Online-Journals.org (International Association of Online Engineering)
Not a member yet
9805 research outputs found
Sort by
Abnormal Behavior Detection in Online Exams Using Deep Learning and Data Augmentation Techniques
Get PDFMassive open online courses (MOOCs) and other forms of distance learning have gained popularity in recent years. The success of remote online exam proctoring determines the integrity of the exam. Deep-learning-powered proctoring services have also grown in popularity. A large number of samples are needed for deep-learning training. The network’s generalization ability is poor due to insufficient training data or an uneven lack of variation. This study illustrates how to analyze students’ anomalous behavior by utilizing a YOLOv5 deep model trained using newly produced dataset. To overcome insufficient training data for deep-learning-related issues, this paper proposes a data-augmentation method based on semantic segmentation. The MobileNetV3 model was used to get an image semantic segmentation mask, which was used to get a binary mask, which in turn was used to replace the image background by using conditional subtraction with randomly selected background images. Finally, randomly pixel-based color augmentation was added to the resulting image. The behavioral detection model used in this study achieved 0.98 mean average precision (mAP) on the produced dataset, showing acceptable detection precision. The experimental findings indicate that the suggested augmentation method improves behavioral detection precision by more than 0.3%
Hemodialysis Patient Death Prediction Using Logistic Regression
Get PDFHemodialysis is a procedure for cleaning the blood from the waste products of the body’s metabolism. this is one of modality to treat end stage kidney disease. There are two main classifications of this disease, namely acute kidney failure and chronic kidney failure. Kidney failure occurs when kidney damage is severe enough or lasts a long time so that the disease is generally the final stage of kidney disease. Dialysis is performed on patients with kidney failure, both acute kidney failure and chronic kidney failure. This study is aimed to predict the mortality risk of hemodialysis patients. The Taiwanese hemodialysis center enrolled a total of 665 hemodialysis patients. The prediction is based on Logistic Regression. Compared with K-Nearest Neighbor, linear discriminant, Tree, and ensemble, Logistic Regression performed better. As for related medical variables like parathyroid surgery, urea reduction ratio, etc., they play a much smaller role in mortality risk factors than diabetes and cardiovascular disease
Effectiveness of Computer Modeling in the Study of Electrical Circuits: Application and Evaluation
Get PDFAbstract—Проблемы данного исследования связаны с недостатками, которые всегда существовали и обострились в последнее время в практике изучения электромагнитных явлений в отдельных электрических цепях в школе. В качестве одного из путей преодоления имеющихся недостатков рассмотрим усиление физической составляющей при исследовании материала электрических цепей. В соответствии с этим проблему исследования можно сформулировать в виде вопроса: какова педагогическая целесообразность использования современных микропроцессорных систем и математического моделирования с точки зрения повышения качества физических знаний и эффективности их применения в учебном процессе? изучение электрических схем? Для решения поставленных задач использовались следующие методы исследования: проведение педагогического эксперимента и анализ его результатов с целью определения эффективности использования компьютерного моделирования при изучении физических основ электрических цепей, теоретический анализ методической литературы. Разработана методика применения компьютерного моделирования и показана его роль в создании условий для внедрения исследовательского метода обучения в практику. В результате педагогического эксперимента доказана эффективность разработанных подходов к использованию компьютерных моделей в экспериментальной деятельности студентов с целью развития интеллектуальных способностей, формирования исследовательского подхода и стимулирования творческой активности студентов. теоретический анализ методической литературы. Разработана методика применения компьютерного моделирования и показана его роль в создании условий для внедрения исследовательского метода обучения в практику. В результате педагогического эксперимента доказана эффективность разработанных подходов к использованию компьютерных моделей в экспериментальной деятельности студентов с целью развития интеллектуальных способностей, формирования исследовательского подхода и стимулирования творческой активности студентов. теоретический анализ методической литературы. Разработана методика применения компьютерного моделирования и показана его роль в создании условий для внедрения исследовательского метода обучения в практику. В результате педагогического эксперимента доказана эффективность разработанных подходов к использованию компьютерных моделей в экспериментальной деятельности студентов с целью развития интеллектуальных способностей, формирования исследовательского подхода и стимулирования творческой активности студентов
Optimizing Patient Medical Records Grouping through Data Mining and K-Means Clustering Algorithm: A Case Study at RSUD Mohammad Natsir Solok
