检索结果-内蒙古大学图书馆

The effect of graph complexity in an energy-based FDI approach

IFAC-PapersOnLine 2024年第4期58卷 622-627页

作者： Jan H. Smith George van Schoor Kenneth R. Uren Thomas Schäfer School of Electrical Electronic and Computer Engineering Faculty of Engineering North-West University South Africa Unit for Energy and Technology Systems Faculty of Engineering North-West University Institute for Process Technology Process Automation and Measurement Technology Zittau/Görlitz Germanuy

This paper introduces a structured approach for creating node signature graphs in energy graph-based visualization for industrial systems, focusing on anomaly detection. It examines the relationship between graph cardinality and the singular value decomposition analysis applied in the energy graph-based visualization method. The results reveal a trade-of between graph complexity and singular value resolution. The study highlights how graph structure affects energy flow monitoring and anomaly detection. It notably enables fault detection in components not represented as nodes, enhancing the methodology in energy-based system monitoring.

关键词： Fault detection isolation Graph reduction Graph matching Hybrid FDI Industrial process Thermal flow process Graph-based anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Improved Bat Algorithm with Deep Learning-Based Biomedical ECG Signal Classification Model

引用

computers, Materials & Continua 2023年第2期74卷 3151-3166页

作者： Marwa Obayya Nadhem NEMRI Lubna A.Alharbi Mohamed K.Nour Mrim M.Alnfiai Mohammed Abdullah Al-Hagery Nermin M.Salem Mesfer Al Duhayyim Department of Biomedical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science and Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversitySaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia

With new developments experienced in Internet of Things(IoT),wearable,and sensing technology,the value of healthcare services has *** evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based *** Electrocardiogram(ECG)signals are generally utilized in examination and diagnosis of Cardiovascular Diseases(CVDs)since it is quick and non-invasive in *** to increasing number of patients in recent years,the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from *** such scenario computer-assisted automated diagnostic tools are important for classification of ECG *** current study devises an Improved Bat Algorithm with Deep Learning Based Biomedical ECGSignal Classification(IBADL-BECGC)*** accomplish this,the proposed IBADL-BECGC model initially pre-processes the input ***,IBADL-BECGC model applies NasNet model to derive the features from test ECG *** addition,Improved Bat Algorithm(IBA)is employed to optimally fine-tune the hyperparameters related to NasNet ***,Extreme Learning Machine(ELM)classification algorithm is executed to perform ECG classification *** presented IBADL-BECGC model was experimentally validated utilizing benchmark *** comparison study outcomes established the improved performance of IBADL-BECGC model over other existing methodologies since the former achieved a maximum accuracy of 97.49%.

关键词： Data science ECG signals improved bat algorithm deep learning biomedical data data classification machine learning

来源：评论

学校读者我要写书评

暂无评论

Optimal Deep Learning Model Enabled Secure UAV Classification for Industry 4.0

引用

computers, Materials & Continua 2023年第3期74卷 5349-5367页

作者： Khalid A.Alissa Mohammed Maray Areej A.Malibari Sana Alazwari Hamed Alqahtani Mohamed K.Nour Marwa Obbaya Mohamed A.Shamseldin Mesfer Al Duhayyim SAUDI ARAMCO Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Information Systems College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Industrial and Systems Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of Information Systems College of Computer ScienceCenter of Artificial IntelligenceUnit of CybersecurityKing Khalid UniversityAbhaSaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Biomedical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Mechanical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology that shows attention to the interaction between machine and human *** the literature,various authors have focused on resolving security problems in UAV communication to provide safety for vital *** current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification(CSODL-SUAVC)model for Industry 4.0 *** suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image ***,the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation(ML-DWT),CSO-related Optimal Pixel Selection(CSO-OPS),and signcryption-based *** proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover *** secret images,encrypted by signcryption technique,are embedded into cover ***,the image classification process includes three components namely,Super-Resolution using Convolution Neural Network(SRCNN),Adam optimizer,and softmax *** integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV *** proposed CSODLSUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct *** simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.

