2022 International Conference on Engineering & MIS (ICEMIS)最新文献_第7页

Estimating the severity of knee osteoarthritis using Deep Convolutional Neural Network based on Contrast Limited Adaptive Histogram Equalization technique 基于对比度有限自适应直方图均衡化技术的深度卷积神经网络估计膝关节骨性关节炎的严重程度

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914285

Amina A. Abdo, Wafa El-Tarhouni, Asma Fathi Abdulsalam, Abdelgader Bubaker Altajori

{"title":"Estimating the severity of knee osteoarthritis using Deep Convolutional Neural Network based on Contrast Limited Adaptive Histogram Equalization technique","authors":"Amina A. Abdo, Wafa El-Tarhouni, Asma Fathi Abdulsalam, Abdelgader Bubaker Altajori","doi":"10.1109/ICEMIS56295.2022.9914285","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914285","url":null,"abstract":"Osteoarthritis is a degenerative joint disease that affects larger joints, including the knee, foot, hip, and spine by infecting the cartilage, which causes bones to rub against each other in extreme pain. Knee osteoarthritis (KOA) manual inspections demand a skilled physician to examine the x-ray image. In this paper, a method for detecting the severity of knee osteoarthritis using a Deep Convolutional Neural Network (3D CNN) is proposed in order to benefit physicians by examining the X-ray images. Here, the Contrast Limited Adaptive Histogram Equalization (CLAHE) technique is used to enhance contrast in images, and this strengthens the current approach. This study presents two models: one for identifying and categorizing normal (KL 0,1) and osteoarthritic results (KL 2, 3, 4). The second model is to assist in distinguishing between severe grades (KL 3, 4) and non-severe grades (KL 2) or normal findings (KL 0,1). For examination, X-ray images from the Knee Osteoarthritis severity grading dataset and the Osteoarthritis Initiative (OAI) dataset are used. Experimental results have demonstrated that the proposed technique achieves accuracy rate of 85.50%, outperforming a number of existing approaches.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114949029","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: 1

Examinations Timetabling System Based on A Genetic Algorithm 基于遗传算法的考试时间安排系统

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914188

Mousay Mohammed, Rema A. Abobaker, Asma M. Aljalil, Abdelsalam M. Maatuk

引用次数: 0

An Empirical study and assessment of minority oversampling with Dynamic Ensemble Selection on COVID-19 utilizing Blood Sample 基于动态集合选择的血液样本COVID-19少数过采样实证研究与评价

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914231

P. Srikanth, C. Behera

{"title":"An Empirical study and assessment of minority oversampling with Dynamic Ensemble Selection on COVID-19 utilizing Blood Sample","authors":"P. Srikanth, C. Behera","doi":"10.1109/ICEMIS56295.2022.9914231","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914231","url":null,"abstract":"The COVID-19 virus disease outbreak that erupted in China at the end of 2019 has had a tremendous and disastrous impact on the rest of the world. It has struck the globe to its core, and the destruction has substantially increased the diagnostic burden. In the pandemic zone, clinicians will be able to cut down on their workload and get the right diagnosis of the new disease great to the use of machine learning. A blood test has emerged as a critical tool for identifying false-positive or false-negative real-time rRT-PCR diagnostics. Notably, this is mostly because it is such a cost-effective and convenient method of detecting probable COVID-19 patients. Among the numerous hard consequences associated with COVID-19 illness has been established as one of the most prevalent among COVID-19 patients. The impetus for this research is the scarcity of post-COVID-19 dataset. Following pre-processing to manage address missing values, oversampling with SMOTE ENN is used to generate several instances and model training is carried out on these data sets. However, it has been demonstrated that normatively dynamic ensemble selection outperforms static selection and dynamic selection. The DI+SMOTEENN+DESKNU exceed existing benchmark Classification algorithms and obtain the best accuracy of 99.6%, according the results.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128847512","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: 1

New Block Cipher Encryption Based On OTP Algorithm 基于OTP算法的新型分组密码加密

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914376

Joy Huda Al-Nemri, Mu'awya Naser

引用次数: 0

E-Learning, Challenges and Opportunities of Instructors in Libyan Higher Institutes 电子学习:利比亚高等院校教师的挑战与机遇

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914178

Alhadi A. Klaib, Mohamed Ahmed M. Talooh, Abdelrahman Arbi

引用次数: 0

Vehicle to Infrastructure in a Semi Dynamic Environment Based on A Novell IoT 7th Layers Framework 基于Novell物联网第7层框架的半动态环境中的车辆到基础设施

