Pub Date : 2022-08-06DOI: 10.11113/humentech.v1n2.26
Ahmed Jamah Ahmed Alnagrat
Today, learning environments (LEs) are proceeding towards virtual environments (VEs) in which a sense of reality can be presented in three dimensions (3D) and a sense of inclusion can be experienced. A virtual learning environment (VLE) can be presented in a more realistic and visual manner with the use of innovative technologies such as virtual reality (VR), mixed reality (MR), and augmented reality(AR). This paper examines how extended reality (XR) approaches and its applications are transforming virtual learning environments in the context of human education and learning. A systematic literature review from the Scopus, Web of Science, IEEE, ACM and Google Scholar databases was conducted in order to better understand XR's contributions to human education as well as learning.The potential uses of XR technology have been discussed in terms of its structure, past, present, and future directions of XR concerning education.The research conducted in this context has determined that XR is mostly being used in fields of education, learninig and simulating an emergency situation. XR technology can be applied to solve problems without causing harm to people or property, particularly in emergency scenarios and safety training. Finally, this study offer several novel approaches for addressing these challenges, as well as potential directions for future researchers seeking to specialize in using these emerging technologies for human education.
今天，学习环境(LEs)正在向虚拟环境(VEs)发展，在虚拟环境中，真实感可以在三维(3D)中呈现，并且可以体验到包容感。通过使用虚拟现实(VR)、混合现实(MR)和增强现实(AR)等创新技术，虚拟学习环境(VLE)可以以更加逼真和可视化的方式呈现。本文探讨了扩展现实(XR)方法及其应用如何在人类教育和学习的背景下改变虚拟学习环境。为了更好地了解XR对人类教育和学习的贡献，我们对Scopus、Web of Science、IEEE、ACM和Google Scholar数据库进行了系统的文献综述。从XR技术的结构、过去、现在和未来在教育方面的发展方向等方面讨论了XR技术的潜在用途。在此背景下进行的研究已经确定，XR主要用于教育、学习和模拟紧急情况等领域。XR技术可用于解决问题，而不会对人员或财产造成伤害，特别是在紧急情况和安全培训中。最后，本研究提供了一些解决这些挑战的新方法，以及未来研究人员寻求专门利用这些新兴技术进行人类教育的潜在方向。
{"title":"Virtual Transformations in Human Learning Environment: An Extended Reality Approach","authors":"Ahmed Jamah Ahmed Alnagrat","doi":"10.11113/humentech.v1n2.26","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.26","url":null,"abstract":"Today, learning environments (LEs) are proceeding towards virtual environments (VEs) in which a sense of reality can be presented in three dimensions (3D) and a sense of inclusion can be experienced. A virtual learning environment (VLE) can be presented in a more realistic and visual manner with the use of innovative technologies such as virtual reality (VR), mixed reality (MR), and augmented reality(AR). This paper examines how extended reality (XR) approaches and its applications are transforming virtual learning environments in the context of human education and learning. A systematic literature review from the Scopus, Web of Science, IEEE, ACM and Google Scholar databases was conducted in order to better understand XR's contributions to human education as well as learning.The potential uses of XR technology have been discussed in terms of its structure, past, present, and future directions of XR concerning education.The research conducted in this context has determined that XR is mostly being used in fields of education, learninig and simulating an emergency situation. XR technology can be applied to solve problems without causing harm to people or property, particularly in emergency scenarios and safety training. Finally, this study offer several novel approaches for addressing these challenges, as well as potential directions for future researchers seeking to specialize in using these emerging technologies for human education.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130839055","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 : 2022-08-06DOI: 10.11113/humentech.v1n2.17
Zhi Ni Tee, D. N. Abang Zaidel, Y. M. Mohd Jusoh, I. Muhamad, Z. Hashim
Encapsulation is the packaging of bioactive compounds to isolate and control their release upon applying specific conditions. By using inulin as the wall material for milk protein encapsulation, it can improve the stability and reduce the rate of protein release which can be related to better digestibility. This study aims to find the best encapsulation parameters for milk protein encapsulation using inulin based on the encapsulation efficiency and evaluate the protein release by simulation of intestinal fluid in vitro. Protein encapsulation was prepared under various parameters including inulin concentration, stirring temperature and stirring speed. The encapsulation parameters were analysed by Response Surface Methodology to obtain the highest encapsulation efficiency, which was subsequently used for the analysis of particle size, zeta potential and protein release kinetics. The results showed that inulin concentration was the most significant in determining encapsulation efficiency, and the highest encapsulation efficiency (75.90%) was achieved at 0.47 % w/v of inulin concentration, stirring temperature of 35.17°C and stirring speed of 510.79 rpm. The inulin-encapsulated milk protein produced under the best encapsulation parameters had an average particle size value of 485.8 nm and zeta potential of -10.5 mV. Zero order kinetics model was most suited to describe the encapsulated milk protein release, indicating slow release of protein that may be associated with better digestibility.
