Papers by Anthony Otuonye
Asian journal of computer science and technology, Oct 28, 2022
This research paper aims at design of an innovative framework scalable and integrated loan manage... more This research paper aims at design of an innovative framework scalable and integrated loan management with Quick Response Code enhancement, which will guarantee easy and better-secured loan validation and processing in microfinance banks and other lending institutions. As the number of microfinance bank customers in need of personal loans rises on a daily basis, especially in the post COVID-19 era, management is faced with the complex job of loan application verification in order to correctly determine eligibility for a loan. There is the challenge of coping with fraudulent customers who make false claims with their loan application documentations, sometimes seeking to access multiple loans from more than one microfinance banks and using single collateral security. There is need for a central regulatory agency that links up major lending institutions in a collaborative effort to forestall incidences of multiple loan access using single loan security. Our new model will also forestall activities of some fraudulent bank officials who go as far as granting credit facilities to their friends and family members without following due process and using their privileged positions to obtain unsecured loans for themselves and their relations, sometimes in excess of bank's statutory lending limits, and in total violation of the provisions of policy of microfinance banking sector. Our new model was designed using the Rapid Application Development (RAD) methodology following its high involvement and concentration on user's viewpoint as well as its ability to change system design on the go based on user demands. Implementation of the new system was done using such development tools as PHP, JavaScript, MySQL, and Visual Studio. Basic functionality testing was carried out on the system to make sure all the buttons on every screen works as desired, and to ascertain that the system could forestallincidences of "insider abuse" and that loan approvals are done according to internal and external regulations.
Asian Journal of Computer Science and Technology
This research paper aims at design of an innovative framework scalable and integrated loan manage... more This research paper aims at design of an innovative framework scalable and integrated loan management with Quick Response Code enhancement, which will guarantee easy and better-secured loan validation and processing in microfinance banks and other lending institutions. As the number of microfinance bank customers in need of personal loans rises on a daily basis, especially in the post COVID-19 era, management is faced with the complex job of loan application verification in order to correctly determine eligibility for a loan. There is the challenge of coping with fraudulent customers who make false claims with their loan application documentations, sometimes seeking to access multiple loans from more than one microfinance banks and using single collateral security. There is need for a central regulatory agency that links up major lending institutions in a collaborative effort to forestall incidences of multiple loan access using single loan security. Our new model will also forestal...
In this research paper, we have developed a new big data processing model using the HACE theorem ... more In this research paper, we have developed a new big data processing model using the HACE theorem to fully harness the potential benefits of the big data revolution and to enhance socio-economic development of in developing countries. The paper proposes a three-tier data mining structure for big data storage, processing and analysis from a single platform and provides accurate and relevant social sensing feedback for a better understanding of our society in real-time. The whole essence of data mining is to analytically explore data in search of consistent patterns and to further validate the findings by applying the detected patterns to new data sets. Big Data concern large-volume, complex, and growing data sets with multiple, autonomous sources. Our data-driven model involves a demand-driven aggregation of information sources, mining and analysis to overcome the perceived challenges of the big data. The study became necessary due to the growing need to assist governments and busines...
International Journal of Intelligent Information Systems, 2024
Musculoskeletal diseases (MSDs), encompasses various conditions affecting muscles, bones, tendons... more Musculoskeletal diseases (MSDs), encompasses various conditions affecting muscles, bones, tendons, ligaments, and joints, resulting to pain, inflammation, and limited mobility, significantly impacting individuals' quality of life. Diagnosing these diseases poses a challenge for healthcare professionals due to symptom similarities with other conditions. To address this, the development of expert systems tailored for musculoskeletal diagnosis has emerged as a promising approach to enhance clinical decision-making and improve patient outcomes. This study aims at developing and evaluating an expert system for musculoskeletal disease diagnosis, by leveraging a knowledge base containing information on common musculoskeletal diseases and symptoms. The system utilized a combination of rule-based and machine learning techniques to provide diagnostic recommendations to physicians. Comparative analysis with experienced physicians, using a dataset of patients with known musculoskeletal diseases, revealed the expert system’s diagnostic accuracy of 92%, recall of 98%, Precision of 91%, F1-Score of 94% and a quicker diagnosis compared to physicians. Additionally, the system demonstrated ease of use and user-friendliness. This project focuses on predictive algorithms, leveraging expert systems dating back to the 1970s, emulating human expert decision-making, particularly in disease diagnosis. The development of an expert system for musculoskeletal disease diagnosis symbolizes the convergence of medical expertise, computer science, and artificial intelligence. By integrating machine learning, natural language processing, and decision support systems, these expert systems have the potential to revolutionize musculoskeletal healthcare delivery. In conclusion, our results show that expert systems hold promise in transforming clinical practice and improving patient outcomes in musculoskeletal healthcare through interdisciplinary collaboration and continuous innovation.
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Papers by Anthony Otuonye