关键词： Unmanned Aerial Vehicles Artificial Intelligence emerging technologies Deep Learning Industry 4.0 image steganography

来源：评论

学校读者我要写书评

暂无评论

Exploiting Mode-Switching between Aerial-RIS and Active Radio in UAV-Assisted Wireless Networks 25

Exploiting Mode-Switching between Aerial-RIS and Active Radi...

引用

25th IEEE Wireless Communications and Networking Conference, WCNC 2024

作者： Zhao, Songhan Long, Yusi Gu, Bo Luong, Nguyen Cong Lyu, Bin Gong, Shimin School Of Intelligent Systems Engineering Sun Yat-sen University Shenzhen Campus China Guangdong Provincial Key Laboratory Of Fire Science And Intelligent Emergency Technology China Phenikaa University Faculty Of Computer Science Viet Nam School Of Communications And Information Engineering Nanjing University Of Posts And Telecommunications China

ISBN: (纸本)9798350303582

In this paper, we employ dual-mode unmanned aerial vehicles (UAVs) equipped with both the active radio frequency (RF) module and aerial reconfigurable intelligent surface (ARIS) to assist ground users (GUs) for both the downlink energy transfer and uplink data transmission in a wireless-powered network. To maximize the GUs' minimum throughput, we propose a collaborative mode switching scheme for the dual-mode UAVs to dynamically switch between the active RF and passive ARIS modes according to the time-varying channel conditions. Besides, we jointly optimize the GUs' transmission control, the UAVs' beamforming, and the trajectory planning strategies. This optimization problem is intractable directly due to the non-convexity in both the objective and constraints. We design an iterative algorithm to first decompose the original problem into several subproblems, and then solve each subproblem individually by approximate optimization methods. Numerical results verify that the UAVs' collaborative mode switching along with their trajectories efficiently improves the transmission performance compared to the benchmarks in which both UAVs are operating in one fixed mode. © 2024 IEEE.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Quantifying Object-Oriented System Complexity: Introducing a Powerful Measurement Tool 13

Quantifying Object-Oriented System Complexity: Introducing a...

引用

13th IEEE International Conference on System engineering and Technology, ICSET 2023

作者： Jasser, Muhammed Basheer Zhen, Lee Ming Issa, Bayan Hong, Ling Mee Al-Hadi, Ismail Ahmed Al-Qasem Sunway University Department of Computing and Information Systems Selangor Sunway City Malaysia University of Aleppo Faculty of Informatics Engineering Syria Institute of Computer Science & Digital Innovation UCSI University Kuala Lumpur Malaysia

ISBN: (纸本)9798350340891

A lot of metrics and tools have been devised to measure the complexity of software systems. Through measurement, software professionals can have a better understanding and control of a software's complexity. In this paper, we reviewed complexity metrics and tools for object-oriented systems. The existing tools measure either implemented systems which may be source code or compile binaries, or class diagrams. The tools that measure implemented systems already offer a wide variety of features to satisfy different needs. However, the tools that measure class diagrams are not only poor in amount, but all take in class diagram XMI files, with none of them taking in PlantUML class diagram source code. PlantUML is a popular text-based UML diagramming tool that enables users to define UML diagrams with a domain specific language then renders the diagram for them. Hence, we developed a web application that measures class diagram complexity via PlantUML class diagram source code. It measures five class metrics and seven system metrics visualized as tables and bar charts, with the results exportable to PDF and CSV. Our tool's measurements were also evaluated to be correct when it is within our scope of supported syntax. © 2023 IEEE.

关键词： Object oriented programming

来源：评论

学校读者我要写书评

暂无评论

Evaluation of RF-EMF Exposure for sub-6GHz 5G NR Massive MIMO Base Station 6

Evaluation of RF-EMF Exposure for sub-6GHz 5G NR Massive MIM...

