Pub Date : 2022-10-19DOI: 10.3991/ijoe.v18i13.33519
Aouatif Arqane, Omar Boutkhoum, Hicham Boukhriss, A. Moutaouakkil
Undoubtedly, the advancements in Machine Learning (ML) and especially ensemble learning models enable researchers to develop numerous fields in ways we had never imagined before. Intrusion Detection System (IDS) is one of these fields that benefits from the aforementioned techniques to identify and classify the security threats with more accuracy. In fact, IDS technology has become an essential component for any defense strategy, since it provides a healthy environment for businesses. Besides, it protects future network infrastructures from intruders and suspicious network activities. In this context, this paper presents a systematic literature review on ensemble learning-based IDS and the datasets used to evaluate the proposed methods. Furthermore, we illustrate the distribution of the reviewed papers by year of publication, datasets utilized and ensemble learning methods. Finally, we discuss the finding of this review and highlight some limitations of the aforementioned models. The overall purpose of this literature review is to provide a guideline on how to choose ensemble learning models to solve IDS issues based on the most efficient and recent trends
{"title":"Intrusion Detection System using Ensemble Learning Approaches: A Systematic Literature Review","authors":"Aouatif Arqane, Omar Boutkhoum, Hicham Boukhriss, A. Moutaouakkil","doi":"10.3991/ijoe.v18i13.33519","DOIUrl":"https://doi.org/10.3991/ijoe.v18i13.33519","url":null,"abstract":"Undoubtedly, the advancements in Machine Learning (ML) and especially ensemble learning models enable researchers to develop numerous fields in ways we had never imagined before. Intrusion Detection System (IDS) is one of these fields that benefits from the aforementioned techniques to identify and classify the security threats with more accuracy. In fact, IDS technology has become an essential component for any defense strategy, since it provides a healthy environment for businesses. Besides, it protects future network infrastructures from intruders and suspicious network activities. In this context, this paper presents a systematic literature review on ensemble learning-based IDS and the datasets used to evaluate the proposed methods. Furthermore, we illustrate the distribution of the reviewed papers by year of publication, datasets utilized and ensemble learning methods. Finally, we discuss the finding of this review and highlight some limitations of the aforementioned models. The overall purpose of this literature review is to provide a guideline on how to choose ensemble learning models to solve IDS issues based on the most efficient and recent trends","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"53 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113982481","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.31897
Aya Alsalihi, Hadeel K. Aljobouri, E. Altameemi
Breast cancer is one of the most common types of cancer among Iraqi women. MRI has been used in the detection of breast tumors for its efficient performance in the diagnosis process providing high accuracy. In this paper, breast MRI image data from 89 patients were classified using GLCM and CNN feature extraction methods. Four models were evaluated consisting of GLCM, CNN, combined GLCM and CNN features based models. The statistical ANOVA feature selection method was used to reduce the redundant features. The reduced feature subset was fed to CNN classifier for obtaining either normal or abnormal breast images. The proposed method was assessed in terms of accuracy, precision, recall and F1-score. The model provided 100% classification accuracy.
{"title":"GLCM and CNN Deep Learning Model for Improved MRI Breast Tumors Detection","authors":"Aya Alsalihi, Hadeel K. Aljobouri, E. Altameemi","doi":"10.3991/ijoe.v18i12.31897","DOIUrl":"https://doi.org/10.3991/ijoe.v18i12.31897","url":null,"abstract":"Breast cancer is one of the most common types of cancer among Iraqi women. MRI has been used in the detection of breast tumors for its efficient performance in the diagnosis process providing high accuracy. In this paper, breast MRI image data from 89 patients were classified using GLCM and CNN feature extraction methods. Four models were evaluated consisting of GLCM, CNN, combined GLCM and CNN features based models. The statistical ANOVA feature selection method was used to reduce the redundant features. The reduced feature subset was fed to CNN classifier for obtaining either normal or abnormal breast images. The proposed method was assessed in terms of accuracy, precision, recall and F1-score. The model provided 100% classification accuracy.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129013676","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.30893
Fatima-Ezzahra Ait-Bennacer, A. Aaroud, K. Akodadi, B. Cherradi
Smart coaching and e-sport platforms have shown a great interest in the recent research studies. Through this study, we aim to globalize the practice of sport, especially Shotokan Karate, by connecting participants and coaches on an international scale through the integration of Artificial Intelligence techniques such as computer vision and deep learning, to give the possibility of carrying out national and international virtual training courses without logistical constraints. The proposed work aims to apply the latest action detection, action recognition, and action classification methods for different Karate movements using the LSTM and the ST-GCN algorithms and proposes these movements in 3D using Video Inference for Human Body Pose and Shape Estimation (VIBE). Our proper Multiview Dataset contains pose estimations of a set of basic movements captured by a karate Shotokan expert (6th DAN Black Belt) from three views (Front view, Left view, and Right view) using OpenPose and FastPose for human body keypoint detection. The current study sets out to detect, recognize, classify and score different participants' movements. We achieved greater than 96% recognition accuracy of this dataset using the LSTM algorithm, and 91.01% using the ST-GCN algorithm.
