Computer Information Technology Research Articles

A Comprehensive Study of Datasets for Research Works in IoT Networks

Internet of Things is a trending subject in the field of Computer Science and Information Technology. When a research scholar tries to find a problem statement in the arena of IoT, he or she probably Google the phrase “Security Issues in Internet of Things”. On this day August 22, 2024, when we searched the Google with this phrase, we got about 48,40,00,000 results in 0.46 seconds. When we searched Google Scholar with the same phrase, we got about 40,70,000 results (0.52 sec). This shows that lakhs of researchers are toiling to find solutions for Security Issues in IoT. There is a new and trending way of research that is finding solutions for issues in IoT using Machine Learning and Deep Learning Models. ML and DL algorithms need large sets of Data to train and test the algorithms. This made us to take up a study on available Datasets for this research topic. When we made review of literature, in this arena of study, we found that researchers are working on only a few datasets, though numerous datasets are available freely on the internet for academic purposes. Hence in this paper we made a comprehensive study of Datasets available for research works in Internet of Things.

Career planning matters: Intelligence-based career path predictions using data mining models - A longitudinal study

It is essential for students to plan their careers because selecting the right career path shapes a person’s life. In such disciplines as computer science, information technology, and software engineering, assisting students toward appropriate employment is even more helpful. Thus, throughout the student’s education, they must evaluate their strengths to determine which professional sector corresponds to their abilities. It is for this reason that this research introduces an intelligencebased career recommendation system that will incorporate the analysis of such factors as the student’s academic performance, economic status, and demographic features to use data mining models in determining the best prospective career path to offer the student a more transparent and more informed vision and course to set on in the future. Three key aspects were addressed: first, one or another model and classifier for assessing the impact of pre-university education on the choice of a profession and, consequently, the selection of technologies were used. Second, these models accurately forecast students' careers using core courses, CGPA, and FYP data. Third, socioeconomic or demographic data was incorporated into the prediction to make it more accurate. Regarding the method of class distribution balancing, the Synthetic Minority Oversampling Technique (SMOTE) approach was used. The study reveals that variables specifying preuniversity education directly impact students’ career choices and that, employing data mining techniques, career choices could be forecasted considering academic performance and other related factors.

The Research Development Track of Internet of Things in the Application Area of Communication Technology

Computer networks, mobile media, and information and communication technology (ICT) have grown progressively, and the development of communication technology is closely connected with that of ICT. This study explored the role played by the Internet of Things as ICT develops. Accordingly, through main path analysis and keyword co-occurrence network analysis, this study was designed to learn the major research development track, cluster status, and future research and development of the Internet of Things in the application area of communication technology.

Methodology for Improving the Educational Process Based on Computer Simulation Models in Secondary Schools (In the Example of 11th Class Computer Science and Information Technology Science)

This article presents the scientific research conducted on the use of computer simulation models in the effective organization of the educational process in general education schools. Also, the stages of creating computer simulation models, recommendations on their use in teaching activities are given. Scientific publications of foreign scientists and CIS countries were analyzed

Predictors of university students’ intentions to enroll in computer programming courses: a mixed-method investigation

Students in technology majors such as Computer Science and Information Technology need to take a series of computer programming courses to graduate. Yet, not all students will persist in taking programming courses as required, and little is known about the factors influencing their enrollment intentions. Research is needed to better understand which factors predict students’ enrollment intentions for programming courses. Based on Expectancy-Value Theory, we surveyed three hundred university students in China to measure their intentions of enrolling in future programming courses and factors influencing their enrollment intentions. Mediated Multiple Indicators Multiple Causes models were run to identify the relationships between these factors and enrollment intentions. Expectancies, intrinsic value, attainment value, and utility value of the courses directly predict enrollment intentions. Peer comparison, quality of teaching, and programming experiences were found to influence enrollment intentions through expectancies and values indirectly. No gender difference was found in expectancies and enrollment intentions. Qualitative data analysis confirmed the findings from the quantitative data analysis and further revealed that course difficulty is another major factor influencing enrollment intentions. These findings have implications for supporting students' expectancies and values in computer programming and curriculum design.

