2022 3rd International Conference on Embedded & Distributed Systems (EDiS)最新文献

Unsupervised Two-Stage TR-PCANet Deep Network For Unconstrained Ear Identification 无约束耳朵识别的无监督两阶段TR-PCANet深度网络

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996536

Aicha Korichi, Meriem Korichi, Maarouf Korichi, Oussama Aiadi

引用次数: 0

An Innovative Smart and Sustainable Low-cost Irrigation System for Smallholder Farmers' Communities 面向小农社区的创新智能和可持续低成本灌溉系统

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996498

Amine Dahane, R. Benameur, Bouabdellah Kechar

引用次数: 3

A Real Time Object Detection System for Infant Safe Sleep Based on YOLOv5 Algorithm 基于YOLOv5算法的婴儿安全睡眠实时目标检测系统

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996513

Randa Nachet, T. B. Stambouli

引用次数: 1

FPGA Implementation of Support Vector Machine for Gait Activity Classification 步态活动分类支持向量机的FPGA实现

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996523

Madaoui Lotfi, M. Kedir-Talha

引用次数: 1

Designing a Web Accessibility Environment for the Visually Impaired 为视障人士设计无障碍网页环境

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996542

Meriem Zeboudj, K. Belkadi

引用次数: 1

Toward memory-centric scheduling for PREM task on multicore platforms, when processor assignments are specified 当指定处理器分配时，在多核平台上实现以内存为中心的PREM任务调度

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996534

Ikram Senoussaoui, M. K. Benhaoua, H. Zahaf, G. Lipari

{"title":"Toward memory-centric scheduling for PREM task on multicore platforms, when processor assignments are specified","authors":"Ikram Senoussaoui, M. K. Benhaoua, H. Zahaf, G. Lipari","doi":"10.1109/EDiS57230.2022.9996534","DOIUrl":"https://doi.org/10.1109/EDiS57230.2022.9996534","url":null,"abstract":"Real-time embedded systems are increasingly being built using commercial-off-the-shelf (COTS) components. Although these components generally offer high performance, they can occasionally incur significant timing delays. Computing precise bounds on timing delays due to contention is difficult without a proper support from the hardware. Rather than estimating contention safe delays, this work aims to avoid it. We consider hardware architectures where each core has a scratchpad memory and the task execution is divided into a memory phase and a computation phase (Predictable Execution Model - PREM). Tasks are allocated to cores by a partitioned scheduling scheme. Then we schedule memory phases using a non-preemptive scheduling approach, while computation phases are scheduled using preemptive single core schedulers. This paper presents a new artificial deadline based approach to avoid contention in memory phases, where tasks memory phases are assigned appropriate deadlines and scheduled by a non-preemptive scheduler (EDF). The effectiveness of the proposed method is evaluated using a set of synthetic experiments in terms of schedulability and analysis time.","PeriodicalId":288133,"journal":{"name":"2022 3rd International Conference on Embedded & Distributed Systems (EDiS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127555860","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 combination of multi and univariate anomaly detection in urban irrigation systems 城市灌溉系统多变量与单变量联合异常检测

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996520

Aurora González-Vidal, Jesús Fernández-García, A. Skarmeta

{"title":"A combination of multi and univariate anomaly detection in urban irrigation systems","authors":"Aurora González-Vidal, Jesús Fernández-García, A. Skarmeta","doi":"10.1109/EDiS57230.2022.9996520","DOIUrl":"https://doi.org/10.1109/EDiS57230.2022.9996520","url":null,"abstract":"Water scarcity is a global concern that requires a more intelligent way to manage the water network in order to minimize consumption and losses. There is a current need for new automated and intelligent decision support systems that employ data analytic advances to analyze in real-time the anomalies and problems that appear in water usage. In our case, we have developed a 3 steps system using unsupervised algorithms, that has been tested on the irrigation of urban parks. Those steps consist of grouping the parks according to similarities in the irrigation by clustering the consumption time series, searching for the dates where multivariate anomalies occur in every group using the Vector Autoregressive Model, and finally, applying an ARIMA framework to each series in the area of those dates. Our methodology reduces the time that anomaly detection univariate systems require for analysing the whole univariate time series by extracting previous knowledge on a multivariate approach. This methodology, when integrated with an IoT platform, is a tool for easing the labelling of real anomalies and can help create supervised datasets for future research in the area. The approach is used in urban scenarios, however, can easily be extended to be an application for smart agriculture scenarios.","PeriodicalId":288133,"journal":{"name":"2022 3rd International Conference on Embedded & Distributed Systems (EDiS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131460205","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