{"title":"Applying Deep Learning and Computer Vision Techniques for an e-Sport and Smart Coaching System Using a Multiview Dataset: Case of Shotokan Karate","authors":"Fatima-Ezzahra Ait-Bennacer, A. Aaroud, K. Akodadi, B. Cherradi","doi":"10.3991/ijoe.v18i12.30893","DOIUrl":"https://doi.org/10.3991/ijoe.v18i12.30893","url":null,"abstract":"Smart coaching and e-sport platforms have shown a great interest in the recent research studies. Through this study, we aim to globalize the practice of sport, especially Shotokan Karate, by connecting participants and coaches on an international scale through the integration of Artificial Intelligence techniques such as computer vision and deep learning, to give the possibility of carrying out national and international virtual training courses without logistical constraints. The proposed work aims to apply the latest action detection, action recognition, and action classification methods for different Karate movements using the LSTM and the ST-GCN algorithms and proposes these movements in 3D using Video Inference for Human Body Pose and Shape Estimation (VIBE). Our proper Multiview Dataset contains pose estimations of a set of basic movements captured by a karate Shotokan expert (6th DAN Black Belt) from three views (Front view, Left view, and Right view) using OpenPose and FastPose for human body keypoint detection. The current study sets out to detect, recognize, classify and score different participants' movements. We achieved greater than 96% recognition accuracy of this dataset using the LSTM algorithm, and 91.01% using the ST-GCN algorithm.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"350 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124319575","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.32501
Priscilla Dinkar Moyya, Mythili Asaithambi
In this work, an attempt has been made to quantify the treatment response due to Neoadjuvant Chemotherapy (NACT) on the publicly available QIN-Breast of TCIA database (N = 25) using Gabor filter derived radiomic features. The Gabor filter bank is constructed using 5 different scales and 7 different orientations. Different radiomic features were extracted from Gabor filtered Dynamic Contrast Enhanced Magnetic Resonance images (DCE-MRI) of patients having 3 different visits (Visit 1: before, Visit 2: after 1st cycle, and Visit 3: the last cycle of NACT). The extracted radiomic features were analyzed statistically and Area Under Receiver Operating Characteristic (AUROC) has been calculated. Results show that the Gabor derived radiomic features could differentiate the pathological differences among all three visits. Energy has shown a significant difference between all the three orientations particularly between Visits 2 & 3. However, Entropy from λ=2 and θ=300 between Visit 2 & 3, Skewness from λ=2 and θ=1200 between Visit 1 & 3 could differentiate the treatment response with high statistical significance of p=0.006 and 0.001 respectively. From the ROC analysis, the better predictors were Short Run Emphasis (SRE), Short Zone Emphasis (SZE), and Energy between Visit 1 & 3 by achieving an AUROC of 76.38%, 75.16%, and 71.10% respectively. Further, the results suggest that the radiomic features are capable of quantitatively compare the breast NACT prognosis that varies across multi-oriented Gabor filters.