{"title":"Encapsulation of Milk Protein with Inulin for Improved Digestibility","authors":"Zhi Ni Tee, D. N. Abang Zaidel, Y. M. Mohd Jusoh, I. Muhamad, Z. Hashim","doi":"10.11113/humentech.v1n2.17","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.17","url":null,"abstract":"Encapsulation is the packaging of bioactive compounds to isolate and control their release upon applying specific conditions. By using inulin as the wall material for milk protein encapsulation, it can improve the stability and reduce the rate of protein release which can be related to better digestibility. This study aims to find the best encapsulation parameters for milk protein encapsulation using inulin based on the encapsulation efficiency and evaluate the protein release by simulation of intestinal fluid in vitro. Protein encapsulation was prepared under various parameters including inulin concentration, stirring temperature and stirring speed. The encapsulation parameters were analysed by Response Surface Methodology to obtain the highest encapsulation efficiency, which was subsequently used for the analysis of particle size, zeta potential and protein release kinetics. The results showed that inulin concentration was the most significant in determining encapsulation efficiency, and the highest encapsulation efficiency (75.90%) was achieved at 0.47 % w/v of inulin concentration, stirring temperature of 35.17°C and stirring speed of 510.79 rpm. The inulin-encapsulated milk protein produced under the best encapsulation parameters had an average particle size value of 485.8 nm and zeta potential of -10.5 mV. Zero order kinetics model was most suited to describe the encapsulated milk protein release, indicating slow release of protein that may be associated with better digestibility.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129010590","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 : 2022-08-06DOI: 10.11113/humentech.v1n2.16
Mira Panadi, K. Mat, N. Rusli, Nur Fadilah Darmansah
The demand for food consumption had increased by 60% due to the increase of human population, resulting in an increasing demand for sheep meat. High cost of imported feed had restricted the growth of the sheep industry. Hence, the objective of this study was to evaluate the cost-effectiveness of feeding total mixed ration (TMR) in the form of creep feed (CF) and growing ration (GR) to Dorper lambs compared to the control (CON) group fed with farm routine diet consisted of Napier grass and commercial pellet. Two (2) experimental phases were conducted, i.e., Phase I (CF) and Phase II (GR), which consisted of twenty (20) Dorper lambs with five (5) lambs in each group. The CF and GR consisted of constant metabolize energy (ME) (11 MJ/kg DM ME). The crude protein (CP) (%) in CF was varied at 14, 16, 18 and 20 for CON 14, CF 16, CF 18 and CF 20 respectively, whereas the CP (%) in GR was varied at 11, 14, 16 and 18 for CON 11, GR 14, GR 16 and GR 18 respectively. The cost of feed/kg gain (RM/kg) of CON 14 (1.63) and CF 18 (1.97) was significantly lowered (p<0.05) than CF 20 (3.35) whereas, GR 16 (8.94) was significantly lowered (p<0.05) than CON 11 (22.92) and GR 18 (23.99). This finding revealed that feeding local feed ingredients in TMR form, resulting in low feeding cost and subsequently higher economic returns. It can be concluded that feeding 18% CP (CF 18) and 16% CP (GR 16) were efficient to enhance the growth performance of pre-and post-weaning Dorper lambs respectively.
