2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)最新文献_第3页

Energy-efficient fault-tolerant routing for wireless sensor networks 无线传感器网络的高能效容错路由

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378705

Khadidja Belkadi, M. Lehsaini

{"title":"Energy-efficient fault-tolerant routing for wireless sensor networks","authors":"Khadidja Belkadi, M. Lehsaini","doi":"10.1109/IHSH51661.2021.9378705","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378705","url":null,"abstract":"The fault-tolerance property is defined by the ability of the network to maintain its functionality without interruption caused by sensor failure. In wireless sensor networks (WSNs), sensor nodes are prone to failures due to various causes: energy depletion, damage due to weather conditions or animals, etc. Moreover, in WSNs, failures caused by depletion of sensor batteries are the most predominant. Hence, the conservation of sensor energy prevents the premature extinction of their batteries, thus increasing the service life of the sensors. To ensure fault-tolerance property in this kind of networks, fault-tolerant protocols use fault recovery algorithms. This mechanism is considered to be an optimistic approach where it is only performed after fault detection; then to avoid breakdowns. Moreover, fault-tolerant routing protocols provide strategies that attempt to delay or avoid any type of failure in order to keep the network functional for as long as possible. In this paper, we propose an energy-efficient cluster-based fault-tolerant routing protocol for WSNs that aims to cover failures before they occur, called EE-FT protocol. EE-FT protocol chooses the shortest reliable paths for routing data to the base station based on Bernoulli's law for selecting reliable nodes. These paths are formed by CHs having more energy. Simulation results show that our proposal provides better performance in terms of network lifetime, end-to-end delay and packet loss rate compared to other protocols.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"82 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":"128159431","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

Broad Band Rectenna Based on Antipodal Vivaldi Antenna and NULT Rectifier 基于对映维瓦尔第天线和NULT整流器的宽带整流天线

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378735

Ali Benayad, M. Tellache

引用次数: 1

Intelligent myoelectric control of a humeral ampulation 肱骨运动的智能肌电控制

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378718

Hachemi Cherrih, M. Kedir-Talha, A. Amirat, A. Hariz, W. Hanniche

引用次数: 2

Soft-CSRNet: Real-time Dilated Convolutional Neural Networks for Crowd Counting with Drones 用于无人机人群计数的实时扩展卷积神经网络

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378749

Imene Bakour, Hadia Nesma Bouchali, S. Allali, Hadjer Lacheheb

{"title":"Soft-CSRNet: Real-time Dilated Convolutional Neural Networks for Crowd Counting with Drones","authors":"Imene Bakour, Hadia Nesma Bouchali, S. Allali, Hadjer Lacheheb","doi":"10.1109/IHSH51661.2021.9378749","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378749","url":null,"abstract":"In recent years, the measurement of crowd density in a real-time video sequence has been a significant field of study. The use of these methods to stop protest scrambling, and social distancing to protect from COVID-19 is a crucial task nowadays. In this article, we introduce a different model for estimating crowd density based on front and vertical drone video sequences. Our proposition consists of an optimized version of a widely used crowd counting model called “CSRNET”. The proposed “SOFT CSRNET” is composed of two parts: a CNN front-end and CNN back-end. The front-end is composed of VGG16 layers constructed in the same way as CSRNet. On the other hand, in the back-end we select five convolutional layers of different size in the aim to get better results in less time. The results demonstrate that our method outperforms CSRNET in terms of MAE, image par second (ips) and proof of efficiency for a real-time videos sequence of drones. Our results are validated, executing the proposed method on Visdrone2019-DET and Visdrone2020-DET datasets.","PeriodicalId":127735,"journal":{"name":"2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH)","volume":"71 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":"127488080","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

Deep Network Construction using Autoencoder for Abnormality Detection in Radiotherapy Service 基于自编码器的放疗异常检测深度网络构建

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378715

Et-Tahir Zemouri, A. Allam

引用次数: 0

Design of Remote Pervasive Health Monitoring System based on Cloud Computing and SOA 基于云计算和SOA的远程普适健康监测系统设计

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378745

A. Azoui, D. Idoughi, K. A. Abdelouhab

引用次数: 1

Swarm Intelligence-based Decision Trees Induction for Classification — A Brief Analysis 基于群体智能的分类决策树归纳分析

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378746

Ikram Bida, Saliha Aouat

{"title":"Swarm Intelligence-based Decision Trees Induction for Classification — A Brief Analysis","authors":"Ikram Bida, Saliha Aouat","doi":"10.1109/IHSH51661.2021.9378746","DOIUrl":"https://doi.org/10.1109/IHSH51661.2021.9378746","url":null,"abstract":"Decision trees are popular machine learning classifiers, they accurately represent the data in a simple manner that closely resembles human reasoning. Since inducing the optimal decision tree is a NP-hard problem, numerous traditional heuristic-based approaches were introduced to tackle it. However, due to the present data explosion, these greedy local methods did not guarantee the induction of an optimal tree. To address this issue, swarm intelligence algorithms have been currently applied to navigate the search space more appropriately, seeking optimal decision trees. The aim of this research study is to give an analysis overview of the most up-to-date existing swarm-based decision trees induction techniques in a shape of a comparative study, where we discuss the different basics, features, characteristics and results. This survey will serve as a guide for the researches community. However, due to the present data explosion, these greedy local methods did not guarantee the induction of an optimal tree. To address this issue, swarm intelligence algorithms have been currently applied to navigate the search space more appropriately, seeking optimal decision trees. The aim of this research study is to give an analysis overview of the most up-to-date existing swarm-based decision trees induction techniques in a shape of a comparative study, where we discuss the different basics, features, characteristics and results. This survey will serve as a guide for the researches community. The aim of this research study is to give an analysis overview of the most up-to-date existing swarm-based decision trees induction techniques in a shape of a comparative study, where we discuss the different basics, features, characteristics and results. This survey will serve as a guide for the researches community.","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":"116291357","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

Smart Home Danger Prediction System to ensure People with Alzheimer's Disease Safety 智能家居危险预测系统确保老年痴呆症患者的安全

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378728

Camille Aissani, Yanis-Fady Akroun, M. Yazid, Siham Bouchelaghem

引用次数: 0

A Smartphone Application for Fall Detection Using Accelerometer and ConvLSTM Network 基于加速度计和ConvLSTM网络的跌倒检测智能手机应用

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378743

Mohamed Ilyes Amara, A. Akkouche, Elhocine Boutellaa, H. Tayakout

引用次数: 2

Two-scale Algorithm to Plan Coverage Paths for Multi-UAVs 多无人机覆盖路径规划的双尺度算法

2020 2nd International Workshop on Human-Centric Smart Environments for Health and Well-being (IHSH) Pub Date : 2021-02-09 DOI: 10.1109/IHSH51661.2021.9378755

Abdelwahhab Bouras, Y. Bouzid, M. Guiatni

引用次数: 2