Bayesian Convolutional Neural Networks for Image Classification with Uncertainty Estimation 基于不确定性估计的贝叶斯卷积神经网络图像分类

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996478

F. Bessai-Mechmache, Maya N. Ghaffar, Rayan Y. Laouti

{"title":"Bayesian Convolutional Neural Networks for Image Classification with Uncertainty Estimation","authors":"F. Bessai-Mechmache, Maya N. Ghaffar, Rayan Y. Laouti","doi":"10.1109/EDiS57230.2022.9996478","DOIUrl":"https://doi.org/10.1109/EDiS57230.2022.9996478","url":null,"abstract":"Over the past decade, deep learning has led to a cutting-edge performance in a variety of fields. However, it faces a fundamental constraint which is the treatment of uncertainty. The representation of the model's uncertainty is of significant importance in areas subject to strict safety or reliability re-quirements. Bayesian deep learning offers a new approach that showcases the degree of reliability of predictions made by neural networks. The present work tests deep learning with Bayesian thinking through a case study of image classification. It puts into practice Bayesian inference to tackle the problem of uncertainty in deep learning and shows its correlation with data quality and model accuracy. To reach this goal, we have implemented a Bayesian convolutional neural network using the variational inference algorithm, Bayes by Backprop. The proposed model was evaluated on an image classification task, with two benchmark datasets. The results' review allowed for validation of the Bayesian approach and showed that it obtains comparable results to those of a non-Bayesian convolutional neural network. Furthermore, the uncertainty of the model was estimated in terms of aleatory and epistemic uncertainty.","PeriodicalId":288133,"journal":{"name":"2022 3rd International Conference on Embedded & Distributed Systems (EDiS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128138635","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-Population-based Parallelization of Ensemble of Differential Evolution Variants for Constrained Real Parameter Optimization 约束实参数优化中基于多种群的差分演化变量集成并行化

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996477

Leyla Belaiche, L. Kahloul, Manel Houimli, Selma Sahraoui, Saber Benharzallah, M. Grid, Nedjma Abidallah

{"title":"Multi-Population-based Parallelization of Ensemble of Differential Evolution Variants for Constrained Real Parameter Optimization","authors":"Leyla Belaiche, L. Kahloul, Manel Houimli, Selma Sahraoui, Saber Benharzallah, M. Grid, Nedjma Abidallah","doi":"10.1109/EDiS57230.2022.9996477","DOIUrl":"https://doi.org/10.1109/EDiS57230.2022.9996477","url":null,"abstract":"Differential evolution (DE) algorithms face performance challenges, which lean on improving solutions quality, speed-up, and exploitation of computational resources. Parallelism represents a suitable paradigm for overcoming the DE challenges. The ensemble of differential evolution variants (EDEV) algorithm is a recent DE algorithm. EDEV constitutes three DE variants (JADE, CoDE, and EPSDE), which may decrease its speedup. In this paper, a multi-population parallel ensemble of differential evolution variants (MPPEDEV) is proposed based on the synchronous master/slave parallel model. The performance of the proposed MPPEDEV is tested using a constrained real parameter problem proposed in CEC 2006. Compared to four state-of-the-art DE algorithms, which are JADE, CoDE, EPSDE, and EDEV, the results show that MPPEDEV outperforms EDEV in terms of execution time and solutions quality, depending on the population size as a control parameter. Furthermore, MPPEDEV and EDEV outperform JADE, CoDE, and EPSDE in terms of solutions' quality.","PeriodicalId":288133,"journal":{"name":"2022 3rd International Conference on Embedded & Distributed Systems (EDiS)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133414039","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

Basic Mobile Robot Prototyping Using RFID 使用RFID的基本移动机器人原型

2022 3rd International Conference on Embedded & Distributed Systems (EDiS) Pub Date : 2022-11-02 DOI: 10.1109/EDiS57230.2022.9996471

I. Akli, Halimatou Boukari Alidou, A. Chekir, Samy Ouazine

引用次数: 0