2022 International Conference on Engineering & MIS (ICEMIS)最新文献_第5页

Blood Cells Classification Using Deep Learning Technique 使用深度学习技术的血细胞分类

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914281

Ismail M. I. Alkafrawi, Zaroug A. Dakhell

{"title":"Blood Cells Classification Using Deep Learning Technique","authors":"Ismail M. I. Alkafrawi, Zaroug A. Dakhell","doi":"10.1109/ICEMIS56295.2022.9914281","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914281","url":null,"abstract":"There are three major types of blood cells, red blood cells (erythrocytes), white blood cells (leukocytes), and platelets (thrombocytes). Together, these three kinds of blood cells add up to a total of 45% of the blood tissue by volume, with the remaining 55% of the volume composed of plasma, the liquid component of blood. These three types play an important role in the human body by increasing immunity by fighting against infectious diseases. The classification and count of blood cells play an important role in the detection of a disease in an individual. It can also assist with the identification of diseases like infections, anemia, leukemia, cancer, etc. This classification will assist the hematologist to distinguish between the types of white blood cells, red blood cells, and platelets present in the human body and find the root cause of diseases. Currently, there is a large amount of research going on in this field. Considering a huge potential in the significance of the classification of different blood cells, a deep learning technique called Convolution Neural Networks will be used which can classify the images of human blood cells into their subtypes namely Neutrophils, Eosinophils, Basophils, Lymphocytes, Monocytes, Immature Granulocytes (Promyelocytes, Myelocytes, and Metamyelocytes), Red blood cells or Erythroblasts and Platelets or Thrombocytes. In this paper, the discussion have been done on a dataset that was acquired in the Core Laboratory at the Hospital Clinic of Barcelona using Convolution Neural Networks.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"13 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":"129629560","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

Utilizing Ear Biometrics for Individual Identifications Using HOG and LBP 利用耳部生物识别技术进行HOG和LBP的个体识别

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914344

Bothaina F. Gargoum, A. Lawgali, Abdalla Mohamed A. E.

引用次数: 1

Evaluating the Relationship of Information Systems to Crisis Management in Libyan Higher Education Institutions 评估利比亚高等教育机构中信息系统与危机管理的关系

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914186

Ahmed M. Amhimmid, Wisam H. Benamer, Abdelsalam M. Maatuk, S. Benamer, Salam F. Elharish, Nadera Elwarfali

{"title":"Evaluating the Relationship of Information Systems to Crisis Management in Libyan Higher Education Institutions","authors":"Ahmed M. Amhimmid, Wisam H. Benamer, Abdelsalam M. Maatuk, S. Benamer, Salam F. Elharish, Nadera Elwarfali","doi":"10.1109/ICEMIS56295.2022.9914186","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914186","url":null,"abstract":"Crisis management is witnessing rapid changes due to advances in information technology, and the development of information systems in various fields, especially in the field of higher education during the spread of the Corona pandemic, has led to the need to study the relationship between information systems and crisis management. This study aims to identify the degree of relationship between the application of the six procedures and controls for information systems and the five stages of crisis management from the point of view of workers in the information and documentation centers at the University of Benghazi, University of Tripoli and the Libyan International Medical University, Libya. The descriptive-analytical method was applied to this study in addition to analyzing the results using a statistical application called the Statistical Package for Social Sciences (SPSS), which was used to calculate the frequencies for each procedure and create tables and charts. To analyze the data, we used Mean and Standard deviations, standard error, Cronbach’s alpha coefficient, and Pearson’s correlation coefficient as a statistical relationship. The study determined whether or not there is a correlation between the independent variables, i.e., the six procedures and controls on the information systems scale (data, physical requirements, software requirements, networks and communications, data and information security, human resources) and the dependent variable, i.e., the five stages on the crisis management scale (the stage of discovery of warning signals, the stage of Preparedness and prevention, damage containment stage, activity recovery stage, learning stage).","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"10 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":"114730850","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

Predicting Stroke Disease Based on Recurrent Neural Network and Optimization techniques 基于递归神经网络和优化技术的脑卒中疾病预测

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914334

Hager Saleh, A. M. Hussien, M. Hassan, Abdelmgeid A. Ali

引用次数: 0

Modeling of Verb Phrases of the Kazakh Language 哈萨克语动词短语的建模

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914015

Gaziza Yelibayeva, B. Razakhova, B. Yergesh, A. Sharipbay, G. Bekmanova, A. Mukanova

引用次数: 0

Breast Cancer Image Classification Using Deep Convolutional Neural Networks 基于深度卷积神经网络的乳腺癌图像分类

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914251

Zahrah Jadah, Aisha Alfitouri, H. Chantar, Mabroukah Amarif, Ahmed Abu Aeshah

{"title":"Breast Cancer Image Classification Using Deep Convolutional Neural Networks","authors":"Zahrah Jadah, Aisha Alfitouri, H. Chantar, Mabroukah Amarif, Ahmed Abu Aeshah","doi":"10.1109/ICEMIS56295.2022.9914251","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914251","url":null,"abstract":"In recent years, convolutional neural network algorithms have made remarkable progress in the classification of medical images such as the classification of breast cancer tumors. Models of deep convolutional neural networks have obtained a higher accuracy rate in medical image recognition. The fine-tuning of images data and parameters are the main task of adapting a pre-trained convolution model in order to improve the classification accuracy. This paper aims to present a model for the use of deep neural networks, specifically convolutional neural network model AlexNet, for breast cancer classification. The model will be used to diagnose breast cancer using histopathological BreakHis images data set. Modifications of parameters and data are applied to increase the model ability for recognizing and classifying the input image and determine whether the image belongs to a benign or malignant tumor. It has been noticed that the training frequency and balanced training data greatly improve classification rate accuracy up to 96%. Our mission is that to achieve a higher accuracy rate than the obtained if repeated improvement of fine-tuning parameters and weights are adopted according to more accurate techniques.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"2011 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":"127374394","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