{"title":"Quantitative Analysis of Breast Cancer NACT Response on DCE-MRI Using Gabor Filter Derived Radiomic Features","authors":"Priscilla Dinkar Moyya, Mythili Asaithambi","doi":"10.3991/ijoe.v18i12.32501","DOIUrl":"https://doi.org/10.3991/ijoe.v18i12.32501","url":null,"abstract":"In this work, an attempt has been made to quantify the treatment response due to Neoadjuvant Chemotherapy (NACT) on the publicly available QIN-Breast of TCIA database (N = 25) using Gabor filter derived radiomic features. The Gabor filter bank is constructed using 5 different scales and 7 different orientations. Different radiomic features were extracted from Gabor filtered Dynamic Contrast Enhanced Magnetic Resonance images (DCE-MRI) of patients having 3 different visits (Visit 1: before, Visit 2: after 1st cycle, and Visit 3: the last cycle of NACT). The extracted radiomic features were analyzed statistically and Area Under Receiver Operating Characteristic (AUROC) has been calculated. Results show that the Gabor derived radiomic features could differentiate the pathological differences among all three visits. Energy has shown a significant difference between all the three orientations particularly between Visits 2 & 3. However, Entropy from λ=2 and θ=300 between Visit 2 & 3, Skewness from λ=2 and θ=1200 between Visit 1 & 3 could differentiate the treatment response with high statistical significance of p=0.006 and 0.001 respectively. From the ROC analysis, the better predictors were Short Run Emphasis (SRE), Short Zone Emphasis (SZE), and Energy between Visit 1 & 3 by achieving an AUROC of 76.38%, 75.16%, and 71.10% respectively. Further, the results suggest that the radiomic features are capable of quantitatively compare the breast NACT prognosis that varies across multi-oriented Gabor filters.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114669258","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.31535
Javier Arturo Gamboa Cruzado, Michelle Rojas-Morales, Jefferson López-Goycochea, Enrique Edgardo Condor Tinoco, Guillermo Paucar-Carlos, Anibal Sifuentes Damián
Everyday thousands of cardiac surgeries are performed worldwide. This article reviews numerous studies on the use of Convolutional Neural Networks and their impact on vascular surgery. The development of computer systems supported by convolutional neural networks that contribute to vascular surgeries represents an important deviation from traditional approaches to the performance of surgical interventions, either through computed tomography verification or the method in which a surgeon ceases to participate in this type of surgical interventions. A systematic literature review (SLR) regarding convolutional neural networks for use in vascular surgeries was conducted for research from 2016 to 2021. The search strategy identified 15,505 papers from various search sources such as ACM Digital Library, EBSCOhost, Google Scholar, IEEE Xplore, MDPI, Microsoft Academic, ProQuest, ScienceDirect, Scopus, Springer, Web of Science, and Wiley Online Library, from which only 70 papers were considered (selected) based on exclusion criteria. The SLR focused on recent studies on convolutional neural networks where their use in vascular surgeries has been identified. This SLR provides readers with a mapping of all identified findings, making a comparison by relevance in regard to their own settings and possible scenarios. Therefore, it is hoped that this research will help other researchers to understand the current status of Convolutional Neural Networks and their application in Vascular Surgeries.
每天全世界都要进行成千上万的心脏手术。本文综述了卷积神经网络的应用及其在血管手术中的影响。由卷积神经网络支持的计算机系统的发展有助于血管手术，这代表了传统的手术干预方法的重要偏离，无论是通过计算机断层扫描验证还是外科医生停止参与这种类型的手术干预的方法。2016 - 2021年对卷积神经网络在血管手术中的应用进行了系统文献综述(SLR)。检索策略从ACM Digital Library、EBSCOhost、Google Scholar、IEEE Xplore、MDPI、Microsoft Academic、ProQuest、ScienceDirect、Scopus、Springer、Web of Science和Wiley Online Library等各种检索源中确定了15505篇论文，其中根据排除标准只有70篇论文被考虑(选择)。SLR关注卷积神经网络的最新研究，其中卷积神经网络在血管手术中的应用已经确定。这台单反相机为读者提供了所有已识别的发现的地图，根据他们自己的设置和可能的情况，通过相关性进行比较。因此，希望本研究能够帮助其他研究者了解卷积神经网络的现状及其在血管外科中的应用。
{"title":"Systematic Literature Review on Convolutional Neural Networks for Vascular Surgeries","authors":"Javier Arturo Gamboa Cruzado, Michelle Rojas-Morales, Jefferson López-Goycochea, Enrique Edgardo Condor Tinoco, Guillermo Paucar-Carlos, Anibal Sifuentes Damián","doi":"10.3991/ijoe.v18i12.31535","DOIUrl":"https://doi.org/10.3991/ijoe.v18i12.31535","url":null,"abstract":"Everyday thousands of cardiac surgeries are performed worldwide. This article reviews numerous studies on the use of Convolutional Neural Networks and their impact on vascular surgery. The development of computer systems supported by convolutional neural networks that contribute to vascular surgeries represents an important deviation from traditional approaches to the performance of surgical interventions, either through computed tomography verification or the method in which a surgeon ceases to participate in this type of surgical interventions. A systematic literature review (SLR) regarding convolutional neural networks for use in vascular surgeries was conducted for research from 2016 to 2021. The search strategy identified 15,505 papers from various search sources such as ACM Digital Library, EBSCOhost, Google Scholar, IEEE Xplore, MDPI, Microsoft Academic, ProQuest, ScienceDirect, Scopus, Springer, Web of Science, and Wiley Online Library, from which only 70 papers were considered (selected) based on exclusion criteria. The SLR focused on recent studies on convolutional neural networks where their use in vascular surgeries has been identified. This SLR provides readers with a mapping of all identified findings, making a comparison by relevance in regard to their own settings and possible scenarios. Therefore, it is hoped that this research will help other researchers to understand the current status of Convolutional Neural Networks and their application in Vascular Surgeries.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129353983","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.32409
