Journal of Computers, Mechanical and Management

The Role of FinTech in Sustainability and United Nations’ Sustainable Development Goals

2024-10-07T18:07:13+03:00

This study investigates the role of FinTech (Financial Technology) in promoting sustainability and advancing the United Nations’ Sustainable Development Goals (SDGs), examining how FinTech innovations in financial inclusion, digital payments, and green finance contribute to economic and environmental sustainability. Employing a comprehensive literature review and thematic analysis, the research utilizes NVivo and Orange Data Mining Tool to analyze data from 77 scholarly articles, industry reports, and case studies on FinTech applications related to sustainability. The findings reveal that FinTech significantly supports SDGs through enhanced financial inclusion, empowering underbanked populations, and by facilitating sustainable investments and green finance initiatives that address climate challenges. Additionally, technologies like blockchain and InsurTech contribute to transparency and resilience, fostering responsible production and inclusive economic growth. Offering valuable insights for policymakers, financial institutions, and technology innovators, the research underscores the importance of regulatory support and cross-sector collaboration in maximizing FinTech’s potential to drive sustainable development. By systematically connecting FinTech innovations with specific SDGs, this study addresses a gap in current research, providing a structured framework that clarifies FinTech's role in advancing sustainable development goals.

A Retrospective Assessment of Machine Learning Models in Heart Rate Prediction

2024-10-10T09:50:44+03:00

Applications of data mining are wide and diverse. Among this health care is a major application of data mining. Heart Disease is the most dangerous life-threatening chronic disease globally. Coronary artery diseases specifically heart-related incidents, persist as prominent contributors to global mortality rates. Timely identification and precise prediction of such incidents hold paramount importance for proactive intervention and minimizing unfavorable consequences. Leveraging a dataset sourced from Kaggle, comprising 303 patient samples and 13 features, our research explores the comparative performance of these machine learning algorithms. Surprisingly, both Random Forest and Logistic Regression models demonstrate identical accuracy rates of 86% in predicting heart rates. This parity in performance prompts further investigation into the underlying factors influencing model convergence. Finally, we stress the significance of thorough model evaluation that goes beyond accuracy, especially when dealing with imbalanced datasets.

Despeckling Ultrasound Thyroid Images

2024-11-05T17:21:34+03:00

Speckle is a type of noise that occurs in ultrasonic imaging that negatively impacts the clarity of the image. This noise can make it challenging for physicians to accurately diagnose conditions. Speckle filtering is an essential step in the preprocessing stage to ensure that valuable information is not lost. So the search for despeckling filters is a difficult task based on their performances and statistics. In this paper, we evaluated different denoising algorithms based on their statistical parameters, like mean, MSE, PSNR, ENL, SSI, SMPI and elapsed time. Based on the above parameters, the filter that uses local statistical parameters as a design performs better than the filters discussed.

Enhancing Educational Experiences Through Animation

2024-11-05T17:05:29+03:00

The integration of animation, virtual reality (VR), and augmented reality (AR) in education has revolutionized the learning experience, making it more engaging, interactive, and effective A comprehensive literature review reveals that animation has proven to be a powerful tool in clarifying complex concepts, particularly in subjects such as science, by visually illustrating abstract ideas. The study also highlights the challenges faced by students in understanding vertebrate anatomy and physiology, emphasizing the need for innovative teaching methods that cater to diverse learning styles. Incorporating visual aids into teaching has been shown to enhance learning outcomes and reduce the time needed to grasp concepts. The study further investigates the design methods and software tools used in creating educational animations, including Adobe Flash, Autodesk Maya, Autodesk 3ds Max, and Blender 3D. The findings of this study underscore the transformative potential of animation, VR, and AR in reshaping traditional teaching methods, making learning more dynamic, accessible, and effective for students across all age groups