Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677817
Beyda S. Abdullah, Barah M. Sulaiman, M. Al-Neima
A new concept in topological space called ici-open set is introduced, depended on the common adjective between i-open and int-open sets. Therefore, every ici-open set is i-open and int-open set. The ici-open sets inherits some properties from i-open and int-open sets, as every ici-open set is a semi-open set. The family of i-open sets forms a topological space if it generated from topology contains just three elements, the third element is set with one element but when contain more than one that is not true. This case has different behavior for the family of ici-open sets, which forms a topological space even if the mention set contains more than one element. In addition, some properties and theorems using ici-open sets have been proved.
{"title":"On ici-Open Sets in Topological Spaces","authors":"Beyda S. Abdullah, Barah M. Sulaiman, M. Al-Neima","doi":"10.1109/ICCITM53167.2021.9677817","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677817","url":null,"abstract":"A new concept in topological space called ici-open set is introduced, depended on the common adjective between i-open and int-open sets. Therefore, every ici-open set is i-open and int-open set. The ici-open sets inherits some properties from i-open and int-open sets, as every ici-open set is a semi-open set. The family of i-open sets forms a topological space if it generated from topology contains just three elements, the third element is set with one element but when contain more than one that is not true. This case has different behavior for the family of ici-open sets, which forms a topological space even if the mention set contains more than one element. In addition, some properties and theorems using ici-open sets have been proved.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129118975","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677679
M. A. Sadeeq, Subhi R. M. Zeebaree
Population growth and the creation of new equipment are accompanied by a constant increase in energy use each day and have created significant consumer issues in energy management. Smart meters (SM) are simply instruments for measuring energy usage and are a significant resource of the evolving technological energy management system. Including precise billing data, information on usage at the user end, installation of two-way communication. SM is the critical component of an intelligent power grid. The Internet of Things (IoT) is a critical partner in the power business leading to intelligent resource management to ensure successful data collection and use. This paper proposes designing and analyzing intelligent energy management systems based on Multi-Agent (MA) and Distributed IoT (DIoT). An efficient approach is proposed to monitor and control power consumption levels of the proposed case study of Duhok Polytechnic University (DPU). DPU consists of Presidency, six colleges, and eight institutes. These fifteen campuses are distributed through a wide geographical area with long distances between each campus (i.e., more than 100 Km). A Node represents each campus, and Wi-Fi makes the connection inside each node. These nodes are connected via the Internet to the Main Control Unit (MCU) represented by Raspberry Pi connected to the cloud. Depending on the received data from the Nodes, the MCU will make the correct decision for each node using intelligent algorithms and the user's requirement. Then, control commands are initiated, and the node's appliances can be controlled automatically (or even manually) from the MCU.
{"title":"Design and Analysis of Intelligent Energy Management System based on Multi-Agent and Distributed IoT: DPU Case Study","authors":"M. A. Sadeeq, Subhi R. M. Zeebaree","doi":"10.1109/ICCITM53167.2021.9677679","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677679","url":null,"abstract":"Population growth and the creation of new equipment are accompanied by a constant increase in energy use each day and have created significant consumer issues in energy management. Smart meters (SM) are simply instruments for measuring energy usage and are a significant resource of the evolving technological energy management system. Including precise billing data, information on usage at the user end, installation of two-way communication. SM is the critical component of an intelligent power grid. The Internet of Things (IoT) is a critical partner in the power business leading to intelligent resource management to ensure successful data collection and use. This paper proposes designing and analyzing intelligent energy management systems based on Multi-Agent (MA) and Distributed IoT (DIoT). An efficient approach is proposed to monitor and control power consumption levels of the proposed case study of Duhok Polytechnic University (DPU). DPU consists of Presidency, six colleges, and eight institutes. These fifteen campuses are distributed through a wide geographical area with long distances between each campus (i.e., more than 100 Km). A Node represents each campus, and Wi-Fi makes the connection inside each node. These nodes are connected via the Internet to the Main Control Unit (MCU) represented by Raspberry Pi connected to the cloud. Depending on the received data from the Nodes, the MCU will make the correct decision for each node using intelligent algorithms and the user's requirement. Then, control commands are initiated, and the node's appliances can be controlled automatically (or even manually) from the MCU.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130128469","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677752
Farah Jawad Al-ghanim, A. M. Al-juboori