Influence of Feature Selection Methods on Breast Cancer Early Prediction Phase using Classification and Regression Tree 基于分类回归树的特征选择方法对乳腺癌早期预测阶段的影响

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914078

Asma Agaal, Mansour Essgaer

{"title":"Influence of Feature Selection Methods on Breast Cancer Early Prediction Phase using Classification and Regression Tree","authors":"Asma Agaal, Mansour Essgaer","doi":"10.1109/ICEMIS56295.2022.9914078","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914078","url":null,"abstract":"In recent years, healthcare data has been growing exponentially. The major challenge is to predict and analyze all this data effectively. Feature selection is a solution in which a subset of informative features is selected from a high-dimensional dataset. Feature selection helps to increase accuracy and remove irrelevant features. In the medical domain, selecting important features for healthcare is essential as it directly affects human health. Several filters, wrapper, and embedded feature selection techniques will be examined in this study including generic univariate selects, select percentile, select k best, Pearson correlation coefficient, mutual information, relief-f, recursive feature elimination, recursive feature elimination with cross-validation, sequential forward selection, sequential backward selection, and select-from-model. The aim is to make the healthcare predictions model named classification and regression tree more accurate by employing feature selection methods, to accurately detect breast cancer in its early stages, where the data is collected from Sebha oncology center in the south of Libya. The performance of the classification and regression tree was seen to be noticeably enhanced when eliminated irrelevant features. Later, our model outperforms other classification methods, namely: logistic regression, naive Bayes, and K-nearest neighbors, by using the optimal subset of features identified by recursive feature elimination.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"7 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":"132641857","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

A Bird’s Eye View on Aspect Oriented Requirements Engineering 面向方面需求工程的鸟瞰图

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914074

Sohil F. Alshareef, Abdelsalam M. Maatuk, T. Abdelaziz, Shadi A. Aljawarneh

{"title":"A Bird’s Eye View on Aspect Oriented Requirements Engineering","authors":"Sohil F. Alshareef, Abdelsalam M. Maatuk, T. Abdelaziz, Shadi A. Aljawarneh","doi":"10.1109/ICEMIS56295.2022.9914074","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914074","url":null,"abstract":"Aspect-oriented software development builds on the concept of separation of concerns. It is concerned with addressing and handling the scattering and tangling issues related to the object-oriented paradigm. The traditional requirements engineering approach cannot address crosscutting concerns properly, which results in the occurrence of the tyranny of the dominant decomposition. Aspect-oriented requirements engineering (AORE) supports identifying and handling crosscutting concerns at the early stages of software development. The approaches and techniques of AORE are an extension of the traditional requirements engineering approaches like viewpoints, use cases, and goal-oriented, while some approaches are purely designed with aspect orientation in mind. This paper surveys the most relevant and popular AORE approaches. Most of the approaches support analysis and design. The focus is on the approaches in the requirements analysis phase. A critical evaluation is set to compare each proposal against the defined activity in requirements analysis. The evaluation of the approaches through the defined criteria showed that the validation and verification of AORE artifacts are not given much attention and focus compared to the identification and treatment of concerns and aspects. The key elements of validation and verification supported by AORE approaches are outlined and discussed.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"56 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":"115600460","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

Practical Design of an Upper Prosthetic Limb Using Three Dimensional Printer with an Artificial Intelligence Based Controller 基于人工智能控制器的三维打印机上肢假肢的实用设计

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914291

A. Elbreki, Safa Ramdan, Faisal Mohamed, Khadija Alshari, Zakariya Rajab, B. Elhub

{"title":"Practical Design of an Upper Prosthetic Limb Using Three Dimensional Printer with an Artificial Intelligence Based Controller","authors":"A. Elbreki, Safa Ramdan, Faisal Mohamed, Khadija Alshari, Zakariya Rajab, B. Elhub","doi":"10.1109/ICEMIS56295.2022.9914291","DOIUrl":"https://doi.org/10.1109/ICEMIS56295.2022.9914291","url":null,"abstract":"A noticeable rate of people suffer from a disability due to war and other reasons. One group of disabled people is those who have lost their arms, which makes it challenging to perform basic tasks. This paper proposes a solution that will make life easier for amputees. The study is based on the EMG (Electromyography) signal acquired from muscles and the movement detected using HMI (Human Machine Interfacing). The practical arm is designed with a computer-aided design using SolidWorks software. A 3D printer FDM (Fused Deposition Modeling) with Polylactic Acid “PLA” was used to fabricate the Prosthetic Limb using an open-source prototype named Hackberry hand from Exiii Company. An actual circuit design is arranged using simple tools that cost more minor and consists of simple sensors, motors, and Arduino Nano. The findings show that the database extracted 416$times$ 4 is presproced classified and tested using KNN (K nearest neighbor) with 94% rate, and obtained 95% with SVM method to recognize four different motions raising the index finger, holding a card with the thumb and forefinger, fist and spread.","PeriodicalId":191284,"journal":{"name":"2022 International Conference on Engineering & MIS (ICEMIS)","volume":"27 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":"125110003","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

Grey Wolf Optimization-Based Improved Closed-Loop Speed Control for a 3-phase IM Motor Drive with SVPWM Switching and V/f Control 基于灰狼优化的SVPWM开关和V/f控制三相IM电机的改进闭环速度控制

2022 International Conference on Engineering & MIS (ICEMIS) Pub Date : 2022-07-04 DOI: 10.1109/ICEMIS56295.2022.9914130

Qusay Hussein Mirdas, N. Yasin, N. Alshamaa

引用次数: 1