引用

6th IEEE International Symposium on Telecommunication Technologies, ISTT 2022

作者： Sali, Aduwati Wali, Sangin Qahtan Osman, Anwar Faizd Universiti Putra Malaysia Systems Engineering Faculty of Engineering WiPNET Research Centre Dept. of Computer and Communication Selangor Malaysia Pat Square Rohde & Schwarz Selangor Malaysia

ISBN: (数字)9781665489423

ISBN: (纸本)9781665489423

The 5G network is intended to accommodate a significant quantity of mobile data traffic and a great number of wireless connections. It improves cost and power consumption;it offers ultra-low latency and ultra-high dependability to enable new services in various sectors. However, the general public is concerned about the possible health dangers linked with 5G equipment's Radio Frequency (RF) radiation, and numerous localities are actively lobbying to prevent 5G implementation. This research measures the maximum exposure emitted by a 5G base station operating on 3.5 GHz. Considering the transmitted power changes over time with data traffic, the analysis is based on a code selective method. Measurements were conducted at two different distances and three different times to investigate the impacts of distance and time on the level of RF-EMF radiation. The maximum radiation from the base station is 11.69V/m, far less than the accepted limit by the ICNIRP standard. © 2022 IEEE.

关键词： Base stations

来源：评论

学校读者我要写书评

暂无评论

Utilizing Machine Learning Algorithms for Effectively Detection IoT DDoS Attacks 1st

Utilizing Machine Learning Algorithms for Effectively Detect...

引用

1st International Conference on Advances in Computing Research, ACR’23

作者： Mughaid, Ala Alqahtani, Ali AlZu’bi, Shadi Obaidat, Ibrahim Alqura’n, Rabee AlJamal, Mahmoud AL-Marayah, Raid Department of Information Technology Faculty of Prince Al-Hussien Bin Abdullah for IT The Hashemite University Zarqa Jordan Department of Networks and Communication Engineering College of Computer Science and Information Systems Najran University Najran Saudi Arabia Computer Science Department Faculty of Science and Information Technology Al Zaytoonah University of Jordan Amman Jordan

ISBN: (纸本)9783031337420

One of the most critical features of the Internet of Things (IoT) is that it allows a massive number of devices to communicate with each other at the same time, for example (cars, smoke alarms, watches, glasses, web cameras, etc.). Given that they can connect to the Internet, the huge demand to convert systems into smart systems that can be controlled remotely increases the chances of cyber-attacks that threaten security and availability becoming more frequent, severe, and in a different form. Distributed Denial of Service (DDoS) attacks have become the most common threats in IoT. These attacks make IoT systems unreliable because complex DDoS attacks cannot be detected by traditional security countermeasures such as firewalls and intrusion detection systems (IDS). In this research, we proposed a model dedicated to work on prediction and detection of DDoS attacks on networks IoT, where we run this model on a NF-BoT-IoT-v2 dataset, which contains 37,763,497 records divided into five categories (Benign, Reconnaissance, DDoS, DoS, and Theft), and then we process our dataset to be more business friendly so it only has two categories (100,000 records broken down into 23,906 benign attacks and 76,094 DDoS attacks). This study used WEKA and MATLAB tools to perform the classification efficiently and find the most important features through feature selection. We used a decision tree (J48) machine learning classifier, a Naive Bayes (NB) classifier, and a random forest (RF) classifier. However, the results were as expected and improved accuracy and efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

Sea Cense - A Commercially Valued Sea Cucumber Analyzer 5

Sea Cense - A Commercially Valued Sea Cucumber Analyzer

引用

5th International Conference on Advancements in Computing, ICAC 2023

作者： Hettiarachchi, Thavishi Herath, Gagani Jayasekara, Kasuni Thushamini, Malmi Attanayaka, Buddhima Gamage, Narmada Nishanthan, G. Dissanayake, D.C.T. SLIIT Faculty of Computing Department of Computer Systems Engineering Malabe Sri Lanka SLIIT Faculty of Computing Department of Information Technology Malabe Sri Lanka South Easetern University Faculty of Technology Department of BST Oluvil Sri Lanka University of Sri Jayawardanapura Department of Zoology Nugegoda Sri Lanka

