International Journal of Human Computing Studies

Interval Potential Method for Solving Transportation Problems Using Mathematical Programming

2025-01-23T08:59:20+00:00

This study explores the interval variant of the potential method as an innovative approach for solving transportation problems within mathematical programming. Traditional methods often fail to address the complexities arising from parameter uncertainties, creating a knowledge gap in deriving reliable solutions under varying conditions. To bridge this gap, the interval potential method is proposed, utilizing interval matrices to define constraints and feasible solutions. The methodology involves constructing the initial transportation plan using the northwest corner method and applying interval analysis to account for data variability. A structured algorithm calculates directional potentials and checks the plan's acceptability, iteratively adjusting for optimal results. Numerical simulations demonstrate the robustness of the proposed method in solving transportation problems with uncertain parameters. Results confirm that this approach identifies optimal interval solutions while maintaining computational efficiency. The implications extend to various fields requiring reliable transportation and logistics optimization under uncertain conditions, such as supply chain management and resource allocation. This work contributes to the broader application of interval analysis in mathematical programming, providing a scalable solution for real-world challenges.

A Framework for Early Detection of Agile Software Development Project Failures using Machine Learning Algorithms

2025-03-05T08:08:15+00:00

In the realm of software development, the early identification of project failures is crucial for ensuring project success and minimizing risks. This study developed an early detection framework using various machine learning models to anticipate potential failures. Agile software projects were used for the study. The framework employed a range of machine learning models including decision tree, bagging classifier, weighted bagging classifier, random forest classifier, weighted random forest classifier, decision tree estimator, and bagging estimator. These models are trained and tested using a dataset comprising 13,238 observations from 12 different software companies, each with 15 variables relevant to project performance and outcomes. Initial training of the different models yielded promising results, with performance ranging between 45% to 55% accuracy during testing. Despite attempts to enhance the model's performance, including refinement of features and algorithms, there were no significant improvements observed. The evaluation results highlight the need for further refinement and optimization of the models used in the framework. In conclusion, while the decision tree classifier, bagging classifier, and random forest exhibited outstanding performance in the training results, the overall evaluation suggests that more work is required to improve the effectiveness of the early detection framework for Agile software project failures. Further research and refinement of the models are necessary to enhance accuracy and reliability in identifying potential project failures early in the Agile software development lifecycle.

Online Book Store Management System: Revolutionizing Literature Retail in the Digital Age

2025-03-13T23:44:57+00:00

Online Book Store Management System approaches literature retail differently. The internet landscape has changed how we access information and make purchases, but this system shows how it can improve the bookshop experience. This online platform lets customers browse, buy, and access a large book collection from home or their phones. Its easy-to-use interface lets customers browse a wide range of genres, authors, and formats. User-generated reviews and ratings let readers choose and discuss books, creating a vibrant and engaging reading community. This Online Book Store Management System simplifies shopping and supports independent writers and publishers through self-publishing and global distribution. It is a dynamic marketplace that unites book lovers with a wide selection of literary content while promoting sustainable resource use through digital services. This system succeeds because it adapts, responds to user feedback, and evolves to meet changing needs and preferences. It shows how technology enhances the love of books, delivering literature to readers and building camaraderie among bookworms. Finally, the Online Book Store Management System combines history and technology to bring a world of reading to users. It opens doors to exploration, discovery, and community, transforming digital book retail. Our online bookshop combines book magic with internet buying. Enjoy the extraordinary.