2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)最新文献_第10页

Fault Detection in Waste Water Treatment Plants using Improved Particle Filter-based Optimized EWMA 基于改进粒子过滤器的优化EWMA污水处理厂故障检测

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231954

I. Baklouti, M. Mansouri, H. Nounou, M. Nounou, A. Hamida

{"title":"Fault Detection in Waste Water Treatment Plants using Improved Particle Filter-based Optimized EWMA","authors":"I. Baklouti, M. Mansouri, H. Nounou, M. Nounou, A. Hamida","doi":"10.1109/ATSIP49331.2020.9231954","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231954","url":null,"abstract":"Environmental, health, and safety concerns are of major importance world-wide. These concerns are closely tied to the availability and quality of water that can be used in various domestic and industrial applications. Therefore, the objective of this paper is to develop a general framework for modeling and monitoring technique that aims at enhancing the operation of wastewater treatment plants. In this work, an improved PF (IPF) method will be developed to better handle the nonlinear and high dimensional state estimation problem involved in modeling wastewater treatment plants. Then, an improved detection control chart to enhance the monitoring of WWTP will be developed. The contributions of this work are the foorfold: 1) to estimate a nonlinear state variables of WWTPs using improved particle filter in three types of weathers (dry, storm and rain). 2) to develop an new optimized EWMA (OEWMA) based on the best selection of smoothing parameter ($lambda$) and control width L. 3) to combine the advantages of state estimation technique, with OEWMA chart to improve the fault detection of WWTP. 4) to investigate the effect of fault types (change in variance and mean in shift) and sizes on the monitoring performances.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124231976","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

The Design, by Physical Topology Optimizing, of a Passive UHF RFID Identification System: Suitable for Applications with Various Constraints 基于物理拓扑优化的无源超高频RFID识别系统设计:适用于各种约束的应用

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231580

Rahma Zayoud, H. Hamam

{"title":"The Design, by Physical Topology Optimizing, of a Passive UHF RFID Identification System: Suitable for Applications with Various Constraints","authors":"Rahma Zayoud, H. Hamam","doi":"10.1109/ATSIP49331.2020.9231580","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231580","url":null,"abstract":"RFID technology is booming. It catches the attention of several researchers. This technology uses the radio wave to identify objects on which an RFID tag is placed. RFID has a lot of advantages, but it also has limitations. Its limits are its sensitivity to liquids, metals and speed.We design an objects identification system by radio frequency that works in different RFID technology application environments, based on passive UHF RFID technology and through the physical topology optimization in real time too. This system is also adapted to various constraints, in order to solve overcome difficulties, related to various applications, at once, and operates, without any problem, in different fields.We use the simulated annealing algorithm to find the optimal physical topology that has the highest average reading rate. RFID antennas are installed on brackets, attached to a tripod system by servo motors. These servo motors are controlled by the middleware, where the simulated annealing optimization algorithm is already implemented, to vary the angles of the detection connectors in an automated way, in order to find the optimal topology. So the optimization process will be guided by an optimization algorithm and not by trial and error processes. Tripod mechanical systems are movable media for antennas to play on XYZ dimensions too.The design of the mechanical system and the choice of materials were made. The first results, such as the identity of each detected object and the identity of each antenna that will detect an object, are here. Following reached results will be shared in several next publications.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128401293","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

Denoising techniques for multi-parametric prostate MRI: A Comparative Study 多参数前列腺MRI去噪技术的比较研究

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231751

A. Latrach, Rania Trigui, Lamia Sellemi

引用次数: 0

Monitoring Consciousness and Spatiotemporal Dynamics During Complex Focal Seizures 监测意识和时空动态在复杂局灶性癫痫发作