V. Ďuriš, Lidia N. Vasileva, S. Chumarov, T. Lengyelfalusy
The problem of improving the educational process of students of scientific, technical and natural science areas of training is one of the relevant aspects of modern pedagogical research. During training, it is necessary to apply new approaches, educational technologies and techniques in order to prepare graduates who are able to independently solve complex scientific, technical and engineering design tasks in the process of modern production. Programming is a universal tool for modeling objects and processes, as well as a powerful tool in developing the thinking of students of scientific, technical and natural science fields of training. The article discusses the issues of formation of programming skills of students based on the use of the Arduino platform. The professional standards are analyzed, the main contradictions of the existing system of training future bachelors in the field of radio electronics and control systems are revealed. The method of organizing effective programming training based on the use of the Arduino platform is presented. The criteria and indicators of the levels of competence formation are given. The results of an experiment on the implementation of the described methodology of teaching programming on the basis of the I.N. Ulyanov Chuvash State University are shown. Using the chi-square criterion, statistical processing of the results of a pedagogical experiment was performed, which convincingly proves that when using the Arduino platform, most students have reached high and advanced levels of programming skills formation.
{"title":"Formation of Programming Skills among Students of Scientific, Technical and Natural Science Areas of Training Using the Arduino Platform","authors":"V. Ďuriš, Lidia N. Vasileva, S. Chumarov, T. Lengyelfalusy","doi":"10.3991/ijoe.v18i12.32409","DOIUrl":"https://doi.org/10.3991/ijoe.v18i12.32409","url":null,"abstract":"The problem of improving the educational process of students of scientific, technical and natural science areas of training is one of the relevant aspects of modern pedagogical research. During training, it is necessary to apply new approaches, educational technologies and techniques in order to prepare graduates who are able to independently solve complex scientific, technical and engineering design tasks in the process of modern production. Programming is a universal tool for modeling objects and processes, as well as a powerful tool in developing the thinking of students of scientific, technical and natural science fields of training. The article discusses the issues of formation of programming skills of students based on the use of the Arduino platform. The professional standards are analyzed, the main contradictions of the existing system of training future bachelors in the field of radio electronics and control systems are revealed. The method of organizing effective programming training based on the use of the Arduino platform is presented. The criteria and indicators of the levels of competence formation are given. The results of an experiment on the implementation of the described methodology of teaching programming on the basis of the I.N. Ulyanov Chuvash State University are shown. Using the chi-square criterion, statistical processing of the results of a pedagogical experiment was performed, which convincingly proves that when using the Arduino platform, most students have reached high and advanced levels of programming skills formation.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114755688","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.33817
H. Alrikabi, H. Hazim
This research is aimed at planning the manner in which the secure 5G communication can be controlled based on traffic floods. To accomplish excellent administration execution of organization observing and 5G directing calculation is inescapable, dynamic steering in actual organization equipment isn't reasonable for practical plans of action. Accordingly, to bring down functional and capital consumption, we propose a strategy called versatile steering made do with the help of 5G (Quality of Service and MANET (Mobile specially appointed Network). A practical 5G steering model which will help with fulfilling the needs of the customers and simultaneously gives huge investment funds in item cost and convenience was presented in this paper. To perform versatile 5G steering, we planned geography in a virtualized climate. We customized CHAOS for network traffic flood the board which goes about as a consistent northward API in 5G directing. Network traffic is infused dynamically from 1MB up to 10MB (connect b/w) in a progressive way for similar organization traffic with 10 organization occurrences. In conclusion, we performed versatile 5G steering applying the control hypothetical method with the assistance of CHAOS and MANET calculations. By looking at two directing situations, we noticed a prominent distinction in throughput for controlling organization traffic application in MANETs. Network traffic flood data is refreshed after clockwork.