{"title":"Cost-effectiveness of Total Mixed Ration with Varying Crude Protein Levels for Feeding Dorper Lambs for Human Consumption","authors":"Mira Panadi, K. Mat, N. Rusli, Nur Fadilah Darmansah","doi":"10.11113/humentech.v1n2.16","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.16","url":null,"abstract":"The demand for food consumption had increased by 60% due to the increase of human population, resulting in an increasing demand for sheep meat. High cost of imported feed had restricted the growth of the sheep industry. Hence, the objective of this study was to evaluate the cost-effectiveness of feeding total mixed ration (TMR) in the form of creep feed (CF) and growing ration (GR) to Dorper lambs compared to the control (CON) group fed with farm routine diet consisted of Napier grass and commercial pellet. Two (2) experimental phases were conducted, i.e., Phase I (CF) and Phase II (GR), which consisted of twenty (20) Dorper lambs with five (5) lambs in each group. The CF and GR consisted of constant metabolize energy (ME) (11 MJ/kg DM ME). The crude protein (CP) (%) in CF was varied at 14, 16, 18 and 20 for CON 14, CF 16, CF 18 and CF 20 respectively, whereas the CP (%) in GR was varied at 11, 14, 16 and 18 for CON 11, GR 14, GR 16 and GR 18 respectively. The cost of feed/kg gain (RM/kg) of CON 14 (1.63) and CF 18 (1.97) was significantly lowered (p<0.05) than CF 20 (3.35) whereas, GR 16 (8.94) was significantly lowered (p<0.05) than CON 11 (22.92) and GR 18 (23.99). This finding revealed that feeding local feed ingredients in TMR form, resulting in low feeding cost and subsequently higher economic returns. It can be concluded that feeding 18% CP (CF 18) and 16% CP (GR 16) were efficient to enhance the growth performance of pre-and post-weaning Dorper lambs respectively.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114091703","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 : 2022-08-06DOI: 10.11113/humentech.v1n2.19
Husnir Nasyuha Abdul Halim, A. Azaman, I. Zulkapri
Osteoarthritis (OA) is the most common type of arthritis affecting approximately 240 million people globally, with increasing prevalence with age. The knee is the most prevalent joint affected by OA and it causes physical disability and decreased motor function which consequently affects the activity of daily living including mobility. Pain is the main symptom that is characterized in OA, which is measured using self-rated scales or questionnaires to determine several aspects of the pain including the intensity, frequency, and pattern. Quantifying pain is a standard clinical practice to diagnose and monitor symptomatic OA, however, its application for severity assessment is not well explored. To date, the severity assessment of knee OA is only by radiographic severity assessment that does not necessarily reflect the symptomatic OA. In this study, gait analysis was performed on symptomatic knee OA patients. Distinctive gait kinematic features were extracted using principal component analysis (PCA). Pain score and the gait features including spatiotemporal and kinematics were used for clustering analysis. Two clustering algorithms, K-means and K-medoids were conducted to cluster samples with similar features to assess knee OA characterization. The clustering solutions were evaluated based on three measures which are the Davies Bouldin index, Calinzki Harabasz index, and Silhouette index. This study discovered that majority of the datasets which is 5 out of 9 datasets had the best performance (fulfill at least 2 out of 3 performance index criteria) when the number of clusters, k is 4 and using the k-means algorithm. These clustering models can be used in the future as the labeling class of symptomatic knee OA that is based on pain and gait characteristics of knee OA. Future studies are suggested to test other pain assessment scores, include other gait features such as kinetic and muscle activity features, and employ various types of feature selection methods to improve the clustering performance.