Foreign Direct Investment (FDI), Computer Information Technology, Corruption Perceptions, Economic Growth, and Trade Openness in BRICS Countries

Given a Indonesia’s openness and exposure to the foreign direct investment (FDI), the current study focusses on FDI, particularly inbound from it, as one of the major local and global factors that affect its economy. There are different viewpoints regarding the this effect because some see it from a positive, optimistic point of view, while some have a negative, pessimistic view that are presented researchers impartially. The goal of this research is to examine FDI, computer information technology, corruption perceptions, economic growth, and trade openness in BRICS countries using panel data from 1990 to 2021. The data used is incoming Foreign Investment data to the BRICS countries. We use the Panel Least Square (PLS) method. Results show that computer information technology, Corruption Perceptions, Economic Growth, and Trade Openness encourage FDI in BRICS countries. The development of information and computer technology has had a significant impact on increasing FDI. The low level of corruption increases investor confidence which has a positive influence on raising the FDI in BRICS countries. Economic growth is certainly an attraction for investors to invest, supported by Trade Openness. Keywords: Foreign Direct Investment (FDI), Computer Information Technology, Corruption Perceptions, Economic Growth, Trade Openness

Application of computer information technology in food quality safety and detection

Nowadays, food safety problems have occurred frequently, and how to ensure food quality safety has become the focus of attention of the whole world. While computer information technology has become a necessary means to control food quality safety along with the continuous improvement of information degree. Computer information technology is the general term mainly used for the management and processing of information, including acquisition, processing, expression, communication, management and evaluation of information. In this paper, the application of computer information technology applied in food industry at home and abroad was mainly summarized, including query and retrieval related information of food science, stimulation of the production process to effectively control the potential risk factors, fast calculation in the process of food production and consumption, network platform design of sensory evaluation instead of complex manual work, and realization the whole process of full traceability for food industrial chain, so as to provide effective supervision channels for the government, establish food industrial traceability system, improve the information degree in food management and play the role of information technology in food safety management and realize the value.

Application of GO programming language for simulation of mass service processes

The subject matter of the article is methods and approaches to software modeling of System of Mass Services on the example of a multi-channel system with a limited queue and failures in case of its overflow. The goal of the work is to justify the feasibility of using modern computer information technologies, namely the Go programming language for modeling System of Mass Services. The following tasks were solved in the article: formulation of the researched System of Mass Services; determination of components, criteria of kinship of System of Mass Services with their software models; general overview of concurrency as a mathematical model; a description of the approaches and tools of the Go programming language. The following methods are used: Go programming language and its tools, concurrency, parallel execution. The following results were obtained: the researched task of mass service was formulated; criteria for comparing the components of System of Mass Services with the Go programming language toolkit were formed; an analysis of the feasibility of using the Go programming language for modeling System of Mass Services was carried out; received further development of tools for computer simulation of System of Mass Services; the application of concurrency approaches, their implementation in the Go programming language, to the modeling of System of Mass Services is proposed. Conclusions: The Go programming language is a very successful technology for modeling System of Mass Services. Its philosophy, way of working, as well as the built-in toolset provide ample opportunities for modeling various System of Mass Services. The use of this language is appropriate and allows to bring the behavior of the program closer to the simulated process, simplify implementation, and reduce the time required for data processing. There are great prospects for the further implementation of a software product implemented in the Go language in the field of mass service process modeling.

Formation of Competences in the Field of Information Security for Future Bachelors of Applied Informatics

