{"title":"Compression of Medical Images using Progressive Coders","authors":"N. Boukhennoufa, L. Djouane, Rima Bouzidi","doi":"10.1109/ICATEEE57445.2022.10093754","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093754","url":null,"abstract":"We have considered, in this paper, two compression methods based on wavelet transform and progressive coding, called EZW (Embedded Zerotree Wavelet) and SPIHT (Set partitioning in hierarchical trees). These techniques provide the opportunity to significantly increase compression ratios while preserving high qualities of reconstructed medical images. Unlike the EZW, the SPIHT approach takes advantage of subband correlations at near and far resolution levels (father-son relationships). A partial ordering by amplitude of the wavelet coefficients of the DWT (Discrete Wavelet Transform), partitioning in hierarchical trees, and scheduling of the transmission of the refinement bits are the three ideas used by SPIHT (the amplitude of each significant coefficient is progressively refined). The goal is to create a digital tool with the required main compression rate and PSNR (Peak Signal to Noise Ratio) limitations for compressing medical images. A development of the two cited algorithms has been carried out. For their evaluation, several medical images from two databases were used. The results prove that these algorithms are very efficient. Also, it has been found that the obtained results with SPIHT method greatly exceed those provided by EZW approach. SPIHT approach is very efficient compared to EZW from the point of view of the compression ratio and the image quality.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124242181","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}
Rabia Rebbah, I. Messaoudene, Mustapha Khelifi, Kheir Benderradji, Yacine Boussaadia, Massinissa Belazzoug, B. Hammache
{"title":"MIMO Cavity Slot Antenna Based on Substrate Integrated Waveguide Technique","authors":"Rabia Rebbah, I. Messaoudene, Mustapha Khelifi, Kheir Benderradji, Yacine Boussaadia, Massinissa Belazzoug, B. Hammache","doi":"10.1109/ICATEEE57445.2022.10093692","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093692","url":null,"abstract":"A cavity-backed planar slot antenna for multiple-input multiple-output (MIMO) applications is studied in this paper. Two slot antenna components are etched on the ground plane and the microstrip-line feeding technique is used for the two elements. The design is constructed using a SIW technique to obtain the best isolation between the elements of the proposed MIMO antenna. The numerical analysis demonstrates that the antenna works at an impedance bandwidth of 7.96–8.03 GHz for | S11 | less than -10 dB with high isolation reaching less than -21 dB at 8 GHz. With a radiation efficiency about 70% and a realized gain more than 4.7 dBi at 8 GHz. The proposed antenna exhibits good radiation performances comparing to the conventional one, including light-weight, and ease fabrication, which makes it appropriate for MIMO-RADAR systems.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122069603","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}
{"title":"Route Planning for a Tractor in an Agriculture Field with Obstacles","authors":"Feriel Fass, D. Ziou, Nassima Kadri","doi":"10.1109/ICATEEE57445.2022.10093717","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093717","url":null,"abstract":"In this article, we propose a trajectory planning method for a tractor in a rural environment. Our method is based on the simultaneous use of offline and real-time acquired data. The offline data is the geographical map of the agricultural field, which is assumed to be known, as well as vehicle driving data prerecorded by several experienced drivers. The depth video and the location of the vehicle are acquired in real time and used with existing data for the detection and avoidance of obstacles. The planning is seen as a constrained optimization problem. The constraints are related to the presence of obstacles which are considered as spatiotemporal events recognized through their geometric structure represented in the depth frames. We show that the proposed approach validated by using real data is effective and fulfills the real-time requirement.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122672697","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}
