检索结果-内蒙古大学图书馆

An Intelligent Big Data Security Framework Based on AEFS-KENN Algorithms for the Detection of Cyber-Attacks from Smart Grid Systems

引用

Big Data Mining and Analytics 2024年第2期7卷 399-418页

作者： Sankaramoorthy Muthubalaji Naresh Kumar Muniyaraj Sarvade Pedda Venkata Subba Rao Kavitha Thandapani Pasupuleti Rama Mohan Thangam Somasundaram Yousef Farhaoui Department of Electrical and Electronics Engineering CMR College of Engineering&TechnologyHyderabad 501401India Department of Electronics and Communication Engineering Vardhaman College of Engineering KacharamShamshabad 501218India Department of Electronics and Communication Engineering Sreenidhi Institute of Science and TechnologyHyderabad 501301India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600062India Department of Electrical and Electronics Engineering Bharat Institute of Engineering and TechnologyHyderabad 501510India Department of Computer Science and Engineering Amrita School of ComputingAmrita Vishwa VidhyapeethamBengaluru 560035India T-IDMS Department of Computer ScienceFaculty of Sciences and TechniquesMoulay Ismail UniversityErrachidia 52000Morocco

Big data has the ability to open up innovative and ground-breaking prospects for the electrical grid,which also supports to obtain a variety of technological,social,and financial *** is an unprecedented amount of heterogeneous big data as a consequence of the growth of power grid technologies,along with data processing and advanced *** main obstacles in turning the heterogeneous large dataset into useful results are computational burden and information *** original contribution of this paper is to develop a new big data framework for detecting various intrusions from the smart grid systems with the use of AI ***,an AdaBelief Exponential Feature Selection(AEFS)technique is used to efficiently handle the input huge datasets from the smart grid for boosting ***,a Kernel based Extreme Neural Network(KENN)technique is used to anticipate security vulnerabilities more *** Polar Bear Optimization(PBO)algorithm is used to efficiently determine the parameters for the estimate of radial basis ***,several types of smart grid network datasets are employed during analysis in order to examine the outcomes and efficiency of the proposed AdaBelief Exponential Feature Selection-Kernel based Extreme Neural Network(AEFS-KENN)big data security *** results reveal that the accuracy of proposed AEFS-KENN is increased up to 99.5%with precision and AUC of 99%for all smart grid big datasets used in this study.

关键词： smart grid Machine Learning(ML) big data analytics AdaBelief Exponential Feature Selection(AEFS) Polar Bear Optimization(PBO) Kernel Extreme Neural Network(KENN)

来源：评论

学校读者我要写书评

暂无评论

Genome-wide exploratory analysis for NARAC dataset with preparation for haplotype block partitioning through minor allele frequency quality control viewpoint

引用

Iran Journal of computer science 2023年第4期6卷 387-396页

作者： Saad, Mohamed N. Zareef, Galena W. Ibrahim, Fatma S. Said, Ashraf M. Hamed, Hisham F. A. Biomedical Engineering Department Faculty of Engineering Minia University Minia Egypt Biomedical Engineering Department Misr University for Science and Technology 6th of October City Egypt Bioinformatics Department Faculty of Computer and Information Minia University Minia Egypt Computer and Software Engineering Department Misr University for Science and Technology 6th of October City Egypt Department of Electrical Engineering Faculty of Engineering Egyptian-Russian University Cairo Egypt Electrical and Electronics Engineering Department Faculty of Engineering Minia University Minia Egypt

This article provides a detailed description, analysis, and visualization of a case–control genome-wide genotypic dataset from the North American Rheumatoid Arthritis Consortium (NARAC). The data is presented in terms of the number of females and males in both cases and controls, as well as the percentage of missing data. The number of alleles and genotypes is also counted, and the minor allele frequency (MAF) is calculated for each single nucleotide polymorphism (SNP). The data is further classified into four categories based on the SNP's MAF, namely, very rare, rare, low frequency, and common SNPs. The regions of these categories in the chromosome are investigated to determine the proportion of SNPs in coding locations and other regions. It is observed that each category has a different proportion in each region of consequence annotation. The data composition in terms of alleles and genotypes is found to be greatly disproportionate. The results present clear insights into the data and its MAF, which can be compared with other datasets. These findings can aid researchers in gaining a comprehensive understanding of such case–control datasets and bring accurate insights into the data. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Genome-wide association study Genome-wide exploratory analysis Minor allele frequency Single nucleotide polymorphism Variant annotation

来源：评论

学校读者我要写书评

暂无评论

Advancing Sustainable IoT Appliance Load Monitoring Through Edge-Enabled Federated Transfer Learning

Advancing Sustainable IoT Appliance Load Monitoring Through ...