Get PDFRSUD Mohammad Natsir Solok, located in Solok City, provides comprehensive individual health services within its premises, offering both inpatient and outpatient care with 24-hour service availability. Inpatient services encompass emergency care and basic health services. A crucial component of healthcare operations is medical records, which consist of documented information pertaining to patient identity, examinations, treatments, procedures, and other services rendered. Medical records are essential and should be meticulously created in written or electronic form to ensure completeness and clarity. One common challenge encountered in maintaining medical records is the presence of overlapping data. To tackle this issue, data mining techniques are employed, with clustering being the primary method of choice. The K-Means algorithm is specifically utilized for clusterization purposes. By applying this data mining process and grouping patient medical records, valuable insights into the patterns of disease spread across different villages can be obtained. After applying K-Means clustering method, four distinct clusters were identified. The first cluster comprises 562 items, the second has 406 items, and the third and fourth have 791 and 279 items, respectively. These findings can serve as a reference for the local government, particularly the Solok City Health Office, to facilitate disease prevention initiatives and awareness campaigns. Decision-making related to disease sources, diagnosis, age, and gender of the affected patient can be informed by this data analysis
Diagnosis of Osteoporosis Using Transfer Learning in the Same Domain
Get PDFThis paper presents a system for diagnosing osteoporosis using x-rays by leveraging transfer learning in the same domain. The proposed system consists of phase 1 and phase 2; each phase includes several stages, as the pre-processing stage appropriately prepares the source image via noise reduction by the average filter, contrast enhancement using histogram equalization, and obtaining the region of interest by employing K-mean and edge detection, followed by the smudging stage through a mean filter with a large window size, which subsequently contributed to facilitating the diagnosis. The stages mentioned in both phases are similar. In phase 1, the model is trained on a large unlabeled x-ray dataset collected from different orthopedic centers to identify the general features of the image. In phase 2, fine-tune the trained model with the target dataset; this approach is beneficial when the target task has limited labeled data or when training a model from scratch is computationally expensive. It is worth noting that two datasets were used as target datasets. The accuracy of diagnosing osteoporosis using the proposed deep convolutional neural network (DCNN) model was 94.5 with the osteoporosis knee x-ray database (Dataset A). The accuracy of diagnosing osteoporosis using transfer learning in the same field was 98.91 when training the proposed DCNN model with a large unlabeled dataset and fine-tuning with the target database, osteoporosis knee x-ray database (Dataset A). The accuracy of diagnosing osteoporosis using the proposed DCNN model was 91.5 with the knee x-ray osteoporosis database (Dataset B). The accuracy of diagnosing osteoporosis using transfer learning in the same field was 96.61 when training the proposed DCNN model with a large unlabeled dataset and fine-tuning with the target knee x-ray osteoporosis database (Dataset B)
Blended Learning in Mathematics Teacher Education: A Systematic Review
Get PDFBlended learning is an active teaching approach widely applied in recent decades, especially in higher education. This study systematically reviews blended learning’s applications in mathematics teacher education based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This study aims to understand the potential of blended learning for various mathematical topics, the common blended learning models, and the benefits and challenges this teaching approach presents for educational stakeholders. Accordingly, 25 studies from the Scopus database are analyzed. The study shows that many studies were conducted between 2019 and 2022, focusing on a few developing countries. In addition, blended learning is extensively used in teaching most mathematics subtopics, especially in courses on teaching methods, with the widespread use of three models: the flipped model, the mixed model, and the online practicing model. Based on this study’s assessment, blended learning has a positive impact on the development of knowledge, skills, and attitudes among preservice teachers. However, it also presents lecturers and prospective teachers with various challenges related to technological infrastructure, teaching materials, digital and professional competence, and students’ knowledge and engagement. The study’s results provide an overview of the application of blended learning in mathematics teacher education and support certain future recommendations for new research directions
Structural Relationship on Factors Influencing Digital Literacy of College Students
