检索结果-内蒙古大学图书馆

Energy-Efficient Routing Using Novel Optimization with Tabu Techniques for Wireless Sensor Network

computer Systems science & engineering 2023年第5期45卷 1711-1726页

作者： Manar Ahmed Hamza Aisha Hassan Abdalla Hashim Dalia H.Elkamchouchi Nadhem Nemri Jaber S.Alzahrani Amira Sayed A.Aziz Mnahel Ahmed Ibrahim Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Digital Media Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt College of Science and Humanities Studies in Alquwayiyah Shaqra UniversitySaudi Arabia

Wireless Sensor Network(WSN)consists of a group of limited energy source sensors that are installed in a particular region to collect data from the *** the energy-efficient data collection methods in largescale wireless sensor networks is considered to be a difficult area in the *** node clustering is a popular approach for ***,the sensor nodes are grouped to form clusters in a cluster-based WSN *** battery performance of the sensor nodes is likewise *** a result,the energy efficiency of WSNs is *** specific,the energy usage is influenced by the loads on the sensor node as well as it ranges from the Base Station(BS).Therefore,energy efficiency and load balancing are very essential in *** the proposed method,a novel Grey Wolf Improved Particle Swarm Optimization with Tabu Search Techniques(GW-IPSO-TS)was *** selection of Cluster Heads(CHs)and routing path of every CH from the base station is enhanced by the proposed *** provides the best routing path and increases the lifetime and energy efficiency of the ***-to-end delay and packet loss rate have also been *** proposed GW-IPSO-TS method enhances the evaluation of alive nodes,dead nodes,network survival index,convergence rate,and standard deviation of sensor *** to the existing algorithms,the proposed method outperforms better and improves the lifetime of the network.

关键词： Wireless sensor networks energy-efficient load balancing energy consumption network’s lifetime cluster heads grey wolf optimization tabu search particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

Mechanical System Vulnerabilities: Advanced Fusion Machine Learning Model for Detecting Ethereum Attack Patterns in IIoT-5.0 Environments 1

引用

7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Sulakhe, Vishal N. Goyal, S.B. Gadekar, Amit Wasnik, Manisha Agarkar, Pankaj Rajawat, Anand Singh Mechanical Engineering Department Sandip University Nashik422213 India Faculty of Information Technology City University Petaling Jaya46100 Malaysia Sandip Institute of Technology and Research Centre Nashik India Ajeenkya D Y Patil School of Engineering Charoli Lohegaon Maharashtra Pune412105 India School of Computer Science and Engineering Sandip University Nashik422213 India

ISBN: (数字)9783031733185

ISBN: (纸本)9783031733178

It is of the utmost significance to keep the reliability and confidentiality of these systems in check in light of the coming advent of Industry 5.0 as well as the growing penetration of the Industrial Internet of Things (IIoT) into complicated mechanical systems. The broad adoption of blockchain technology, and in particular Ethereum, brings with it a new set of opportunities as well as hazards that have an impact on the complicated dynamic that exists between machines, data, and decentralized applications. This research investigates an advanced fusion machine learning model with the intention of locating dangerous patterns and likely attack vectors that target Ethereum transactions and contracts within IIoT-5.0 systems. The results of this investigation are intended to be used in future research. The detection of these patterns and vectors is the primary focus of the model. In an era in which there is a transition taking place in the industrial sector, this research presents a novel technique for improving cybersecurity. Examining the specific flaws that may exist in mechanical systems after they have been integrated with blockchain solutions is the strategy that will be utilized. Our model shows tremendous promise in recognizing abnormalities and potential dangers by utilizing a combination of supervised learning techniques and unsupervised learning approaches. These techniques allow for the model to develop without being directly monitored by a human. This paves the way for preventative safety precautions to be included in the design of the future generation of industrial systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Ethereum

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Analysis of Identifying Patients with Chronic Kidney Disease

A Comprehensive Analysis of Identifying Patients with Chroni...