{"title":"Cluster Analysis of Biomechanical Gait Data and Pain Score as a Potential Classification of Severity in Knee Osteoarthritis","authors":"Husnir Nasyuha Abdul Halim, A. Azaman, I. Zulkapri","doi":"10.11113/humentech.v1n2.19","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.19","url":null,"abstract":"Osteoarthritis (OA) is the most common type of arthritis affecting approximately 240 million people globally, with increasing prevalence with age. The knee is the most prevalent joint affected by OA and it causes physical disability and decreased motor function which consequently affects the activity of daily living including mobility. Pain is the main symptom that is characterized in OA, which is measured using self-rated scales or questionnaires to determine several aspects of the pain including the intensity, frequency, and pattern. Quantifying pain is a standard clinical practice to diagnose and monitor symptomatic OA, however, its application for severity assessment is not well explored. To date, the severity assessment of knee OA is only by radiographic severity assessment that does not necessarily reflect the symptomatic OA. In this study, gait analysis was performed on symptomatic knee OA patients. Distinctive gait kinematic features were extracted using principal component analysis (PCA). Pain score and the gait features including spatiotemporal and kinematics were used for clustering analysis. Two clustering algorithms, K-means and K-medoids were conducted to cluster samples with similar features to assess knee OA characterization. The clustering solutions were evaluated based on three measures which are the Davies Bouldin index, Calinzki Harabasz index, and Silhouette index. This study discovered that majority of the datasets which is 5 out of 9 datasets had the best performance (fulfill at least 2 out of 3 performance index criteria) when the number of clusters, k is 4 and using the k-means algorithm. These clustering models can be used in the future as the labeling class of symptomatic knee OA that is based on pain and gait characteristics of knee OA. Future studies are suggested to test other pain assessment scores, include other gait features such as kinetic and muscle activity features, and employ various types of feature selection methods to improve the clustering performance.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130668226","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 : 2022-08-06DOI: 10.11113/humentech.v1n2.30
Voon Hueh Goh, M. A. Ayob, Nurul Izzati Darul Zaman, Y. Hau
Cardiovascular disease (CVD) is a heart related disease and is the top silent killer in worldwide. Frequent electrocardiogram (ECG) monitoring for patients with CVD is vital to check if arrhythmia occurs. Though there are lots of commercialized portable ECG monitoring device available, many of them are dedicated to professional clinical staff with complex user interface, or only targeted to specific arrhythmia for home monitoring with lack of data management system. In this study, an in-house developed ECG monitoring device was integrated with an Android-based mobile application through Bluetooth wireless communication and implements Google Cloud Technology. The Android-based mobile app supports main features of real-time ECG graph display, automated location detector, data management system and simple arrhythmia detection. The ECG graph displays acquired ECG signal in real-time by in-house ECG acquisition unit through Bluetooth wireless communication and stored as text files in phone’s local memory. Firebase Authentication and Firebase Storage based on Google Cloud technology are implemented for data management system development. This allows users and administrators to upload or access data securely through online Google Cloud Platform. Three types of heart rhythm, namely normal sinus rhythm, bradycardia and tachycardia can be classified based on heart rate analysis. Smartphone’s location service is enabled to allow user shares their location with caretaker in emergency case. The final solution utilizes the Internet-of-Things (IoT) technology to facilitate heart disease management towards telemedicine applications.
