Wasit Journal of Computer and Mathematics Science最新文献_第4页

Feature Selection and Dynamic Network Traffic Congestion Classification based on Machine Learning for Internet of Things 基于机器学习的物联网特征选择与动态网络流量拥塞分类

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-07-01 DOI: 10.31185/wjcms.150

Ahmed A. Elngar, Adriana Burlea‐Schiopoiu

{"title":"Feature Selection and Dynamic Network Traffic Congestion Classification based on Machine Learning for Internet of Things","authors":"Ahmed A. Elngar, Adriana Burlea‐Schiopoiu","doi":"10.31185/wjcms.150","DOIUrl":"https://doi.org/10.31185/wjcms.150","url":null,"abstract":"The network traffic congestion classifier is essential for network monitoring systems. Network traffic characterization is a methodology to classify traffic into several classes supporting various attributes. In this paper, payload-based classification is suggested for network traffic characterization. It has a broad scope of utilization like network security assessment, intrusion identification, QoS supplier, et cetera; furthermore, it has significance in investigating different suspicious movements in the network. Numerous supervised classification techniques like Support Vector Machines and unsupervised clustering methods like K-Means connected are used in traffic classification. In current network conditions, minimal supervised data and unfamiliar applications influence the usual classification procedure's performance. This paper implements a methodology for network traffic classification using clustering, feature extraction, and variety for the Internet of Things (IoT). Further, K-Means is used for network traffic clustering datasets, and feature extraction is performed on grouped information. KNN, Naïve Bayes, and Decision Tree classification methods classify network traffic because of extracted features, which presents a performance measurement between these classification algorithms. The results discuss the best machine learning algorithm for network congestion classification. According to the outcome, clustering (k-means) with network classification (Decision Tree) generates a higher accuracy, 86.45 %, than other clustering and network classification","PeriodicalId":224730,"journal":{"name":"Wasit Journal of Computer and Mathematics Science","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128059821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Optimum Design of Scanned Linear Antenna Array Using Sine Cosine Optimization Algorithm 基于正弦余弦优化算法的扫描线性天线阵列优化设计

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-07-01 DOI: 10.31185/wjcms.135

Alhussein Alturfi, S. Goyal, Amrit Kaur

引用次数: 0

On θg**- Closed Sets in Topological Spaces 论拓扑空间中的θg**-闭集

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-07-01 DOI: 10.31185/wjcms.124

Ahmed Hussein Wajan Alrikabiu, Ali Khalaf Hussain

引用次数: 0

Using Speech Signal for Emotion Recognition Using Hybrid Features with SVM Classifier 基于混合特征与SVM分类器的语音信号情感识别

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-03-31 DOI: 10.31185/wjcm.102

Fatima A.Hammed, Loay E. George

{"title":"Using Speech Signal for Emotion Recognition Using Hybrid Features with SVM Classifier","authors":"Fatima A.Hammed, Loay E. George","doi":"10.31185/wjcm.102","DOIUrl":"https://doi.org/10.31185/wjcm.102","url":null,"abstract":"Emotion recognition is a hot topic that has received a lot of attention and study,owing to its significance in a variety of fields, including applications needing human-computer interaction (HCI). Extracting features related to the emotional state of speech remains one of the important research challenges.This study investigated the approach of the core idea behind feature extraction is the residual signal of the prediction procedure is the difference between the original and the prediction .hence the visibility of using sets of extracting features from speech single when the statistical of local features were used to achieve high detection accuracy for seven emotions. The proposed approach is based on the fact that local features can provide efficient representations suitable for pattern recognition. Publicly available speech datasets like the Berlin dataset are tested using a support vector machine (SVM) classifier. The hybrid features were trained separately. The results indicated that some features were terrible. Some were very encouraging, reaching 99.4%. In this article, the SVM classifier test results with the same tested hybrid features that published in a previous article will be presented, also a comparison between some related works and the proposed technique in speech emotion recognition techniques.","PeriodicalId":224730,"journal":{"name":"Wasit Journal of Computer and Mathematics Science","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121384630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Face detection by using Haar Cascade Classifier 基于Haar级联分类器的人脸检测

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-03-31 DOI: 10.31185/wjcm.109

S. Hashim, Paul McCullagh

引用次数: 0

Blockchain and Machine Learning as Deep Reinforcement 区块链和机器学习作为深度强化

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-03-31 DOI: 10.31185/wjcm.103

