Computer Science Research Articles

Managementul riscurilor transformaționale ale educației matematice și informatice din Republica Moldova

The article addresses the significant transformations in mathematics and IT education in the Republic of Moldova. The challenges facing mathematics and IT education are identified: implementation of the new curriculum concept, resistance to change on the part of teachers, inadequate teacher training, lack of resources and infrastructure, risk of ineffective assessment. The principles of developing the new school curriculum focus on adapting to the sociocultural context, respecting individual learning needs, training essential skills for professional and personal life, and integrating disciplines for sustainable skills. The need to update teaching methods, including interactive and innovative approaches, the use of digital technology, and the development of critical and creative thinking are emphasized. It is proposed to create individualized learning paths and use digital educational resources to improve the learning process. As a result, continuous training of mathematics and computer science teachers is recommended through programs that include learning themes centered on pedagogical models, tools and innovative methodologies, such as the Conditional knowledge strategy, realistic mathematical education, the Flipped Classroom method, video-pedagogy, virtual reality, augmented reality and mixed reality technologies, to stimulate students' motivation and their active involvement in the educational process.

Advancing Education in Challenging Times: A Review of the XVI International Conference on Mathematics, Science and Technology Education (ICon-MaSTEd 2024)

Abstract This paper presents a comprehensive review of the XVI International Conference on Mathematics, Science and Technology Education (ICon-MaSTEd 2024), held from May 15-17, 2024, at Kryvyi Rih State Pedagogical University, Ukraine. The conference, organized in a hybrid format, brought together over 100 attendees from 9 countries, showcasing cutting-edge research and innovations in educational practices amid global challenges. The review synthesizes key themes and findings from 37 selected papers across various domains, including Mathematics Education, Science Education, Computer Science Education, and Educational Technology. Notable trends include the increased integration of artificial intelligence and digital technologies in education, the development of 21st-century skills, and adaptive strategies for education in crises. Particular attention is given to studies addressing the unique educational challenges faced in Ukraine, demonstrating the resilience and innovation of educators and researchers in conflict-affected regions. The paper highlights significant contributions in areas such as online learning environments, visual thinking in mathematics, AI applications in mental health education, and the design of university digital ecosystems.

THE SPECIFIC FEATURES OF TEACHING MODERN PROGRAMMING LANGUAGES IN PEDAGOGICAL HIGHER EDUCATION INSTITUTIONS

This article examines the relevance and necessity of teaching the Python programming language for the professional and methodological training of future computer science teachers in pedagogical universities. Python software is one of the modern programming languages and is being implemented at all levels of education. For this reason, it is necessary that a future computer science teacher has the knowledge and skills to use Python to learn the basics of programming.

Rematerialization

In this essay, I examine memory optimization as both a fundamental component of digital operations and a feminist form of cultural resistance to digital colonialism through a multimedia installation by the Latinx artist collective Cog•nate Collective. Through close reading, I demonstrate how their 2021 installation And will be again…transforms the work of memory optimization through an ecofeminist countermapping of the US-Mexico border and its histories of data extraction through dispossession. I analyze the various components of the multimedia installation, including the collaborative process of Indigenous language translations of an eponymous passage by Gloria Anzaldúa. I frame my analysis through a sociotechnical reclamation of the computer science term rematerialization. In doing so, I reorient the term rematerialization to showcase how Latinx artists recompute historical data of the US-Mexico borderlands to produce anticolonial collective memories as spiritual technologies of resistance.

