects features based on the validation performance of the machine learning model. Hence, the number of selected features is not predetermined and adjusts dynamically to the dataset. Additionally, we openly s

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

Skin lesion classification using transfer learning

引用

Soft Computing 2024年第20期28卷 12337-12343页

作者： Nivedhitha, G. Kalpana, P. Sidthik, A. Sheik Rani, V. Anusha Singh, Ajith B. Rajagopal, R. Department of Computer Science and Engineering Sri Krishna College of Technology Tamil Nadu Coimbatore India Department of Electrical and Electronics Engineering VSB College of Engineering and Technical Campus Tamilnadu Coimbatore642109 India Department of Electronics and Instrumentation Engineering Saveetha Engineering College Tamilnadu Chennai India Department of Electrical and Electronics Engineering Sri Krishna College of Technology Tamil Nadu Coimbatore India Department of Electrical and Electronics Engineering Francis Xavier Engineering College Tirunelveli India

This work presents an essential module for the Transfer Learning approach's classification of melanoma skin lesions. Melanoma, a highly lethal form of skin cancer, poses a significant health threat globally. Image analysis plays a crucial role in enhancing the accuracy of malignant skin lesion classification. Although neural networks trained on extensive datasets have emerged as the latest solution, their scalability remains a challenge. This study proposes an efficient method for classifying skin lesions utilizing labelled data from open sources, leveraging EfficientNet as the foundational model to robustly capture discriminative features from diverse visual perspectives. Validation of the proposed algorithms relies on the classifier's capacity to distinguish between classes is measured by the Area Under the Receiver Operating Characteristic (AUC-ROC) curve. AUC-ROC score greater than zero denotes better classification performance. Our proposed model achieves an impressive score of 98.65%. In contrast to existing approaches, our method demonstrates swift and accurate identification and segmentation of melanoma skin lesions, showcasing its efficacy in advancing the field of skin lesion classification. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Dermatology

来源：评论

学校读者我要写书评

暂无评论

Advancing Deepfake Detection Using Xception Architecture:A Robust Approach for Safeguarding against Fabricated News on Social Media

引用

computers, Materials & Continua 2024年第12期81卷 4285-4305页

作者： Dunya Ahmed Alkurdi Mesut Cevik Abdurrahim Akgundogdu College of Information Engineering Al-Nahrain UniversityBaghdad10011Iraq Department of Electrical and Computer Engineering Altinbas UniversityIstanbul34000Turkey Electrical and Electronics Engineering Department Istanbul University-CerrahpasaIstanbul34320Turkey

Deepfake has emerged as an obstinate challenge in a world dominated by ***,the authors introduce a new deepfake detection method based on Xception *** model is tested exhaustively with millions of frames and diverse video clips;accuracy levels as high as 99.65%are *** are the main reasons for such high efficacy:superior feature extraction capabilities and stable training mechanisms,such as early stopping,characterizing the Xception *** methodology applied is also more advanced when it comes to data preprocessing steps,making use of state-of-the-art techniques applied to ensure constant *** an ever-rising threat from fake media,this piece of research puts great emphasis on stringent memory testing to keep at bay the spread of manipulated *** also justifies better explanation methods to justify the reasoning done by the model for those decisions that build more trust and *** ensemble models being more accurate have been studied and examined for establishing a possibility of combining various detection frameworks that could together produce superior ***,the study underlines the need for real-time detection tools that can be effective on different social media sites and digital ***,protecting privacy,and public awareness in the fight against the proliferation of deepfakes are important *** significantly contributing to the advancements made in the technology that has actually advanced detection,it strengthens the safety and integrity of the cyber world with a robust defense against ever-evolving deepfake threats in ***,the findings generally go a long way to prove themselves as the crucial step forward to ensuring information authenticity and the trustworthiness of society in this digital world.

关键词： Deepfake Detection Xception architecture data processing image processing intelligent information systems social media security

来源：评论

学校读者我要写书评

暂无评论

Hybrid Recommender System Using Systolic Tree for Pattern Mining

引用

computer Systems Science & engineering 2023年第2期44卷 1251-1262页

作者： S.Rajalakshmi K.R.Santha Department of Computer Science Engineering Sri Venkateswara College of EngineeringSriperumbudurIndia Department of Electrical and Electronics Engineering Sri Venkateswara College of EngineeringSriperumbudurIndia

A recommender system is an approach performed by e-commerce for increasing smooth users’*** pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of *** work will present the implementation of sequence pattern mining for recommender systems within the domain of *** work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender *** feature selec-tion's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target *** will mitigate the feature vector's dimensionality by eliminating redundant,irrelevant,or noisy *** work pre-sents a new hybrid recommender system based on optimized feature selection and systolic *** features were extracted using Term Frequency-Inverse Docu-ment Frequency(TF-IDF),feature selection with the utilization of River Forma-tion Dynamics(RFD),and the Particle Swarm Optimization(PSO)*** systolic tree is used for pattern mining,and based on this,the recommendations are *** proposed methods were evaluated using the MovieLens dataset,and the experimental outcomes conﬁrmed the efﬁciency of the *** was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborativeﬁltering,the precision of 0.89 was achieved.

关键词： Recommender systems hybrid recommender systems frequent pattern mining collaborativeﬁltering systolic tree river formation dynamics particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：