Hiba S. Mahdi

引用次数: 0

IoT sensor network data processing using the TWLGA Scheduling Algorithm and the Hadoop Cloud Platform 物联网传感器网络数据处理采用TWLGA调度算法和Hadoop云平台

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-03-31 DOI: 10.31185/wjcm.122

M. Rashid, Wisam Abed

引用次数: 1

Security In Wireless Sensor Networks Based On Lightweight Algorithms : An Effective Survey 基于轻量级算法的无线传感器网络安全:一项有效研究

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-03-31 DOI: 10.31185/wjcm.106

Mohammed abd, H. Majeed, Sif. K. Ebis

{"title":"Security In Wireless Sensor Networks Based On Lightweight Algorithms : An Effective Survey","authors":"Mohammed abd, H. Majeed, Sif. K. Ebis","doi":"10.31185/wjcm.106","DOIUrl":"https://doi.org/10.31185/wjcm.106","url":null,"abstract":"At the level of both individuals and companies, Wireless Sensor Networks (WSNs) get a wide range of applications and uses. Sensors are used in a wide range of industries, including agriculture, transportation, health, and many more. Many technologies, such as wireless communication protocols, the Internet of Things, cloud computing, mobile computing, and other emerging technologies, are connected to the usage of sensors. In many circumstances, this contact necessitates the transmission of crucial data, necessitating the need to protect that data from potential threats. However, as the WSN components often have constrained computation and power capabilities, protecting the communication in WSNs comes at a significant performance penalty. Due to the massive calculations required by conventional public-key and secret encryption methods, information security in this limited context calls for light encryption techniques. In many applications involving sensor networks, security is a crucial concern. On the basis of traditional cryptography, a number of security procedures are created for wireless sensor networks. Some symmetric-key encryption techniques used in sensor network setups include AES, RC5, SkipJack, and XXTEA. These algorithms do, however, have several flaws of their own, including being susceptible to chosen-plaintext assault, brute force attack, and computational complexity.","PeriodicalId":224730,"journal":{"name":"Wasit Journal of Computer and Mathematics Science","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125454571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SAR Calculation in a Child Seven-Layer Head Model at 2.1 and 2.6 GHz 2.1和2.6 GHz下儿童七层头部模型SAR计算

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-03-31 DOI: 10.31185/wjcm.105

G. Ahmed, A. Sallomi

引用次数: 0

A Control System of DC Motor Speed: Systematic Review 直流电机转速控制系统综述

Wasit Journal of Computer and Mathematics Science Pub Date : 2023-03-31 DOI: 10.31185/wjcm.121

Muhammad Hilal, H. Alrikabi, Ibtisam A. Aljazaery

{"title":"A Control System of DC Motor Speed: Systematic Review","authors":"Muhammad Hilal, H. Alrikabi, Ibtisam A. Aljazaery","doi":"10.31185/wjcm.121","DOIUrl":"https://doi.org/10.31185/wjcm.121","url":null,"abstract":"The first sources of direct current (DC) were invented, DC machines were one of the first types of electro-mechanical machines used. DC machines are more advantageous over AC machines as regards to Speed regulation and versatility. A DC motor is an electrical actuator with a lot of control that is used in a lot of applications, like robotic manipulators, guided vehicles, steel rolling mills, cutting tools, overhead cranes, electrical traction, and other applications. Due to their speed-torque characteristics and ease of control, DC motors are utilized extensively in industries for demanding variable speed applications. In terms of controller design and implementation, the process control industry has seen numerous advancements over the past two decades. In the industry, there is a great demand for automatic controllers that can respond quickly and accurately to perform precise tasks. The feedback loop is an essential component of system control that must be utilized in order to achieve the desired performance in the majority of systems. Numerous control strategies have been developed for various feedback control systems in order to achieve rapid system dynamic response. Controls in a drive system are crucial if the reference speed is to be accurately and quickly tracked, with little or no steady-state error and as little overshoot as possible. This paper presents the Systematic literature review that was conducted as covers pertinent established concepts and techniques related to the DC motor speed control system design, for applications that require actuators with accurate speed characteristics. Simulation and real time implementation results employed for DC motor speed control systems in various literature are analysed and discussed.","PeriodicalId":224730,"journal":{"name":"Wasit Journal of Computer and Mathematics Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132187406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0