检索结果-内蒙古大学图书馆

2nd International Conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Dharmateja, M. Rama, Prabha K.P. Asha, N. Nithya, P. Lalitha, S. Manojkumar, P. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Arunai Engineering College Department of Computer Science and Engineering Tamil Nadu Tiruvannamalai India Bannari Amman Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu Sathyamangalam India

ISBN: (纸本)9798350382952

Wireless Sensor Actuator Networks (WSANs) are sensitive to cyber threats due to present static encryption techniques. Adaptive security methods are required in WSAN settings to reduce evolving dangers and maintain data integrity. The paper introduces a novel method for encrypting WSAN data using AI and machine learning. Long Short-Term Memory (LSTM) networks process data, Genetic Algorithms (GAs) optimize encryption, and Isolation Forests detect threats in real-time. The proposed system achieved remarkable performance, with scores of 98% data integrity, 96% error repair, and 95% threat detection accuracy. Encryption rates reach their max at 200 Mbps, with optimal resource usage (30% CPU, 25% RAM) and a 5% false positive rate. The proposed AI-driven security architecture improves data integrity, encryption speed, and overall security efficacy in WSANs, surpassing existing methods. The paper overcomes the limitations of static encryption methods and proposes a proactive protection mechanism against developing cyber threats, making a substantial contribution to WSAN security improvement. © 2024 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Data Augmentation and Random Multi-Model Deep Learning for Data Classification

引用

Computers, Materials & Continua 2023年第3期74卷 5191-5207页

作者： Fatma Harby Adel Thaljaoui Durre Nayab Suliman Aladhadh Salim EL Khediri Rehan Ullah Khan Computer Science Department Future Academy-Higher Future Institute for Specialized Technological StudiesEgypt Department of Computer Systems Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawar25120Pakistan Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Computer Sciences Faculty of Sciences of GafsaUniversity of GafsaGafsaTunisia

In the machine learning(ML)paradigm,data augmentation serves as a regularization approach for creating ML *** increase in the diversification of training samples increases the generalization capabilities,which enhances the prediction performance of classifiers when tested on unseen *** learning(DL)models have a lot of parameters,and they frequently ***,to avoid overfitting,data plays a major role to augment the latest improvements in ***,reliable data collection is a major limiting ***,this problem is undertaken by combining augmentation of data,transfer learning,dropout,and methods of normalization in *** this paper,we introduce the application of data augmentation in the field of image classification using Random Multi-model Deep Learning(RMDL)which uses the association approaches of multi-DL to yield random models for *** present a methodology for using Generative Adversarial Networks(GANs)to generate images for data *** experiments,we discover that samples generated by GANs when fed into RMDL improve both accuracy and model *** across both MNIST and CIAFAR-10 datasets show that,error rate with proposed approach has been decreased with different random models.

关键词： Data augmentation generative adversarial networks classification machine learning random multi-model deep learning

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

On a New Rough Clustering Based on Optimization 13

On a New Rough Clustering Based on Optimization

引用

Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Furuta, Sakuya Endo, Yasunori Master's Program in Risk and Resilience Engineering Degree Programs in Systems and Information Engineering Graduate School of Science Annd Technology University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki305-8573 Japan Institute of Systems and Information Engineering University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki305-8573 Japan

ISBN: (纸本)9798350373332

The purpose of this study is to develop and investigate a new rough clustering based on optimization. We propose a restructured algorithm using only one variable, instead of the algorithm described using two variables in existing methods. We also perform numerical examples using artificial data and the Iris and Wine datasets. This research has the potential to be used as a method for determining false negatives and false positives in cancer diagnosis. © 2024 IEEE.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Voting Classifier and Metaheuristic Optimization for Network Intrusion Detection