引用

2024 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2024

作者： Natarajan, Yuvaraj Wadhwa, Gitanjali Sri Preethaa, K.R. Sundaram, Karthic Rama Abirami, K. Kpr Institute of Engineering and Technology Computer Science and Engineering Coimbatore641407 India Dresden01062 Germany Curtin University Faculty of Engineering and Science Department of Electrical and Computer Engineering Malaysia

ISBN: (纸本)9798350357905

Non-intrusive Appliance Load Monitoring (NALM) is essential for efficient electricity consumption tracking in households, promoting eco-friendly practices, and cost reduction. Privacy concerns in real-world NALM implementations can be addressed using federated learning. However, challenges persist, such as limited training data, edge model customization, and resource constraints. We introduce a practical federated learning framework for NALM, leveraging cloud-based model compression, collaborative data collection, and personalized edge and multi-task learning models through unsupervised transfer learning. Our advanced load monitoring model offers precise energy disaggregation through real-world experimentation, making it a leading solution for non-intrusive appliance load monitoring on edge devices. It maintains excellent learning performance and user privacy. Future research should aim to enhance federated learning efficiency and tackle remaining challenges in practical NALM implementations © 2024 IEEE.

关键词： Cost reduction

来源：评论

学校读者我要写书评

暂无评论

Highly efficient ternary organic solar cells with excellent open-circuit voltage and fill factor via precisely tuning molecular stacking and morphology

引用

science China Chemistry 2024年第3期67卷 963-972页

作者： Dinghong Sun Zhenyu Chen Jianfeng Zhang Wei Song Jingyu Shi Jintao Zhu Yuanyuan Meng Fei Jin Shuncheng Yang Ziyi Ge Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China Faculty of Material Science and Chemical Engineering Ningbo UniversityNingbo 315211China Zhejiang Provincial Engineering Research Center of Energy Optoelectronic Materials and Devices Ningbo Institute of Materials Technology&EngineeringChinese Academy of SciencesNingbo 315201China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing 100049China Department of Chemical and Environmental Engineering University of Nottingham NingboNingbo 315100China

The micro-morphology and molecular stacking play a key role in determining the charge transport process and nonradiative energy loss, thus impacting the performances of organic solar cells(OSCs). To address this issue, a non-fullerene acceptor PhC6-IC-F with alkylbenzene side-chain, possessing optimized molecular stacking, complementary absorption spectra and forming a cascade energy level alignment in the PM6:BTP-eC9 blend, is introduced as guest acceptor to improve efficiency of ternary OSCs. The bulky phenyl in the side-chain can regulate crystallinity and optimizing phase separation between receptors in ternary blend films, resulting in the optimal phase separations in the ternary films. As a result, high efficiencies of 18.33% as photovoltaic layer are obtained for PhC6-IC-F-based ternary devices with excellent fill factor(FF) of 78.92%. Impressively, the ternary system produces a significantly improved open circuit voltage(V_(oc)) of 0.857 V compared with the binary device,contributing to the reduced density of trap states and suppressed non-radiative recombination result in lower energy loss. This work demonstrates an effective approach for adjusting the aggregation, molecular packing and fine phase separation morphology to increase V_(oc) and FF, paving the way toward high-efficiency OSCs.

关键词： alkylbenzene side-chain morphology regulation ternary blends organic solar cells

来源：评论

学校读者我要写书评

暂无评论

Data Augmentation and Random Multi-Model Deep Learning for Data Classification

引用

computers, Materials & Continua 2023年第3期74卷 5191-5207页

作者： Fatma Harby Adel Thaljaoui Durre Nayab Suliman Aladhadh Salim EL Khediri Rehan Ullah Khan Computer Science Department Future Academy-Higher Future Institute for Specialized Technological StudiesEgypt Department of Computer Systems Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawar25120Pakistan Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Sciences Faculty of Sciences of GafsaUniversity of GafsaGafsaTunisia

In the machine learning(ML)paradigm,data augmentation serves as a regularization approach for creating ML *** increase in the diversification of training samples increases the generalization capabilities,which enhances the prediction performance of classifiers when tested on unseen *** learning(DL)models have a lot of parameters,and they frequently ***,to avoid overfitting,data plays a major role to augment the latest improvements in ***,reliable data collection is a major limiting ***,this problem is undertaken by combining augmentation of data,transfer learning,dropout,and methods of normalization in *** this paper,we introduce the application of data augmentation in the field of image classification using Random Multi-model Deep Learning(RMDL)which uses the association approaches of multi-DL to yield random models for *** present a methodology for using Generative Adversarial Networks(GANs)to generate images for data *** experiments,we discover that samples generated by GANs when fed into RMDL improve both accuracy and model *** across both MNIST and CIAFAR-10 datasets show that,error rate with proposed approach has been decreased with different random models.

