4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022)最新文献

Backend as a Service Cloud Computing Integrated with Cross-platform Mobile Development Framework to Create an E-learning application that works in Mobile and Web with a single codebase 后端即服务云计算与跨平台移动开发框架集成，以创建一个使用单个代码库在移动和Web上工作的电子学习应用程序

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.511

Osama mohammed ahmed

{"title":"Backend as a Service Cloud Computing Integrated with Cross-platform Mobile Development Framework to Create an E-learning application that works in Mobile and Web with a single codebase","authors":"Osama mohammed ahmed","doi":"10.24086/cocos2022/paper.511","DOIUrl":"https://doi.org/10.24086/cocos2022/paper.511","url":null,"abstract":"Many platforms are emerging recently and businesses need to work with all of them, therefore, creating applications that work on multiplatform like Android, IOS, Windows …etc. is necessary these days.Building a separate native application for each platform as well as working separately with both Frontend and Backend is costly in several respects, including time, effort and cost.using Cross-platform tools and frameworks is the best solution to the problem of multiple platforms and the need to deal with all of them. This paper discusses the most famous, modern, and widely used Cross-platform tools to introduce the best way to build an E-learning application that works natively in multiplatform using only one programming language, and even it doesn’t require work with the Backend side. Finally, we have created a sample E-learning application using Flutter with Firebase as a Backend. Due to the Corona pandemic, e-learning has become a mandatory requirement as a primary or secondary method of education, this application work on all platforms (Mobile and Desktop), and we tested it on Android and Web Browsers.","PeriodicalId":137930,"journal":{"name":"4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125183077","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

Diagnosis of Parkinson's disease through EEG signals based on artificial neural network and cuckoo search algorithm 基于人工神经网络和布谷鸟搜索算法的脑电信号诊断帕金森病

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.698

Rzgar Sirwan Raza, Adil Hussein Mohammed

{"title":"Diagnosis of Parkinson's disease through EEG signals based on artificial neural network and cuckoo search algorithm","authors":"Rzgar Sirwan Raza, Adil Hussein Mohammed","doi":"10.24086/cocos2022/paper.698","DOIUrl":"https://doi.org/10.24086/cocos2022/paper.698","url":null,"abstract":"Parkinson's disease is a degenerative nervous system condition that impairs mobility. If the condition is not detected early enough, it might have permanent effects for the sufferer. A novel approach for identifying Parkinson's disease is provided in this research, which employs machine optimization and learning techniques. The suggested method's diagnosis procedure may be broken down into three primary steps: \"preprocessing,\" \"feature extraction,\" and \"classification.\" Preprocessing the EEG data is the initial stage in the suggested technique. Database samples are treated using discrete wavelet analysis to remove the destructive influence of noise on the input signals using signal analysis for this aim. The suggested method's second phase will employ principal component analysis to remove duplicate features and minimize data dimensionality. The artificial neural network model is trained and the classification model is built using the retrieved features. The effectiveness of the suggested technique is examined in terms of criteria such as accuracy, sensitivity, and specificity during the experimentation phase, and the results are compared to existing learning models. The findings revealed that the suggested technique enhances illness diagnostic accuracy by at least 8.25% and may be utilized as a useful tool in disease diagnosis.","PeriodicalId":137930,"journal":{"name":"4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129485556","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

Seismic low-frequency shadow detection based on the Levenberg-Marquardt reassignment operators using S-transforms 基于s变换Levenberg-Marquardt重分配算子的低频地震阴影检测

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.632

R. Anvari, Adil Hussein Mohammed, S. Rashidi

引用次数: 1

Machine Learning Approaches to Enable Resource Forecasting Process of Road Tunnels Construction 公路隧道建设资源预测的机器学习方法