The purpose of the study is to develop a model for developing competencies in the field of information security for bachelors in the field of Applied Information Science. The relevance of this problem is determined by modern requirements for enterprise employees and, accordingly, the process of their training. Demand for qualified employees who have skills not only in their field of activity, but also in areas relevant to the information society, such as information culture and the ability to provide an information enterprise.Materials and research methods. To achieve this goal, a competency-based approach was used to activate the process of developing the readiness and ability of subjects to make independent decisions, express independent judgments and at the same time participate in a common cause, create relationships with other participants in joint activities. The following methods were used in the work: analysis of pedagogical, scientific, technical and methodological literature on the research problem, systematization and generalization and visual presentation of the results.Results. As part of the study, a tabular model for the formation of competencies in the field of information security was developed based on the competency-based approach. The article reflects a model for developing competence in the field of information security using the example of additional professional competencies - 2 (the ability to take part in project management, organizing IT infrastructure and information security management) in the process of studying the discipline “Information Security”. The component blocks of the developed model are described: diagnostic, motivational, theoretical, practical and control-analytical. In accordance with the stages of this process of developing competencies and the tasks to be solved at each stage, various innovative forms and methods are presented. The results of the paper show that the process of developing competencies in the field of information security among bachelors in the “Applied Information Science” area is complex and multifaceted. Even though bachelors of applied computer science will not perform the same job functions as information security specialists, their training should be sufficient to enable them to design and build safe and reliable information systems. The pedagogical search is not completed, but it has acquired the necessary boundaries, unique centers of crystallization around which the academic discipline is designed.Conclusion. We can conclude that training specialists in the field of information security is an urgent task of modern society, the solution of which is dependent on scientific justification and identification of a set of necessary competencies that a modern specialist should have. The components of competencies in the field of information security that we have identified, the generalized tabular model of these competencies that we have proposed, as well as the stages, methods and forms of developing these competencies among bachelors of Applied Information Science require additional study. The conducted research allows us to outline ways to solve the multifaceted and complex problem of forming students’ competencies in the field of information security, taking into account modern requirements for the training of specialists not only in the field of computer science and information technology.

The development of an EU-wide nutrition and physical activity expert knowledge base to support a personalised mobile application across various EU population groups.

A healthy lifestyle comprising regular physical activity and an adequate diet is imperative for the prevention of non-communicable diseases such as hypertension and some cancers. Advances in information computer technology offer the opportunity to provide personalised lifestyle advice directly to the individual through devices such as smartphones or tablets. The overall aim of the PROTEIN project (Wilson-Barnes etal., 2021) was to develop a smartphone application that could provide tailored and dynamic nutrition and physical activity advice directly to the individual in real time. However, to create this mobile health (m-health) smartphone application, a knowledge base of reference ranges for macro-/micronutrient intake, anthropometry, biochemical, physiological and sleep parameters was required to underpin the parameters of the recommender systems. Therefore, the principal aim of this emerging research paper is to describe the process by which experts in nutrition and physiology from the PROTEIN consortium collaborated to develop the nutritional and physical activity requirements, based upon existing recommendations, for 10 separate population groups living within the EU including, but not limited to healthy adults, adults with type 2 diabetes mellitus, cardiovascular disease, excess weight, obesity and iron deficiency anaemia. A secondary aim is to describe the development of a library of 24-h meal plans appropriate for the same groups and also encompassing various dietary preferences and allergies. Overall, the consortium devised an extensive nutrition and physical activity knowledge base that is pertinent to 10 separate EU user groups, is available in 7 different languages and is practically implemented via a library of culturally appropriate, 24-h meal plans.

International Journal of Scientific Research in Computer Science, Engineering and Information Technology

In a landscape brimming with an extensive array of movies globally, navigating through the multitude of options to find films that suit one's unique preferences can prove to be a difficult assignment for viewers. The sheer volume of choices often leaves individuals feeling overwhelmed, presenting a challenge in selecting a movie that resonates with their tastes. Consequently, movie Service providers are accountable for the duty of furnishing a recommendation system that enhances the user experience by assisting them in discovering movies that complement their preferences. Previous research into recommendation systems, particularly those employing Machine Learning (ML) algorithms, has proved they were better than the conventional recommendation methods. However, there remains a requirement for further refinement, especially in circumstances in which users face difficulties in identifying movies within their favorite genres. Prolonged looks for the appropriate film can exacerbate issues such as information scarcity and chilly launch challenges. To deal with these problems effectively, we propose the implementation of a recommender system based on machine learning focused on movie genres, leveraging the algorithm known as KNN, or K-nearest Neighbors. Our proposed solution features a user-friendly interface hosted in a well-lit web application, equipped utilizing a slider bar functionality that empowers users to specify their taste in movies and get personalized suggestions for similar titles. Through the integration of user feedback and choices, our system aims to deliver customized advice that is better suited to individual interests and tastes, thereby improving the overall movie-viewing experience.