引用

Computers, Materials & Continua 2023年第2期74卷 3183-3198页

作者： Doaa Sami Khafaga Faten Khalid Karim Abdelaziz A.Abdelhamid El-Sayed M.El-kenawy Hend K.Alkahtani Nima Khodadadi Mohammed Hadwan Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt The Department of Civil and Environmental Engineering Florida International UniversityMiamiFLUSA Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Managing physical objects in the network’s periphery is made possible by the Internet of Things(IoT),revolutionizing human *** attacks and unauthorized access are possible with these IoT devices,which exchange data to enable remote *** attacks are often detected using intrusion detection methodologies,although these systems’effectiveness and accuracy are *** paper proposes a new voting classifier composed of an ensemble of machine learning models trained and optimized using metaheuristic *** employed metaheuristic optimizer is a new version of the whale optimization algorithm(WOA),which is guided by the dipper throated optimizer(DTO)to improve the exploration process of the traditionalWOA *** proposed voting classifier categorizes the network intrusions robustly and *** assess the proposed approach,a dataset created from IoT devices is employed to record the efficiency of the proposed algorithm for binary attack *** dataset records are balanced using the locality-sensitive hashing(LSH)and Synthetic Minority Oversampling Technique(SMOTE).The evaluation of the achieved results is performed in terms of statistical analysis and visual plots to prove the proposed approach’s effectiveness,stability,and *** achieved results confirmed the superiority of the proposed algorithm for the task of network intrusion detection.

关键词： Voting classifier whale optimization algorithm dipper throated optimization intrusion detection internet-of-things

来源：评论

学校读者我要写书评

暂无评论

A Novel Approximate Message Passing Detection for Massive MIMO 5G System

引用

Computer systems science & engineering 2023年第6期45卷 2827-2835页

作者： Nidhi Gour Rajneesh Pareek Karthikeyan Rajagopal Himanshu Sharma Mrim M.Alnfiai Mohammed A.AlZain Mehedi Masud Arun Kumar Department of Computer Science&Engineering JECRC UniversityJaipurIndia Centre for Nonlinear Systems Chennai Institute of TechnologyChennaiIndia Department of Electronics and Communication Engineering and University Centre for Research&Development Chandigarh UniversityMohaliIndia Department of Information Technology College of Computer and Information TechnologyTaif UniversityP.O.Box 11099Taif21994Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099TaifSaudi Arabia Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia

Massive-Multiple Inputs and Multiple Outputs(M-MIMO)is considered as one of the standard techniques in improving the performance of Fifth Generation(5G)radio.5G signal detection with low propagation delay and high throughput with minimum computational intricacy are some of the serious concerns in the deployment of *** evaluation of 5G promises a high quality of service(QoS),a high data rate,low latency,and spectral efficiency,ensuring several applications that will improve the services in every *** existing detection techniques cannot be utilised in 5G and beyond 5G due to the high complexity issues in their *** the proposed article,the Approximation Message Passing(AMP)is implemented and compared with the existing Minimum Mean Square Error(MMSE)and Message Passing Detector(MPD)*** outcomes of the work show that the performance of Bit Error Rate(BER)is improved with minimal complexity.

关键词： AMP MMSE MPD 5G

来源：评论

学校读者我要写书评

暂无评论

Support Vector Machine Based Handwritten Hindi Character Recognition and Summarization

引用

Computer systems science & engineering 2022年第10期43卷 397-412页

作者： Sunil Dhankhar Mukesh Kumar Gupta Fida Hussain Memon Surbhi Bhatia Pankaj Dadheech Arwa Mashat Department of Computer Science&Engineering Swami Keshvanand Institute of TechnologyManagement&GramothanJaipurRajasthan302017India Department of Electrical Engineering Sukkur IBA UniversityPakistan Department of Mechatronics Engineering Jeju National UniversityJeju63243Korea Department of Information Systems College of Computer Science and Information TechnologyKing Faisal UniversitySaudi Arabia Faculty of Computing&Information Technology King Abdulaziz UniversityRabigh21911Saudi Arabia

In today’s digital era,the text may be in form of *** research aims to deal with the problem by recognizing such text and utilizing the support vector machine(SVM).A lot of work has been done on the English language for handwritten character recognition but very less work on the under-resourced Hindi language.A method is developed for identifying Hindi language characters that use morphology,edge detection,histograms of oriented gradients(HOG),and SVM classes for summary *** rank employs the summary to extract essential phrases based on paragraph position,phrase position,numerical data,inverted comma,sentence length,and keywords *** primary goal of the SVM optimization function is to reduce the number of features by eliminating unnecessary and redundant *** second goal is to maintain or improve the classification system’s *** experiment included news articles from various genres,such as Bollywood,politics,and *** proposed method’s accuracy for Hindi character recognition is 96.97%,which is good compared with baseline approaches,and system-generated summaries are compared to human *** evaluated results show a precision of 72%at a compression ratio of 50%and a precision of 60%at a compression ratio of 25%,in comparison to state-of-the-art methods,this is a decent result.

