Int. J. Online Biomed. Eng.最新文献_第5页

Hybrid and Collaborative Networks Approach: Online Learning Integrated Project and Kolb Learning Style in Mechanical Engineering Courses 混合和协作网络方法:机械工程课程的在线学习集成项目和Kolb学习方式

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.34333

N. Jalinus, Ganefri, Mahesi Agni Zaus, R. Wulansari, Rahmat Azis Nabawi, Hendra Hidayat

{"title":"Hybrid and Collaborative Networks Approach: Online Learning Integrated Project and Kolb Learning Style in Mechanical Engineering Courses","authors":"N. Jalinus, Ganefri, Mahesi Agni Zaus, R. Wulansari, Rahmat Azis Nabawi, Hendra Hidayat","doi":"10.3991/ijoe.v18i15.34333","DOIUrl":"https://doi.org/10.3991/ijoe.v18i15.34333","url":null,"abstract":"Engineering education is very important to prepare quality graduates. An alternative hybrid and collaborative networks approach in learning is the current choice. This study aims to explain the online learning integrated project and Kolb learning style in mechanical engineering courses to enhance students' academic achievement which is implemented through a hybrid and collaborative networks approach. The research method used is a quantitative approach with the posttest control group design method. We carry out learning activities using Project and Kolb Learning on higher education students from Mechanical Engineering Education who take part in learning this project. Students who participate are limited to small groups, which are divided according to their learning styles groups, and the implementation is carried out in a hybrid and collaborative through e-learning and face-to-face. Collecting data using Kolb Learning Styles Inventory, and achievement test. While the data analysis used descriptive analysis and one-way Anova with the help of SPSS software. The results of this study indicate that there is a difference in the average academic achievement of students based on the four learning style groups, and the thinker learning style group has the highest average academic achievement among the four. The selection of appropriate learning styles and learning models has an impact on optimal and effective academic achievement.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114869949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Identifying Retinal Diseases on OCT Image Based on Deep Learning 基于深度学习的OCT图像视网膜疾病识别

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.33639

Abdelhafid Errabih, Mohyeddine Boussarhane, B. Nsiri, A. Sadiq, My Hachem El yousfi Alaoui, R. Thami, Brahim Benaji

{"title":"Identifying Retinal Diseases on OCT Image Based on Deep Learning","authors":"Abdelhafid Errabih, Mohyeddine Boussarhane, B. Nsiri, A. Sadiq, My Hachem El yousfi Alaoui, R. Thami, Brahim Benaji","doi":"10.3991/ijoe.v18i15.33639","DOIUrl":"https://doi.org/10.3991/ijoe.v18i15.33639","url":null,"abstract":"Computer-aided diagnosis has the potential to replace or at least support medical personnel in their everyday responsibilities such as diagnosis, therapy, and surgery. In the area of ophthalmology, artificial intelligence approaches have been incorporated in the diagnosis of the most frequent ocular disorders, such as choroidal neovascularization (CNV), diabetic macular oedema (DMO), and DRUSEN; these illnesses pose a significant risk of vision loss. Optical coherence tomography (OCT) is an imaging technology used to diagnose the aforementioned eye disorders. It enables ophthalmologists to see the back of the eye and take various slices of the retina. The goal of this research is to automate the diagnosis of retinopathy, which includes CNV, DME, and DRUSEN. The approach employed is a deep learning-based, and transfer learning technique, applying to a public dataset of OCT pictures and two pertained neural network models VGG16 and InceptionV3, which are trained on the big database \"ImageNet.\" That allows them to be able to extract the main features of millions of images. Furthermore, fine-tuning approaches are applied to outperform the feature extraction method, by modifying the hyperparameters. The findings showed that the VGG16 model performed better in classification than the InceptionV3 architecture, with a 0.93 accuracy.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125754119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cooperative and Competitive Serious Game for Operations and Supply Chain Management: Didactical Concept and Final Evaluation 运营与供应链管理中的合作与竞争严肃博弈:教学概念与最终评价

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.35089

Giovanni Romagnoli, Matteo Galli, Davide Mezzogori, Davide Reverberi

引用次数: 0

Employing Transfer Learning for Diagnosing COVID-19 Disease 迁移学习在COVID-19疾病诊断中的应用

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.35761

Lafta Raheem Ali, S. A. Jebur, M. M. Jahefer, B. Shaker

{"title":"Employing Transfer Learning for Diagnosing COVID-19 Disease","authors":"Lafta Raheem Ali, S. A. Jebur, M. M. Jahefer, B. Shaker","doi":"10.3991/ijoe.v18i15.35761","DOIUrl":"https://doi.org/10.3991/ijoe.v18i15.35761","url":null,"abstract":"Corona virus’s correct and accurate diagnosis is the most important reason for contributing to the treatment of this disease. Radiography is one of the simplest methods to detect virus infection. In this research, a method has been proposed that can diagnose disease based on radiography (X-ray chest) and deep learning techniques. We conducted a comparative study by using three diagnosis models; the first one was developed by using traditional CNN, while the two others are our proposed models (second and third models). The proposed models can diagnose the COVID-19 infection, normal cases, lung opacity, and Viral Pneumonia according to the four categories in the covid19 radiography dataset. The transfer learning technology had used to increase the robustness and reliability of our model, also, data augmentation was used for reducing the overfitting and to increase the accuracy of the model by scaling rotation, zooming, and translation. The third model showed higher training accuracy of 93.18% compared to the two other models that are dependent on using traditional convolution neural networks with an accuracy of 70.28% of the first model, while the accuracy of the second model that uses data augmentation with traditional convolution neural is 90.1%, while the testing accuracy models was 68.27% for the first model, 87.55% for the second model, and 86.03% for the third model.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133115310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Artificial Neural Network Hyperparameters Optimization: A Survey