引用

computer, Communication and Control (IC4), International Conference on

作者： S. Geetha C. N. Marimuthu S. Maheswari B. Deepa Faculty of Information and Communication Engineering Anna University Chennai India Department of Electronics and Communication Engineering Nandha Engineering College Erode India Department of Computer Science and Engineering Nandha Engineering College Erode India

Chronic Kidney Disease (CKD) is a prevalent and progressive health condition affecting millions of individuals worldwide. Early identification and management of CKD are critical to mitigate its adverse effects on patients’ health and reduce the burden on healthcare systems. This study presents a comprehensive analysis of various methodologies and approaches for identifying patients with Chronic Kidney Disease. The research encompasses a detailed review of traditional and emerging diagnostic techniques, by exploring the sensitivity, specificity, and accuracy of these methods, considering their applicability in diverse patient populations and healthcare settings. Furthermore, this analysis delves into the role of artificial intelligence (AI) and machine learning in enhancing CKD detection and risk prediction. The synthesis of this comprehensive analysis provides valuable insights into the current landscape of CKD identification and offers recommendations for optimizing diagnostic strategies.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Effective Anatomy Learning Using Markerless Augmented Reality Interface for Medical Education

Effective Anatomy Learning Using Markerless Augmented Realit...

引用

Advances in Data engineering and Intelligent Computing Systems (ADICS), International Conference on

作者： S. Athinarayanan M. Masthan Saravanan Chandrasekaran V. Ashwin Ram Mahesh T R Vivek V Department of CSE School of Computing Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology (Deemed to be University) Avadi Chennai India Arffy Technologies Private Limited Bengaluru Karnataka India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai Tamil Nadu Department of Computer Science and Engineering (AIML) SRM Institute of Science and Technology Ramapuram Chennai India Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru India

ISBN: (数字)9798350364828

ISBN: (纸本)9798350364835

Anatomy is a branch of biology dealing with the identification and explanation of living things body systems. Human anatomy is a significant chapter in every Biology class for secondary and post-secondary students. Traditional approaches and tools for studying human body anatomy include manuals with illustrations and images, as well as artificial anatomy mannequins. It isn't sufficient but and its miles tough to assist medical students to recognize it with actual and correct information and images approximately the anatomy of our human body. This is due to students' inability to visualize the actual configuration of human anatomy body parts and their lack of familiarity with 2D representations in textbooks. Furthermore, some students have difficulty interpreting 2D representations in textbooks, making it impossible for them to comprehend and gain information as quickly as possible in studying the layout of human anatomy body parts. Using Google AR Core and Unity3D, we proposed a system that builds a human anatomy learning android application that assists the medical students to visualize and analyze the Human Anatomy subject in an interactive way by using the Augmented Reality (AR) technique. The markerless AR approach is being used to create this scheme which uses the novel method to use the mobile computing platform as an alternative learning tool for studying the intricate structures of human body anatomy more practically and engagingly.

关键词： Human anatomy Image recognition Operating systems Layout Manuals Biology Internet

来源：评论

学校读者我要写书评

暂无评论

Architecture for AI-Based Validation of Wastewater Management Using Open Data Exchange Technique

Architecture for AI-Based Validation of Wastewater Managemen...

引用

2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： William, P. Oyebode, Oluwadare Joshua Ramu, Gandikota Gupta, Manish Alzubaidi, Laith H. Srivastava, Arun Pratap Sanjivani College of Engineering Savitribai Phule Pune University Department of Information Technology Pune India Afe Babalola University Civil and Environmental Engineering Ekiti State Ado-Ekiti Nigeria Institute of Aeronautical Engineering Department of Computer Science and Engineering Hyderabad500043 India Lovely Professional University Division of Research and Development Phagwara India The Islamic University Faculty of Engineering Najaf Iraq Lloyd Institute of Engineering and Technology Department of CSE Uttar Pradesh Greater Noida201308 India