Facial recognition has been broadly used in advanced intelligent systems (i.e: smart video surveillance, intelligent access control system, and online payment). The performance of existing algorithms for automatic facial recognition is hampered by various covariates like pose variations, face aging, disguises, and makeup. Disguises and makeup are especially used to intentional or unintentional changes facial appearance to either hide one's personal identity or impersonate someone's different identity. While new algorithms continue to improve performance, most face recognition systems are liable to failure when disguised or makeup altered, which is one of the most challenging factors to overcome. With enormous capability and promising results, deep learning technology becomes attracted to the greatest attention to the research in a diversity of computer vision tasks. In order to overcome this problem, the database of disguised and makeup faces (DMFD) is used. In this paper, face features are extracted by Linear Discriminant Analysis (LDA). Facial recognition is done by using proposed hybrid-deep learning Classifier for more precise feature learning. Also, we compared the proposed method with two pre-trained models (AlexNet and VGG16). The Experimental results taking after implementation and testing showed the effectiveness of the proposed system provided better precision by (94%)
{"title":"Face Identification Under Disguise and Makeup Based on Hybrid Deep Learning","authors":"Farah Jawad Al-ghanim, A. M. Al-juboori","doi":"10.1109/ICCITM53167.2021.9677752","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677752","url":null,"abstract":"Facial recognition has been broadly used in advanced intelligent systems (i.e: smart video surveillance, intelligent access control system, and online payment). The performance of existing algorithms for automatic facial recognition is hampered by various covariates like pose variations, face aging, disguises, and makeup. Disguises and makeup are especially used to intentional or unintentional changes facial appearance to either hide one's personal identity or impersonate someone's different identity. While new algorithms continue to improve performance, most face recognition systems are liable to failure when disguised or makeup altered, which is one of the most challenging factors to overcome. With enormous capability and promising results, deep learning technology becomes attracted to the greatest attention to the research in a diversity of computer vision tasks. In order to overcome this problem, the database of disguised and makeup faces (DMFD) is used. In this paper, face features are extracted by Linear Discriminant Analysis (LDA). Facial recognition is done by using proposed hybrid-deep learning Classifier for more precise feature learning. Also, we compared the proposed method with two pre-trained models (AlexNet and VGG16). The Experimental results taking after implementation and testing showed the effectiveness of the proposed system provided better precision by (94%)","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126149876","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677693
Saifaldeen Alabadee, Karam Thanon
Malware classification is one of the most important issues in Information security, because of the huge new numbers of these malwares. Therefore, more classification methods have been proposed. Random forest (RF) is one of the extremely method in many studies or deferent feature extraction methods. It has been considered as one of the efficient methods of malware classification due to it is accurate results. In this paper, machine learning based RF classifier had been proposed to evaluate the performance of the Random Forest implementation. The RF classifier showed high performance as a detector. It has a good capability of classifying huge number of features with unimportant features. Both training and classifying accuracy have increased by reduction of the number of training feature in dataset. The RF classifier have achieved 95.3% of accuracy.
{"title":"Evaluation and Implementation of Malware Classification Using Random Forest Machine Learning Algorithm","authors":"Saifaldeen Alabadee, Karam Thanon","doi":"10.1109/ICCITM53167.2021.9677693","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677693","url":null,"abstract":"Malware classification is one of the most important issues in Information security, because of the huge new numbers of these malwares. Therefore, more classification methods have been proposed. Random forest (RF) is one of the extremely method in many studies or deferent feature extraction methods. It has been considered as one of the efficient methods of malware classification due to it is accurate results. In this paper, machine learning based RF classifier had been proposed to evaluate the performance of the Random Forest implementation. The RF classifier showed high performance as a detector. It has a good capability of classifying huge number of features with unimportant features. Both training and classifying accuracy have increased by reduction of the number of training feature in dataset. The RF classifier have achieved 95.3% of accuracy.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126952903","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677834
Mohanned A.M. Al-Ja'afari, Firas Abedi, L. F. Al-Rammahi
Nonlinearity and memory effects are huge challenges for traditional High-Power Amplifier (HPA), since they cause a noisy transmitted signal and accumulated error, which eventually reduce the efficiency of the HPA. This paper proposes a new approach to handle these challenges, we utilized a standard Volterra Filter to deals with the nonlinearity and memory effect, in addition, we included FIR filter to further improve the reduction of memory distortion. The simulation results of the proposed method overcome the other methods in terms of accuracy and accumulated error. These results suggest that our method is quite appropriate for traditional HPA for practical applications that suffer from such distortions.