关键词： Support vector machine(SVM) optimization precision Hindi character recognition optical character recognition(OCR) automatic summarization and compression ratio

来源：评论

学校读者我要写书评

暂无评论

Routing and Spectrum Assignment in Spatial Channel Network-Based Inter-Datacenter Networks

Routing and Spectrum Assignment in Spatial Channel Network-B...

引用

2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Zheng, Weichang Zheng, Yu Yang, Mingcong Yang, Kun School of Information and Communication Engineering Yangtze Delta Region Institute University of Electronic Science and Technology of China Quzhou China Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Japan Huawei Technologies Department of R&d Wuhan China School of Information and Communication Engineering University of Electronic Science and Technology of China Sichuan China

We introduce spatial channel networks (SCNs) to the interconnection of data center networks (DCNs). We propose an integer linear programming (ILP) model to solve the routing and spectrum assignment problem for SCN-bas... 详细信息

ISBN: (纸本)9798350312614

关键词： datacenter network (DCN) integer linear programming (ILP) routing and spectrum assignment Spatial channel network (SCN)

来源：评论

学校读者我要写书评

暂无评论

A Simulation Algorithm for Multi-path Link of Digital Modulated Signals 10th

A Simulation Algorithm for Multi-path Link of Digital Modula...

引用

10th China Conference on Command and Control, C2 2022

作者： Song, Qingping Gao, Hongxing Zhao, Kailan Cao, Shuo Yu, Yue Science and Technology on Information Systems Engineering Laboratory Beijing Institute of Control and Electronic Technology Beijing100038 China

ISBN: (纸本)9789811960512

In order to test the processing ability and receiving detection ability of wireless communication receiver for multi-path fading and white Gaussian noise, it is necessary to simulate the carrier signal and a variety of modulation signals transmitted through multi-path and superimposed with white Gaussian noise. Firstly, according to the distance between transceivers and the location of obstacles, this paper theoretically analyzes the synthetic signal in the two path scenario. On this basis, the general carrier signal expression with more transmission paths and white Gaussian noise is analyzed, and the signal expression of four common digital modulation modes are deduced in this scenario, so as to complete the simulation of the signal with white Gaussian noise after multi-path fading channels. The simulation results show that the algorithm can effectively and accurately simulate the modulated signal in multi-path and noise environment, which provides conditions for signal reception and detection, so it has high application value. © 2022, Chinese Institute of Command and Control.

关键词： Multipath fading

来源：评论

学校读者我要写书评

暂无评论

Yolo Based License Plate Detection of Triple Riders and Violators

Yolo Based License Plate Detection of Triple Riders and Viol...

引用

2023 International Conference on Computer Communication and Informatics, ICCCI 2023

作者： Nandhakumar, R.G. Devi, K. Nirmala Krishnamoorthy, N. Shanthi, S. Pranesh, V.R. Nikhalyaa, S. Kongu Enginering College Perundurai Department of Computer Science and Engineering Tamilnadu Erode India Vellore Institutte of Technology School of Information and Engineering Department of Software Systems and Engineering Vellore India

ISBN: (纸本)9798350348217

Road safety is of prime importance as road accidents are among the biggest causes of deaths in the country. Road Accidents are majorly due to violators and lawbreakers of road safety rules like not wearing helmets, triple riding etc. Even though there are many smart systems to monitor these violations, it is complicated to keep a track of the data and view it efficiently anywhere. Also monitoring the permit details of other state vehicles is hard. A method was proposed to address this issue. based on Deep learning and Optical Character Recognition (OCR). Here we detect the riders not wearing helmet and triple riders using object detection by comparing YOLOv2 and YOLOv3. This simplifies the task of traffic police who can't continuously and efficiently monitor all the violators. We gathered our data from three different sources. Kaggle was used to collect the data set. A number of items can be recognized by the real-time object recognition system YOLO in a single frame. It recognizes object more precisely and faster than other recognition systems. It can predict up to 9000 classes and even unseen classes. It divides the image into m∗m matrix and each grid detects objects within itself. The trained model is tested using a test dataset set after training in order to measure the performance. For Number plate detection we use OCR based character recognition. The recognized license plate images of violators are captured and stored in a database which is then sent to the concerned department. The stored data can be easily accessed using the developed mobile app. Metrics considered for evaluation is Accuracy. The average is utilized to assess object detection models like R-CNN and YOLO. The average calculates a score by comparing the detected box to the ground-truth bounding box. The better the score, the more precise the model's detections are. When compared to YOLOv2, YOLOv3 exhibits strong performance in terms of accuracy with 95.5%. © 2023 IEEE.

关键词： Object detection

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：