ISBN: (纸本)9798350333244

To processing plant-wide data, it is not uncommon for there to be issues with sensors. Some examples of these issues include sensor failures, sensor calibration difficulties, sensor fouling and blockage, and connection problems between sensors, actuators, and the data management system. These problems may have an effect on the quality of the data, which will make it more difficult to implement sophisticated data-driven monitoring and control of (crucial) water operations. A method for the intelligent validation of data is provided in this article. The sensor data coming from a wastewater treatment plant are validated and verified by this process. The application for data validation has been integrated, tested, and put into production at the water utility known as Water Net. The method of validation is predicated on an anomaly detector that, in the event that an anomaly is found, combines (statistical) threshold-based procedures, (AI-based) autoencoder model predictions, and a component for data reconciliation. This occurrence repeats itself whenever an anomaly of some kind is found. In spite of the signal's volatility, the autoencoder models displayed outstanding levels of accuracy and great reconciliation performance. In addition, signals for both verified and raw data are provided in a way that is extremely near to real time to a dashboard. This keeps the dashboard up to date with the most recent information. Validated data may also be utilized as a screening tool for data that is being ingested by another AI-based model in order to monitor and intelligently manage the wastewater treatment plant, as well as to minimize greenhouse gas emissions and energy consumption while maintaining effluent water quality requirements. These goals may be accomplished while still meeting all applicable criteria. If this were done, it would be in compliance with the regulations for maintaining the effluent water's quality. © 2023 IEEE.

关键词： Wastewater treatment

来源：评论

学校读者我要写书评

暂无评论

Stereo Matching for Face Images Based on Feature Points

引用

Chinese Journal of Electronics 2023年第2期19卷 241-244页

作者： Yinghui Wang Bing Xiao Qiongfang Wang Faculty of Computer Science and Engineering Xi'an University of Technology Xi'an China Department of Computer Science Shaanxi Normal University Xi'an China Faculty of of Automation and Information Engineering Xi'an University of Technology Xi'an China

Stereo matching is the key of reconstructing 3D face model from 2D face images and Barnard's algorithm is one of the classical stereo matching algorithms based on feature points. In order to enhance the stability of extracting feature points, reduce computational complexity and minimize the effect of subjective factors, in this paper, Barnard's algorithm of edge point matching was improved from two aspects: edge point sets of left and right face images were extracted with dyadic wavelet transform, rather than comparing gray values of adjacent pixels; on the other hand, edge points in binocular stereo face images were matched under epipolar constraint in parallel binocular stereo matching. Experimental results demonstrate that stability and efficiency of stereo matching algorithm are both improved.

关键词： Wavelet transforms Technological innovation Solid modeling Three-dimensional displays Image edge detection Education Medical services

来源：评论

学校读者我要写书评

暂无评论

Two Layer Symmetric Cryptography Algorithm for Protecting Data from Attacks

引用

computers, Materials & Continua 2023年第2期74卷 2625-2640页

作者： Muhammad Nadeem Ali Arshad Saman Riaz Syeda Wajiha Zahra Shahab SBand Amir Mosavi Department of Computer Science Abasyn UniversityIslamabad44000Pakistan Department of Computer Science National University of TechnologyIslamabad44000Pakistan Future Technology Research Center National Yunlin University of Science and TechnologyDouliuYunlin64002Taiwan Institute of Information Society University of Public ServiceBudapest1083Hungary John Von Neumann Faculty of Informatics Obuda UniversityBudapestHungary Institute of Information Engineering Automation and MathilticsSlovak University of Technology in BratislavaSlovakia

Many organizations have insisted on protecting the cloud server from the outside,although the risks of attacking the cloud server are mostly from the *** are many algorithms designed to protect the cloud server from attacks that have been able to protect the cloud server ***,the attackers have designed even better mechanisms to break these security *** cryptography is the best data protection algorithm that exchanges data between authentic *** this article,one symmetric cryptography algorithm will be designed to secure cloud server data,used to send and receive cloud server data securely.A double encryption algorithm will be implemented to send data in a secure ***,the XOR function will be applied to plain text,and then salt technique will be ***,a reversing mechanism will be implemented on that data to provide more data *** decrypt data,the cipher text will be reversed,salt will be removed,andXORwill be *** the end of the paper,the proposed algorithm will be compared with other algorithms,and it will conclude how much better the existing algorithm is than other algorithms.

