检索结果-内蒙古大学图书馆

Impact of Fuel Cell System on Under Frequency Load Shedding Scheme Design

Distributed Generation and Alternative Energy Journal 2022年第5期37卷 1329-1348页

作者： Jha, Rajeev Khan, Baseem Department of Electrical & Electronics Engineering Allenhouse Institute of Technology Kanpur India Department of Electrical and Computer Engineering Hawassa University Hawassa Ethiopia

The drop in frequency is a direct consequence of generation deficiency, either due to loss of generation or an increase in load. Therefore, in this work, to compensate for this generation deficiency following large disturbances, a fuel cell system (FCS) could be the most effective *** the introduction of a proportional-integral (PI) controller to the FCS, the power output of the FCS can be further modified. In the present work, a two-area hydro-thermal interconnected system is being considered and simulated in MATLAB with and without FCS. From the simulation results, it is found that by using a FCS (with and without PI), the load shedding amount is reduced and the under-frequency load shedding (UFLS) scheme is made more effective. © 2022 River Publishers.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Development of Novel-Epoxy-Based Transformer Bushing Insulator for High Breakdown Voltage (BDV) 3

Development of Novel-Epoxy-Based Transformer Bushing Insulat...

引用

3rd International Conference on Emerging Trends in electrical, Control, and Telecommunication engineering, ETECTE 2024

作者： Siddique, Abubakar Akram, Laraib Aslam, Waseem Mishal, Areeba Shahid, Muhammad Usama Ahmed, Haseeb Department of Electrical and Biomedical Engineering Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan Department of Electrical Electronics & Computer Engineering University of Sargodha Sargodha Pakistan

ISBN: (纸本)9798331504861

In today’s trends, nanocomposites have garnered significant interest due to their potential to enhance dielectric properties and be used as insulators. Incorporating nanoparticles into the base epoxy makes achieving highly efficient dielectric materials feasible. However, the low electric field stress management capability and insufficient relative permittivity of typical epoxy provide a hindrance. Efforts have been made to overcome these limitations by adding nanosized fillers with high relative permittivity to the epoxy to enhance the dielectric properties. This research study focuses on the development of Novel-Epoxy-Based Transformer Bushing Insulator using nanomaterial Al2O3 and SiO2. The epoxy resin served as the base material, with nano-fillers added to improve its dielectric properties. The hardener was added to initiate the curing process and create a highly crosslinked structure. Surfactants were introduced to improve the interaction between the epoxy resin and nanoparticles. The nano-silica and nano-alumina particles were combined in different ratio configurations to create the nanocomposites by using the preparation method;Sol-Gel and Green Synthesis, which were subsequently tested for their dielectric properties. The proposed sample is the nanocomposite made by the green synthesis method and with the combination of 0.3 g + 0.3 g of the nanoparticle. Results show improved dielectric strength of the proposed nanocomposites compared to conventional porcelain materials. This paper presents an environment friendly approach for developing epoxy-based transformer bushing insulators, offering enhanced performance. ©2024 IEEE.

关键词： Permittivity

来源：评论

学校读者我要写书评

暂无评论

Robust -Controller Design for Discrete-Time Positive T-S Fuzzy Systems Using Dual Approach

引用

IEEE Transactions on Systems, Man, and Cybernetics: Systems 2022年第2期52卷 706-715页

作者： Ahmadi, Elham Zarei, Jafar Razavi-Far, Roozbeh Department of Electrical and Electronics Engineering Shiraz University of Technology Shiraz Iran Department of Electrical and Computer Engineering University of Windsor Windsor Canada

In this article, a new approach is proposed for stability analysis and controller design of nonlinear discrete-time positive systems by means of the Takagi-Sugeno fuzzy model. The closed-loop stability and the positivity constraint are guaranteed by synthesizing a linear co-positive Lyapunov function and by applying the parallel distributed compensation controller. In contrast to the state-of-the-art approaches for ensuring the ell {1} -stability of the positive system which are based on bilinear matrix inequalities, the proposed optimal robust control design under ell {1} -induced performance is derived based on linear programming framework. It has been shown that the computational complexity of the proposed optimization problem can be effectively reduced. Finally, a numerical example and the Leslie population model are adopted to show the capabilities of the proposed method. © 2013 IEEE.

