检索结果-内蒙古大学图书馆

ROF systems performance efficiency based on continuous phase frequency shift keying phase modulation scheme

Journal of Optical Communications 2024年 45卷 s417-s429页

作者： Eid, Mahmoud M. A. Sorathiya, Vishal Lavadiya, Sunil Abd El-Aziz, Ismail A. Asaduzzaman, Sayed Rehana, Hasin Ali Mohammed Ibrahim, Abd El-Naser Rashed, Ahmed Nabih Zaki Department of Electrical Engineering College of Engineering Taif University Taif Saudi Arabia Department of Information and Communication Technology Marwadi University Rajkot India Benha Faculty of Engineering Benha University Benha Egypt Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Department of Computer Science and Engineering University of Dhaka Dhaka Bangladesh Higher Institute of Electronic Engineering Belbeis Ministry of Higher Education 10th of Raman Belbeis Egypt Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt

Radio over fiber (ROF) technique has been presented with hybrid ordinary modulation technology to achieve improvement in optical communication network performance. Fiber Bragg grating (FBG) is employed in single mode (SM) optical channel in order to enhance the transmission environment with dispersion compensation. The continuous phase frequency shift keying phase modulation (CPFSKPM) technique is included in this study. Both previous and proposed models have been inspected and investigated. Min. bit error rate (BER), max. Q factor, signal/noise ratio (SNR), received power (RP), and noise figure (NF) are the most essential parameters able to explain the behavior performance of optical communication network model. © 2021 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Fiber Bragg gratings

来源：评论

学校读者我要写书评

暂无评论

Analytical Survey on the Security Framework of Cyber-Physical Systems for Smart Power System Networks

Analytical Survey on the Security Framework of Cyber-Physica...

引用

2022 International Conference on Cyber Resilience, ICCR 2022

作者： Ali Al-Jumaili, Ahmed Hadi Muniyandi, Ravie Chandren Hasan, Mohammad Kamrul Singh, Mandeep Jit Siaw Paw, Johnny Koh Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi43600 Malaysia University of Fallujah Computer Centre Department Anbar00964 Iraq Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Electrical Electronic and System Engineering Selango Bangi43600 Malaysia Universiti Tenaga Nasional Department of Electronic and Communication Engineering Selango Kajang Malaysia

ISBN: (纸本)9781665461221

Cyber-Physical Power System (CPPS) is one of the most critical infrastructure systems due to deep integration between power grids and communication networks. In the power system, cascading failure is spreading more readily in CPPS, even leading to blackouts as well as there are new difficulties with the power system security simulation and faults brought by physical harm or network intrusions. The current study summarized the cross- integration of several fields such as computer and cyberspace security in terms of the robustness of Cyber-Physical Systems, viewed as Interconnected and secure network systems. Therefore, the security events that significantly influenced the power system were evaluated in this study, besides the challenges and future directions of power system security simulation technologies were investigated for posing both challenges and opportunities for simulation techniques of power system security like building a new power system to accelerate the transformation of the existing energy system to a clean, low-carbon, safe, and efficient energy system which is used to assure power system stability through fusion systems that combine the cyber-physical to integrate the battery power station, power generation and renewable energy resources through the internet with the cyber system that contains Smart energy system control and attacks. © 2022 IEEE.

关键词： Cyber Physical System

来源：评论

学校读者我要写书评

暂无评论

Adaptive position tracking control of the lower limb exoskeleton robot with an uncertain dynamic model 18

Adaptive position tracking control of the lower limb exoskel...