Framework of Computer Science Learning Through Hybrid Service Learning Oriented Visual Toward the Continuum of Visualization Thinking and Generic Skills

Computer Science learning requires students to think logically and understand its practical implementation in real-life situation clearly. However, the lack of learning activities that bridge the gap between theory and practice hinders their ability to depict learned concepts in real-world scenarios and master generic skills. Therefore, Computer Science education necessitates visualising learning concepts in real-life contexts, such as implementing Service Learning activities. However, in the current post-COVID-19 endemic situation, it is not feasible to implement this approach fully face-to-face. Thus, integrating Service Learning activities through technology-mediated means is essential in Computer Science education. Hybrid Service Learning activities, using technology as a medium, are instructional designs that provide opportunities for students to apply theoretical knowledge practically in real-life situations. Therefore, in this study, Computer Science learning activities were designed with visual materials through a hybrid service learning website to support the continuum of students' visual thinking and their generic skills. Subsequently, the effects of Computer Science learning activities on the continuum of students' visual thinking, level of generic skills, and perception were analyzed. A quasi-experimental study design was used, which involved a total of 27 respondents and took 15 weeks to complete. The research data was analyzed using descriptive analysis and inferential statistics. The results of paired t-test for the continuum of students' visual thinking levels, including visual thinking, visual learning, and visual communication, indicated an improvement with a significant difference of [p<0.05] between the pre- and post-activities. In terms of students' generic skills levels, the paired t-test for the pre-Service Learning [PS], during-Service Learning [DS], and post-Service Learning [AS] phases showed a significant difference of [p<0.05], which indicated an increase in students' mastery of skills and changes between each phase. Furthermore, students' perceptions revealed positive feedback towards hybrid service learning. Overall, based on the findings of this study, a framework for visual-based hybrid service learning was developed as a guide for Computer Science education to support the continuum of students' visual thinking and their level of generic skills.

Conditions for training future computer science teachers based on a systems approach

The article deals with the issues of training future teachers of computer science at the Karaganda University named after Academician E.A. Buketov. The requirements for Hard-skills, Soft-skills of future teachers of computer science as specialists who own modern pedagogical and information technologies in accordance with the requirements of innovative socially-oriented development of Kazakhstan are highlighted. The content of educational programs, the catalogue of elective bachelor's degree courses «6B01505-Computer Science», «6B01506-Computer Science, ICT and Robotics» developed on the basis of a system and competency based approachs in collaboration with employers, are analysed. The purposeful work on preparing future informatics teachers for professional activities, owning digital technologies, is described, which contributes to their active life and professional adaptation, further personal and professional self-realization. Some aspects of the introduction of innovative approaches to the training of teaching staff are highlighted with an emphasis on improving the education content, the formation of a high level of information culture among future informatics teachers. The authors concluded that the logic of the disciplines’ sequence studied, the optimization of the content of educational programs in collaboration with teachers of schools, will lead to the formation of professional Hard-skills and personal Soft-skills competencies of future computer science teachers.

Modern Analysis Design And Implementation Of An (SMS) Application Banking

SMS –Banking is a value-added service solution that allows banked customers to be able to perform certain banking operations related to their account such as balance viewing, transfer, etc. via the mobile network operator's SMS service. The integrated platforms for these services include added values, with one part connected to the mobile network via the SS7 protocol stack and the other end to the IP network. The development of SMS-based mobile applications requires the installation of a text messaging gateway that allows interconnection between the two networks (telecommunications and computer). OZEKI is open source software. It is an SMS gateway that can receive SMS from GSM network and forward them to another network. It supports several types, allowing SMSC to be linked between them or between a GSM network and another network (IP for example). The OZEKI portal therefore makes it possible to set up value-added services. Computer Science has a dynamic computer park that allows them to develop and conduct effective research in Computer Science because information technology makes the fundamental pillar in development for the progress made in the world today as Computer Science Department students have the necessary tools for them to help in their research.