关键词： Lyapunov functions

来源：评论

学校读者我要写书评

暂无评论

Face Attribute Convolutional Neural Network System for Data Security with Improved Crypto Biometrics

引用

computer Systems Science & engineering 2023年第6期45卷 2351-2362页

作者： S.Aanjanadevi S.Aanjankumar K.R.Ramela V.Palanisamy Department of Computer Applications Alagappa UniversityKaraikudi630003TamilnaduIndia Department of Computer Science and Engineering Sri Raaja Raajan College of Engineering and TechnologyAmaravathipudur630301TamilnaduIndia Department of Electrical and Electronics Engineering Ultra College of Engineering and TechnologyMadurai625020TamilnaduIndia

Due to the enormous usage of the internet for transmission of data over a network,security and authenticity become major *** challenges encountered in biometric system are the misuse of enrolled biometric templates stored in database *** describe these issues various algorithms are implemented to deliver better protection to biometric traits such as physical(Face,fingerprint,Ear etc.)and behavioural(Gesture,Voice,tying etc.)by means of matching and verification *** this work,biometric security system with fuzzy extractor and convolutional neural networks using face attribute is proposed which provides different choices for supporting cryptographic processes to the confidential *** proposed system not only offers security but also enhances the system execution by discrepancy conservation of binary *** Face Attribute Convolutional Neural Network(FACNN)is used to generate binary codes from nodal points which act as a key to encrypt and decrypt the entire data for further *** Artificial Intelligence(AI)into the proposed system,automatically upgrades and replaces the previously stored biometric template after certain time period to reduce the risk of ageing difference while *** codes generated from face templates are used not only for cryptographic approach is also used for biometric process of enrolment and *** main face data sets are taken into the evaluation to attain system performance by improving the efficiency of matching performance to verify *** system enhances the system performance by 8%matching and verification and minimizes the False Acceptance Rate(FAR),False Rejection Rate(FRR)and Equal Error Rate(EER)by 6 times and increases the data privacy through the biometric cryptosystem by 98.2%while compared to other work.

关键词： FACNN biometric cryptography AI FAR FRR EER

来源：评论

学校读者我要写书评

暂无评论

Biosensor Development in Medical Science for Disease Detection

Biosensor Development in Medical Science for Disease Detecti...

引用

2024 International Conference on Emerging Innovations and Advanced Computing, INNOCOMP 2024

作者： Sharma, Ashish Chandel, Garima Garg, Setu Katiyar, Gauri Shrivastav, Kamayani Garg, Rinku Chandigarh University Department of Electrical Engineering Punjab India Chandigarh University Department of Electronics and Communication Engineering Mohali India ITS Engineering College Department of Electronics and Communication Engineering Greater Noida India GCET Department of Electrical and Electronics Engineering UP Greater Noida India Chandigarh University Department of Computer Applications Mohali India

ISBN: (纸本)9798350376470

Medicines are a very important part of lives of human beings. Not only now but from a thousand years ago. Medical science has also proved its evidence in terms of medicines and the right diagnosis of diseases in time with the help of sensors. Right now, medical science has too much development. Biosensors has increased it demand as due to its real time monitoring in following areas: Biomedical diagnosis, drug monitoring, chemicals and many more Biosensors were introduced in the medical era in the 19th century. Researchers are trying to modify the sensors. Developing a sensor that provides fast response, accuracy and selectivity is a mega challenge. A sensor cannot be made without electric components. This paper tries to represent how various sensors are used in medical science Organ transplants, microsurgery, etc. are running successfully with the use of biosensors. In this work the impact of the use of various biosensors on human body is taken in to account. Multiple and mass transfer of magnetic particles and effect if infrared microscopy in the application of biosensors is considered taken in to account after covid 19. © 2024 IEEE.