{"title":"Mobile Electrocardiogram Monitoring System with Cloud-Based Approach","authors":"Voon Hueh Goh, M. A. Ayob, Nurul Izzati Darul Zaman, Y. Hau","doi":"10.11113/humentech.v1n2.30","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.30","url":null,"abstract":"Cardiovascular disease (CVD) is a heart related disease and is the top silent killer in worldwide. Frequent electrocardiogram (ECG) monitoring for patients with CVD is vital to check if arrhythmia occurs. Though there are lots of commercialized portable ECG monitoring device available, many of them are dedicated to professional clinical staff with complex user interface, or only targeted to specific arrhythmia for home monitoring with lack of data management system. In this study, an in-house developed ECG monitoring device was integrated with an Android-based mobile application through Bluetooth wireless communication and implements Google Cloud Technology. The Android-based mobile app supports main features of real-time ECG graph display, automated location detector, data management system and simple arrhythmia detection. The ECG graph displays acquired ECG signal in real-time by in-house ECG acquisition unit through Bluetooth wireless communication and stored as text files in phone’s local memory. Firebase Authentication and Firebase Storage based on Google Cloud technology are implemented for data management system development. This allows users and administrators to upload or access data securely through online Google Cloud Platform. Three types of heart rhythm, namely normal sinus rhythm, bradycardia and tachycardia can be classified based on heart rate analysis. Smartphone’s location service is enabled to allow user shares their location with caretaker in emergency case. The final solution utilizes the Internet-of-Things (IoT) technology to facilitate heart disease management towards telemedicine applications.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"3 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114043589","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 : 2022-08-06DOI: 10.11113/humentech.v1n2.21
Ahmed Jamah Ahmed Alnagrat, R. Ismail, Syed Zulkarnain Syed Idrus
Extended Reality (XR) technologies can play a significant role in proving huge value to education following the changed circumstances universities faced during pandemic. This study presents Virtual Reality (VR) as a means of enhancing learning in education and training field during outbreak. This paper represents the use of XR technologies in a wide variety of settings, including the context of the education, learning, and training. Considering the most significant papers with a total of 2,270 articles from conferences and journals were obtained through online search was conducted from databases such as Google Scholar, Scopus, Web of Science (WoS), IEEE Xplore, ACM Digital Library, Springer Link, Research Gate, and Academia. The number of papers released, and the number of references obtained in both databases have a substantial-high influence. Researchers performing literature searches using bibliographic databases as their initial and dominant resource to customized and filtered sort out the most relevant publications examined based on abstract and key words such as Extended reality, Virtual reality, VR training, COVID-19, Distance education, Virtual environments, Education, Virtual Laboratories. According to the findings, XR equips students to gain professional skills to their subject as well as to increase the performance of learning quality and improve training.
随着大学在大流行期间面临的环境变化，扩展现实(XR)技术可以在证明教育的巨大价值方面发挥重要作用。本研究将虚拟现实技术(VR)作为疫情期间加强教育培训领域学习的一种手段。本文介绍了XR技术在各种环境中的应用，包括教育、学习和培训环境。通过Google Scholar、Scopus、Web of Science (WoS)、IEEE Xplore、ACM Digital Library、Springer Link、Research Gate和Academia等数据库进行在线检索，获得了最重要的论文，共计2270篇来自会议和期刊的文章。在两个数据库中发表的论文数量和获得的参考文献数量具有相当高的影响。研究人员利用文献数据库作为初始和主导资源进行文献检索，根据扩展现实、虚拟现实、VR培训、COVID-19、远程教育、虚拟环境、教育、虚拟实验室等摘要和关键词，定制和过滤整理出最相关的文献。根据研究结果，XR使学生获得专业技能，并提高学习质量和改进培训的表现。
{"title":"The Significant and Challenges of Extended Reality Technologies in Learning and Training during Covid-19 Pandemic","authors":"Ahmed Jamah Ahmed Alnagrat, R. Ismail, Syed Zulkarnain Syed Idrus","doi":"10.11113/humentech.v1n2.21","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.21","url":null,"abstract":"Extended Reality (XR) technologies can play a significant role in proving huge value to education following the changed circumstances universities faced during pandemic. This study presents Virtual Reality (VR) as a means of enhancing learning in education and training field during outbreak. This paper represents the use of XR technologies in a wide variety of settings, including the context of the education, learning, and training. Considering the most significant papers with a total of 2,270 articles from conferences and journals were obtained through online search was conducted from databases such as Google Scholar, Scopus, Web of Science (WoS), IEEE Xplore, ACM Digital Library, Springer Link, Research Gate, and Academia. The number of papers released, and the number of references obtained in both databases have a substantial-high influence. Researchers performing literature searches using bibliographic databases as their initial and dominant resource to customized and filtered sort out the most relevant publications examined based on abstract and key words such as Extended reality, Virtual reality, VR training, COVID-19, Distance education, Virtual environments, Education, Virtual Laboratories. According to the findings, XR equips students to gain professional skills to their subject as well as to increase the performance of learning quality and improve training.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114613408","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 : 2022-08-06DOI: 10.11113/humentech.v1n2.20
