Online-Journals.org (International Association of Online Engineering)
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Gamification in Mobile Applications: The Regulation of Children’s Course Games by Commensurability Education System
Get PDFThe nation’s education-related information reform is making slow progress in light of the recent significant advancements in information technology. Early childhood education informatization has become a crucial part of the national education informatization building, serving as the first link in the chain of lifelong learning. This paper analyzes the significance of using children’s games in the classroom and the significance of incorporating new media resources into children’s course games by fusing the benefits of new media resources for teaching in a real-world educational setting. The goal is to realize the gamification of early childhood education courses and strengthen the management and deepening of course resources. The study also shows that customer involvement serves as a mediator between a better brand experience and a consumer’s desire to make another purchase from the business. Subsequent interviews demonstrated that the following factors accounted for users’ motivations for using the app: rewards, competition, feeling of accomplishment, and knowledge acquisition; engagement and identity clarified how using the gamified application affected users’ attitude and loyalty towards the main service. In summary, our contribution advances the understanding of how gamified affordances can enhance consumer experiences by adding value to the focus brand that is facilitated by a third-party app as well as the gamified consuming experiences themselves
Best Practices for Increasing Employee Engagement and Completion Rates in Online Courses: A Case Study on Creating a Culture of Learning
Get PDFThis case study examines how the human resource department at the target company used features of their learning management system (LMS) to successfully implement a learning and development (L&D) program where employees were motivated not only to engage with courses in a meaningful way but also to complete them at a rate that was higher than that typically seen for eLearning courses. The research discusses the results of a study on the case organization and presents the implications of the findings
Closing the Cloud Skills Gap with Learner-Centric Performance Support Experiences: Case Study: IBM Center for Cloud Training
Get PDFSpurred by the urgent need to respond to a growing worldwide technology skills gap, the IBM Cloud Skills Initiative, launched in 2019, today plays an important role in supporting IBM’s commitment to provide people with the skills needed to fill the jobs of tomorrow. The IBM Center for Cloud Training (ICCT) serves as a critical learning resource for helping achieve the initiative’s goal of closing the global cloud skills gap. Through an innovative training program launched in October 2020, ICCT offers Performance Support Experiences (PSEs) designed to motivate and support learners and facilitate their achievement of program credentials and their pursuit of IBM Cloud certification. With PSEs that include online, real-time, and customized study support, ICCT surpassed its stated goal of credentialing participants by the end of 2022. The primary purpose of this article is to describe the components of the program and outcomes achieved and in so doing demonstrate the value of the center’s PSE-based approach to learning
Flexible Ureteroscopy Lithotripsy Operative Time Prediction Model for the Treatment of Kidney Stones
Get PDFEffective time and resource management is crucial not only in the operating room but also in healthcare supply chains. Healthcare supply chains involve the movement of medical supplies, equipment, and medications from manufacturers to healthcare providers. Effective management is crucial to ensuring that patients receive the care they need promptly. In the operating room, it is essential to have an information process in place to effectively manage time and resources during the current surgical procedure. This paper focuses on developing a predictive model for the operating time of flexible ureteroscopy for kidney stones. The model can forecast surgical and preoperative time based on patient characteristics and surgeon experience. The model can assist in planning ureteroscopy procedures and preventing surgical complications, which is crucial not only for the operating room but also for healthcare supply chains. The paper presents a study that compares different feature selection methods and regression techniques. The study found that sequential backward selection combined with the extra tree regressor was the most effective approach
Transforming Healthcare Data Management: A Blockchain-Based Cloud EHR System for Enhanced Security and Interoperability
Get PDFThe adoption of cloud-based electronic health record (EHR) systems and blockchain technology in healthcare is gaining attention for enhancing data security and interoperability. This research focuses on designing and implementing a blockchain-based cloud EHR system. It explores selecting suitable blockchain technology, cloud infrastructure, and data management methods to ensure patient data confidentiality, integrity, and availability. The architecture and components of the system, including the blockchain network, cloud storage layer, and user interface, are thoroughly discussed. A pilot study evaluates the system’s feasibility and performance, showcasing improved data protection, sharing, and management compared to traditional EHR systems. The potential benefits, drawbacks, and barriers to adoption of a blockchain-based cloud EHR system are examined. This research provides valuable insights and recommendations for healthcare institutions considering the implementation of such systems, addressing the challenges, and offering guidance for successful adoption
Remote Heart Rate Monitoring Device Using the Internet of Things
Get PDFCardiovascular diseases are the leading cause of death worldwide. Therefore, this study aims to develop a mobile application utilizing the Internet of Things (IoT) to monitor patients’ heart rate. The study employed a quantitative approach and a pre-experimental design. The experiment was conducted according to the research plan and involved 20 patients. The Scrum methodology was used for the development of the mobile application. The results reveal a significant improvement in patient and family satisfaction after using the IoT-enabled mobile application. In addition, the average measurement time has decreased to 6.025 minutes, which represents a significant difference compared to the traditional method. The number of measurements has increased from seven to 14 per week, averaging two regular daily measurements. The measurement device has alleviated the concerns of family members who are taking care of loved ones with cardiovascular disease. This tool gives users greater peace of mind, enabling them to take accurate and reliable measurements 24/7