关键词： Data augmentation generative adversarial networks classification machine learning random multi-model deep learning

来源：评论

学校读者我要写书评

暂无评论

An experimental and numerical approach for optimization of internal and external corrugations with various geometries in cylindrical thin-walled concertina energy absorbers under quasi-static axial load

引用

Mechanics of Advanced Materials and Structures 2024年第25期31卷 6628-6642页

作者： Rahpeima, Reza Nateghi Boroujeni, Iman Nia, Ali Alavi Graduate institute of biomedical electronics and bioinformatics College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan Department of Mechanical Engineering Tarbiat Modares University Tehran Iran Department of Mechanical Engineering Bu-Ali Sina University Hamedan Iran

Thin-walled tubes have been extensively used as energy absorbers in many engineering structures that are under dynamic or quasi-static loads. In this article, the effect of corrugation and its geometry on the collapse characteristics of aluminum concertina tubes under quasi-static axial load is investigated both experimentally and numerically. The numerical simulations were performed with the use of LS-Dyna commercial software. Then, several chosen samples were tested experimentally to verify the results of the simulation. Forty different samples with four different corrugation geometries including singly isosceles triangular corrugation, continual isosceles triangular corrugation, continual scalene triangular corrugation, and continual semi-circular corrugation, and each with 10 different size dimensions were simulated. Among all of these simulations, six of them, each with two replicates were subjected to experimental tests. Experimental examples are aluminum cylindrical thin-walled tubes with the same thickness, height, and diameter that corrugations with different geometries are applied to them by the use of the cold rolling method. Finally, to describe the findings in more theoretical terms, a comparison between our obtained results and earlier theoretical investigations is made. The results show a significant influence of corrugations application on the improvement of the collapse characteristics of the cylindrical tubes so that the collapse style of intact tubes can be controlled by applying corrugations. The results show that by increasing the amplitude and number of corrugations, the absorbed energy, and the initial maximum force decrease. It is also found that among the different corrugation geometries, the corrugations with singly isosceles triangular geometry have the highest energy absorption as well as the lowest initial maximum force. © 2023 Taylor & Francis Group, LLC.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

Development of a Smart Shoe for Blind and Visual Impaired People

Development of a Smart Shoe for Blind and Visual Impaired Pe...

引用

2024 International Conference on engineering and Computing, ICECT 2024

作者： Ramzan, Aneeqa Mustafa, Rafay Kamran, Yashfa NUTECH Department of Electrical Engineering Islamabad Pakistan GIKI Faculty of Computer Science and Engg. Swabi Topi Pakistan IIUI Department of Electrical and Computer Engineering Pakistan

ISBN: (纸本)9798350349719

Providing adequate clinical and technical aid to blinds and visually impaired persons can be very challenging as it put financial strain on families due to the medical examination, treatment, surgical procedures and assistive devices expenses. The specialists to the mentioned individuals' ratio is low and exposure to ophthalmologists is limited. Either requirement of smartphone applications with need of internet connection or only direction oriented solutions but unable to avoid obstacles are the issues in existing market solutions. This paper proposes a novel technology of smart assistant aid for blind and visually impaired people (SSVIP) by developing a smart shoe prototype with sensors to detect obstacles, wet surfaces and ground vibrations, providing real-Time feedback to the user. If any of these are detected, the controller activates the buzzer and vibration motor, providing both audible alerts based on the detected sensor signal in order to alarm the wearer and tactile feedback respectively. SSVIP is then tested on 20 iterations after configuring and calibrating sensors and getting the optimized 20 units for ultrasonic sensor, 650 threshold for water sensor. Output accuracies of 87%, 80% and 83% for ultrasonic sensor, water sensor and vibration sensor resnectively and resulting overall 83% accuracy was acheived. © 2024 IEEE.

