REENGINEERING TECHNIQUE ADAPTATION OF LEGACY SOFTWARE SYSTEMS

В статье рассматривается адаптация методики реинжиниринга унаследованных систем. Приводится обзор подходов к реинжинирингу. Несмотря на то, что термин «реинжиниринг» в первую очередь относится к изменению бизнес процессов, он удачно подходит и к модернизации программного обеспечения. Обосновывается необходимость адаптации методики. В статье описывается применение адаптированной методики на примере реинжиниринга программного комплекса для прогнозных исследований ТЭК. Приведен исторический обзор версий ПК «ИНТЭК» и описаны поэтапно все шаги проведения его реинжиниринга на основе агентно-сервисного подхода The article presents an adaptation of the legacy systems reengineering technique. An overview of approaches to reengineering is given. Although the term “reengineering” primarily refers to changing business processes, it is well suited to software development. The necessity of adapting the method has been substantiated. The article describes the application of the described methodology on the example of software complex reengineering for predictive research of the fuel and energy complex. A historical overview of the current problem is given and all stages of INTEC PC reengineering are described step by step

Factors Influencing Teacher Efficacy in Inclusive Education

The present research attempted to examine the relative importance of student-related and school-related factors in accounting for teacher efficacy in inclusive education. The research adopted a predictive research design, and the sample of the research consisted of teachers (N = 292) working in public middle schools in the province of Niğde in the Central Anatolia Region of Turkey. To determine the factors influencing teacher efficacy in inclusive education, Teacher Demographic Information Questionnaire and Teacher Efficacy for Inclusive Practices scale were used. In the research, multiple regression analysis was conducted to examine how well each set of independent variables — student-related factors and school-related factors — predicted teacher efficacy in inclusive education. According to the findings, student-related and school-related factors significantly influence teacher efficacy in inclusive education. Regarding the student-related factors, parental involvement, among other variables, was the most substantial predictor of teacher efficacy in inclusive education. Also, in terms of school-related factors, class size was the most substantial predictor of teacher efficacy in inclusive education.

The Predictive Research of Dynamic Milling Force Based on Data Mining

In this paper, surface accuracy of the work-piece was improved by mining large amounts of machining data and obtaining potentially valuable information. By using data mining technology, a dynamic milling force prediction model has been established to keep with its working. The model was developed by a combination of Regression Analysis and RBF Neural Network. The internal relation of the data were analyzed in this study, such as milling force, cutting parameters, temperature, vibration and surface quality et.al, and the methods of Cluster Analysis and Correlation Analysis was used to extract and induct dynamic milling force variations on the effects with different situations. The results suggest that the proposed dynamic milling force model had a better prediction effect, which ensure production quality, reduce the occurrence of chatter and provide a more accurate basis for selecting process parameters.

Risk Prediction of Sports Events Based on Gray Neural Network Model

In this paper, neural network is used as a predictive network modeling method, with the support of MATLAB Neural Toolbox, based on the implementation of predictive research. A risk warning model is designed for sports events relying on neural network s to reduce the losses caused by risk accidents. First, the article introduces a literature review of sports event risk warning, combined with the sports event risk warning index system; summarizes the main advantages of using neural network and fuzzy theory; and establishes a sports event risk warning model relied on neural network. The article starts with the application of gray network in sports risk warning design, starting from the necessity of applying gray network in sports event risk warning; analyzes the risk warning model and operation process; and conducts sample data verification to verify this power of the model. Practice has proved that the application of gray neural network in sports events can play a role in risk warning.