Get PDFIn the era of rapid development of science and electronic technology, cultivating students’ digital literacy has become one of the key goals. This study aims to explore the causal relationship between students’ cognitive engagement, behavioral engagement, emotional engagement, and digital literacy. For this purpose, 454 college students participated in the survey held in March 2022. According to the results of the structural equation model, (1) students’ cognitive engagement significantly influenced emotional engagement, behavioral engagement, and digital literacy. (2) Students’ cognitive and behavioral engagement is related to their digital literacy. (3) Emotional engagement could not predict digital literacy. (4) Behavioral engagement moderated the relationship between cognitive engagement and digital literacy. This study emphasizes socio-emotional ability, which critically explores the value of online information between meaningful information and fake news. In conclusion, higher education should be designed to cultivate each dimension by clearly recognizing the sub-dimensions of digital literacy
The Effect of Strengths/Opportunities and Weaknesses/Challenges on Online Learning during the COVID -19 Pandemic
Get PDFThis paper researched the effect of strengths, opportunities and weaknesses or challenges on the online learning process during the COVID-19 pandemic. The research approach focuses on curriculum implementation and teaching quality using information technology systems (online teaching platforms). The research included 146 teachers (lower secondary and upper secondary school level), from whose responses we identified the strengths and opportunities as well as the weaknesses and challenges of online learning. While analyzing the data, we tested the construct reliability and noticed that Cronbach’s Alpha turned out to be at an acceptable level. From the paired sample t-test data analysis, it has also been concluded that, in the online learning process, strengths and opportunities are more considerable than weaknesses and challenges. Furthermore, linear regression indicated that the adjusted R-square of this model is 0.353, which signifies that the independent variables, strengths and opportunities and weaknesses or challenges, have an effect of 35.30% on the dependent variables, the curriculum implementation and the teaching quality, when using the information technology systems. As a result, we reached the conclusion that the positive effect of strengths and opportunities is higher than the negative effect of weaknesses or challenges
The Requirements for Heutagogical Attunement within STEAM Education
Get PDFAs we launch into an era marked by rapid technological advancements, education is experiencing disruptive transformations. Central to this shift is the integration of Artificial Intelligence (AI), predictive hybrid cloud strategies, and large language models (LLMs) like ChatGPT. As technology, AI becomes increasingly central to education; this paper explores the evolution of pedagogy in response to these changes, with a focus on the horizon. This investigation delves into the challenges and opportunities arising from the integration of AI, predictive hybrid cloud strategies, and LLMs into education, especially in the context of self-determined learning or heutagogy. The research looks into the role of collaboration, innovation, and adaptability in shaping curricula that prepare students for the fast-paced and dynamic landscape of the future, supported by AI, autonomous systems, and high-performance computing. The significance of problem- or project-based learning and cross-disciplinary collaboration is addressed, as this paper underscores the potential for preparing someone capable of future careers across various sectors. By integrating technology into education, the vision is of a globally connected, skilled, and innovative workforce ready to navigate a rapidly evolving world. Future research in this area might illuminate the potential of collaboration networks to drive sustainable improvements in learning and well-being
Enhancing Oral Production in Integrated English Blended Teaching through a Production-Oriented Approach: An Action Research Study
Get PDFA huge theory-practice gap is reflected in very limited previous research on a Production- Oriented Approach (POA) in tertiary education. Based on POA and Blended Learning theory, both qualitative and quantitative methods, including questionnaires, classroom observation, and interviews, were used to collect data during and after each round of action research, aiming at bridging the gap between theory and practice, exploring building an Integrated English blended teaching model with POA theory as a guide in planning-acting-observing-reflecting, summarizing the action plan, and improving the efficiency of oral production of integrated English blended teaching. Two rounds of action research were carried out in the Oral production of Integrated English blended classroom teaching, each containing 4 steps: problemsfocusing, plan-proposing, process-observing, and assessing & reflection. In the second round, some improvements were practiced solving the problems that occurred in the first round, focusing more on application and assessment. Applying the Integrated English blended teaching model with POA theory proved that POA has a positive effect on improving the teaching effect and students’ evaluation of teaching activities, teaching models, personal learning evaluation, and teachers’ teaching evaluation, which may contribute to the understanding of the impact of technology on oral production in IEBT and provide practical insights for educators to effectively leverage technology for enhancing students’ oral production skills