引用

18th IEEE Conference on Industrial electronics and Applications, ICIEA 2023

作者： Yuan, Ting Zhang, Chi Yi, Feng Lv, Pingping Li, Shupei Zhang, Meitong Ningbo University Ningbo Instituteof Materials Technology and Engineering Chinese Academy of Sciences Faculty of Electrical Engineering and Computer Science Ningbo315201 China Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials Technology and Engineering Ningbo315201 China University of Chinese Academy of Sciences Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences College of Materials Science and Opto-Electronic Technology Ningbo315201 China Hebei University of Science and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences School of Electrical Engineering Ningbo315201 China

ISBN: (纸本)9798350312201

In this paper, an adaptive position control method combining proportional-derivative (PD) control, RBF neural network-based sliding mode (SM) control, and feedforward (FF) control, i.e., PD-FF-SM control, is proposed to deal with the dynamic uncertainties, disturbances, and slow response in lower limb exoskeleton robot system. The Lagrange method is utilized to establish dynamic models that ignore the uncertainties and disturbances in the swing phase and supporting phase. Then, the PD feedback controller is designed with a sliding surface function, to keep the system stable. The FF controller is adopted to improve the response by using dynamic models. And the RBF neural network-based SM controller is designed to compensate for the uncertainties and disturbances. The system's stability is verified by Lyapunov's theorem. The simulation results show that the proposed control method can effectively reduce the error of position tracking and response time with inaccurate dynamic modeling. © 2023 IEEE.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

IoT-Based Mobile Drug Dispenser for Developing Countries 8

IoT-Based Mobile Drug Dispenser for Developing Countries

引用

8th IET Smart Cities Symposium, SCS 2024

作者： Machingamidze, Keith Rushambwa, Munyaradzi Charles Yogesh, C.K. Palaniappan, Rajkumar Vijean, Vikneswaran Nabi, Fizza Ghulam Harare Institute of Technology Harare Zimbabwe School of Computer Science and Engineering Vellore Institute of Technology India Department of Mechatronics Engineering College of Engineering University of Technology Bahrain Bahrain Faculty of Electronic Engineering and Technology Universiti Malaysia Perlis Malaysia Department of Industrial Engineering and Management University of the Punjab Pakistan

ISBN: (纸本)9781837242672

This research focuses on the development of an Internet of Things (IOT) -based mobile drug dispenser that utilizes a line following robot, Node MCU, mobile applications, and a desktop application to ensure efficient drug administration. The line following robot is designed to navigate through a predefined path to deliver drugs to patients, while the Node MCU enables wireless communication and control. The mobile and desktop applications allow healthcare professionals to control and monitor the line following robot. This system aims to improve medication adherence and to enhance patient care. The IOT-based mobile drug dispenser has the potential to revolutionize drug administration in various healthcare settings, including hospitals, clinics, and home care. © The Institution of engineering & technology 2024.

关键词： Home health care

来源：评论

学校读者我要写书评

暂无评论

Deep learning for brain age estimation: A systematic review

引用

Information Fusion 2023年 96卷 130-143页

作者： Tanveer, M. Ganaie, M.A. Beheshti, Iman Goel, Tripti Ahmad, Nehal Lai, Kuan-Ting Huang, Kaizhu Zhang, Yu-Dong Del Ser, Javier Lin, Chin-Teng Department of Mathematics Indian Institute of Technology Indore Simrol Indore453552 India Department of Robotics University of Michigan Ann ArborMI48109 United States Department of Human Anatomy and Cell Science Rady Faculty of Health Sciences Max Rady College of Medicine University of Manitoba WinnipegMB Canada Biomedical Imaging Lab National Institute of Technology Silchar Assam 788010 India Department of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan Data Science Research Center Duke Kunshan University China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom Derio48160 Spain Bilbao48013 Spain School of Computer Science Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia

Over the years, Machine Learning models have been successfully employed on neuroimaging data for accurately predicting brain age. Deviations from the healthy brain aging pattern are associated with the accelerated brain aging and brain abnormalities. Hence, efficient and accurate diagnosis techniques are required to elicit accurate brain age estimations. Several contributions have been reported in the past for this purpose, resorting to different data-driven modeling methods. Recently, deep neural networks (also referred to as deep learning) have become prevalent in manifold neuroimaging studies, including brain age estimation. In this review, we offer a comprehensive analysis of the literature related to the adoption of deep learning for brain age estimation with neuroimaging data. We detail and analyze different deep learning architectures used for this application, pausing at research works published to date quantitatively exploring their application. We also examine different brain age estimation frameworks, comparatively exposing their advantages and weaknesses. Finally, the review concludes with an outlook towards future directions that should be followed by prospective studies. The ultimate goal of this paper is to establish a common and informed reference for newcomers and experienced researchers willing to approach brain age estimation by using deep learning models. © 2023 Elsevier B.V.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Straight-line: A new global path planning algorithm for Mobile Robot 2

Straight-line: A new global path planning algorithm for Mobi...