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231891

Ibtissem Khouaja, Imane Youkana, M. Saafi

引用次数: 0

4G and 5G technologies: A Comparative Study 4G和5G技术:比较研究

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231605

Emna Hajlaoui, A. Zaier, Abdelhakim Khlifi, Jihed Ghodhbane, M. Hamed, L. Sbita

{"title":"4G and 5G technologies: A Comparative Study","authors":"Emna Hajlaoui, A. Zaier, Abdelhakim Khlifi, Jihed Ghodhbane, M. Hamed, L. Sbita","doi":"10.1109/ATSIP49331.2020.9231605","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231605","url":null,"abstract":"Driven by the growing demand for quality assured mobility; new promising technologies have emerged, such as 4G and 5G networks, in order to meet users’ needs. Indeed, 4G networks unceasingly seek to improve the offered services and to guarantee a certain level of quality of service (QoS) for users while moving with high speeds. On his side, 5G standard is on its way. Promising superfast speeds and an end to congestion, the technology is expected to revolutionize mobile networks and create new economic opportunity: but how exactly will it do this and what makes it different to 4G standards?In this context, the purpose of the paper is a detailed study on 4G and 5G technologies. Thereby, we outline the various characteristics of 4G systems, i.e. their contributions and their behaviors in terms of QoS conservation during the movement of subscribers. The similarities and differences between the two standards have been studied to show the need to integrate LTE with WiMAX. Then, results found are well compared by the theoretical parameters of 5G technologies to precisely track the difference between 4G and 5G networks.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"36 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124986314","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: 18

A multimodal Physiological-Based Stress Recognition: Deep Learning Models’ Evaluation in Gamers’ Monitoring Application 基于生理的多模态压力识别:深度学习模型在玩家监控应用中的评估

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-09-01 DOI: 10.1109/ATSIP49331.2020.9231666

S. Dhaouadi, Mohamed O. M. Khelifa

{"title":"A multimodal Physiological-Based Stress Recognition: Deep Learning Models’ Evaluation in Gamers’ Monitoring Application","authors":"S. Dhaouadi, Mohamed O. M. Khelifa","doi":"10.1109/ATSIP49331.2020.9231666","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231666","url":null,"abstract":"emotional states detection from physiological signals has many potential applications. In Human-Machine or Human-Human interaction systems, stress detection could provide users with improved services and can be a tool for monitoring and preventing potential stress-related pathologies. Traditional machine learning techniques for automatic stress recognition have been used in previous researches but they sometimes present specific limitations. The emergence of deep learning permits the reveal of underlying patterns in body response witch, otherwise would not be easily observed. In this paper we explore the application of Long Short-Term Memory (LSTM) and Deep Neural (DNN) Networks for real time stress monitoring in young gamers. We base our study on their body responses. For this, we use physiological signals such as the electrocardiography (ECG), the electrodermal activity (EDA), and the electromyography (EMG), measured by non-invasive wearable sensors. The result of the study provides an evaluation of both models’ capacity in predicting real time gamers’ emotional state built on the variation of their physiological parameters.","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129199499","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: 8

Multi-band Frequency Reconfigurable Planar Bow-tie Antenna 多波段频率可重构平面领结天线

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2020-02-28 DOI: 10.1109/ATSIP49331.2020.9231617

M. Mabrouki, A. Gharsallah

引用次数: 2

AI-based Pilgrim Detection using Convolutional Neural Networks 基于人工智能的卷积神经网络朝圣者检测

2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) Pub Date : 2019-11-18 DOI: 10.1109/ATSIP49331.2020.9231549

Marwa Ben Jabra, Adel Ammar, A. Koubâa, O. Cheikhrouhou, H. Hamam

{"title":"AI-based Pilgrim Detection using Convolutional Neural Networks","authors":"Marwa Ben Jabra, Adel Ammar, A. Koubâa, O. Cheikhrouhou, H. Hamam","doi":"10.1109/ATSIP49331.2020.9231549","DOIUrl":"https://doi.org/10.1109/ATSIP49331.2020.9231549","url":null,"abstract":"Pilgrimage represents the most important Islamic religious gathering in the world where millions of pilgrims visit the holy places of Makkah and Madinah to perform their rituals. The safety and security of pilgrims is the highest priority for the authorities. In Makkah, 5000 cameras are spread around the holy mosques for monitoring pilgrims, but it is almost impossible to track all events by humans considering the huge number of images collected every second. To address this issue, we propose to use an artificial intelligence technique based on deep learning and convolutional neural networks to detect and identify Pilgrims and their features. For this purpose, we built a comprehensive dataset for the detection of pilgrims and their genders. Then, we develop two convolutional neural networks based on YOLOv3 and Faster-RCNN for the detection of Pilgrims. Experiment results show that Faster RCNN with Inception v2 feature extractor provides the best mean average precision over all classes (51%). A video demonstration that illustrates a real-time pilgrim detection using our proposed model is available at [1].","PeriodicalId":384018,"journal":{"name":"2020 5th International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114939507","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: 4