Jia Eek Ong, M. A. As’ari
COVID-19 originated in Wuhan, China, in December 2019 and quickly became a global outbreak in January 2020. COVID-19 is a disease caused by SARS-CoV-2, which is a human transmission disease. Since it is a human transmission disease, thus mass gathering in public is not allowed to prevent the possible spread of COVID-19. However, the current monitoring technology, such as closed-circuit television (CCTV), only cover a limited area of the public and lack of mobility. Image classification is one of the approaches that can detect crowds in an image and can be done through either machine learning or deep learning approach. Recently, deep learning, especially convolutional neural networks (CNNs) outperform classical machine learning in image classification and the common approach for modelling CNN is through transfer learning. Thus, this study aims to develop a convolutional neural network that can detect illegal crowd gathering from offline drone view images through image classification using the transfer learning technique. Several models are used to train on the same dataset obtained, and the all-model performance is evaluated through a confusion matrix. Based on performance analysis, it shows that the ResNet50 model outperforms the VGG16 model and InceptionV3 model by achieving 95% test accuracy, 95% precision, 95% recall and 95% F1-score. In conclusion, it can be concluded that the deep learning approach uses a pre-trained convolutional neural network that can be used to classify object images in this study.
{"title":"Drone Image Based Illegal Crowd Detection For Covid-19 Disease Prevention Via Convolutional Neural Networks (CNNs) Transfer Learning","authors":"Jia Eek Ong, M. A. As’ari","doi":"10.11113/humentech.v1n2.20","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.20","url":null,"abstract":"COVID-19 originated in Wuhan, China, in December 2019 and quickly became a global outbreak in January 2020. COVID-19 is a disease caused by SARS-CoV-2, which is a human transmission disease. Since it is a human transmission disease, thus mass gathering in public is not allowed to prevent the possible spread of COVID-19. However, the current monitoring technology, such as closed-circuit television (CCTV), only cover a limited area of the public and lack of mobility. Image classification is one of the approaches that can detect crowds in an image and can be done through either machine learning or deep learning approach. Recently, deep learning, especially convolutional neural networks (CNNs) outperform classical machine learning in image classification and the common approach for modelling CNN is through transfer learning. Thus, this study aims to develop a convolutional neural network that can detect illegal crowd gathering from offline drone view images through image classification using the transfer learning technique. Several models are used to train on the same dataset obtained, and the all-model performance is evaluated through a confusion matrix. Based on performance analysis, it shows that the ResNet50 model outperforms the VGG16 model and InceptionV3 model by achieving 95% test accuracy, 95% precision, 95% recall and 95% F1-score. In conclusion, it can be concluded that the deep learning approach uses a pre-trained convolutional neural network that can be used to classify object images in this study.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128236335","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 : 2022-08-06DOI: 10.11113/humentech.v1n2.27
A. Alnagrat, Rizalafande Che Ismail, Syed Zulkarnain Syed Idrus, Rawad Mansour Abdulhafith Alfaqi
Nowadays technology development in real life will reflect on education inexorably. Today, the concept of Extended Reality (XR) technologies (XRs), such as virtual reality (VR), augmented reality (AR), and mixed reality (MR), as very promising technological tools for education. The purpose of these technologies is to facilitate human life. In this context, educational technologies create new opportunities for students and teachers every day especially in education field. With various virtual environments (VE) and imaging systems, content that needs to be learned can be presented independently of school and classrooms in a low-cost and safe environment. As a result, teachers can create their own content with various applications, providing them with freedom of flexibility, and creativity. In this context, it is seen that XR has started to be used in various fields in education. When these fields and subjects are examined, it is observed that there is a concentration in the fields of education. The purpose of this narrative review is to describe the accelerators of XR (VR, AR, MR) technology in education settings. This literature review was conducted by conducting a systematic search of relevant articles and literature reviews through the university's online library, Google Scholar, Web of Science, IEEE Xplore, and the ACM Digital Library. In this paper, the authors demonstrate the main components of XR technology in the educational process. A comprehensive review of XR technology including education, and learning was provided. The authors identify limitations and conclude with future work of XR in educational uses.