Research on the strategy of intelligent analysis to improve sports person psychological experience in the era of artificial intelligence

Artificial intelligence (AI) is an excellent potential technology that is evolving day-to-day and a critical avenue for exploration in the world of computer science & engineering. Owing to the vast volume of data and the eventual need to turn this data into usable knowledge and realistic solutions, artificial intelligence approaches and methods have gained substantial prominence in the knowledge economy and community world in general. AI revolutionizes and raises athletics to an entirely different level. Although it is clear that analytics and predictive research have long played a vital role in sports, AI has a massive effect on how games are played, structured, and engaged by the public. Apart from these, AI helps to analyze the mental stability of the athletes. This research proposes the Artificial Intelligence assisted Effective Monitoring System (AIEMS) for the specific intelligent analysis of sports people’s psychological experience. The comparative analysis suggests the best AI strategies for analyzing mental stability using different criteria and resource factors. It is observed that the growth in the present incarnation indicates a promising future concerning AI use in elite athletes. The study ends with the predictive efficiency of particular AI approaches and procedures for further predictive analysis focused on retrospective methods. The experimental results show that the proposed AIEMS model enhances the athlete performance ratio of 98.8%, emotion state prediction of 95.7%, accuracy ratio of 97.3%, perception level of 98.1%, and reduces the anxiety and depression level of 15.4% compared to other existing models.

Religious Fundamentalism as the Predictor of Secondary Students’ Obedience to Authority During Pandemic

This study aims to evaluate the levels of SMPN 1 Ambulu Jember ( Junior High School 1 of Ambulu, Jember Regency) students’ obedience to authority, ascertain the levels of religious fundamentalism of the SMPN 1 Ambulu Jember students, and determine whether religious fundamentalism affects students’ obedience to authority. This study is quantitative predictive research, employing descriptive analysis and linear regression on the population of SMPN 1 Ambulu Jember students. The subjects were 139 students, chosen using proportional random sampling and simple random sampling. As for the instrumentals, the study used Obedient-Disobedient Tendency Scale with a reliability of 0.911 and Religious Fundamentalism Scale with a reliability of 0,758. The findings demonstrated that 52% of the subjects possess a low level of obedience to authority, whereas 55% of them have a high level of religious fundamentalism. The R-value obtained by the variable of hardiness on the variable of happiness was quite significant, namely 0.825. The R-square value of 0.680 also indicated that religious fundamentalism played a role in obedience to authority for 68% and 32% while having other factors as well. The significance value of 0.00 < 0.05 means that the research hypothesis is accepted. Keywords: religious fundamentalism, obedience, students

The effect of supervisor's authority on auditor's response

The purpose of this study was to examine the effect of referent power, expert power, legitimate power, reward power, and coercive power as independent variables on performance improvement and impression management as the dependent variable. This study aims to answer exploratory, descriptive, explanatory, and predictive research using a survey method in the form of a questionnaire containing a list of statements that will be given to respondents to be filled in to obtain information from respondents and data processing using the WarpPLS 5.0 application. The results showed that referent power, reward power, and coercive power affected performance improvement and impression management, while expert power and legitimate power did not affect performance improvement and impression management.

International studies in an unpredictable world: still avoiding the difficult problems?

We revisit and empirically evaluate crucial yet under-examined arguments articulated in “God Gave Physics the Easy Problems” (2000), the authors of which emphasized that, in International Relations (IR) predictions, predominant nomothetic approaches should be supplemented with concrete scenario thinking. We test whether the IR predictive toolkit is in fact dominated by nomothetic generalizations and, more broadly, map the methodological profile of this subfield. We build on the TRIP database, supplementing it with extensive original coding to operationalize the nuances of predictive research. In particular, we differentiate between nomoscopic predictions (predictive generalizations) and idioscopic predictions (predictions for concrete situations), showing that this distinction is not reducible to other methodological cleavages. We find that even though in contemporary IR an increasing number of articles seek to provide predictions, they consistently avoid predictions about concrete situations. The proportion of idioscopic predictions is stably small, with an even smaller proportion of predictions that develop concrete narratives or specify any determinate time period. Furthermore, those idioscopic studies are mostly limited to a niche with specialized themes and aims. Thus, our research shows that the critical claims from 20 years ago are still relevant for contemporary IR, as the “difficult problem” of developing predictive scenarios is still consistently overlooked in favor of other objectives. Ultimately, the types of predictions that IR scholars develop depend on their specific aims and constraints, but the discipline-wide result is a situation in which international studies’ ambition to provide predictions grows, but they tend to reproduce the same limitations as they did in 2000.