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Data science is a science that is currently very popular and can be applied in various industries. Of course, the need for proficient people in this field is growing in demand by many businesses, including large corporations. Data science is a science that combines expertise in a particular field of science with programming, mathematics, and statistics skills. The goal is to extract knowledge or information from data. The problem that usually occurs in the data science process is at the data modeling stage, namely the accuracy of the mathematical model that will be used to obtain the estimated parameter values. To overcome this problem, this research was conducted to test the correctness of analytic derivatives in mathematical models and conduct data modeling using analytic derivatives that have been tested to obtain the estimated value of each parameter. The validation process is carried out using an analytic and numeric gradient comparison. If the comparison of the two values is close to zero, then the analytical derivatives used are correct. The parameter estimation method used is the Maximum Likelihood Estimation. In this research, it was concluded that the value of the analytic gradient is the same or close to the numeric gradient value for each parameter so that the analytic derivatives are correct and can be used for the next stage. With the results of this research, the expected implication is to get more accurate data modeling so that the conclusions obtained are more precise. [ABSTRACT FROM AUTHOR]

This article, as an example of the integration of disciplines, is focused on the issues of combining knowledge, skills and practical experience at all levels of training of software engineering specialists and synthesizing knowledge directed to specific field goals are discussed. At the same time, modern information and communication technologies are considered as a means of integration that connects mathematics and computer sciences with each other. [ABSTRACT FROM AUTHOR]

Embedding technology in teaching and learning (T&L) becomes necessary, especially during open distance learning (ODL). Mobius is a math-based online platform that provides interactive T&L applications to meet the ODL requirements. This platform is built on Maple software with intelligent grading and response, where students can attempt several random questions within the same subtopic and get an immediate response. However, students' response to this platform is the primary concern. Thus, this study analyzed the students' feedback on using Mobius for Calculus I. The content designs, implementation, and students' experience using this platform are discussed. The respondents in this study were 20 non-mathematical students in the second semester of Bachelor of Information Technology, Faculty of Computer and Mathematical Sciences, UiTM Shah Alam. Students were given access to Mobius and required to complete all the exercises on selected topics in Calculus I - techniques of differentiation, chain rule, techniques of integration and application of integration. Finally, their feedback is recorded and analyzed. The result shows that most students showed positive feedback on using Mobius to improve their Calculus I understanding and recommended using Mobius in T&L sessions. [ABSTRACT FROM AUTHOR]

In this paper an advanced stochastic approach based a lattice rule with improved generating vector has been obtained and studied. The Unified Danish Eulerian Model (UNI-DEM) is a key element in our investigation since it is one of the most advanced large-scale mathematical models that describes adequately all physical and chemical processes. The calculations are done in a large spatial domain, which covers completely the European region and the Mediterranean, for certain time period. What is more, it studies the transportation of a number of pollutants and all these make it a perfect case study. The paper compares the described lattice rule and demonstrates its superiority over the plain Monte Carlo approach and Fibonacci based lattice rule. The proposed approach is robust and computationally efficient in estimating multidimensional integrals and thus sensitivity indices, which is vital in scientific computing. [ABSTRACT FROM AUTHOR]

Cloud users and service providers are the leading players in the cloud computing environment. This environment comprises data centers, hosts, agents and virtual machines. The cloud user's application of varied loads is leased on the provider's resources. Scientific applications are large-scale complex workflow problems that demand more computing power. The cloud fulfills the workflow requirements of huge availability and increased computational power. One of the most crucial issues of cloud computing is scheduling tasks for the system's effective functioning. This paper reviews several existing task-scheduling techniques based on diverse metrics. This work will help the investigators to gain a better understanding of task scheduling techniques. In order to boost an algorithm's performance, a few strategies are offered. [ABSTRACT FROM AUTHOR]

The paper presents the analysis results of scientometric data of modern Russian research in Computer science to form and evaluate thematic trends, as well as determine their position relative to the trends of world scientific publications. The study is based on the methods of scientometric analysis of bibliographic data to reveal the thematic distribution of scientific publications, including in retrospect. The bibliographic database of the scientific electronic library eLIBRARY.Ru, the Scopus database, as well as the annual reports "Research fronts" published by Clarivate Analytics were used as data sources. In the course of the study, an examination of scientific publications was carried out, and internal research fronts were identified. A conclusion is drawn about the catching-up position of Russian research in the field of Computer sciences, and an assumption is made about the thematic areas that will be relevant in Russia in the coming years. [ABSTRACT FROM AUTHOR]

This research was conducted to obtain Faculty Quality assurance at the Faculty of Computer Science, Santo Thomas Catholic University. The scope includes the vision and mission, curriculum, journals and research on lecturers. The Faculty's Vision and Mission and the Study Program's Vision and Mission aim to have future directions and goals to be better and achieve for the future of the Faculty of Computer Science. RAD is a combination of various structured techniques with prototyping techniques and joint application development techniques to accelerate system or application development. From the definitions of this RAD concept, it can be seen that application development using the RAD method can be done in a relatively faster time. With the quality assurance application system at the Faculty of Computer Science, Santo Thomas Catholic University, it can be made efficiently. Programs that are made can be implemented for assessment and arranged in such a way as to be sequential values that make faculty quality guidelines. [ABSTRACT FROM AUTHOR]

The present situation is investigated and the relevance of the stage of prototyping of user interfaces as intermediary of human-machine interaction in the process of software development is substantiated. The necessity of improving the methodology of teaching graphic disciplines and the relevance of studying the technologies of «UX/UI Design» in the process of professional training of future bachelor's in computer science as a perspective direction in view of the demands of the labor market and as a factor that raises the level of motivation of students for professional activity in general and on the formation of graphic competence. The methodical provision of the course is described, the structure and content of the theoretical and practical part of the course are presented, which is focused on the study of the technology of «UX/UI Design». The mathematical modeling of the discipline learning process «UX/UI Design» is described. The use of mathematical modeling to develop a model for training the discipline «UX/UI Design» provided the basis for the creation of a system of scientific-methodical and computer support of pedagogical activities and outlined the perspectives of designing a pedagogical technology for the formation of graphic competence of future Bachelor of Computer Sciences in the course of studying the discipline «UX/UI Design». [ABSTRACT FROM AUTHOR]

The article examines probabilistic logic as applied to computer science and its problems. Probabilistic logic is treated as a generalization of formal logic. In many cases, the application of probabilistic logic occurs under conditions of uncertainty. Probabilistic logic uses a model approach. Computer science also uses a model approach. Probabilistic logic describes uncertainty using quantitative values of probability. Computer science describes uncertainty using the concept of information entropy. The article introduces the concept of informational logical uncertainty. The article finds a connection between probabilistic logic and entropy. This connection makes it possible to build a probabilistically logical model. This connection makes it possible to create probabilistically logical modeling, which is in many ways an analogue of information modeling. The purpose of probabilistically logical modeling is to overcome information and logical uncertainty. [ABSTRACT FROM AUTHOR]