如今，现实生活中的技术发展将不可避免地反映在教育上。今天，扩展现实(XR)技术(XR)的概念，如虚拟现实(VR)、增强现实(AR)和混合现实(MR)，作为非常有前途的教育技术工具。这些技术的目的是为了方便人类的生活。在这种背景下，教育技术每天都为学生和教师创造新的机会，特别是在教育领域。通过各种虚拟环境(VE)和成像系统，需要学习的内容可以在低成本和安全的环境中独立于学校和教室呈现。因此，教师可以通过各种应用程序创建自己的内容，为他们提供灵活性和创造力的自由。在这种背景下，可以看到XR已经开始在教育的各个领域得到应用。当考察这些领域和科目时，可以观察到，在教育领域有一个集中。这篇叙述性综述的目的是描述XR (VR, AR, MR)技术在教育环境中的加速器。本文献综述是通过该大学的在线图书馆、Google Scholar、Web of Science、IEEE Xplore和ACM数字图书馆对相关文章和文献综述进行系统搜索进行的。本文介绍了XR技术在教育过程中的主要组成部分。从教育、学习等方面对XR技术进行了综述。作者指出了局限性，并总结了XR在教育应用中的未来工作。
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Pub Date : 2022-08-06DOI: 10.11113/humentech.v1n2.18
Azeddin Laraki Abduh, Mohd Riduan Mohamad, M. Salleh
The knee brace is a very popular medical device commonly used for rehabilitation and injury prevention of knees. However, conventional knee braces can be very expensive for patients with limited financial resources. Previous study on low-cost knee braces conducted by Alexander Hendricks (2018) only consisted of braces design for Medial Collateral Ligament (MCL) and Lateral Collateral Ligament (LCL) injuries. This paper aims to create a new low-cost knee brace design using 3D printing material that can be used for MCL, LCL and Anterior Cruciate Ligament (ACL) injuries. The proposed design was developed and tested using SolidWorks simulation features. The simulated materials were set similar to the materials of three dimensional (3D) printing filaments and the dimensions of the knee braces were based upon an actual patient. The results of this study showed that the new designs have been improved in term of Factor of Safety (FOS), due to its adjustable hinges, while the price is much cheaper than conventional knee braces. In conclusion, the aims for this study have been achieved to develop a low-cost knee brace that can be used for MCL, LCL and ACL injuries.
{"title":"Low-cost Knee Brace Prototype for Rehabilitation After Sports Injury","authors":"Azeddin Laraki Abduh, Mohd Riduan Mohamad, M. Salleh","doi":"10.11113/humentech.v1n2.18","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.18","url":null,"abstract":"The knee brace is a very popular medical device commonly used for rehabilitation and injury prevention of knees. However, conventional knee braces can be very expensive for patients with limited financial resources. Previous study on low-cost knee braces conducted by Alexander Hendricks (2018) only consisted of braces design for Medial Collateral Ligament (MCL) and Lateral Collateral Ligament (LCL) injuries. This paper aims to create a new low-cost knee brace design using 3D printing material that can be used for MCL, LCL and Anterior Cruciate Ligament (ACL) injuries. The proposed design was developed and tested using SolidWorks simulation features. The simulated materials were set similar to the materials of three dimensional (3D) printing filaments and the dimensions of the knee braces were based upon an actual patient. The results of this study showed that the new designs have been improved in term of Factor of Safety (FOS), due to its adjustable hinges, while the price is much cheaper than conventional knee braces. In conclusion, the aims for this study have been achieved to develop a low-cost knee brace that can be used for MCL, LCL and ACL injuries.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121980890","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 : 2022-08-06DOI: 10.11113/humentech.v1n2.25
Nurul Ain Abdul Rahman, Raeisya Marha Pathu Rahman, Fauziah Abd Rahim, Zahari Hasan, Raja Mohd Aizat Raja Izaham
The idea of bacterial scanning is realistic not only in operating rooms but also everywhere around human because bacteria and viruses grow everywhere. It is the job of individual and the community to keep the environment hygiene at all times. Several devices such as sterilizers, ultraviolet (UV) and autoclave are helpful to clean door handles, toilets, washbasins, railings, keyboards, seats, etc. However, those devices require either physical intact or chemical exposure to disinfect the areas without initial identification whether the bacteria are presence or not. If bacteria can be detected at the earliest time possible, preventive and initiative action can be taken and harmful bacteria can be