{"title":"An Efficient Classification System for Brain Tumor Based on Convolutional Neural Network","authors":"Bentahar Heythem, Mohamed Djerioui, B. Nesrin","doi":"10.1109/ICATEEE57445.2022.10093735","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093735","url":null,"abstract":"A brain tumor is a fatal disease that affects children and adults The disease might be detected using a physical exam or a neurological exam, but for the classification, it is done with biopsy. That last one is concerned with brain surgery, which is very hard and complicated in itself. Early detection and classification could help to choose the perfect plan for treatment. With the great development and change in technology, DL techniques could help in diagnosis and classification without any huge risks. Using the available data of Magnetic Resonance Imaging (MRI), that is studied by the radiologist, In our study, we took two approaches, the first including a transfer learning model and the second including a Convolutional Neural Network (CNN) model, to both classify different types of brain tumors. With the CNN approach, we managed to achieve an accuracy of 90 %. The experimental results show that our proposed CNN gives the best accuracy as compared to the transfer learning model.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128349038","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}
Mohamed Imed Khelil, Mohamed Ladjal, M. A. Ouali, H. Bennacer
{"title":"Sensor Anomaly Detection using Self Features Organizing Maps and Hierarchical-Clustring for Water Quality Assessment","authors":"Mohamed Imed Khelil, Mohamed Ladjal, M. A. Ouali, H. Bennacer","doi":"10.1109/ICATEEE57445.2022.10093763","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093763","url":null,"abstract":"Sensor fault, outlier, and anomaly detection are essential in many fields and applications to identify anomalies, abnormal data, or outliers that are different from the usual sensor data streams, effectively guaranteeing the validity of the measurements obtained by multiple sensors. Water quality assessment applications often frequently depend on multiple sensors that are situated in remote areas. It is necessary to account for apparent sensor failures and insufficient input data to obtain useful and powerful information from evaluating the corresponding measurements. In this paper, self-organizing features maps (SFOM)-based methods and hierarchical clustering (HC) are applied to several physicochemical parameters data anomaly detection in water quality assessment. In this study, the surface water quality from Mostaganem's Cheliff Dam was advanced assessed (Algeria). The performances and the efficacy of the proposed approaches in feature selection using SFOM and sensor anomaly detection process by SFOM and HC techniques were demonstrated successfully involved in water quality assessment. This result has a major impact on our monitoring system's performance both technically (lower learning times and anomaly detection) and economically (some less sensors required).","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129052496","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}
{"title":"Sensorless Control with Back EMF Integration Method for E-bike","authors":"N. Tadrist, Hocine Zeroug","doi":"10.1109/ICATEEE57445.2022.10093760","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093760","url":null,"abstract":"With ever-increasing concerns on our environment, there is a fast growing interest in electric bike with a motor mounted either at the front and at the rear wheel. In addition, there it is a pressing need for researchers to develop advanced electric-drive systems. This paper investigates potential performances and describes the running mode of an e-bike for transportation which uses a Brushless DC motor with an outer rotor mounted at the front wheel with a nominal torque of 10Nm and 250W with planetary gear. The controller uses an outer speed and inner current control loop using sensorless technique back-EMF based.. It is shown that the e-bike is able to start and run at convenient speed estimated with average minimum speed of 2Km/h and high speed up to 25 Km/h with a battery autonomy lasting up to 2h under semi flat and hilly distance less than 7%. We show that this speed control from low and high speed can be well tuned and adapted to various paths that fits the cyclist own comfort and desired acceleration. Also, the findings show also that the battery autonomy can be doubled if there is intermittent cycling periods.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123905329","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}
K. Amara, Hoceine Kennouche, Ali Aouf, O. Kerdjidj, N. Zenati, O. Djekoune, Mohamed Amine Guerroudji