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.34399

Zahraa Saddi Kadhim, Hasanen S. Abdullah, K. I. Ghathwan

引用次数: 3

Expert Web System: Diagnosis of Visual Diseases 专家网络系统:视觉疾病诊断

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.33397

Alejandro Boza-Chua, Karen Gabriel-Gonzales, L. Andrade-Arenas

{"title":"Expert Web System: Diagnosis of Visual Diseases","authors":"Alejandro Boza-Chua, Karen Gabriel-Gonzales, L. Andrade-Arenas","doi":"10.3991/ijoe.v18i15.33397","DOIUrl":"https://doi.org/10.3991/ijoe.v18i15.33397","url":null,"abstract":"Sight is one of the senses with the greatest sup- port for our daily life because the brain receives 80% of the information visually. However, it is one of the most neglected senses in Latin America, mainly in Peru. This is because since that in this country the sense of sight is related to the second disability with the highest percentage. Thus, 76% of the visually impaired population lost their sight due to lack of treatment or lack of early detection of any visual disease. For this reason, the present research work originated, which has the purpose of designing and implementing an expert web system oriented to the welfare of the vulnerable population regarding visual diseases and the care of the sense of sight. Therefore, the Buchanan methodology was used for the development of this project, which contains 5 phases of development and planning. This methodology allowed the identification of viable requirements for the expert web system, as well as the study of detailed solutions and design. Thus, it allowed the development of an expert web system that complies with the eye care, through early diagnosis. Finally, as a result of the present research work, it was obtained that the expert web system meets 88% of satisfaction, the value obtained through a questionnaire to a sample of 60 people, including patients and specialists of the company called MK Optical Center.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"594 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123189673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Database System for Storing Tuberculosis Sputum Sample Images as an AI Training Dataset 作为人工智能训练数据集的肺结核痰样本图像存储数据库系统

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.28245

H. H. Muljo, A. S. Perbangsa, T. W. Cenggoro, Kartika Purwandari, D. Sudigyo, B. Pardamean

引用次数: 2

Multi Objective Optimization Algorithms for Mobile Robot Path Planning: A Survey 移动机器人路径规划的多目标优化算法综述

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.34397

Baraa M. Abed, Wesam M. Jasim

引用次数: 1

Naïve Bayes and K-Nearest Neighbor Algorithms Performance Comparison in Diabetes Mellitus Early Diagnosis Naïve贝叶斯与k近邻算法在糖尿病早期诊断中的性能比较

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.34143

Haviluddin, N. Puspitasari, Aji Ery Burhandenny, Andi Dhiya Awalia Nurulita, Dinnuhoni Trahutomo

引用次数: 0

Control of an Exoskeleton for Lower Limb Rehabilitation Using ANFIS 基于ANFIS的下肢康复外骨骼控制

Int. J. Online Biomed. Eng. Pub Date : 2022-12-06 DOI: 10.3991/ijoe.v18i15.33805

Ayeh Arabiat, Mohammad Matahen, Omar Abu Zaid, M. Zgoul

{"title":"Control of an Exoskeleton for Lower Limb Rehabilitation Using ANFIS","authors":"Ayeh Arabiat, Mohammad Matahen, Omar Abu Zaid, M. Zgoul","doi":"10.3991/ijoe.v18i15.33805","DOIUrl":"https://doi.org/10.3991/ijoe.v18i15.33805","url":null,"abstract":"Exoskeletons are powered robotic devices designed to be worn by humans to provide physical assistance or power augmentation. In this work, a control system for a powered exoskeleton is designed. This exoskeleton is aimed at aiding in the rehabilitation of Spinal Bifidas. Spinal Bifida is the most common disability in childhood after Cerebral Palsy, it is a defective development of the spinal cord during conception. Two phases for this work are presented: system identification and control using ANFIS. While it is difficult to attain an accurate dynamical model of complex system, this work employed ANFIS to help control and stabilize the system. Gait trajectories were obtained by modeling the system as a linear inverted pendulum, a simulation was performed with a traditional controller. Afterwards, trajectory data was obtained and used to train and test ANFIS to create the model and controller. One, two and three inputs were investigated to train the ANFIS. Results showed that the one-input model visibly failed to follow the trajectory. The average RMSE for the two-input model was 0.096, and for the three-inputs, the RMSE on average was higher; 0.19, making it worse, however the knee model contrastingly showed improvement, as the RMSE was lower by 2% for the knee specifically.","PeriodicalId":247144,"journal":{"name":"Int. J. Online Biomed. Eng.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122918229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0