{"title":"Secure Chaos of 5G Wireless Communication System Based on IOT Applications","authors":"H. Alrikabi, H. Hazim","doi":"10.3991/ijoe.v18i12.33817","DOIUrl":"https://doi.org/10.3991/ijoe.v18i12.33817","url":null,"abstract":"This research is aimed at planning the manner in which the secure 5G communication can be controlled based on traffic floods. To accomplish excellent administration execution of organization observing and 5G directing calculation is inescapable, dynamic steering in actual organization equipment isn't reasonable for practical plans of action. Accordingly, to bring down functional and capital consumption, we propose a strategy called versatile steering made do with the help of 5G (Quality of Service and MANET (Mobile specially appointed Network). A practical 5G steering model which will help with fulfilling the needs of the customers and simultaneously gives huge investment funds in item cost and convenience was presented in this paper. To perform versatile 5G steering, we planned geography in a virtualized climate. We customized CHAOS for network traffic flood the board which goes about as a consistent northward API in 5G directing. Network traffic is infused dynamically from 1MB up to 10MB (connect b/w) in a progressive way for similar organization traffic with 10 organization occurrences. In conclusion, we performed versatile 5G steering applying the control hypothetical method with the assistance of CHAOS and MANET calculations. By looking at two directing situations, we noticed a prominent distinction in throughput for controlling organization traffic application in MANETs. Network traffic flood data is refreshed after clockwork.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131035383","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.30743
Adil Hamamous, N. Benjelloun
In this paper, we are interested in the study of the use of the Electronics Workbench (EWB) simulator in the study of amplitude modulation and demodulation. We conducted a study with 50 Moroccan students in the second year of the scientific baccalaureate option physical sciences at the high school Abdellah Laroui of the city of Fez. Using the pre-test and post-test methodology with an experimental group (25 students) and a control group (25 students). The results of the two groups are analyzed using the student t-test. The results obtained in the post-test show that the average of the test administered to both groups, control (MG-Con) and experimental (MG-Exp), found a non-significant difference (MG-Exp - MG-Con = 15,36- 15,08 = 0,28 > 0. In addition, using interviews, we asked students and teachers to give their opinions on questions about the use of the Electronics Workbench (EWB) simulator in learning. The results obtained show that the laboratory experiments cannot replace the simulator (EWB) which can be used as an alternative pedagogical means to help students understand the concepts in electricity.
{"title":"The Added Value of Integrating the Electronics Workbench Simulator in the Teaching of Electrical Concepts to Moroccan High School Students","authors":"Adil Hamamous, N. Benjelloun","doi":"10.3991/ijoe.v18i12.30743","DOIUrl":"https://doi.org/10.3991/ijoe.v18i12.30743","url":null,"abstract":"In this paper, we are interested in the study of the use of the Electronics Workbench (EWB) simulator in the study of amplitude modulation and demodulation. We conducted a study with 50 Moroccan students in the second year of the scientific baccalaureate option physical sciences at the high school Abdellah Laroui of the city of Fez. Using the pre-test and post-test methodology with an experimental group (25 students) and a control group (25 students). The results of the two groups are analyzed using the student t-test. The results obtained in the post-test show that the average of the test administered to both groups, control (MG-Con) and experimental (MG-Exp), found a non-significant difference (MG-Exp - MG-Con = 15,36- 15,08 = 0,28 > 0. In addition, using interviews, we asked students and teachers to give their opinions on questions about the use of the Electronics Workbench (EWB) simulator in learning. The results obtained show that the laboratory experiments cannot replace the simulator (EWB) which can be used as an alternative pedagogical means to help students understand the concepts in electricity.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114464751","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.31877
Govind Maniam, J. Sampe, R. Jaafar, A. A. Hamzah, N. M. Zin