Influence of critical thinking on LLM usage among Universitat d’Andorra students

As large language models continue to reshape educational practices, a comprehensive evaluation of critical thinking’s influence on large language models’ usage becomes essential. This study examines how students in the fields of education and computer science at the Universitat d’Andorra interact with large language models, with a particular focus on understanding their learning experiences, decision-making strategies, and problem-solving approaches. Using qualitative and quantitative methods, the research analyzes the frequency and purposes of using these technologies, as well as the critical thinking processes students employ to assess the reliability and relevance of content generated by artificial intelligence. Findings reveal a spectrum of attitudes towards large language models, ranging from enthusiastic adoption to skepticism. While many students appreciate the immediate and personalized academic support, content generation assistance, and writing skill improvement offered by these tools, concerns about the accuracy and potential biases of the outputs are prevalent. Notably, students demonstrate varying levels of the activation of their critical thinking skills when engaging with large language models, with some actively investigate the reliability of artificial intelligence generated information, while others exhibit a more passive reliance on these technologies. The study also highlights distinct usage patterns between computer science and education students. The results contribute to a deeper understanding of student behavior in the context of artificial intelligence enhanced education, providing valuable insights for educational institutions aiming to integrate these tools into their curricula effectively. Furthermore, this research emphasizes the need to enhance critical thinking skills within educational programs to empower students to navigate the complexities of large language models capabilities and limitations.

Modern Analysis Design And Implementation Of An (SMS) Application Banking

SMS –Banking is a value-added service solution that allows banked customers to be able to perform certain banking operations related to their account such as balance viewing, transfer, etc. via the mobile network operator's SMS service. The integrated platforms for these services include added values, with one part connected to the mobile network via the SS7 protocol stack and the other end to the IP network. The development of SMS-based mobile applications requires the installation of a text messaging gateway that allows interconnection between the two networks (telecommunications and computer). OZEKI is open source software. It is an SMS gateway that can receive SMS from GSM network and forward them to another network. It supports several types, allowing SMSC to be linked between them or between a GSM network and another network (IP for example). The OZEKI portal therefore makes it possible to set up value-added services. Computer Science has a dynamic computer park that allows them to develop and conduct effective research in Computer Science because information technology makes the fundamental pillar in development for the progress made in the world today as Computer Science Department students have the necessary tools for them to help in their research.

Using Supervised and Unsupervised Machine Learning Models to Analyze Students Academic Performance

Examination result repositories generated by most universities can serve as machine learning datasets for training various models to gain insights from the data. These datasets can train multiple linear regression models to determine a student's cumulative grade point average (CGPA), or the score that a student will get in specific courses. Additionally, classification-based supervised machine learning models can use these datasets to provide insights into the class result that a student will obtain. These insights can be invaluable for academic advising and early intervention. Moreover, these datasets can train clustering-based unsupervised machine learning models, such as the K-means clustering model, to understand how student results are grouped into various clusters. This information can be crucial for planning and evaluating the quality of the university. This paper uses the dataset of undergraduate students' examination results from the Department of Computer Science at the University of Nigeria, Nsukka, to train three supervised machine learning models and one unsupervised machine learning model, utilizing Jupyter Notebook as the Python IDE. The training results showed acceptable accuracies of 91.5% for the Naïve Bayes model and 95.1% for the Decision Tree model. The linear regression model demonstrated a negligible root mean square error of 8.23×10−18, while the K-means clustering model exhibited an acceptable Silhouette metric of 0.12.

Integrating Quantum Computing Into Blockchain: Strategies for Overcoming Scalability and Security Challenges

, , , , & Department of Computer Science and Pure & Applied Physics Ladoke Akintola University of Technology Ogbomoso, Oyo State, Nigeria E-mails: golamiji@lautech.edu.ng, soolabiyisi@lautech.edu.ng, woismaila@lautech.edu.ng, ofalade28@pgschool.lautech.edu.ng, ljmkadeola@gmail.com ABSTRACT The rapid progression of quantum computing has created new opportunities for advancing blockchain technology, particularly in addressing its two primary challenges which are scalability and security. As blockchain adoption grows, traditional consensus mechanisms reveal significant inefficiencies, causing transaction bottlenecks and increased latency. Additionally, the advent of quantum computing poses a significant threat to the classical cryptographic algorithms foundational to blockchain security. This research introduces an innovative approach that harnesses quantum computing to address these dual challenges. To enhance scalability, this research proposes integrating Grover's algorithm and Post Quantum encryption alogrithms to optimize transaction selection and validation, significantly reducing time complexity compared to classical methods. On the security front, the research introduces post-quantum cryptographic techniques to strengthen blockchain networks against quantum adversaries. Simulations conducted on IBM Qiskit Quantum Computer Simulator demonstrate that the proposed framework achieves superior efficiency, cost-effectiveness, and faster transaction processing with Grover's algorithm and Post Quantum encryption alogrithms compared to the current classical systems. These improvements highlight the potential benefits of utilizing quantum computing to deploy quantum-enhanced blockchain. Keywords: Quantum, Computing, IBM, Qiskit, blockchain, Post-Quantum, Encryption CISDI Journal Reference Format Gabriel, O., Olabiyisi, S.O., Ismaila, W.O., Falade, O.A., & Alawode O. (2024): Integrating Quantum Computing Into Blockchain: Strategies for Overcoming Scalability and Security Challenges. Computing, Information Systems, Development Informatics & Allied Research Journal. Vol 15 No 3, Pp 15-28. dx.doi.org/10.22624/AIMS/CISDI/V15N3P2 Available online at www.isteams.net/cisdijournal