关键词： Bio-element Biological Organism Biosensors Transducers

来源：评论

学校读者我要写书评

暂无评论

Optimizing Packet Delivery in Underwater Wireless Sensor Networks: A Comparative Study of Genetic Bee Colony and Ant Colony Algorithms 9

Optimizing Packet Delivery in Underwater Wireless Sensor Net...

引用

9th International Conference on Communication and electronics Systems, ICCES 2024

作者： Kannappan, A. Kolagani, Nagesh Kandaswamy, Vijay Anand Vishnupriyan, J. Saveetha School of Engineering Simats Department of Electronics and Communication Engineering Chennai India Saveetha School of Engineering Simats Department of Computer Science and Engineering Chennai India Chennai Institute of Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350377972

Physically Underwater communication adopt the bio inspired genetic bee colony formed network communication structures. Underwater environment condition Communication is established between the Transmitting node and in between several clustering relay nodes to reach receiver nodes. Transmitting nodes are placed on sea bed areas at certain depth and clustering relay nodes are placed in various underwater depth conditions dipping the sensor nodes. Also, underwater battery life is very hard and battery replacement is a very tough task. Hence, an alternate solution of optimization battery capacity utilization is used. This optimization algorithm improves Packet delivery ratio by comparing genetic bee algorithm with Ant colony algorithm. Hence, equivalence of two algorithms implemented in underwater conditions. The genetic bee colony Algorithm produces better output results more than 4 to 6 percentage compared to ant colony parameter output. The genetic bee colony algorithm offers a maximum clustering node technique compared to ant colony algorithm. Its greater support for saving energy consumption extending battery life. © 2024 IEEE.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

A systematic literature review of visual feature learning: deep learning techniques, applications, challenges and future directions

引用

Multimedia Tools and Applications 2024年 1-58页

作者： Abdullahi, Mohammed Oyelade, Olaide Nathaniel Kana, Armand Florentin Donfack Bagiwa, Mustapha Aminu Abdullahi, Fatimah Binta Junaidu, Sahalu Balarabe Iliyasu, Ibrahim Ore-ofe, Ajayi Chiroma, Haruna Department of Computer Science Ahmadu Bello University Zaria Zaria Nigeria Department of Mechanical Engineering Ahmadu Bello University Zaria Nigeria Department of Computer Engineering Ahmadu Bello University Zaria Nigeria College of Computer Science and Engineering University of Hafr Al Batin Hafar Al-Batin31991 Saudi Arabia School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Belfast United Kingdom

Visual Feature Learning (VFL) is a critical area of research in computer vision that involves the automatic extraction of features and patterns from images and videos. The applications of VFL are vast, including object detection and recognition, facial recognition, scene understanding, medical image analysis, and autonomous vehicles. In this paper, we propose to conduct extensive systematic literature review (SLR) on VFL based on deep learning algorithms. The paper conducted an SLR covering deep learning algorithms such as Convolutional Neural Networks (CNNs), Autoencoders, and Generative Adversarial Networks (GANs) including their variants. The review highlights the importance of VFL in computer vision and the limitations of traditional feature extraction techniques. Furthermore, it provides an in-depth analysis of the strengths and weaknesses of various deep learning algorithms for solving problems in VFL. The discussion of the applications of VFL provides an insight into the impact of VFL on various industries and domains. The review also analyzed the challenges faced by VFL, such as data scarcity and quality, overfitting, generalization, interpretability, and explainability. The discussion of future directions for VFL includes hybrid techniques, unsupervised feature learning, continual learning, attention-based models, and explainable AI. These techniques aim to address the challenges faced by VFL and improve the performance of the models. The systematic literature review concludes that VFL is a rapidly evolving field with the potential to transform many industries and domains. The review highlights the need for further research in VFL and emphasizes the importance of responsible use of VFL models in various applications. The review provides valuable insights for researchers and practitioners in the field of computer vision, who can use these insights to enhance their work and ensure the responsible use of VFL models. © The Author(s), under exclusive licence to

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling and Fusion Approach for Underwater Net Cage Damage Detection in Aquaculture

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling ...

引用

2024 IEEE International Conference on Consumer electronics-Asia, ICCE-Asia 2024

作者： Huang, Xiang-Rui Chen, Yi-Cheng Chen, Liang-Bi Hu, Wu-Chih National Penghu University of Science and Technology Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering Penghu Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798331530839

In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection. © 2024 IEEE.