引用

2nd IEEE International Conference on electronic engineering, ICEEM 2021

作者： Nasr, Aida A. El-Bahnasawy, Nirmeen A. El-Sayed, Ayman Tanta University Faculty of Computers and Information Information Technology Dept. Egypt Menoufia University Faculty of Electronic Engineering Computer Science and Engineering Dept Egypt

ISBN: (纸本)9781665418423

Today most organizations use mobile robots for many purposes and to perform difficult and repetitive tasks. Robots are used to transport goods from one place to another within factories and warehouses. It is also used to provide different services in government and private institutions, as it can interact with people and help them to obtain different services with high quality and very quickly without any trouble. For the robot performs its functions better, it needs a path planning algorithm to avoid obstacles and works faster. Therefore, we develop a new algorithm called straight line algorithm. The new algorithm can get the optimal path with shortest length in low running time. The new algorithm searches for the optimal solution in the critical region firstly. This way capable of finding the shortest path faster. We evaluate straight-line algorithm with Genetic algorithm GA. We find that the new algorithm outperforms better than the GA in terms, distance, speed, and running time. © 2021 IEEE.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Improving Subset Linear Discriminant Analysis Algorithm Using Overlapping Clustering

Improving Subset Linear Discriminant Analysis Algorithm Usin...

引用

2023 Al-Sadiq International Conference on Communication and Information technology, AICCIT 2023

作者： Mandeel, Thulfiqar H. Ahmad, Muhammad Imran Khalid, Noor Aldeen A. Hassan, Mustafa Hamid Kadhim, Mohammed Hayder Imam Ja'afar Al-Sadiq University College of Information Technology Department of Computer Techniques Engineering Muthanna Iraq Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Perlis Malaysia Bilad Alrafidain University College Department of Medical Instruments Engineering Techniques Diyala Iraq Imam Ja'afar Al-Sadiq University College of Information Technology Muthanna Iraq Jabir Ibn Hayyan for Medical and Pharmaceutical Sciences Department of Information Technology Najaf Iraq

ISBN: (纸本)9798350341881

In recent years, there have been many proposals to improve the performance of traditional linear discriminant analysis (LDA). One of these is subset-improving linear discriminant analysis (S-LDA), which is based on clustering the whole set of classes into subsets and performing the LDA locally on these subsets. However, this algorithm suffers from an improper mapping of the classes to the corresponding subset during the testing procedure due to the inevitable discrepancy between the images used for training and those for testing. This discrepancy is caused either by spatial distortion or noise. The wrong mapping is severe when the number of data samples is small which is a common scenario in biometric datasets. In this paper, overlapping clustering is proposed for class clustering, to overcome the aforementioned problem. The proposed algorithm outperforms the S-LDA by 35.4% in mapping accuracy when using the PolyU palmprint database, 36.96%, resp. 33.92% when using left resp. Right palm images from the IIT Delhi Touchless Palmprint Database. © 2023 IEEE.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition Method based on Guided Fusion of Facial Expression and Bodily Posture 8

Emotion Recognition Method based on Guided Fusion of Facial ...

引用

8th IEEE International Conference on Cloud Computing and Intelligence Systems, CCIS 2022

作者： Zhong, Huang Danni, Zhang Fuji, Ren Min, Hu Juan, Liu Anqing Normal University School of Electronic Engineering and Intelligent Manufacturing Anqing246011 China Hefei University of Technology School of Computer Science and Information Hefei230009 China University of Tokushima Faculty of Engineering Tokushima770800 Japan