COMPUTATIONAL EXPERIMENTS WHEN STUDYING MATERIALS PROPERTIES INFLUENCED BY "MIXTURE" FACTORS

Short information on computational materials science is given, with the methodology of material properties fields, in composition and process coordinates, as the part of it and as the background of the study presented in this paper. One of the main means of the methodology is random scanning the whole and local fields. These tools were developed and used to solve many problems in materials science related to the properties defined by mutually independent factors. The purpose of the study presented in this paper has been to develop the tool for random scanning the fields of properties effected by "mixtures" of q components, linearly related portions of components in rangers from 0 to 1, with their sum equal to 1. In these cases, the factors domain (or subregion of it) presents the simplex. The special designs of experiments to get reduced polynomials describing the fields in simplex coordinates are used. Two procedures for generating any number of uniformly distributed points on the simplex have been developed. These points define the virtual mixtures simulated in computational experiments. The procedures were tested by scanning the fields of two rheological characteristics of lime suspension filled with "short", “medium", and "long" cellulose fibers. Experimental-statistical models in the form of reduced polynomials for effective viscosity at shear rate equal to1 s-1 and for the rate of destruction of liquid structure (parameters of power-law model of flow, K = η1 and m) obtained in previous study are used to determine the levels of these characteristic for each of simulated mixture. Computational experiments were carried out, in which the fields of η1 and m in whole simplex domain and in some of its zones were scanned, allowing the generalizing indices of the fields and different correlations between η1 and m in different zones of mixture triangle to be estimated. The developed tools, the procedures of generating random points, which would define the simulated compositions of the "mixtures", make significant contribution to the progress of the methodology of recipe-technological fields of properties and to computational materials science.

Scientific interest in rehabilitation: a bibliometric analysis

Purpose: It is aimed to conduct bibliometric analysis to explore scientific interest in rehabilitation. The date of bibliometric analysis was 17.01.2023, and a total of 410.000 documents from all times to this date were analyzed. Materials and Methods: The data for this study was obtained from Scopus, a multidisciplinary database, for the period of sixty-two years (1960-2022) using the keyword ‘rehabilitation’. Our bibliometric analysis includes articles, authors, subject area, document types, countries, languages, affiliations, publication years, citations, and number of citations. Since Scopus allows the download of 2000 data at a time, citation reports after 2021 were examined. Results: 109,138 of 410.000 articles were in all open Access and 342.918 were in English. When we look at the distribution of the number of articles by year, there were 10,095 articles in 2023, 27,615 articles in 2022, 25,594 articles in 2021, and 22,718 articles in 2020. Documents types were; article (72.5%), conference paper (9.9%), review (9.8%), book chapter (2.3%), and editorial (1.7%). Documents according to subject areas were as follows; Medicine (N=282.301), Health Professions (N=66,434), Engineering (N=53,704), Neuroscience (N=26,016), Computer Science (N=25,326), Social Sciences (N=23,080), Psychology (N=21,384), Nursing (N=19.481). A total of 199 cited documents have been reached. Sixty-two in 2023; 132 in 2022; 5 in 2021. The h index was 4. Conclusion: We see that 'Rehabilitation' is increasingly becoming an area of interest for many different disciplines, as developing technology and quality of life in the field of health are at the forefront of treatment approaches.

