检索结果-内蒙古大学图书馆

An energy-aware routing scheme based on a virtual relay tunnel in flying ad hoc networks

Alexandria engineering Journal 2024年 91卷 249-260页

作者： Hosseinzadeh, Mehdi Ali, Saqib Mohammed, Adil Hussein Lansky, Jan Mildeova, Stanislava Yousefpoor, Mohammad Sadegh Yousefpoor, Efat Hassan Ahmed, Omed Rahmani, Amir Masoud Mehmood, Asif Institute of Research and Development Duy Tan University Da Nang Viet Nam School of Medicine and Pharmacy Duy Tan University Da Nang Viet Nam Department of Information Systems College of Economics and Political Science Sultan Qaboos University Al Khoudh Muscat Oman Department of Communication and Computer Engineering Faculty of Engineering Cihan University-Erbil Kurdistan Region Iraq Department of Computer Science and Mathematics Faculty of Economic Studies University of Finance and Administration Prague Czech Republic Department of Computer Engineering Dezful Branch Islamic Azad University Dezful Iran Department of Information Technology University of Human Development Sulaymaniyah Iraq Future Technology Research Center National Yunlin University of Science and Technology Yunlin Taiwan Department of Biomedical Engineering Gachon University Gyeonggi-do Seongnam-si13120 Korea Republic of

Flying ad hoc networks (FANETs) tackle diverse challenges, for example, dynamic topological structure, high mobility of nodes, low density, and energy restrictions. These challenges make problems in designing reliable and stable routing in FANETs. Hence, the design of a routing algorithm is essential for transferring data between drones. In this paper, an energy-aware routing scheme based on a virtual relay tunnel (EARVRT) is proposed in flying ad hoc networks. EARVRT includes a virtual relay tunnel (VRT) that manages relay nodes in the route discovery process and lowers network overhead. Moreover, three metrics, namely route energy, hop counts, and a new metric called path correlation are regarded in the path selection operation. Note that correlation is defined with regard to two scales, including the cosine similarity of two nodes and their distance. EARVRT is evaluated according to delay, network longevity, consumed energy, and packet delivery rate. Then, our scheme is compared with three methods, namely LoCaL, O-LAR, and PSO-GLFR. These results show the superiority and success of EARVRT in comparison with other algorithms. © 2024 The Author(s)

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Performance Assessment of Multi-Controller in Software Defined Network 4

Performance Assessment of Multi-Controller in Software Defin...

引用

4th IEEE International Conference on Computing, Communication, and Intelligent systems, ICCCIS 2023

作者： Jaiswal, Ankita Patra, Sudhansu Shekhar Dash, Bibhuti Bhusan Barik, Lalbihari Pandey, Trilok Nath Mishra, Manoj Ranjan School of Computer Engineering KIlT Deemed to Be University Bhubaneswar India King Abdulaziz University Faculty of Computing and Information Technology in Rabigh Department of Information Systems Saudi Arabia School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350306118

In a network design, the control plane and the data plane are separated by the architectural concept of software defined networking (SDN). A centralised controller that serves as the only point of control for the whole network is introduced by the SDN architecture. The controller serves as a logically centralized entity in charge of communicating the appropriate rules to a switch's flow table. Using a single controller to handle a lot of flows becomes insufficient. A lot of large-scale networks have employed multi-controller SDN to meet their objectives. In this research, we use a multi-controller infinite buffer waiting queue model to analyze the system performance metrics. Both numerical and simulated assessments are used to illustrate the proposed model. © 2023 IEEE.

关键词： Controllers

来源：评论

学校读者我要写书评

暂无评论

A Mathematical Comparison Between Response-Time Analysis and Real-Time Calculus for Fixed-Priority Preemptive Scheduling 34

A Mathematical Comparison Between Response-Time Analysis and...

引用

34th Euromicro Conference on Real-Time systems, ECRTS 2022

作者： Pollex, Victor Slomka, Frank INCHRON AG Erlangen Germany Institute of Embedded Systems/Real-Time Systems Faculty of Engineering and Computer Science Universität Ulm Germany

ISBN: (纸本)9783959772396

Fixed-priority preemptive scheduling is a popular scheduling scheme for real-time systems. This is accompanied by a vast amount of research on how to analyse and check whether these systems satisfy their real-time requirements. Two methods that emerged from this research are the response-time analysis and the real-time calculus. These two methods have been compared empirically on the basis of several abstract systems showing that for some systems one method gives better results than the other and for other systems both methods appear to give the same results. However, empirical analyses inherently contain uncertainty. To get a definitive answer we compare both methods mathematically and we show that both methods give the same results for systems that use fixed-priority preemptive scheduling and independent tasks. © Victor Pollex and Frank Slomka