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

The Applied Research of E-commerce Technology from the Perspective of Communication Studies

Computing Education Interventions to Increase Gender Equity from 2000 to 2020: A Systematic Literature Review

Although gender parity has been achieved in some STEM fields, gender disparities persist in computing, one of the fastest-growing and highest-earning career fields. In this systematic literature review, we expand upon academic momentum theory to categorize computing interventions intended to make computing environments more inclusive to girls and women and consider how those characteristics vary by the success of the intervention. Particular attention is given to the efficacy of broadening participation and success for women in computer science, information technology, and related fields. After scrutinizing 168 relevant studies, 48 met the inclusion criteria and were included. We introduce a framework for gender equity in computing, expanding on existing research on academic and STEM momentum to encompass new domains representing social and structural momentum. Our analysis reveals the complex roles of intervention domains, strategies, goals, levels, and duration in shaping their efficacy. Implications for theory, research, and practice are discussed.

Pengaruh Live Streaming Tiktok Sebagai Aplikasi Komunikasi Digital Dan Dampaknya Pada Purchase Intention (Studi Kasus Brand Senikersku)

The digital age brings significant changes with the advent of computer information technology and the internet. Digital media provides easier and faster access to information, allowing direct interaction between individuals and organizations through various platforms, including TikTok live streaming. TikTok has become popular as a digital communication platform that allows brands to interact directly with consumers, including in the context of the Snikersku brand. This study aims to analyze the effect of TikTok live streaming as a digital communication application on consumer purchase intention for skincare products for Brand Senikersku. This research uses a descriptive analysis method with a qualitative approach, mainly through literature study. Data was collected from various sources such as books, journals, the internet, and previous research to gain a deeper understanding of the influence of TikTok live streaming on consumer purchase intention. The results showed that TikTok live streaming has a significant influence on consumer purchase intention towards Brand Senikersku. Direct interaction between brands and consumers, as well as entertainment and product visualization presented in live streaming, play an important role in increasing consumer purchase intention. In TikTok live streaming, entertainment and product visualization are key to influencing consumer purchase intentions. The combination of live interaction, entertainment, and product information increases brand awareness, builds trust, and increases sales for the Snikersku brand.

Application of computer data model in the characteristics and evolution of ceramic decorative painting

With the rapid development of computer technology, computer information technology has made intelligent transformation to all industries. It is particularly important to optimize the computerization of ceramic painting. This paper analyzes the development of ceramic decorative painting and the basic principle of computer data model, determines the method of combining ceramic decorative painting with computer data model, and establishes a computer data model for feature extraction of ceramic decorative painting. And 1015 images of self-made ceramic decorative paintings are applied to carry out simulation analysis. The results show that compared with the traditional classification algorithm based on non deep learning and the partial classification algorithm based on deep learning, the average F1 value of the hybrid neural network model is 96.4%, which is 1.5% higher than the best traditional model. This shows that the designed computer data model for feature extraction of ceramic decorative painting has a good effect on the classification and feature recognition of ceramic painting. This has laid a certain foundation for the computerized optimization of ceramic decorative painting and provided a good support for the healthy development of ceramic decorative painting in the information age.

Study on Comparative Analysis of Production of Dry Fruit Economic Forest Products Based on Big Data

The analysis of economic forest products production in Shandong Province mainly focuses on economic forest production and output value as well as economic forest plantation area, capital and labour input. By analysing the above, the basic situation of economic forest products production in Shandong Province can be understood on a macro level, laying the foundation for the subsequent study of the relevant data of the farmers, and at the same time providing a reference for the relevant management. There is an obvious gap between the production value of economic forest products in Shandong Province and that of the whole country. By combining modern information technologies such as 3S, Internet of Things, artificial intelligence, big data, cloud computing and other modern information technologies, we have established an integrated modern forest cultivation technology system ranging from the intelligent evaluation of forest terrain conditions, ecological environment simulation and simulation to the precise monitoring and diagnosis of forest growth, intelligent equipment and variable irrigation and fertilisation, etc. It is of great practical significance to expand the scale of production value of economic forest products in Shandong Province and narrow the gap with the national average level by carrying out research on the production and management efficiency of economic forest products in Shandong Province.

