2022 5th International Conference on Computing and Informatics (ICCI)最新文献_第5页

Comparative study of machine learning techniques based on TQWT for EMG signal classification 基于TQWT的肌电信号分类机器学习技术比较研究

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756080

Nahla F. Abdel-Maboud, S. Parusheva, Marco Alfonse, A. Salem

引用次数: 2

Camera-based Human Counting for COVID-19 Capacity Restriction 基于摄像机的COVID-19容量限制人工计数

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756073

Hazem Hossam, M. Ghantous, Mohammed Abdel-Megeed Salem

{"title":"Camera-based Human Counting for COVID-19 Capacity Restriction","authors":"Hazem Hossam, M. Ghantous, Mohammed Abdel-Megeed Salem","doi":"10.1109/icci54321.2022.9756073","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756073","url":null,"abstract":"In this paper, a Human Counting system is implemented for COVID-19 capacity restrictions. It was implemented using the deep learning model You Only Look Once version 3(YOLOv3) to detect and count the people in a room. The system also can monitor the social distancing between the people in the room while labeling each person as “safe” or “unsafe” depending on whether they respect the social distancing protocols that the World Health Organization recommended or not. To make the project user friendly, a Graphical User Interface (GUI) was implemented to allow the user to choose the source of their images that will be used as input to be processed by the system. An experiment was carried out to evaluate the performance of the system under different conditions and in different scenarios where the evaluation was done according to some metrics such as accuracy, precision and recall. The output results from this experiment were demonstrated in details and compared to a similar algorithm as both algorithms focused on people detection using images from an inclined camera. The results show an accuracy of 96% for detection and the number of people counted.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"330 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115969931","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

Deep learning techniques for the fully automated detection and segmentation of brain MRI 脑MRI全自动检测和分割的深度学习技术

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756119

A. Tamer, Ahmed Youssef, Mohammed Ibrahim, M. Aziz, Youssef Hesham, Zeyad Mohammed, M. M. Eissa, Soha Ahmed, Ghada Khoriba

{"title":"Deep learning techniques for the fully automated detection and segmentation of brain MRI","authors":"A. Tamer, Ahmed Youssef, Mohammed Ibrahim, M. Aziz, Youssef Hesham, Zeyad Mohammed, M. M. Eissa, Soha Ahmed, Ghada Khoriba","doi":"10.1109/icci54321.2022.9756119","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756119","url":null,"abstract":"Over the past decade, auto-segmentation for tumors has drawn a lot of attention due to its significant impact on cancer treatment. Auto-segmentation architectures have a significant role in alleviating the enormous workload on the medical staff. This has motivated us to explore the latest solutions in auto-segmentation to use it in auto-segmentation. It works on automatically contouring tumors to make radiology treatment more attainable since manual contouring is repetitive and subjective to human error. Auto-segmentation usually strives to achieve high accuracy to reduce the time the radiologists take to contour the tumor. Saving time is critical as instead of contouring all the tumors, the radiologist can spend the time editing on the segmented tumor thus more patients can be diagnosed in less amount of time. There have been a lot of auto-segmentation architectures created for general purposes like the Segnet which is sometimes used in medical segmentation, but such architectures fail to achieve high accuracy especially in the details of the tumor. The U-Net is an auto-segmentation architecture specifically created for auto-segmentation on medical images like MRI and CT. The U-Net architecture can achieve high accuracy of segmentation with fewer amounts of data. We improved U-Net performance by using residual blocks on each layer of the architecture itself usually referred to as Res-U-Net. Our final proposed fine-tuned Res-U-Net model has achieved 97.10% on the used data which was the best of our 3 proposed fine-tuned models. The used data was Low-grade gliomas (LGGS) brain tumor dataset.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128151733","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

Multi-criteria selection of industrial robots: modelling users' preferences in combined AHP-Entropy-TOPSIS 工业机器人的多准则选择:用ahp -熵- topsis联合建模用户偏好

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756084

I. Petrov

引用次数: 1

NEKO: Proposal of the first super-agile methodology to improve work efficiency NEKO:提出了第一个提高工作效率的超敏捷方法

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756085

Juan Patricio Marroquin Gavelan, Perla Patricia Peralta Mezones, Ciro A. Rodríguez