{"title":"Augmented Reality for medical practice: a comparative study of Deep learning models for Ct-scan segmentation","authors":"K. Amara, Hoceine Kennouche, Ali Aouf, O. Kerdjidj, N. Zenati, O. Djekoune, Mohamed Amine Guerroudji","doi":"10.1109/ICATEEE57445.2022.10093691","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093691","url":null,"abstract":"The coronavirus disease has hardly affected medical healthcare systems worldwide. Physicians use radiological examinations as a primary clinical tool for diagnosing patients with suspected COVID-19 infection. Recently, deep learning approaches have further enhanced medical image processing and analysis, reduced the workload of radiologists, and improved the performance of radiology systems. This paper addresses medical image segmentation; we present a comparative performance study of four neural networks ’NN’ models, U-Net, 3D-Unet, KiU-Net and SegNet, for aid diagnosis. Additionally, we present his 3D reconstruction of COVID-19 lesions and lungs and his AR platform with augmented reality, including AR visualization and interaction. Quantitative and qualitative assessments are provided for both contributions. The NN model performed well in the AI-COVID-19 diagnostic process. The AR-COVID-19 platform can be viewed as an ancillary diagnostic tool for medical practice. It serves as a tool to support radiologist visualization and reading.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127511630","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}
{"title":"Investigating the Effect of Mo Doping on Properties of n-type ZnO Films","authors":"Warda Darenfad, N. Guermat, K. Mirouh","doi":"10.1109/ICATEEE57445.2022.10093739","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093739","url":null,"abstract":"This paper focused on study of 100% ZnO and doped with Molybdenum (Mo) in different concentrations (0.25, 0.5 and 0.75%) deposited by spray pyrolysis method in order to study the effect of dopant on the structural, optical and electrical properties of ZnO with the aim of improving its properties for use as a conductive transparent electrode in thin-film solar cells. After the characterization of our films and the corresponding discussions, we can conclude that: the XRD analysis confirmed that the films made from undoped and Mo-doped ZnO are polycrystalline with a hexagonal structure of the Wurtzite type with an orientation preferential (002), with no other phase detected. The transmittance decreases with the addition of Mo to ZnO. Therefore, Mo does not improve the transmittance of ZnO for concentrations between 0.25% up to 0.75%. The electrical analysis shows that Mo affects the electrical properties of ZnO by increasing the electrical conductivity with a high value of 1.176 (Ω.cm)-1 for the ZnO:0.25%Mo film.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126885453","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}
Abdelouadoud Loukriz, M. Drif, A. Bouchelaghem, D. Saigaa, Ahmed Bendib, Kichene Moadh
{"title":"Current Balancing and PSO Methods-Based PV Array Output Power Optimization: A Comparative Study","authors":"Abdelouadoud Loukriz, M. Drif, A. Bouchelaghem, D. Saigaa, Ahmed Bendib, Kichene Moadh","doi":"10.1109/ICATEEE57445.2022.10093690","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093690","url":null,"abstract":"The phenomenon of mismatch between the modules constituting a photovoltaic (PV) array is one of the problems that frequently occur in PV systems, in particular, the shading issue, which may result in less energy production. To deal with this issue, various configuration methods have been adopted in the literature. However, these configuration methods are suffering from implementation complexity in practice, such as more wiring, more sensors, the need to have more processing, and more memory use. In the present paper, a comparative study between the current balancing (CB) and particle swarm optimization (PSO)-based PV reconfiguration methods is carried out using MATLAB/Simulink software. The reached findings under varying partial shading conditions (PSCs) are investigated to determine the best approach among them.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127046584","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}
{"title":"CFAR Ship Detection in SAR Images Based on the Generalized Rayleigh Mixture Models","authors":"Hicham Madjidi, T. Laroussi, Faiçal Farah","doi":"10.1109/ICATEEE57445.2022.10093718","DOIUrl":"https://doi.org/10.1109/ICATEEE57445.2022.10093718","url":null,"abstract":"Synthetic Aperture Radar (SAR) is a powerful equipment that has gained popularity as it synthetically produces higher resolution images in any weather conditions and even at night. For this reason, the SAR can be used to detect ships using Constant False Alarm Rate (CFAR) algorithms. In this paper, based on the Expectation-Maximization (EM) algorithm, we introduce the Generalized Rayleigh Mixture Model (GRMM), for characterizing sea clutter. In doing this, we use an adaptive global threshold to generate a censorship map that indicates if each sample in the image is likely a target pixel. Experiments carried out on a real SAR image, show that the GRMM-CFAR detector transcends the existing detectors.","PeriodicalId":150519,"journal":{"name":"2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121131361","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}