Students online learning experience during emergency remote teaching in higher education

For actionable insight, this study explored computer science and information technology students’ online learning experience in an emergency remote teaching during the COVID-19 pandemic in a public technical university in Ghana. A mixed method research of both quantitative and qualitative design was used to expand the evidence base. The inherent set of factors of the learning experience were determined by an exploratory factor analysis and confirmed with a multiple regression. Six factors comprising sense of concern, institutional support, effective communication, connectedness, mediated technologies, and stress levels explained 66.5% of the variance in the patterns of relationship. All factors had positive regression weights and added significantly to the prediction. Potentials identified comprised positive reactions to institutional support, improved lecturer-student interaction, active participation, accessible course contents, and moderately high future online learning expectations. The challenges included unpreparedness, unreliable Internet, high cost of data, and incidental learning design and pedagogy. Evidently, the higher education landscape shifted during the pandemic in obvious ways to merit further studies and reflective online learning administration to inform robust technology-oriented post-pandemic practices.

Employers Feedback on the Performance of the College of Computing Studies, Information and Communication Technology (CCSICT) Graduates

This study is an assessment of the employer’s feedback on the performance of College of Computing Studies, Information and Communication Technology (CCSICT) graduates in the workplace with respect to quality and quantity of work, job knowledge, and working relationships.
 The study used a descriptive research method utilizing the employers of employed graduates as key informants. The respondents were purposely chosen who are managers or supervisors of companies and institutions of the graduates. Data from the 98 employers were gathered using a survey questionnaire. Weighted mean, frequency count, percentage, and rank were used to interpret the result of the survey.
 Results showed that graduates are employed in the Information and Communication Technology (ICT) industry. This means that the graduates have jobs related to their course. The majority of employers who participated in the survey are from the private sector. Employers were very satisfied with the graduate's quality and quantity of work, job knowledge, and work relationship. The top attributes used to evaluate the graduates' performance were the quantity of work and the working relationships. The findings suggested putting emphasis on written and oral communication skills and improving networking, troubleshooting skills, and graphics and design skills.

АНАЛІЗ СТАНУ СВІТОВОГО РИНКУ ПРАЦІ В УМОВАХ ГЛОБАЛЬНОЇ ДІДЖИТАЛІЗАЦІЇ

In the context of the Fourth Industrial Revolution, there is a continuous transformation of processes in the labor market. Digitalization of society affects the structure of the employment sector, when some professions become obsolete due to automation of work processes. At the same time, there is a demand for new competencies aimed at working in an online environment. The purpose of this article is to analyze current global economic and technological trends affecting the transformation of the labor market and the formation of new socio-economic relations in the context of the formation of the digital economy. The author draws attention to changes in the nature of work and forms of work activity, requirements for professional skills and abilities. It shows how changes related to the digitalization of the economy directly affect the issues of training and retraining of the most popular specialists. The article systematizes the main global trends in the labor market caused by the digitalization of the economy and the widespread introduction of Information Computer Technologies. In the course of the research, the author revealed that digitalization of the economy has the opposite impact on labor markets, leading to multidirectional processes in the medium term, which is expressed in the reduction of low-skilled jobs, an increase in the level of robotization of production, differentiation of forms of Organization of production, revision of types of economic relations. As a result of digital transformation in industry, it became possible to produce products with higher quality, and the human factor became less significant in many production and technology sectors. The negative consequences of digitalization include the disappearance of a large number of professions, the release of workers, and an increase in unemployment. The author concludes that digital inequality in regional labor markets, with its further development, may negatively affect ensuring the country's economic sovereignty. At the same time, the results of the study suggest that no automation can completely replace a person, so forecasting total unemployment due to the robotization of production is temporary.

Enhanced Empowering Futures through Online Job Portal

This research aims to develop a job web portal for the students in the Faculty of Computer Science and Information Technology. The main aims of this portal are to connect with industries and act as an online recruitment tool to support students in finding the right IT job after graduation. Furthermore, this system enhances the understanding of the concept and importance of the job portal for students in universities. A survey was conducted to identify the students’ problems with the existing portal of the faculty and to gather their requirements, which can be incorporated into the portal to be developed.