No. 20/2024

Online archive of Computer Science and Mathematical Modelling

No. 20/2024

1. Mateusz Maj - Performance comparison of Julia and Python programming languages based on available literature

   Pages: 5 - 17
   Abstract: The Julia language is a fast-growing high-level programming language. Its developers suggest that the quality and implementation of innovative compilation technology (Just-In-Time Compilation) beats Python in terms of algorithm execution times. The selection of the right programming language to implement an algorithm is of paramount importance. In today’s world every millisecond saved can determine the success of a product. The choice has a direct impact on the performance of the application or the execution of the algorithm. Consequently, a comparison analysis of modern or emerging technologies becomes particularly important. This article is the first part of a comparative analysis, the continuation of which [21] expands the research on the subject of this paper. In this context, the article presents summary of the existing literature and discusses the time performance of Julia and Python programming languages. In addition, test results and published source codes were reproduced and verified in a research environment. In the second part of the article [21], the research was extended to include more algorithms and to check the performance of each language on graphics cards.
   Keywords Python, Julia, comparison, performance
   Full article: 5_17_mmaj_performance_comparison_1.pdf
2. Amali S. Theresa, Sahaya A. Sudha - Mathematical optimization for nutritional equity: A decision-making and transportation model for implementing SDG-10

   Pages: 19 - 28
   Abstract: The Sustainable Development Goal 10 (SDG-10) aims to diminish inequalities within and among countries, including discrepancies in healthcare and nutrition. This study focuses on developing a mathematical model to assist in selecting the most nutritious food based on key health criteria – calcium, vitamins, carbohydrates, and proteins. With the application of multi-criteria decision-making (MCDM) techniques, the optimal food choice is determined to enhance health equity. Furthermore, the transportation problem is used to minimize the cost of distributing this nutritional knowledge and resources to a larger population. The integration of these mathematical approaches ensures that nutritious food choices are both effective and accessible, contributing to a reduction in health-related inequalities.
   Keywords Sustainable Development Goal 10 (SDG-10), health inequality, nutrition optimization
   Full article: 19_28_suda_theresa_mathematicaloptimization_csmm_20_2024.pdf
3. Rafał Wasiluk - Overview of techniques for detecting object’s features and embedding them in multidimensional spaces

   Pages: 29 - 37
   Abstract: It is evident that each object in the real world possesses unique properties. A subset of these characteristics can be readily described in quantitative terms. Examples of such features include the number of wheels in a vehicle, the floor area of a residential property, or the year of construction of a building. However, certain characteristics of objects exhibit a higher level of complexity. Examples of such features include object shape, color, and texture. These characteristics, frequently defined in terms of objects depicted in images, represent the primary characteristics that can be identified in real-world objects. The processing of these visual attributes has been the subject of scientific research for decades, and the literature on this topic is extensive. The objective of this article is to synthesize the existing methods for detecting object’s shape, color, and texture and embedding them in multidimensional spaces. By applying these methods, it is possible to represent the features of the object as points in multidimensional spaces. Such representations can be used to solve multicriteria optimization problems.
   Keywords visual features, feature extraction, feature embedding
   Full article: 29_37_r.wasiluk_overview_csmm_20_2025.pdf
4. Parana Yehan Yapa, Achala Pallegedara - Mathematical modeling of cutting effects on flank and bottom edge of end-milling

   Pages: 39 - 46
   Abstract: This ongoing study replicates a new mechanistic model for cutting forces in flat-end milling activity. The model considered the total cutting force due to the bottom edge and the flank edge together, which is a unique feature. The model development for flank cutting force coefficients utilizes an exponential function of the instantaneous uncut chip thickness to incorporate size effect for flank cutting in a non-linear least squares algorithm. After the flank cutting force coefficients are calibrated, the instantaneous calibrated coefficients for the bottom cutting force are obtained by calculating the difference between the total measured force and flank force component. This means you can assume the bottom cutting force coefficients are constant values. The cutting force model has been verified through experiments based on different cutting conditions.
   Keywords end-milling, linear least-square method, Levenberg-Marquardt method
   Full article: 39_46_py_yapa_mathematicalmodeling_csmm_20_2024.pdf