Current Issue
Volume 10 - Issue 01 (January - February 2026)
| Title: | Interpreting Partitional Clustering Using Ancient Indian Philosophy |
| Authors: | Saisuresh Sunkara, Nunna Srinivasa Rao, A. V. Dattatreya Rao |
| Source: | International Journal of Latest Research in Engineering and Management, pp 01 - 03, Vol 10 - No. 01, 2026 |
| Abstract: | Clustering is a central technique in statistics, machine learning, and data science that focuses on partitioning objects into groups based on similarity. While hierarchical clustering builds relationships gradually, partitional clustering directly divides data into a predefined number of meaningful groups, emphasizing efficiency, clarity, and representational balance. Although partitional clustering algorithms such as K-means, K-medoids, K-medians, K-modes, and Fuzzy K-means are products of modern computational science, their conceptual foundations resonate deeply with ancient Indian philosophical thought. Indian spiritual traditions have long emphasized clear classification, appropriate placement, and harmony among diverse elements. The vast corpus of Hindu philosophical literature reflects systematic partitioning of knowledge according to nature, function, and purpose. In particular, the Prasthāna Traya—the Upanishads, the Bhagavad Gita, and the Brahma Sutras—presents reality through structured divisions that guide human understanding and action. In this paper, partitional clustering is adopted as the primary analytical framework to explore these philosophical parallels. The direct and goal-oriented nature of partitional clustering closely aligns with the Hindu philosophical emphasis on discernment, balance, and practical realization. By examining major partitional clustering algorithms alongside insights from Prasthāna Traya, this work establishes a conceptual bridge between modern data science methodologies and ancient Indian spiritual wisdom. |
| Keywords: | Partitional clustering, K-means, Prasthāna Traya, Indian philosophy, Machine learning. |
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| Title: | Review and Recent History of the Fractals Research in Bulgaria |
| Authors: | Boyko Ranguelov |
| Source: | International Journal of Latest Research in Engineering and Management, pp 04 - 15, Vol 10 - No. 01, 2026 |
| Abstract: | The review is presenting the history and development of the recent fractals’ research in Bulgaria during the last decades. The aim of this study is to make more familiar the topic in front of the international fractal’s society. It is focused on the entire list of publications related to this research attached as Appendix. Additionally several examples, illustrations and comments are presented just to give a short view to the results of these investigations. Everyone who needs to be more familiar with the methods, data and results can use the bibliography to find more information about the achievements on this topic. The structure is following simple rules– initiation, maturity stage and recently presented papers. Tables show fractal dimensions determined for different examples from the fields of geodynamics on the Earth, some planets and satellites of the Solar system, applications to the seismic hazard assessment, topography and digital elevation models and their relationships with geophysical fields, etc. There is also an example of the fractal analysis of visual art pictures, etc. The conclusions confirm the effective results, potential to progressive development, needs to fulfill gaps and future vision on the development especially focused to the younger generation of investigators. |
| Keywords: | Bulgaria, Fractals, Research,Review. |
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| Title: | The Level of Globalization Challenges Encountered by Developmental Education Teachers in Catmon District |
| Authors: | Dexter R. Arnejo |
| Source: | International Journal of Latest Research in Engineering and Management, pp 16 - 18, Vol 10 - No. 01, 2026 |
| Abstract: | This paper examines the level of globalization challenges encountered by developmental education teachers in the Catmon District, Cebu Province, focusing on five domains: pedagogical practices, technological integration, professional development, classroom management, and community & stakeholder engagement. Using a descriptive-quantitative design with 191 stratified‑randomly selected teachers from a population of 358, the study employed a researcher‑developed 7‑point Likert‑scale instrument and analyzed weighted means to estimate perceived challenge levels. Results show moderate to high challenge in pedagogical practices (M≈5.47–5.49), technological integration (M≈5.47–5.69), and classroom management (M≈5.60–5.83), all interpreted as ―Challenged‖. Professional development concerns range from slightly challenged to challenged (M=5.29–5.38), while community and stakeholder engagement difficulties are ―Slightly Challenged‖ (M=5.02–5.20). These findings highlight persistent resource, contextual, and capacity constraints that complicate globalization-responsive teaching in a rural district. Implications include digital equity investments, context-driven professional development, and structured school–community alignment. |
| Keywords: | Globalization challenges, developmental education, rural schools, pedagogical practices, technological integration, professional development, classroom management, stakeholder engagement |
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| Title: | Artificial Intelligence-Enabled Supply Chain Competency as a Driver of Bio-Circular-Green (BCG) Sustainability Performance: Empirical Evidence from Thailand |
| Authors: | Kasidit Chaiphawang, Sermsiri Nindum, Siripan Jeenaboonrueng, Niwest Jeenaboonrueng, Benchawan Benchakorn |
| Source: | International Journal of Latest Research in Engineering and Management, pp 19 - 21, Vol 10 - No. 01, 2026 |
| Abstract: | This study investigates the structural role of Artificial Intelligence (AI) utilization in enhancing supply chain competency and Bio-Circular-Green (BCG) sustainability performance among organizations in Chiang Rai Province, Thailand. A quantitative survey was conducted with 400 respondents using structured questionnaires. Reliability testing indicated excellent internal consistency (Cronbach’s alpha = 0.96). Descriptive statistics, correlation analysis, and regression modeling were applied. Results show moderate AI utilization across SCOR processes, with the highest adoption in planning and the lowest in delivery operations. Supply chain competency was moderate overall, while BCG performance outcomes were high, particularly in environmental performance. Regression analysis confirms that AI utilization significantly influences supply chain competency (β = 0.889, p < 0.001), which in turn significantly influences BCG outcomes (β = 0.882, p < 0.001). The findings support a competence-mediated pathway in which AI adoption strengthens operational capabilities that subsequently drive sustainability performance. The study contributes empirical evidence to engineering management literature by demonstrating how AI-enabled digital transformation supports regional sustainable development strategies. |
| Keywords: | Artificial Intelligence, BCG Economy, Digital Transformation, Supply Chain Competency, Sustainability Performance |
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