2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)最新文献_第4页

Zomraty: E-Blood Bank Android Application for Donors and Life Savers Zomraty:为献血者和救生者提供的电子血库Android应用程序

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378752

M. A. Oukebdane, S. Ghouali, Karima Ghazali, M. Feham

{"title":"Zomraty: E-Blood Bank Android Application for Donors and Life Savers","authors":"M. A. Oukebdane, S. Ghouali, Karima Ghazali, M. Feham","doi":"10.1109/IHSH51661.2021.9378752","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378752","url":null,"abstract":"Every day, thousands of people around the world receive an emergency blood transfusion because they undergo major surgery or a serious injury that needs replacing the lost blood. Or because they suffer from bleeding in the digestive system, from an ulcer, from a disease such as leukemia or kidney disease that causes anemia (not having enough healthy red blood cells), a blood disorder or severe liver problems, or even because of cancer treatments such as radiation therapy and chemotherapy. According to the American Red Cross, every 2 seconds someone in the U.S needs blood, this means that America alone needs 14,400 blood donors daily, considering that only one donor can save three needy blood transfusions. This is not all. About 38 percent of Americans are not eligible to donate blood or platelets, measure for that in the rest of the world. It would be terrifying to need a blood donor, given these numbers. Based on this, we created the Zomraty Application, which aims primarily to save thousands of lives in Algeria as a basic first stage for people who need a blood transfusion. Where it connects volunteers to donate blood and people in need by providing detailed information about the donor that allows the needy person to choose the volunteer who is closest and most suitable.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134285123","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: 3

An Improved Simulated Annealing Algorithm for Optimization of Protein Folding Problem 蛋白质折叠问题优化的一种改进模拟退火算法

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378742

Nabil Boumedine, S. Bouroubi

引用次数: 1

Single channel EMG classification using DWT and SVM 基于DWT和SVM的单通道肌电信号分类

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378707

Cherrih Hachemi, M. Talha, Hadjer Zairi, Karim Meddah

引用次数: 5

A New Stochastic Petri Nets Modeling for Dual Cluster Heads Configuration in Energy-Harvesting WSNs 能量收集WSNs双簇头结构的随机Petri网模型

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378741

Oukas Nourredine, Menouar Boulif

引用次数: 5

Feature Importance Evaluation of Smartphone Touch Gestures for Biometric Authentication 智能手机触摸手势生物识别认证特征重要性评估

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378750

Youcef Ouadjer, M. Adnane, Nesrine Bouadjenek

引用次数: 5

Human shadow: remote monitoring system 人影:远程监控系统

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378713

Belkhir Maria, B. Abdelkader, Bouyakoub Samia, Laroui Meriem

引用次数: 0

Fake News detection Using Machine Learning 利用机器学习检测假新闻

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378748

Nihel Fatima Baarir, Abdelhamid Djeffal

{"title":"Fake News detection Using Machine Learning","authors":"Nihel Fatima Baarir, Abdelhamid Djeffal","doi":"10.1109/IHSH51661.2021.9378748","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378748","url":null,"abstract":"The phenomenon of Fake news is experiencing a rapid and growing progress with the evolution of the means of communication and Social media. Fake news detection is an emerging research area which is gaining big interest. It faces however some challenges due to the limited resources such as datasets and processing and analysing techniques. In this work, we propose a system for Fake news detection that uses machine learning techniques. We used term frequency-inverse document frequency (TF-IDF) of bag of words and n-grams as feature extraction technique, and Support Vector Machine (SVM) as a classifier. We propose also a dataset of fake and true news to train the proposed system. Obtained results show the efficiency of the system. In this work, we propose a system for Fake news detection that uses machine learning techniques. We used term frequency-inverse document frequency (TF-IDF) of bag of words and n-grams as feature extraction technique, and Support Vector Machine (SVM) as a classifier. We propose also a dataset of fake and true news to train the proposed system. Obtained results show the efficiency of the system.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132013043","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

EMG & EIMG measurement for Arm & Hand motions using custom made instrumentation based on Raspberry PI 使用基于树莓派的定制仪器进行手臂和手部运动的肌电和脑电图测量

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378716

Abdelakram Hafid, S. Benouar, Hachemi Cherrih, Benayad Ali, M. Talha

引用次数: 1

Decision-making based on decision tree for ball bearing monitoring 基于决策树的滚珠轴承监测决策

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378734

Riadh Euldji, Mouloud Boumahdi, M. Bachene

{"title":"Decision-making based on decision tree for ball bearing monitoring","authors":"Riadh Euldji, Mouloud Boumahdi, M. Bachene","doi":"10.1109/IHSH51661.2021.9378734","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378734","url":null,"abstract":"The vibrations produced by rotating machines affect people and the environment in many ways. They affect comfort, work capacity, health, and safety. For this, condition monitoring is an indispensable tool to track the evolution of vibrations. In the condition monitoring process of rotating machines, maintenance decision-making is subject to constraints relating to the lack of performance of the material resources and the unavailability of experts in the field on the sites, and sometimes the inability of these experts to make a decision. For this reason, a methodology based on two approaches: the vibration analysis and the decision tree to model of the decision-making is proposed. A set of data is collected from vibration signals analysis taken from a set of experiments performed on ball bearings. Then a classification algorithm is applied to build the decision tree. Finally, expert rules are extracted. These rules will be used in the development of a decision-making system, called an expert system. The effectiveness of the proposed methodology is demonstrated in this study.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115054880","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: 3

Text-Independent Speaker Identification using Mel-Frequency Energy Coefficients and Convolutional Neural Networks 基于mel频率能量系数和卷积神经网络的文本无关说话人识别

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378726

Déhia Abdiche, K. Harrar

{"title":"Text-Independent Speaker Identification using Mel-Frequency Energy Coefficients and Convolutional Neural Networks","authors":"Déhia Abdiche, K. Harrar","doi":"10.1109/IHSH51661.2021.9378726","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378726","url":null,"abstract":"Automatic Speaker Identification (ASI) is a biometric technique, which had achieved reliability in real applications, with standard feature extraction methods such as Linear Predictive Cepstral Coefficients (LPCC), Perceptual Linear Prediction (PLP), and modeling methods such as Gaussian mixture model (GMM), etc. However, the success of these manual approaches was quickly hampered by the emergence of big data, and the inability of scientists to manipulate large amounts of data, which led researchers to move towards automatic methods such as deep neural networks. In this work, a Convolutional Neural Network (CNN) is suggested for speaker identification in text-independent mode. Mel-Frequency Energy Coefficients (MFEC) method was used for extracting the characteristics of audio signals and the obtained coefficients were injected into the convolutional neural network model for classification (identification). In addition, a comparison was made between the proposed method and the existing traditional methods. Experimental results show that the proposed structure resulted in a speaker identification rate of 97.89%, which is much higher than the rates obtained in the old state of the art methods.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132390211","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