关键词： Cryptography symmetric algorithm encryption decryption cipher text cloud security asymmetric algorithm

来源：评论

学校读者我要写书评

暂无评论

Retraction Note: Optimizing radio access in 5G vehicle networks using novel machine learning-driven resource management

引用

Optical and Quantum Electronics 2024年第10期56卷 1-2页

作者： Natarajan, Rajesh Mahadev, Natesh Alfurhood, Badria Sulaiman Ranjith, Christodoss Prasanna Zaki, John Manu, M. N. Information Technology Department College of Computing and Information Sciences University of Technology and Applied Sciences-Shinas Shinas Oman Department of Computer Science and Engineering Vidyavardhaka College of Engineering Mysore India Department of Computer Sciences College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh Saudi Arabia Computer and Systems Department Faculty of Engineering Mansoura University Mansoura Egypt Department of Information Science and Engineering SJBIT Bengaluru India

来源：评论

学校读者我要写书评

暂无评论

Utilizing Image Recognition Methods for the Identification and Counting of Live Nematodes in Petri Dishes

Utilizing Image Recognition Methods for the Identification a...

引用

International Carpathian Control Conference (ICCC)

作者： Martin Radvansky Alena Kadlecova Milos Kudelka Department of Computer Science Faculty of Electrical Engineering and Computer Science VSB-TU Ostrava Ostrava-Poruba Czech Republic Department of Experimental Biology Faculty of Science Palacky University Olomouc Czech Republic

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

This article addresses a system designed for identifying and quantifying several species of nematodes, free-living and parasitic, placed on Petri dishes using modern image recognition methods. Traditional methods of counting nematodes are often time-consuming and prone to errors, leading to inaccurate biological and ecological study results. Our method employs advanced machine learning algorithms and computer vision to detect and count live nematodes automatically. The process utilizes algorithms to recognize specific larval characteristics, such as size and shape. This allows for high accuracy and efficiency while minimizing human intervention. The results demonstrate that our approach is robust and precise and can be widely utilized in biological research and applications.

关键词： computer vision Image recognition Machine learning algorithms Accuracy Shape Pipelines Machine learning

来源：评论

学校读者我要写书评

暂无评论

Diabetes Prediction Using Machine Learning Techniques: A Case Study from Jordan

Diabetes Prediction Using Machine Learning Techniques: A Cas...

引用

Information Technology (ACIT)

作者： Raed Alazaidah Radwan Batyha Ghassan Samara Esraa Al Henawi Maram Y. Al-Safarini Ahmad A. Samhan Ali Elrashidi Mo’Ath Alluwaici Deana Al-Omari Department of Data Science and AI Faculty IT Zarqa University Zarqa Jordan Department of Computer Science Faculty of IT Applied Science Private University Amman Jordan Department of Computer Science Faculty of IT Zarqa University Zarqa Jordan Department of Software Engineering Faculty of IT Zarqa University Zarqa Jordan Department of Electrical Engineering University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Diabetes is one of the most common diseases in Jordan. It is the main reason of death among Jordanian adult citizens. Worldwide, 48% of all deaths are due to Diabetes occurred before the age of 70 years. Hence, this research is interested in the early prediction of this disease among Jordanian people. To achieve this main objective, Machine Learning (ML) is utilized through a large number of classification models and considering five well-known evaluation metrics. These classification models have been trained on a primary dataset that has been collected for the purpose of the research. The results revealed that BayesNet and NaiveBayes are the best classification models to handle the task of the early prediction of Diabetes in Jordan

关键词： Measurement Machine learning Predictive models Diabetes Bayes methods Information technology Diseases

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：