Rapid transmission of the coronavirus disease via droplets and particles has led to a global pandemic. Expeditious detection of SARS-Cov-2 RNA in the environment is attainable by using Bio-FET sensors. This work proposes a Bio-FET sensor interface module with IoT implementation to amplify signals from a Bio-FET for SARS-Cov-2 detection and monitoring. The sensor interface module was programmed to read the signals using a micro-controller and process information to determine the presence of SARS-Cov-2. The proposed Bio-FET sensor interface module was also set to transmit data to the Cloud via W-Fi to be stored and displayed on a dashboard. The prototype Bio-FET sensor interface module was simulated in PSpice for signal amplification, and hardware implementation has been done by using low-cost components for data transmission to the Cloud. The hardware consists of an AD620 instrumentation amplifier module, voltage sensor module, Neo-6m GPS sensor module, an OLED display, and an ESP8266-32 bit micro-controller. The results of both the simulation and the hardware implementation are similar. The emulated negative and positive Bio-FET signal outputs were successfully amplified from 15.9mV and 45.8mV to 1.59V and 4.58V, respectively, using an AD620 instrumentation amplifier. The gathered location, time, date, output voltage, and SARS-Cov-2 presence results were successfully stored and displayed on the Cloud dashboard.
{"title":"Bio-FET Sensor Interface Module for COVID-19 Monitoring Using IoT","authors":"Govind Maniam, J. Sampe, R. Jaafar, A. A. Hamzah, N. M. Zin","doi":"10.3991/ijoe.v18i12.31877","DOIUrl":"https://doi.org/10.3991/ijoe.v18i12.31877","url":null,"abstract":"Rapid transmission of the coronavirus disease via droplets and particles has led to a global pandemic. Expeditious detection of SARS-Cov-2 RNA in the environment is attainable by using Bio-FET sensors. This work proposes a Bio-FET sensor interface module with IoT implementation to amplify signals from a Bio-FET for SARS-Cov-2 detection and monitoring. The sensor interface module was programmed to read the signals using a micro-controller and process information to determine the presence of SARS-Cov-2. The proposed Bio-FET sensor interface module was also set to transmit data to the Cloud via W-Fi to be stored and displayed on a dashboard. The prototype Bio-FET sensor interface module was simulated in PSpice for signal amplification, and hardware implementation has been done by using low-cost components for data transmission to the Cloud. The hardware consists of an AD620 instrumentation amplifier module, voltage sensor module, Neo-6m GPS sensor module, an OLED display, and an ESP8266-32 bit micro-controller. The results of both the simulation and the hardware implementation are similar. The emulated negative and positive Bio-FET signal outputs were successfully amplified from 15.9mV and 45.8mV to 1.59V and 4.58V, respectively, using an AD620 instrumentation amplifier. The gathered location, time, date, output voltage, and SARS-Cov-2 presence results were successfully stored and displayed on the Cloud dashboard. ","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133921577","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}
Pub Date : 2022-09-14DOI: 10.3991/ijoe.v18i12.33515
A. Y. Al-Zoubi, M. Dmour, R. Aldmour
Remote laboratories have been developed at many universities worldwide to provide students with access to apparatus and experiments via the Internet around the clock, thus giving partner institutions the opportunity to share resources, expensive equipment and specialized laboratories, whether within a single country or at regional and international levels. Universities usually implement learning management systems (LMS) such as Moodle and Blackboard to enable students to interact, carry out learning activities and access remote labs. However, remote labs generate enormous amounts of data, which is stored, processed, analyzed, and accessed using centralized systems that lack transparency, traceability, security features, trustworthiness, and reliability. In addition, they are vulnerable to the single point of failure problem due to centralization. The application of blockchain technology in remote labs is proposed as a promising solution for future online learning as it combines a new pedagogical approach with various state-of-the-art technologies in an era that embraces Education 4.0 as the education norm. Furthermore, a novel blockchain-based framework for remote labs allows data streaming and transfer in a decentralized, transparent, traceable, reliable, secure, and trustful manner, where only authorized peers can join or access the network, thereby providing privacy of students’ data files and reports. An initial pilot of an Ethereum-based remote lab show promising result for effective management of online experiments, originally hosted in a Moodle LMS.
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