{"title":"Improved Assessment of HPA by Using Volterra Series and FIR Filter","authors":"Mohanned A.M. Al-Ja'afari, Firas Abedi, L. F. Al-Rammahi","doi":"10.1109/ICCITM53167.2021.9677834","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677834","url":null,"abstract":"Nonlinearity and memory effects are huge challenges for traditional High-Power Amplifier (HPA), since they cause a noisy transmitted signal and accumulated error, which eventually reduce the efficiency of the HPA. This paper proposes a new approach to handle these challenges, we utilized a standard Volterra Filter to deals with the nonlinearity and memory effect, in addition, we included FIR filter to further improve the reduction of memory distortion. The simulation results of the proposed method overcome the other methods in terms of accuracy and accumulated error. These results suggest that our method is quite appropriate for traditional HPA for practical applications that suffer from such distortions.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115498827","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677720
Hiba Dhivaa Ali, A. Abdulqader
Traditional Vehicular Ad-hoc Networks (VANETs) can efficiently be supplemented with the software-defined networking (SDN) paradigm which uses independent planes for data transmission and control. Integrating the SDN with the VANETs is a part of the development of intelligent VANETs. This integration technology has collected the attentions of researchers. In this paper, a new simulation model called the IoT-VANET is suggested with the SDN controller to enhance the communication between vehicles. This model uses the mininet-IoT simulator. For the purpose of comparison with previous work, a simulation model called the WiFi-VANET is built. It uses the mininet-WiFi software in two ways. Firstly, utilizing the Vehicle to Vehicle (V2V) communication performance evaluation based on the Road Side Units (RSU) and SDN controller. Three controllers of the Ryu (a Japanese word means flow), Python-based OpenFlow (POX) and centralized controller are exploited. Secondly, using the V2V communication performance evaluation based on the Global Positioning System (GPS). In terms of average delay and throughput, the performance evaluations of these two models show that the IoT-VANET is more efficient than the WiFi-VANET.
软件定义网络(SDN)使用独立的平面进行数据传输和控制，可以有效地补充传统的车载自组织网络(vanet)。SDN与vanet的融合是智能vanet发展的一部分。这种集成技术引起了研究人员的广泛关注。本文提出了一种基于SDN控制器的IoT-VANET仿真模型，以增强车辆间的通信能力。该模型使用微型物联网模拟器。为了与以往的工作进行比较，本文建立了WiFi-VANET的仿真模型。它以两种方式使用迷你wifi软件。首先，利用基于路旁单元(RSU)和SDN控制器的车对车(V2V)通信性能评估。他们利用了Ryu(日语中意为流)、基于python的OpenFlow (POX)和集中式控制器三种控制器。其次，采用基于全球定位系统(GPS)的V2V通信性能评估。在平均延迟和吞吐量方面，这两种模型的性能评估表明IoT-VANET比wi - fi - vanet更高效。
{"title":"Using Software Defined Network (SDN) Controllers to Enhance Communication between Two Vehicles in Vehicular AD HOC Network (VANET)","authors":"Hiba Dhivaa Ali, A. Abdulqader","doi":"10.1109/ICCITM53167.2021.9677720","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677720","url":null,"abstract":"Traditional Vehicular Ad-hoc Networks (VANETs) can efficiently be supplemented with the software-defined networking (SDN) paradigm which uses independent planes for data transmission and control. Integrating the SDN with the VANETs is a part of the development of intelligent VANETs. This integration technology has collected the attentions of researchers. In this paper, a new simulation model called the IoT-VANET is suggested with the SDN controller to enhance the communication between vehicles. This model uses the mininet-IoT simulator. For the purpose of comparison with previous work, a simulation model called the WiFi-VANET is built. It uses the mininet-WiFi software in two ways. Firstly, utilizing the Vehicle to Vehicle (V2V) communication performance evaluation based on the Road Side Units (RSU) and SDN controller. Three controllers of the Ryu (a Japanese word means flow), Python-based OpenFlow (POX) and centralized controller are exploited. Secondly, using the V2V communication performance evaluation based on the Global Positioning System (GPS). In terms of average delay and throughput, the performance evaluations of these two models show that the IoT-VANET is more efficient than the WiFi-VANET.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115723744","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677861
Qusai AL-Durrah, S. Sadkhan
The area of cyber warfare is vast, with several subtopics attracting interest from researchers. We start with the obvious fundamental question that is: what is cyberwarfare? We compare definitions that already exist to see where there is agreement or disagreement. We notice that there is no commonly recognized definition and that the terms “cyberwar” and “cyberwarfare” are not properly distinguished. In order to address these challenges, we present a defining model to help describe both cyber warfare and cyber war. Following that, the paper identifies nine cyber warfare research challenges and reviews current research in each. Finally, we make recommendations for how future initiatives in the field might best advance the subject.