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.718

A. Mahmoodzadeh, S. Rashidi, Adil Hussein Mohammed, Hunar Farid Hama, ,. H. Hashim Ibrahim

{"title":"Machine Learning Approaches to Enable Resource Forecasting Process of Road Tunnels Construction","authors":"A. Mahmoodzadeh, S. Rashidi, Adil Hussein Mohammed, Hunar Farid Hama, ,. H. Hashim Ibrahim","doi":"10.24086/cocos2022/paper.718","DOIUrl":"https://doi.org/10.24086/cocos2022/paper.718","url":null,"abstract":"Increasing demand for tunneling projects, increases attention to time and cost required for their construction. Most of parameters which are affecting on the time and cost of tunnel construction are unknown. The purpose of this paper is to provide a method to predict the construction time and cost of a road tunnelusing linear regression (LR) method. In order to train the LR method, some datasets are obtained from the historical road tunnels. To verify the feasibility of the proposed method, it has been applied to a road tunnel. All of the forecasted results have been compared with the actual results obtained during the tunnel construction and the accuracy of the predictions has been investigated. According to three statistical evaluation criteria of root mean square error (RMSE), mean absolute percentage error (MAPE) and determination of the coefﬁcient (R2), a very high accuracy has been obtained in the prediction results. The RMSE, MAPE and R2 indices have been calculated as 0.0005 days, 0.9380637% and 0.9874 for the construction time, respectively; and 7.1194 US$,0.78891593% and 0.9873 for the construction cost, respectively.","PeriodicalId":137930,"journal":{"name":"4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131406735","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

Review of IoT and Robotics application (Special case Study in Iraq and Kurdistan Region) 物联网与机器人应用综述(以伊拉克和库尔德斯坦地区为例)

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.510

Abdullah A. Nahi, Laith R. Flaih, K. Jasim, Rajan Hossian

引用次数: 0

Unsupervised Feature Selection Method based on Structural Particularity of Minimum Spanning Tree 基于最小生成树结构特殊性的无监督特征选择方法

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.828

Rojiar Pir Mohammadiani, Maryam Mozaffari, Soma Solaiman Zadeh

引用次数: 0

The relationships for some topological structures via fuzzy, soft ,and fuzzy soft sets 通过模糊集、软集和模糊软集确定某些拓扑结构的关系

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.713

S. Saleh, Mohammed Hussein Shukur, A. Al-Salemi

引用次数: 1

Performance Evaluation of Source Code Plagiarism Detection System 源代码抄袭检测系统的性能评价

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.732

引用次数: 0

YOLO-V3 Based Real-time Drone Detection Algorithm 基于YOLO-V3的无人机实时检测算法

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.502

Hamid R. Alsanad, Amin Z sadik

引用次数: 4

Face spoofing detection and Authentication Using Linear Binary Patterns, Gabor Features and Support Vector Machine 基于线性二值模式、Gabor特征和支持向量机的人脸欺骗检测与认证

4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022) Pub Date : 1900-01-01 DOI: 10.24086/cocos2022/paper.819

Ahmed Mamoon Alkababji, Mustafa Haitham Alhabib, Mustafa Zuhaer Al-Dabagh

{"title":"Face spoofing detection and Authentication Using Linear Binary Patterns, Gabor Features and Support Vector Machine","authors":"Ahmed Mamoon Alkababji, Mustafa Haitham Alhabib, Mustafa Zuhaer Al-Dabagh","doi":"10.24086/cocos2022/paper.819","DOIUrl":"https://doi.org/10.24086/cocos2022/paper.819","url":null,"abstract":"Face detection and authentication have become an active field of research material in recent years duo to the increased use of face dependent access control systems, which can be considered as a good alternative to other biometric features such as fingerprint duo to its easily accessible, non- intrusive nature that makes it very important during the ongoing pandemic years. However, this method doesn’t come without security risks related to adversaries seeking to gain unauthorized access to the system. Face spoofing is a security breach attempt occurs when the attacker tries to deceive the face-enabled access control system by displaying a photo, video or wearing a mask of an authorized person to gain access. The paper in hand suggests a method for face anti-spoofing by utilizing some of the well-known feature extraction techniques usually associated with face detection and recognition, namely the LBP and Gabor features, in addition to the commonly used SVM classifier for identifying real and spoofed feces. The algorithm is implemented successfully on multiple individuals, achieving performance levels comparable to other accredited methods in terms of FAR, FRR and HTER verification criteria, aspiring for more advancedand effective methods.","PeriodicalId":137930,"journal":{"name":"4th International Conference on Communication Engineering and Computer Science (CIC-COCOS’2022)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132354233","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