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914013

Saleh Hussein Al-awami, Mousa Faraj Al-Najar

{"title":"Vehicle to Infrastructure in a Semi Dynamic Environment Based on A Novell IoT 7th Layers Framework","authors":"Saleh Hussein Al-awami, Mousa Faraj Al-Najar","doi":"10.1109/ICEMIS56295.2022.9914013","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914013","url":null,"abstract":"A large number of accidents and the resulting injuries are a common problem all over the world, especially in populated cities, and one of the main causes of deaths is the inability of the police and hospital to know the exact location of the accident. The system aims to reduce death rates from accidents and improve the speed of response in police stations and hospitals to provide the necessary assistance. A survey of relevant works in this paper has been studied and their work is explained. Accordingly, we proposed a framework consisting of multi-layers which is the measurement that all platforms will use. It uses Global System of Mobile (GSM) media access to collect specific information about a car accident on the road, it is used to send a message from the location to the server and then to the police and hospital, based on the Internet of Things (IoT) and uses The Global Positioning System (GPS) to locate the accident. The proposed model is implemented by simulating real situations and different scenarios using the CupCarbon simulator to illustrate the working of the system that simulates and deals with the police and ambulance response to the accident scene. the proposed IoT framework architecture contains of 7th layers that shall be used by developers to implement IoT based applications. This proposed IoT architecture has shown the well interoperability between its different layers, easily to follow up, easily to integrated with intelligent systems and machine learning, and easily to scale into other IoT platforms.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116996021","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: 1

Double Compression Efficiency for Image Data Hiding using Integer Wavelet Transform 利用整数小波变换实现图像数据隐藏的双重压缩效率

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914045

A. Ukasha

引用次数: 0

Comparison of Some Machine Learning Algorithms for Predicting Heart Failure 预测心力衰竭的几种机器学习算法的比较

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914325

Ramadan A. M. Elghalid, Ahmed Alwirshiffani, A. Mohamed, Fatimah Husayn Amir Aldeeb, Aisha Andiasha

{"title":"Comparison of Some Machine Learning Algorithms for Predicting Heart Failure","authors":"Ramadan A. M. Elghalid, Ahmed Alwirshiffani, A. Mohamed, Fatimah Husayn Amir Aldeeb, Aisha Andiasha","doi":"10.1109/ICEMIS56295.2022.9914325","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914325","url":null,"abstract":"In this modern era, people are working hard to meet their physical needs and non-effective their ability to spend time for themselves which leads to physical stress and mental disorder. Many reports state that heart failure is caused by many diseases that we ignore and chronic diseases as well as the global epidemic of the Coronavirus. Heart failure does not mean that it will stop at any moment but rather that the heart is not working as it should. Heart failure, also known as congestive heart failure, is a condition that develops when your heart does not pump enough blood for your body’s needs. This paper aims to predict if someone is at high risk of being diagnosed as a heart patient using different machine learning methods. We have collected datasets to analyze data and mining using 7 algorithms of machine learning to predict whether the patient suffers from heart failure or not. This paper used a dataset retrieved from kaggle repository, which consists of 12 attributes (Features). This work is implemented using K-Nearest Neighbors (KNN), Naïve Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (TD) and Neural Network (NN) algorithms. Results showed that Logistic Regression, Support Vector Machine and Neural Network respectively gave the best result with an accuracy of up to 94.57%.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133107728","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

Service Quality in eLearning 在线学习中的服务质量

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914135

Loui Al-Jawarneh, T. Mohammed

引用次数: 2

Speech Recognition for Early Detecting Alzheimer’s Disease by Using Machine Learning Algorithms 基于机器学习算法的语音识别早期检测阿尔茨海默病

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914339

Hanein O. MohamedShreif, A. Lawgali

{"title":"Speech Recognition for Early Detecting Alzheimer’s Disease by Using Machine Learning Algorithms","authors":"Hanein O. MohamedShreif, A. Lawgali","doi":"10.1109/ICEMIS56295.2022.9914339","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914339","url":null,"abstract":"Alzheimer’s disease is a neuronal disease defined by the gradual onset of cognitive, emotional, and linguistic deficits. These assaults are severe enough to disrupt patients’ everyday social and professional lives. Nowadays, the use of speech recognition is appealing since it is non-invasive, inexpensive, and has contributed to improving accuracy. Also, it’s one of the major and innovative topics of investigation by researchers. Many other aspects may affect the accuracy of detecting Alzheimer’s including feature extraction, the number of attributes utilized for feature selection, and the classifiers used. In this paper we proposed model, which involves feature extraction and imperative attribute selection step, also classification using the machine learning algorithm support vector machine classifier. We added a new linguistic feature (silence rate) that would have the effect to increase the accuracy rate of our model. According to the current data, our proposed model can be strongly recommended for the early detection of Alzheimer’s patients from healthy people with 88% accuracy.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116086071","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: 1