• The Mathematical Education
• /
• v.62 no.3
• /
• pp.435-455
• /
• 2023

This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12spc
• /
• pp.664-674
• /
• 2021

The relevance of this scientific research is determined by the negative impact of the COVID-19 pandemic on the current trends and dynamics of world tourism development. This article aims to identify patterns of development of the modern tourist market, analysis of problems and prospects of development in the context of the COVID-19 pandemic. Materials and methods. General scientific methods and methods of research are used in the work: analysis, synthesis, comparison, analysis of statistical data. The analysis of the viewpoints of foreign and domestic authors on the research of the international tourist market allowed us to substantiate the actual directions of tourism development due to the influence of negative factors connected with the spread of a new coronavirus infection COVID-19. Economic-statistical, abstract-logical, and economic-mathematical methods of research were used during the process of study and data processing. Results. The analysis of the current state of the tourist market by world regions was carried out. It was found that tourism is one of the most affected sectors from COVID-19, as, by the end of 2020, the total number of tourist arrivals in the world decreased by 74% compared to the same period in 2019. The consequence of this decline was a loss of total global tourism revenues by the end of 2020, which equaled $1.3 trillion. 27% of all destinations are completely closed to international tourism. At the end of 2020, the economy of international tourism has shrunk by about 80%. In 2020 the world traveled 98 million fewer people (-83%) relative to the same period last year. Tourism was hit hardest by the pandemic in the Asia-Pacific region, where travel restrictions are as strict as possible. International arrivals in this region fell by 84% (300 million). The Middle East and Africa recorded declines of 75 and 70 percent. Despite a small and short-lived recovery in the summer of 2020, Europe lost 71% of the tourist flow, with the European continent recording the largest drop in absolute terms compared with 2019, 500 million. In North and South America, foreign arrivals declined. It is revealed that a significant decrease in tourist flows leads to a massive loss of jobs, a sharp decline in foreign exchange earnings and taxes, which limits the ability of states to support the tourism industry. Three possible scenarios of exit of the tourist industry from the crisis, reflecting the most probable changes of monthly tourist flows, are considered. The characteristics of respondents from Ukraine, Germany, and the USA and their attitude to travel depending on gender, age, education level, professional status, and monthly income are presented. About 57% of respondents from Ukraine, Poland, and the United States were planning a tourist trip in 2021. Note that people with higher or secondary education were more willing to plan such a trip. The results of the empirical study confirm that interest in domestic tourism has increased significantly in 2021. The regression model of dependence of the number of domestic tourist trips on the example of Ukraine with time tendency (t) and seasonal variations (Turˆt = 7288,498 - 20,58t - 410,88∑5) it forecast for 2020, which allows stabilizing the process of tourist trips after the pandemic to use this model to forecast for any country. Discussion. We should emphasize the seriousness of the COVID-19 pandemic and the fact that many experts and scientists believe in the long-term recovery of the tourism industry. In our opinion, the governments of the countries need to refocus on domestic tourism and deal with infrastructure development, search for new niches, formats, formation of new package deals in new - domestic - segment (new products' development (tourist routes, exhibitions, sightseeing programs, special rehabilitation programs after COVID) -19 in sanatoriums, etc.); creation of individual offers for different target audiences). Conclusions. Thus, the identified trends are associated with a decrease in the number of tourist flows, the negative impact of the pandemic on employment and income from tourism activities. International tourism needs two to four years before it returns to the level of 2019.

• Clean Technology
• /
• v.25 no.1
• /
• pp.81-90
• /
• 2019

A dielectric barrier discharge (DBD) plasma reactor packed with $Ni-CeO_2/{\gamma}-Al_2O_3$ catalyst was used for the dry ($CO_2$) reforming of propane (DRP) to improve the production of syngas (a mixture of $H_2$ and CO) and the catalyst stability. The plasma-catalytic DRP was carried out with either thermally or plasma-reduced $Ni-CeO_2/{\gamma}-Al_2O_3$ catalyst at a $C_3H_8/CO_2$ ratio of 1/3 and a total feed gas flow rate of $300mL\;min^{-1}$. The catalytic activities associated with the DRP were evaluated in the range of $500{\sim}600^{\circ}C$. Following the calcination in ambient air, the ${\gamma}-Al_2O_3$ impregnated with the precursor solution ($Ni(NO_3)_2$ and $Ce(NO_3)_2$) was subjected to reduction in an $H_2/Ar$ atmosphere to prepare $Ni-CeO_2/{\gamma}-Al_2O_3$ catalyst. The characteristics of the catalysts were examined using X-ray diffraction (XRD), transmission electron microscopy (TEM), field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectrometry (EDS), temperature programmed reduction ($H_2-TPR$), temperature programmed desorption ($H_2-TPD$, $CO_2-TPD$), temperature programmed oxidation (TPO), and Raman spectroscopy. The investigation revealed that the plasma-reduced $Ni-CeO_2/{\gamma}-Al_2O_3$ catalyst exhibited superior catalytic activity for the production of syngas, compared to the thermally reduced catalyst. Besides, the plasma-reduced $Ni-CeO_2/{\gamma}-Al_2O_3$ catalyst was found to show long-term catalytic stability with respect to coke resistance that is main concern regarding the DRP process.

• Journal of Korean Elementary Science Education
• /
• v.41 no.4
• /
• pp.740-753
• /
• 2022

This study was conducted to develop and apply an out-of-school STEAM program model based on Social-Emotional Learning (SEL) for underprivileged students in the lower grades. To this end, a STEAM program based on SEL was developed, with the following characteristics. First, by integrating traditional STEAM learning elements and SEL elements, a structured program was designed with consistent stages, including mindfulness meditation→present an authentic situation→creative design→emotional experiences→reflection. Second, the program was structured so that elementary school students could develop mathematical thinking and scientific inquiry skills in problem-solving situations in daily life. Third, the detailed themes for each STEAM program involved storytelling-based problem situations, as well as activities centered on play and sympathy to reflect the educational needs of underprivileged students. From these characteristics, a total of five programs were developed and applied to 16 teachers and 354 lower-grade elementary school students in 16 community children centers nationwide. The results were as follows. First, while students' satisfaction with the STEAM program was 4.16, there were no significant differences in STEAM satisfaction according to gender. Second, while all students' interest and self-efficacy, which was one of sub factors of STEAM attitude, were significantly improved, no significant difference was seen in STEAM attitudes according to gender. Third, although students' SEL competencies were not significantly improved, relationship skills, which were among the sub factors of SEL competencies, were significantly improved, and there were no significant differences in SEL competencies according to gender. From these results, a discussion on the effect of the out-of-school STEAM program for underprivileged students and directions for follow-up studies was suggested.