关键词： Real time systems

来源：评论

学校读者我要写书评

暂无评论

Cost-Effective HWIL testing methodology for SALS guided missiles

引用

Materials Today: Proceedings 2022年 62卷 2509-2515页

作者： Todi, Ivana Kuzmanovi, Vladimir University of Belgrade Faculty of Mechanical Engineering Weapon Systems Department Kraljice Marije 16 Belgrade 11120 Serbia University of Belgrade Faculty of Mathematics Department for Computer Science and Informatics Studentski Trg 16 Belgrade 11000 Serbia

Verifying a new missile design requires a series of successful real-life tests on a firing range in various scenarios. Such an approach is extremely expensive and requires complex infrastructure and logistics. The costs of developing a new missile design can be significantly reduced by applying extensive and well thought out laboratory testing prior to any real-life test. Laboratory tests such as Hardware-In-The-Loop (HWIL) simulation enable the missile to be tested in a controlled environment inside a laboratory. HWIL testing methodology enables engineers to test the missile or its components in various simulated scenarios that correspond to real-life flights. Usually, a five-axis motion platform is used to perform HWIL simulation of terminal guidance. Three inner axes of the five-axis motion platform are used for simulation of the missiles body angles, while the two outer axes are used for simulation of the target movement relative to the missile. Such an approach requires spacious laboratories and expensive equipment. In this paper, we present a cost-effective HWIL testing methodology for Semi-Active-Laser-Seeker (SALS) guided missiles. The presented methodology requires only a three-axis motion platform and a fixed laser source. In the paper, we propose a two-stage HWIL testing procedure. In the first stage, the INS algorithm, guidance algorithm and autopilot algorithms are verified. In the second stage of the proposed HWIL testing methodology, the terminal guidance algorithm based on SALS angles is verified. Besides the HWIL testing methodology, we present the guidance law used in the testing procedure as well as the design of intercommunication between all the devices required to perform the tests. Next, the obtained results after each stage of the proposed HWIL testing methodology are presented and analyzed. Finally, a conclusion is drawn and limitations of the proposed testing methodology are explained. © 2020

关键词： Embedded systems

来源：评论

学校读者我要写书评

暂无评论

Adaptive Methods for Kernel Initialization of Convolutional Neural Network Model Applied to Plant Disease Classification 11

Adaptive Methods for Kernel Initialization of Convolutional ...

引用

11th IEEE Open Conference of Electrical, Electronic and Information sciences, eStream 2024

作者： Lagnaoui, Saloua Boumais, Khaoula Fallah, Saad El En-Naimani, Zakariae Haddouch, Khalid Matuzevicius, Dalius ENSA Sidi Mohamed Ben Abdellah University Laboratory Engineering Systems and Applications Fez Morocco Sidi Mohammed Ben Abdallah University ENSA Laboratory AI Data Science and Emerging Systems Fez Morocco Private University of Fez Systems and Sustainable Environment Laboratory Faculty of Engineering Sciences Fez Morocco ENSET Laboratory Computer Science AI and Cyber Security University of Hassan II Casablanca Mohammedia Morocco Vilnius Gediminas Technical University Faculty of Electronics Department of Electronic Systems Vilnius Lithuania

ISBN: (纸本)9798350352412

Convolutional Neural Networks are instrumental in artificial intelligence, especially in image processing, where their ability to autonomously learn hierarchical features has led to significant breakthroughs. However, the success of these models is intricately tied to the judicious choice of hyperparameters, which include the configuration of convolutional layers, activation functions, and kernel initialization methods. This research explores kernel initialization methods in Convolutional Neural Network models, seven diverse initialization methods (Glorot Uniform, Ones initialization, Zero initialization, Constant initialization, Random initialization, HeNormal initialization, and Orthogonal initialization) are comprehensively compared. The primary objective is to showcase the sensitivity of Convolutional Neural Networks to these various initialization techniques. The study not only aims to reveal the nuanced impact of kernel initialization but also introduces an adaptive method to enhance model performance. By delving into the intricacies of initialization methods, this research contributes to the improvement of Convolutional Neural Networks effectiveness, especially in critical applications like Plant Disease classification. © 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

A Perceptual Data Cleansing Model (SDCM) for Reducing the Dirty Data

A Perceptual Data Cleansing Model (SDCM) for Reducing the Di...

引用

2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Al-Madi, Mohammad Azmi Abdel-Wahab, Ahmed Alshanty, Mohammed Bawazeer, Shaikhan Alzahrani, Mohammed Al-Zaytoonah University of Jordan Faculty of Science and Information Technology Department of Computer Sciences Amman Jordan Arab Open University Faculty of Computer Studies Riyadh Saudi Arabia Al-Azhar University Deprtment of Systems and Computers Engineering Cairo Egypt