关键词： Aquaculture

来源：评论

学校读者我要写书评

暂无评论

Enhancing Early Detection of Lung Cancer through Advanced Image Processing Techniques and Deep Learning Architectures for CT Scans

引用

computers, Materials & Continua 2024年第10期81卷 271-307页

作者： Nahed Tawfik Heba M.Emara Walid El-Shafai Naglaa F.Soliman Abeer D.Algarni Fathi EAbd El-Samie Computers and Systems Department Electronics Research InstituteEl NozhaHuckstep Cairo12622Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Lung cancer remains a major concern in modern oncology due to its high mortality rates and multifaceted origins,including hereditary factors and various clinical *** stands as the deadliest type of cancer and a significant cause of cancer-related deaths *** diagnosis enables healthcare providers to administer appropriate treatment measures promptly and accurately,leading to improved prognosis and higher survival *** significant increase in both the incidence and mortality rates of lung cancer,particularly its ranking as the second most prevalent cancer among women worldwide,underscores the need for comprehensive research into efficient screening *** in diagnostic techniques,particularly the use of computed tomography(CT)scans,have revolutionized the identification of lung *** scans are renowned for their ability to provide high-resolution images and are particularly effective in detecting small,calcified areas,crucial for identifying earlystage lung ***,there is growing interest in enhancing computer-aided detection(CAD)*** algorithms assist radiologists by reducing false-positive interpretations and improving the accuracy of early cancer *** study aims to enhance the effectiveness of CAD systems through various ***,the Contrast Limited Adaptive Histogram Equalization(CLAHE)algorithm is employed to preprocess CT scan images,thereby improving their visual *** refinement is achieved by integrating different optimization strategies with the CLAHE *** CutMix data augmentation technique is applied to boost the performance of the proposed model.A comparative analysis is conducted using deep learning architectures such as InceptionV3,ResNet101,Xception,and *** study evaluates the performance of these architectures in image classification tasks,both with and without the implementation of the CLAHE *** empirical findings of the study demonst

关键词： Lung cancer detection CLAHE algorithm optimization deep learning classification feature extraction healthcare applications

来源：评论

学校读者我要写书评

暂无评论

Predicting Earthquake Damage and Rehabilitation Intervention using Adaptive Fuzzy C-Means-Based Support Vector Machine 2

Predicting Earthquake Damage and Rehabilitation Intervention...

引用

2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Kumar, Pradeep S. Jasim, Laith Basha, C.H. Hussaian Rafikiran, Shaik Ramulu, Kothuri Parashu Department of Electronics and Communication Engineering Nitte Meenakshi Institute of Technology Bengaluru India The Islamic University of Babylon Babylon Iraq Department of Electrical & Electronics Engineering School of Engineering SR University Warangal India Department of Electrical & Electronics Engineering Sri Venkateswara College of Engineering Tirupati India Department of Computer Science and Engineering Indur Institute of Engineering and Technology Nizamabad India

ISBN: (纸本)9798331504960

Earthquakes are the greatest rates of human loss among natural disasters in a past 20 years. Predicting rehabilitation intervention and damage grades is significant, especially in the moderate aftermath of a strong earthquake as prioritized in post-earthquake housing rescue requires data about damage extent. However, building collapses caused by earthquakes lead to huge loss of property and life. Therefore, an Adaptive Fuzzy C-means-based Support Vector Machine (AFCM-SVM) is proposed to predict earthquake damage and rehabilitation intervention using Machine Learning (ML). Initially, the xBD dataset is employed to evaluate the proposed technique and min-max normalization is established which enhances numerical stability. The AFCM is utilized to segment the building effectively and Gray-Level Co-occurrence Matrix (GLCM) is employed for extraction. Finally, SVM is performed to predict the earthquake damage and rehabilitation intervention. When compared with existing approaches like Convolutional Neural Networks (CNN) and Siamese Neural Networks, the AFCM-SVM achieves a better f1-score of 0.945 respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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：