prevented from infecting towards any personal. Hence, the development of Scan De Microbes is intended to address this situation. This system was developed as a scanning device to indicate the accumulation of bacteria on user’s hand where most interaction between a person and the surrounding is done by hand (i.e. eating, opening door, etc). The developed device is able to capture image of the hand which was illuminated by UV light under dark surrounding. Due to wide range of smart phone camera specification, all captured images were converted to a standard size image that acceptable for the application to process. The captured images later were processed and the orange color spot that appeared on the hand was calculated due to reaction of the bacteria with the hand. Results showed the estimated percentage of the accumulated bacteria on the hand from the processed images. The result page in the developed application was then displayed. This data later on can be saved and share wirelessly using Bluetooth of any apps available on the smartphone. Multiple images with different percentage of accumulated bacteria were tested using the application. The finding is conclusive and can be used as a preliminary accessor tool to investigate or detect any potential bacteria that already accumulate on the user’s hand. This development may assist the user in global warfare with the invisible enemy known to man as germ or bacteria in order to improve the livelihood and well-being of humans.
{"title":"Scan De Microbes Using MIT App Inventor","authors":"Nurul Ain Abdul Rahman, Raeisya Marha Pathu Rahman, Fauziah Abd Rahim, Zahari Hasan, Raja Mohd Aizat Raja Izaham","doi":"10.11113/humentech.v1n2.25","DOIUrl":"https://doi.org/10.11113/humentech.v1n2.25","url":null,"abstract":"The idea of bacterial scanning is realistic not only in operating rooms but also everywhere around human because bacteria and viruses grow everywhere. It is the job of individual and the community to keep the environment hygiene at all times. Several devices such as sterilizers, ultraviolet (UV) and autoclave are helpful to clean door handles, toilets, washbasins, railings, keyboards, seats, etc. However, those devices require either physical intact or chemical exposure to disinfect the areas without initial identification whether the bacteria are presence or not. If bacteria can be detected at the earliest time possible, preventive and initiative action can be taken and harmful bacteria can be prevented from infecting towards any personal. Hence, the development of Scan De Microbes is intended to address this situation. This system was developed as a scanning device to indicate the accumulation of bacteria on user’s hand where most interaction between a person and the surrounding is done by hand (i.e. eating, opening door, etc). The developed device is able to capture image of the hand which was illuminated by UV light under dark surrounding. Due to wide range of smart phone camera specification, all captured images were converted to a standard size image that acceptable for the application to process. The captured images later were processed and the orange color spot that appeared on the hand was calculated due to reaction of the bacteria with the hand. Results showed the estimated percentage of the accumulated bacteria on the hand from the processed images. The result page in the developed application was then displayed. This data later on can be saved and share wirelessly using Bluetooth of any apps available on the smartphone. Multiple images with different percentage of accumulated bacteria were tested using the application. The finding is conclusive and can be used as a preliminary accessor tool to investigate or detect any potential bacteria that already accumulate on the user’s hand. This development may assist the user in global warfare with the invisible enemy known to man as germ or bacteria in order to improve the livelihood and well-being of humans.","PeriodicalId":168265,"journal":{"name":"Journal of Human Centered Technology","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133599198","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}
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