ISBN: (纸本)9798350358131

In Sri Lanka, sea cucumbers are a highly sought-after marine product that is traded abroad. It has gained significant attention in recent years due to its high demand in the seafood market and its medicinal properties. Yet, the Sri Lankan Sea cucumber industry has not been able to fully realize its potential due to barriers like inaccurate methods for identifying and predicting the quality of sea cucumber species and the inability to provide a proper market value. This study offers an innovative solution that automates the evaluation and classification of sea cucumbers utilizing advanced computer vision and machine learning approaches. The proposed analyzer incorporates a multi-step approach, including image preprocessing, feature extraction, and classification. A set of preprocessed images are used to extract textural and distinguished color-based characteristics. These characteristics are then used to accurately classify sea cucumber species and grade them according to quality criteria using a machine learning algorithm. This project introduces a novel approach to analyzing sea cucumber length to calculate the price using a mobile application, making the task more efficient and accessible. The proposed solution 'Sea Cense' comprises 4 models that are developed using the CNN algorithm. These models' experimental findings demonstrated accuracy levels exceeding 85%. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

How to Improve IT Specialists Training for Designing Cyber-Physical systems 10

How to Improve IT Specialists Training for Designing Cyber-P...

引用

10th Mediterranean Conference on Embedded Computing, MECO 2021

作者： Pinkevich, Vasiliy Platunov, Alexey Kluchev, Arkady ITMO University Faculty of Software Engineering and Computer Systems Saint Petersburg Russia

ISBN: (纸本)9780738133614

Many universities today offer special courses or entire master programs for cyber-physical systems (CPS) developers training. A multi-aspect design route of the CPS creation is considered as the methodological vector, which should provide a parallel, balanced, and integrated movement from the task to the product. The most important part is knowledge and skills in computing, aimed at designing computing platforms and CPS application software. However, the ongoing segmentation in computing reduces the interdisciplinary interaction effectiveness. We consider the development of an integral perception of a computing system based on a multi-level and multi-domain representation model and a deep understanding of the fundamental universal mechanisms of its functioning as a way to improve the quality of design and the efficiency of interaction between computer specialists. This can be achieved by the development of microarchitectural descriptions of a computing system and its components, filling the gap between architectural representation and implementation-level documents. These principles should be implemented even during specialists training. The means of creating such models and descriptions, as well as the educational laboratory complex of distance learning, which supports the proposed approach, are demonstrated. © 2021 IEEE.

关键词： Embedded systems

来源：评论

学校读者我要写书评

暂无评论

Stereo ORB-SLAM3 Underwater Performance Evaluation

Stereo ORB-SLAM3 Underwater Performance Evaluation

引用

Electrical engineering (ICEENG), International Conference on

作者： Hossam Elkeshky Samer A. Mohamed Mohammed I. Awad Hossam Abd El Munim Mechatronics Engineering Dept. Faculty of Engineering Ain Shams University Cairo Egypt Electrical and Electronic Engineering Dept. Faculty of Engineering and Design University of Bath Bath UK Computer Systems and Engineering Dept. Faculty of Engineering Ain Shams University Cairo Egypt

ISBN: (数字)9798331519018

ISBN: (纸本)9798331519025

Site exploration and navigation missions in hazardous locations are examples of the widespread applications of autonomous mobile robots. Efficient simultaneous localization and mapping (SLAM) is essential for the functionality of such robots. Visual SLAM (VSLAM) has become a cost-effective and attractive solution for all types of vehicles in the field. ORB-SLAM3 and its preceding versions are prevailing visual SLAM algorithms in recent literature. ORB-SLAM3 builds a three-dimensional map based on images and supplies a continuous estimate of the vehicle’s pose. This paper demonstrates an experimental evaluation of stereo ORB-SLAM3 performance in scenes with diverse backgrounds. Online ORB-SLAM3 is tested in multiple aerial and underwater environments. The performance of the algorithm is evaluated by comparing against ground-truth estimates provided by offline structure-from-motion techniques. Results show that ORB-SLAM3 can function in structured environments providing acceptable accuracy and satisfactory performance given the right conditions. The algorithm achieves average standard deviation values of 4 cm in underwater scenes depending on the complexity of the followed trajectory.

关键词： Visualization Simultaneous localization and mapping Accuracy Three-dimensional displays Structure from motion Pose estimation Trajectory Complexity theory State estimation Standards

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：