{"title":"Cyberwarfare Techniques: Status, Challenges and Future trends","authors":"Qusai AL-Durrah, S. Sadkhan","doi":"10.1109/ICCITM53167.2021.9677861","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677861","url":null,"abstract":"The area of cyber warfare is vast, with several subtopics attracting interest from researchers. We start with the obvious fundamental question that is: what is cyberwarfare? We compare definitions that already exist to see where there is agreement or disagreement. We notice that there is no commonly recognized definition and that the terms “cyberwar” and “cyberwarfare” are not properly distinguished. In order to address these challenges, we present a defining model to help describe both cyber warfare and cyber war. Following that, the paper identifies nine cyber warfare research challenges and reviews current research in each. Finally, we make recommendations for how future initiatives in the field might best advance the subject.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128257453","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677645
M. Shahiri, Mahdi Eskandari
The two-latent variable stochastic block model is a new graph synthetic model making a connection between the conventional stochastic block model and real-world networks. In this model, each node contains two latent variables such that at least one of these two latent variables is unknown. Still, this model lonely is not able to model a real-world network. Side information is another component that sometimes exists beside a real-world network. In this paper, we will investigate the asymptotic behavior of the two-latent variable stochastic block model in the presence of side information. Two different types of side information are considered in this paper: noisy labels and partially revealed labels side information. For each case, the necessary and sufficient conditions for the exact recovery of the desired latent variable are obtained via semidefinite programming optimization. It is shown that these conditions are tight and create a phase transition for the exact recovery.
{"title":"Exact Recovery of Two-Latent Variable Stochastic Block Model with Side Information","authors":"M. Shahiri, Mahdi Eskandari","doi":"10.1109/ICCITM53167.2021.9677645","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677645","url":null,"abstract":"The two-latent variable stochastic block model is a new graph synthetic model making a connection between the conventional stochastic block model and real-world networks. In this model, each node contains two latent variables such that at least one of these two latent variables is unknown. Still, this model lonely is not able to model a real-world network. Side information is another component that sometimes exists beside a real-world network. In this paper, we will investigate the asymptotic behavior of the two-latent variable stochastic block model in the presence of side information. Two different types of side information are considered in this paper: noisy labels and partially revealed labels side information. For each case, the necessary and sufficient conditions for the exact recovery of the desired latent variable are obtained via semidefinite programming optimization. It is shown that these conditions are tight and create a phase transition for the exact recovery.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130967578","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677860
Muataz Abd Al-Mohsen, A. S. Abbas
The significance of the study lies in the crowdsourcing tool that supports software engineering tasks externally by different, unidentified groups of people who send ideas and opinions over the Internet. Software engineering Crowdsourcing global online work scheduling software engineering tasks such as requirements extraction, requirements analysis, design, testing, and coding is the basic principle or idea of requirements engineering. The impact of software engineering crowdsourcing has increased in recent years due to the clear and visible impact that has touched and worked on multiple aspects of software engineering. In this study, a search was conducted to obtain crowdsourcing opinions about one of the important and commonly used Iraqi sites from different groups, ages, and specialties, in which about (151) people participated to express their opinion by answering (9) questions with the word yes or no, because the questions are of an answering style Easy, simple and fast, for the purpose of extracting the required and useful information for engineering requirements, which serves as the basis for project planning. These methods are used in the thesis concept for data mining using classification techniques to discover unknown categories of data. This includes decision trees, Logistic Regression, random forests Classifier, and k-nearest neighbor algorithm, with an evaluation of each method showing the best result using classification techniques that were the best result using the 98% decision trees and random forests Classifier technique while is more than adequate. Work on the same data set.