{"title":"NEKO: Proposal of the first super-agile methodology to improve work efficiency","authors":"Juan Patricio Marroquin Gavelan, Perla Patricia Peralta Mezones, Ciro A. Rodríguez","doi":"10.1109/icci54321.2022.9756085","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756085","url":null,"abstract":"Agile methodologies are the preferred strategy for work teams around the world thanks to their rapid response to changes and adaptability. However, this prioritization of efficiency and speed has neglected the well-being of the most important element of any project: the teams. This article presents NEKO as a super-agile methodology focused on people and that aims to prioritize the mental health of workers without neglecting effectiveness, relying on new technologies such as Artificial Intelligence to enhance its processes. During the research stage, using the methodology proposed by Kitchenham, fifteen articles were analyzed and allowed us to rescue the strengths and identify the problems presented by the agile methodologies most used today. Then, the proposal was developed dividing it into three phases; each including events, artifacts, and tools to achieve your goal. Later, during the discussion, the proposal was contrasted with the methodologies initially analyzed and it was concluded that taking the points in favor of these and adding state-of-the-art technology focused on the well-being of the teams is synonymous with efficiency, meaning a possible change in the paradigm of the current world of work.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131812196","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: 6

Satellite Orbit Prediction Based on Recurrent Neural Network using Two Line Elements 基于两线元递归神经网络的卫星轨道预测

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756063

Alaa Osama, Mourad Raafat, A. Darwish, Sara Abdelghafar, A. Hassanien

引用次数: 3

Dependable CNC Controller using Raspberry pi and Cloud Computing 可靠的数控控制器使用树莓派和云计算

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756095

Nashwa Mosaad Osman, K. Elshafey, Ahmed N. El-Mahdy

{"title":"Dependable CNC Controller using Raspberry pi and Cloud Computing","authors":"Nashwa Mosaad Osman, K. Elshafey, Ahmed N. El-Mahdy","doi":"10.1109/icci54321.2022.9756095","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756095","url":null,"abstract":"Numerically Controlled machines are widely used in many industrial applications. A CNC machine's essential element is the controller, and it is responsible for controlling and navigating the machine tools as well as implementing industrial processes. Despite the fact that numerous controllers have been invented and utilized in CNC applications in recent years, the vast majority of them have certain restrictions and drawbacks as a result of design methodologies. The goal of this article is to design and build a Fault detector and Diagnostic Automatic Controller (FDAC) to be used in CNC machines and is considerably improve the CNC machines performance. FDAC has a closed-loop control system that can automatically control and drive servo motors. FDAC will prevent losses of work pieces and damage of machine parts. FDAC could improve accuracy and reliability while enabling the rapid maintenance of industrial processes in a variety of CNC applications. FDAC records the alarm codes in real time on the cloud as well as their diagnostic history in order to build an accurate knowledge and reliability base system that does not depend on randomness or predictions. It also can be applied to traditional machines and is not expensive at all.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133664905","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 Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework 用于关系数据库到资源描述框架映射的新型图形终极处理器

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756069

A. Daoud, Khalid M. Hosny, Ehab Mohamed

{"title":"New Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework","authors":"A. Daoud, Khalid M. Hosny, Ehab Mohamed","doi":"10.1109/icci54321.2022.9756069","DOIUrl":"https://doi.org/10.1109/icci54321.2022.9756069","url":null,"abstract":"The World Wide Web Consortium (W3C) RDB2RDF Work Group (RDB2RDF-WG) recommended two mapping languages, Direct Mapping (DM) and Relational Database to RDF Mapping Language (R2RML) for Mapping Relational Databases (RDBs) to Resource Description Framework (RDF). Direct Mapping directly maps the RDB schema to RDF using a collection of simple transformations, whereas R2RML is a language for manually created mappings from RDB tables to RDF output. The manual creation of mapping is complex, error-prone, and time-consuming, where any single mistake could produce an invalid output document. In this paper, a new Graphical Ultimate Processor (GUP) is proposed for mapping from RDBs to RDF. The proposed mapping processor is called RDB2RDF-GUP, but for simplicity, we shall represent RDB2RDF-GUP by RUP. This processor acts as a standalone tool with a Graphical User Interface (GUI) that facilitates the mapping process and supports a diversity of other features. This new processor is a useful tool for integrating the databases in Semantic Web applications that incorporate all data formats into a combined knowledge model. Through a small set of GUI screens, RUP enables the users to perform the most required tasks by selecting from the available lists most of the time rather than writing. This processor is simple and very useful for domain experts and semi-experts. Our results show that the proposed processor, RUP, outperforms other existing processors in the usability and the number of supported features.","PeriodicalId":122550,"journal":{"name":"2022 5th International Conference on Computing and Informatics (ICCI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121203247","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

Shallow And Deep Learning In Footstep Recognition: A Survey 浅学习与深度学习在脚步识别中的应用综述

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756118

Ayman Iskandar, Marco Alfonse, Mohamed Roushdy, El-Sayed M. El-Horbaty

引用次数: 2

Deep Learning Toward Preventing Web Attacks

2022 5th International Conference on Computing and Informatics (ICCI) Pub Date : 2022-03-09 DOI: 10.1109/icci54321.2022.9756057

Abdelrahman S. Hussainy, Mahmoud A. Khalifa, Abdallah Elsayed, Amr Hussien, M. A. Razek

引用次数: 2