ISBN: (纸本)9798350347050

Data cleansing approaches aim at revealing and reducing different types of outsourced errors. Such errors introduce a major issue as data cleansing often involves costly computations and time consumption. Data cleansing is complicated as most of the errors within the obtained data emerge in different forms, such as typos, duplicates, noncompliance with business rules, outdated data, and missing values. In this paper, the Supervised Dataset Cleaning Model (SDCM) is proposed in order to detect and reduce different types of outsourced errors that are stored in the data repository according to the supervised cleaning rules that are practiced from the previous cleaning processes. The findings indicates that the cleaning execution time can be reduced with this supervised model and the accuracy of the model is also increased when it covers the entire training rules and classified error types derived from the data warehouse. There are some expected future directions, which include: implementing full scale of SDCM and comparing the results obtained with different current methods. By comparing different data cleaning algorithms with SDCM, a knowledge gap is likely to arise in the search for further future improvements. © 2023 IEEE.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

引用

computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif Mehmood Zhonglong Zheng Rizwan Khan Ahmad Al Smadi Farah Shahid Shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

来源：评论

学校读者我要写书评

暂无评论

Network Intrusion Detection Based on Feature Selection and Hybrid Metaheuristic Optimization

引用

computers, Materials & Continua 2023年第2期74卷 2677-2693页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Manal Abdullah Alohali Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.

关键词： Feature selection grey wolf optimization dipper throated optimization intrusion detection internet-of-things(IoT)

来源：评论

学校读者我要写书评

暂无评论

A language for graph database evolution and its implementation in Neo4j 42

A language for graph database evolution and its implementati...

引用

42nd International Conference on Conceptual Modeling: ER Forum, 7th Symposium on Conceptual Modeling Education, SCME 2023, Project Exhibitions, Posters and Demos, and Doctoral Consortium, ER-Companion 2023

作者： Hausler, Dominique Klettke, Meike Störl, Uta University of Regensburg Data Engineering Group Faculty of Informatics and Data Science Bajuwarenstrasse 4 Regensburg93053 Germany University of Hagen Chair of Databases and Information Systems Faculty of Mathematics and Computer Science Universitätsstrasse 1 Hagen58084 Germany

In this article, we present an evolution language for graph databases and a method to realize evolution operations on graph databases and their schema. Graph database management systems like Neo4j can be used for different scenarios: they can store graphs where no semantic constraints are checked. It is also possible to use them to store graphs where the structure of nodes and relationships is regular, for example, because the nodes and relationships of a graph have been generated by an application. In the latter case, these structures may change, that means they can undergo evolution. Currently, there is no established evolutionary language for graphs. However, evolution operations (such as add, rename, delete, merge, copy, split and move) have already been developed for other database models. In this article, we will not only use the established evolution operations but additionally extend the operations appropriated. After analyzing evolution operators explicitly in the context of graph databases, we also created a new graph-specific operation: transform. Moreover, we suggest an evolution language to graph data and show how it can be executed on the graph database schema as well as on the instances (i.e. the graphs themselves). In doing so, some operations can be implemented native based on Cypher, others non-native using the APOC library for Neo4j. © 2023 CEUR-WS. All rights reserved.

关键词： evolution graph databases evolution graph evolution language graph schema description

来源：评论

学校读者我要写书评

暂无评论

A Machine Learning Approach in Predictive Maintenance in the IoT Enabled Industry 4.0 4

A Machine Learning Approach in Predictive Maintenance in the...

引用

4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Madasamy, Sathiyakeerthi Shankar, B. Prabhu Yadav, Rakesh Kumar Jayalakshmi, K.P. Solution Architect Pilvi Systems Inc LewisvilleTX75057 United States Alliance University Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka562106 India Srm Institute of Science and Technology Department of Computer Science and Engineering Uttar Pradesh Ghaziabad201204 India St Joseph Engineering College Department of Electronics and Communication Engineering Karnataka Mangaluru India

ISBN: (纸本)9798350300888

Predictive maintenance using machine learning is a powerful technique for industries seeking to enhance their operations with minimize downtime. In an IoT-enabled Industry 4.0 environment, this approach can be taken to a new level by leveraging the vast amounts of data generated by connected devices. To implement a machine learning methodology to projecting conservation in an Industry 4.0 environment, several key steps need to be taken. First, data from IoT devices across the industrial ecosystem should be collected and centralized in a data lake or similar storage system. This data should include information on equipment health, sensor readings, and other relevant metrics. Next, the data should be preprocessed and transformed to ensure its quality and consistency. This may involve cleaning, normalization, and feature engineering to create relevant variables for use in machine learning models. Once the data has been preprocessed, a range of machine learning models can be trained on it to predict equipment failures or other maintenance issues. This may involve ongoing tuning and optimization of model hyperparameters or retraining the models on new data as it becomes available. Finally, the predictions generated by the machine learning models should be integrated into a broader maintenance management system to enable timely action. This may include triggering maintenance requests, generating work orders, or even automating maintenance tasks through the use of robots or other industrial automation technologies. By implementing a machine learning method to projecting preservation in an IoT-enabled Industry 4.0 environment, industries can optimize their operations, minimize downtime, and improve overall equipment effectiveness. © 2023 IEEE.

关键词： Industry 4.0

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：