{"title":"Use Crowdsourcing in Software Engineering for The Development of The Website","authors":"Muataz Abd Al-Mohsen, A. S. Abbas","doi":"10.1109/ICCITM53167.2021.9677860","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677860","url":null,"abstract":"The significance of the study lies in the crowdsourcing tool that supports software engineering tasks externally by different, unidentified groups of people who send ideas and opinions over the Internet. Software engineering Crowdsourcing global online work scheduling software engineering tasks such as requirements extraction, requirements analysis, design, testing, and coding is the basic principle or idea of requirements engineering. The impact of software engineering crowdsourcing has increased in recent years due to the clear and visible impact that has touched and worked on multiple aspects of software engineering. In this study, a search was conducted to obtain crowdsourcing opinions about one of the important and commonly used Iraqi sites from different groups, ages, and specialties, in which about (151) people participated to express their opinion by answering (9) questions with the word yes or no, because the questions are of an answering style Easy, simple and fast, for the purpose of extracting the required and useful information for engineering requirements, which serves as the basis for project planning. These methods are used in the thesis concept for data mining using classification techniques to discover unknown categories of data. This includes decision trees, Logistic Regression, random forests Classifier, and k-nearest neighbor algorithm, with an evaluation of each method showing the best result using classification techniques that were the best result using the 98% decision trees and random forests Classifier technique while is more than adequate. Work on the same data set.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123032881","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}
Pub Date : 2021-08-25DOI: 10.1109/ICCITM53167.2021.9677704
Rawaa K. Hamza, K. Rijab, Mohammed A. Hussien
The Electrocardiogram (ECG) data has been used to diagnose and analyze heart issues. For that The ECG data compression is one of the most important studies in biomedical engineering. The ECG signal compression benefits storage data, data transmission rate decrease, and communication bandwidth reduction. The proposed work deal with the ECG signal compression method of ECG signals using Discrete Wavelet Transform (DWT). The DWT compressed the signal energy in a smaller change in data and has perfect localization assets in frequency & time. The DWT threshold has been selected to perform for the DWT coefficients depending on the signal's Energy Packing Efficiency (EPE). The Huffman encoder has been used to encoding the selected DWT coefficient. The results of the proposed method show better performance with higher compression ratios and good quality reconstructed signals. For Example the Compression ratio (CR) =16.33, 10.57,and 7.75 with percent root mean square difference (PRD)=1.5%, 1.3%, and 1.02% for using different DWT(Harr transform, Bior1.1, and Db2), respectively.
{"title":"The ECG data Compression by Discrete Wavelet Transform and Huffman Encoding","authors":"Rawaa K. Hamza, K. Rijab, Mohammed A. Hussien","doi":"10.1109/ICCITM53167.2021.9677704","DOIUrl":"https://doi.org/10.1109/ICCITM53167.2021.9677704","url":null,"abstract":"The Electrocardiogram (ECG) data has been used to diagnose and analyze heart issues. For that The ECG data compression is one of the most important studies in biomedical engineering. The ECG signal compression benefits storage data, data transmission rate decrease, and communication bandwidth reduction. The proposed work deal with the ECG signal compression method of ECG signals using Discrete Wavelet Transform (DWT). The DWT compressed the signal energy in a smaller change in data and has perfect localization assets in frequency & time. The DWT threshold has been selected to perform for the DWT coefficients depending on the signal's Energy Packing Efficiency (EPE). The Huffman encoder has been used to encoding the selected DWT coefficient. The results of the proposed method show better performance with higher compression ratios and good quality reconstructed signals. For Example the Compression ratio (CR) =16.33, 10.57,and 7.75 with percent root mean square difference (PRD)=1.5%, 1.3%, and 1.02% for using different DWT(Harr transform, Bior1.1, and Db2), respectively.","PeriodicalId":406104,"journal":{"name":"2021 7th International Conference on Contemporary Information Technology and Mathematics (ICCITM)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125596982","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}
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