The 3D tree dataset: an artistic experiment using a voxel-based GAN

AbstractIn visual culture, Generative Adversarial Networks (GANs) have been used to generate two-dimensional images, video, and three-dimensional forms. Whilst there are a relatively large number of conditional datasets of two-dimensional images, there are fewer datasets of three-dimensional objects available for training, evaluation, and practical use. In this paper, we introduce a synthetic dataset of 3D trees that provide novel geometric challenges for machine learning and describe our use of this dataset in training and qualitative evaluation via a public exhibition and survey. The 3D Tree Dataset was made using random variations of 76 bespoke tree templates based on art historical references to favor interesting, beautiful, and varied trunk and branch shapes. In generating and experimenting with this dataset, we wanted to know how a geometrically complex series of organic forms would challenge voxel-GANs compared to existing datasets comprising industrial objects such as chairs and cars. As an interdisciplinary project between visual arts and computer science, we used 3D printing and animation to visualize and communicate our outputs to non-specialist audiences. In this paper, we describe and share the 3D Tree Dataset, outline the process of generating the dataset, describe the GAN architecture and application used to test the dataset and discuss the results relative to our artistic and cultural goals.

Wkład ośrodków statystycznych w Krakowie i we Wrocławiu w rozwój metod klasyfikacji i analizy danych

The year 2022 marked the 10th anniversary of the passing of Prof. Kazimierz Zając, the long-standing head of the Department of Statistics and later the director of the Institute of Statistics, Econometrics and Computer Science at Krakow University of Economics, while 2023 marked the 10th year of the passing of Prof. Zdzisław Hellwig, the long-standing head of the Department of Statistics and director of the Institute of Economic Cybernetics at Wroclaw University of Economics. Both professors were the scientific leaders of statistical centres at the above-mentioned universities. The aim of the article is to present the contribution of Polish statisticians to the development of the theoretical foundations and empirical research in the field of numerical taxonomy and methods of data classification and analysis. Particular emphasis is placed on the achievements of Professor Zając and Professor Hellwig and their students and associates. According to the authors of this work, recalling the achievements of these scholars is especially important as most commonly cited sources on data classification and analysis are mainly English-language.

Quantum Machine Learning: Bridging Quantum Computing and Artificial Intelligence

Abstract: This comprehensive article explores the burgeoning field of Quantum Machine Learning (QML), examining its foundational principles, key algorithms, and potential applications. We delve into the fundamentals of quantum computing, including qubits, quantum gates, and the challenges of quantum measurement and decoherence. The article provides an indepth analysis of Quantum Support Vector Machines (QSVM) and Quantum Neural Networks (QNN), comparing them with their classical counterparts and highlighting their unique advantages and limitations. We investigate the promising applications of QML in material science, cryptography, and optimization problems, showcasing its potential to revolutionize drug discovery, secure communication, and complex problem-solving. The review also addresses the significant challenges facing QML, including hardware constraints, error correction, algorithm development, and integration with classical systems. By synthesizing current research and identifying future directions, this article offers a comprehensive overview of QML's transformative potential in artificial intelligence and computational science, while acknowledging the hurdles that must be overcome to fully realize its capabilities.