A Deep Learning Approach for Malnutrition Detection
Get PDFThe timely detection of malnutrition in children is of paramount importance, as it allows for early intervention and treatment. This proactive approach not only prevents further health deterioration but also fosters proper growth, minimizing the long-term consequences of malnutrition, such as stunted growth, impaired cognitive development, and increased vulnerability to diseases. Our work encompasses the creation of a new dataset comprising images of children in Healthy, Undernourished, Stunting, and Wasting categories. The core objective is to assess the deep learning model performance in classifying these children images. The experimentation is carried out by varying epochs, batch size, optimizers AdamW, Adamax, and RMSprop; and different values of the learning rate 0.1, 0.01, 0.001, and 0.0001 during model training. The model is trained on image dataset constructed by cleaning images generated by the stable diffusion model. The model is tested on randomly selected child images from websites. The model successfully classified two classes with 95% accuracy, 97.6% F1 score, precision 97.6%, and 97.6% recall with Adam optimizers, 0.0001 learning rate, and Batch size 4. Additionally, for the four-class categorization scenario, the study broadens the classification. The model achieved 88.87% accuracy, 90.3% recall, 90.2% precision, and an F1 score of 90% for four-class categorization with AdamW optimization, 0.0001 learning rate, and batch size 6. These results are satisfactory for prediction of malnutrition category in children
Development of a Digital Twin Prototype for Industrial Manufacturing Monitoring System Using IoT and Augmented Reality
Get PDFThe world is currently abuzz with the rapid development of technology in the era of Industrial Revolution 4.0. Various technological advancements are facilitating progress and accelerating the development of industrial technology. This evolution has led to automation in production processes, transitioning toward digitalization. With the implementation of sensors that provide real-time data, production processes can now be monitored remotely. However, direct monitoring is still necessary at times to periodically check the condition of each operating machine. Therefore, there is a need for technology that can monitor production processes and reduce high maintenance costs. Currently, numerous new technologies are emerging to enhance the performance and efficiency of production processes in various industries. One such technology is the digital twin. A digital twin is a visual representation that offers insights into the continuous operations of a system. This research focuses on an industrial manufacturing monitoring system that integrates the Internet of Things (IoT) and augmented reality (AR) technologies. The system is composed of an application and a prototype machine in the form of a conveyor, which can simulate a digital twin of the prototype machine. It also transmits sensor data and error notifications to the application in real time. The designed system can serve as a prototype for implementing digital twin technology, combining IoT and AR. This makes it possible to apply the technology to machinery and production tools in various industrial sectors
River Water Quality Analysis Using Arduino-Based Sensor of the Cikapundung River, Indonesia
Get PDFRiver water is essential for people’s lives and environmental health. There is a need to manage river water to maintain river water quality. This research aims to develop a river water quality analysis system that is practical, easy, and capable of storage and processing using several sensors connected to a computer system. The tools used in this research are Arduino UNO R3 board and sensors. River water samples with various characteristics were taken from four spots of the Cikapundung River. The results showed that river water quality analysis can be done using sensor-based Arduino UNO R3. The temperature at the four spots ranges from 27–32oC and is included in the safe category for sanitation use. Judging from the turbidity factor, the turbidity value of river water is in the high category, namely 49.2–58.1 NTU, which is unsuitable for sanitary use. Regarding the TDS factor, the TDS range in river water is 150–222 ppm, indicating that river water is not polluted. Meanwhile, the pH value shows that the pH range of river water is alkaline and can be used for sanitation with a range of 7.93–8.16. This indicates that the water quality in the Cikapundung River that needs attention is the turbidity factor. It takes awareness of the surrounding community and government agencies to work together to improve the river’s environmental health sustainably
Development of Internet of Things Trainer Kit as a Learning Media for Digital Circuit Subjects in Higher Education
Get PDFThis research and development project aimed to create learning materials in the form of an Internet of Things (IoT) trainer kit specifically designed for the Digital Circuit course. The goal was to enhance student motivation and learning outcomes by facilitating a comprehensive understanding of the subject matter. The research methodology employed was research and development (R&D) utilizing the Instructional Development Institute (IDI) development model, which consists of define, develop, and evaluate stages. Primary data were gathered from experts in instrumentation, media, and materials, as well as feedback from lecturers and students. The findings revealed a high level of validity for the IoT trainer kit learning media. Media experts assigned a validity value of 0.93, while material experts provided a validity value of 0.86. The practicality of the media was confirmed by favorable responses from lecturers, indicating a practicality score of 87.31%. Additionally, students’ responses after the trial reflected a high practicality rating of 83.25%. Regarding effectiveness, the IoT trainer kit learning media demonstrated success in improving student learning outcomes, with a gain score of 77.25%, affirming its effectiveness. In conclusion, the IoT trainer kit Learning Media is considered valid, practical, and effective for teaching digital circuits within the Electrical Engineering Study Program at Muhammadiyah University of West Sumatra. Its utilization is expected to boost student engagement, creativity, and learning outcomes, potentially improving the overall quality of education