关键词： Ultrasonic sensors

来源：评论

学校读者我要写书评

暂无评论

14-Bit SAR ADC with on-Chip Digital Bubble Sorting Calibration Technology

引用

Chinese Journal of Electronics 2025年第1期34卷 125-136页

作者： Hua Fan Zhuorui Chen Tongrui Xu Franco Maloberti Qi Wei Quanyuan Feng School of Integrated Circuit Science and Engineering(Exemplary School of Microelectronics) University of Electronic Science and Technology of China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Chongqing Institute of Microelectronics Industry Technology University of Electronic Science and Technology of China Department of Electrical Computer and Biomedical Engineering University of Pavia Department of Precision Instrument Tsinghua University Institute of Microelectronics Southwest Jiaotong University

This article designs a 14-bit successive approximation register analog-to-digital converter（SAR ADC）.A novel digital bubble sorting calibration method is proposed and applied to eliminate the effect of capacitor mismatch on the linearity of the SAR ADC. To reduce the number of capacitors, a hybrid architecture of a high 8-bit binary-weighted capacitor array and a low 6-bit resistor array is adopted by the digital-to-analog（DAC）. The common-mode voltage VCM-based switching scheme is chosen to reduce the switching energy and area of the DAC. The time-domain comparator is employed to obtain lower power consumption. Sampling is performed through a gate voltage bootstrapped switch to reduce the nonlinear errors introduced when sampling the input signal. Moreover, the SAR logic and the whole calibration is totally implemented on-chip through digital integrated circuit（IC） tools such as design compiler, IC compiler, etc. Finally, a prototype is designed and implemented using 0.18 μm bipolar-complementary metal oxide semiconductor（CMOS）-double-diffused MOS 1.8 V CMOS technology. The measurement results show that the SAR ADC with on-chip bubble sorting calibration method achieves the signal-to-noise-and-distortion ratio of 69.75 dB and the spurious-free dynamic range of 83.77 dB.

关键词： Semiconductor device measurement Capacitors Linearity Switches Calibration System-on-chip Frequency measurement Time-domain analysis Sorting Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Robustness of generative AI detection: adversarial attacks on black-box neural text detectors

引用

International Journal of Speech Technology 2024年第4期27卷 861-874页

作者： Fishchuk, Vitalii Braun, Daniel Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands Department of High-tech Business and Entrepreneurship University of Twente Enschede Netherlands

The increased quality and human-likeness of AI generated texts has resulted in a rising demand for neural text detectors, i.e. software that is able to detect whether a text was written by a human or generated by an AI. Such tools are often used in contexts where the use of AI is restricted or completely prohibited, e.g. in educational contexts. It is, therefore, important for the effectiveness of such tools that they are robust towards deliberate attempts to hide the fact that a text was generated by an AI. In this article, we investigate a broad range of adversarial attacks in English texts with six different neural text detectors, including commercial and research tools. While the results show that no detector is completely invulnerable to adversarial attacks, the latest generation of commercial detectors proved to be very robust and not significantly influenced by most of the evaluated attack strategies. © The Author(s) 2024.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Investigation of Mutual-Coupling Free Condition of Two RFID Tags Technology using Overlapping Study 10

Investigation of Mutual-Coupling Free Condition of Two RFID ...

引用

10th IEEE Asia-Pacific Conference on Applied Electromagnetics, APACE 2024

作者： Ali, Mohamad Fakrie Mohamad Ayop, Osman Bin Murad, Noor Asniza Binti Rahim, Mohamad Kamal A. Dewan, Raimi Bin Zubir, Farid Bin Universiti Teknologi Malaysia Faculty of Electrical Engineering Johor Bahru Malaysia Universiti Teknologi Malaysia Faculty of Electrical Engineering Communication Engineering Department Johor Bahru Malaysia Universiti Teknologi Malaysia Faculty of Electrical Engineering Biomedical Engineering and Health Science Department Johor Bahru Malaysia

ISBN: (纸本)9798350364163

Mutual coupling between antennas is a significant issue in telecommunication devices such as RFID tags. The coupling may degrade the overall performance. It can cause frequency detuning by altering the antenna's overall inductance. In systems incorporating multiple antenna technologies, avoiding frequency detuning is crucial for optimal performance. Low frequency (LF) or high frequency (HF) RFID tags operating at short read range via near field magnetic resonance. Embedding multiple tags in a single card can lead to unavoidable frequency detuning due to the coupling effect, resulting in system failure and undetectable tags. This paper investigates the mutual coupling behavior of two RFID tag technologies under various overlapping conditions. The two loops antenna coupling area overlapping is varies by changing the position in x and y directions. The study examines the self-resonant frequency (SRF) of the RFID tags. Results indicate that overlapping RFID tags causes frequency detuning for both tags. However, certain overlapping conditions (around 25% overlapping area) can achieve a mutual coupling-free state. © 2024 IEEE.

关键词： Magnetic couplings

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：