Refik Anadol’s AI-Based Digital Art and Its Intellectual Connotations

This article delves into the digital art produced by the internationally renowned Turkish artist Refik Anadol and his team, emerging at the intersection of diverse disciplines such as mathematics, physics, computer science, and aesthetics, within the context of its intellectual connotations. This qualitative study encompasses 26 projects featured on the Refik Anadol Studio’s website. In addition to the projects, we utilize as data sources the videos, visuals and texts that are available on the website, Anadol’s social media posts, audience comments, interviews, academic articles, and news and critiques related to his works. We analyze the works in the context of the artistic creation process, the nature of the technological collaboration, the relationship established with memory, time, space and audience, particularly in the context of the meanings they signify, and we assess the data we obtain along with their philosophical connections. In short, Anadol transforms public data such as images, sounds, and social media posts that constitute collective memory into art with the aid of digital technology capabilities, especially artificial intelligence, creating in these works molecular, fluid, transient intermediate spaces by superimposing different temporal and spatial layers, images, and realities. Through art, he opens up for discussion questions such as what is the position of the artist in the age of artificial intelligence; how art can help us understand the relationship between the virtual and the real; and what it means to experience memory in the digital age. The heterotopic spaces he constructs in his works offer utopian imagery which suggests a life based on peace, optimism, and relationship shared among humans, nature, and other forms of existence.

Numerical and Symbolic Analysis for Mathematical Problem-Solving with Maple

This study explores the versatile capabilities of Maple, a widely used mathematical software, in addressing a wide range of numerical and symbolic computations essential for scientific and engineering applications. The researchers investigated Maple's diverse suite of tools, including numerical integration, nonlinear equation solving, polynomial interpolation, symbolic integration, and various numerical methods. Through an in-depth literature review, illustrated case studies, and detailed performance evaluations, the paper demonstrates the effectiveness and accuracy of Maple's computational approaches in dealing with complex problems in various areas of applied mathematics. This study's findings underscored Maple's tremendous value as a reliable and comprehensive software package for researchers, scientists, and professionals involved in advanced mathematical analysis and scientific computing. Furthermore, the paper highlighted Maple's versatility in creating high-quality three-dimensional plots, crucial for visualizing and analyzing complex mathematical and scientific data. Using either sets or lists, the ability to display multiple surfaces in a single three-dimensional plot showcases Maple's power in data visualization and communicating complex ideas. By positioning Maple as a powerful platform for solving versatile mathematical problems, this study highlights the software's indispensable role in advancing scientific discoveries and engineering innovations.

ВЛИЯНИЕ СОВРЕМЕННОГО ИЗМЕНЕНИЯ КЛИМАТА НА ИСПАРЕНИЕ С ВОДНОЙ ПОВЕРХНОСТИ В ИЛЕ-БАЛКАШСКОМ БАССЕЙНЕ

Using the Ile-Balkash basin as an example, changes in evaporation from the water surface over the last 40 years, as well as changes in the main meteorological elements that affect evaporation, are considered. Within the framework of this work, the changes in evaporation from the water surface for 1996-2020 in relation to the previous period of 1980-1995 were assessed. It was established that over the last 20 years, there was a slight increase in evaporation at many lowland stations of the Ile-Balkash basin and it is about 1-10 %. In mountainous areas and near large water areas, such as Balkash and Ulken Almaty Lakes, there is a decrease in evaporation by about 2-9 %. The main factors influencing the change in evaporation values from the water surface were analyzed. It was concluded that the increase in evaporation from the water surface at the lowland stations in the Ile-Balkash basin is mainly due to the increase in air temperature and some increase in precipitation, and the decrease in evaporation in mountainous areas and near a water area is caused by the decrease of average wind speed and an insignificant increase in air humidity. This study can help support decision making in the agriculture and water resources sector, since evaporation from the water surface is involved in many hydrological, climatic and hydrodynamic models. Therefore, the obtained results can be used in many scientific calculations.

Диагностика тесноты междисциплинарных связей по семестровым экзаменационным оценкам студентов в период смешанных форм обучения в вузе

The analysis of the closeness of interdisciplinary connections, built with the help of exam grades received by students in previous and subsequent disciplines, according to the sequence of their study according to the curriculum. The influence of the knowledge of mathematical disciplines on the knowledge of general engineering disciplines and the dependence of knowledge between the disciplines of a special block, achieved both in full-time and distance learning, is considered. The closeness of interdisciplinary ties was established on the basis of the results of the bachelor’s examinations in the field of Computer Science and Computer Engineering, conducted both before the outbreak and during the development of the pandemic.