ISBN: (纸本)9781665477352

Aiming at single modality video emotion recognition of face or body is easily affected by occlusion, angle deflection, and low emotional intensity, we propose an emotion recognition method based on guided fusion of facial expression and bodily posture (GF-FB). Firstly, Resnet50 and DNN are used to obtain intra-frame facial texture vector and bodily skeleton vector. Meanwhile, the whole-body geometric feature captured by the transformer encoder, is guided to obtain facial enhancement vector and bodily enhancement vector by the vectors of two modalities, respectively. Then, an inter-frame time encoder is designed to describe spatio-temporal features of facial enhancement sequence and bodily enhancement sequence. Finally, the heterogeneous features adaptive fusion module is constructed to realize the weight allocation of facial enhancement branch and bodily enhancement branch. Experimental results on the BabyRobot Emotion Dataset show that the accuracy of proposed method reaches 78.22%, which is 6.22% higher than baseline network. © 2022 IEEE.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

A Deep and Systematic Review of the Intrusion Detection Systems Based on Machine Learning and Deep Learning Techniques

A Deep and Systematic Review of the Intrusion Detection Syst...

引用

International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： Guhan N K Sindhu Ravindran Ramachandran M Vikneswaran Vijean Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India Faculty of Electronic Engineering & Technology Universiti Malaysia Perlis Kampus Alam UniMAP Perlis Malaysia

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

Intrusion detection systems are the primitive elements in safeguarding vital infrastructures, which are able to identify malicious activity on hosts or networks. The efficient IDS must be able to handle a variety of threats is a difficult security cum threat related problems. Numerous strategies have been put out in the literature as of right now to increase intrusion detection efficiency while taking into account some of these restrictions, like mobility and resource limitations. This review paper discusses about the early research works on performed on IDS using Deep Learning and Machine Learning techniques. This paper provides a qualitative assessment of these methods and deeper insights about the analysis as well as a summary of the field's current themes and the methods used to train and implement IDSs. We address the overall limitations of these solutions, namely the types of attacks that these approaches are unable to identify and the setup limitations that are specific to each of these works, even though they offer insightful information and solutions for certain aspects of these constraints.

关键词： Deep learning Cloud computing Accuracy Recurrent neural networks Computational modeling Wireless networks Intrusion detection Communication system security Long short term memory Cyberattack

来源：评论

学校读者我要写书评

暂无评论

Novel Bendable Mnxca(0.90−X)Ni0.10fe2o4 Substrate Based Symmetrical Metamaterial Absorber for Rf Energy Harvesting Application to Achieve Sustainable Development Goals

SSRN

引用

SSRN 2024年

作者： Hasan, Mohammad Shakibul Islam, Mohammad Tariqul Ouda, Mohammad Alenezi, Abdulmajeed M. Soliman, Mohamed S. Samsuzzaman, Md. Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Electrical Engineering Technology College of Engineering & Technology University of Doha for Science and Technology Doha24449 Qatar Department of Electrical Engineering Faculty of Engineering Islamic University of Madinah Madinah41411 Saudi Arabia Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia Department of Computer and Communication Engineering Faculty of Computer Science and Engineering Patuakhali Science and Technology University Bangladesh

This article presents a bendable substrate MnxCa(0.90−x)Ni0.10Fe2O4 based metamaterial absorber for RF energy harvesting from Wifi frequency of 5 GHz to the achievement of the Sustainable Development Goals. The bendable metamaterial absorber (BMMA) energy harvester unit cell constructed with the physical dimension of 21 × 21 *** proposed unit cell consist of cross sign shaped resonator surrounded by circular ring resonator is located middle portion and boundary split outer ring resonator. Based on the simulation findings, the proposed BMMA energy harvester provides maximum energy harvesting efficiency of 99.42% at 5 GHz. Due to the symmetrical design, the energy harvester unit cell shows excellent angle insensitive up to 90 degrees for incident angle and polarization angle. The proposed BMMA exhibits single negative properties, and it shows excellent harvesting efficiency for various bending conditions. The lightweight, flexibility of the structure indicate that MnxCa(0.90−x)Ni0.10Fe2O4 based bendable metamaterial absorber energy harvester have significant potential for RF energy harvesting application from wifi frequency of 5 GHz and it achieve Sustainable Development Goals (SDGs), specially alignment with SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities),and SDG 13 (Climate Action). © 2024, The Authors. All rights reserved.

关键词：

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：