• The Journal of Korean Academy of Sensory Integration
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• v.19 no.3
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• pp.44-60
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• 2021

Objective : The purpose of this study was to identify the characteristics of domestic single-subject research related to the participation of students with intellectual disabilities in classes. Methods : We investigated a total of five papers to determine the features and qualitative levels of the papers being analyzed. Results : A total of 12 subjects were studied, and experiments were conducted at all stages. All research used a multiple baseline design. The independent variables were the positive behavior support approach (2), the strength-oriented activities approach, the self-decision teaching and learning model approach, and the self-monitoring approach. As a dependent variables, there were four pieces set up exclusively for class participation behavior, and one that was set up mixed with class interruptions behaviors. The qualitative level of the studies to be analyzed was 100% of the high level. Conclusion : Through this study, single-subject studies that applied interventions related to participation in class for intellectual disabilities in elementary schools have confirmed that effective interventions were applied and that the quality levels were reliable.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.260-268
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• 2022

The article considers the training, competitiveness of specialists, professional mobility, professionalism and competence of specialists in the context of distance learning. The advantages of distance learning are shown. The characteristic features of distance learning in the preparation of students and in the implementation of these technologies in the educational process of higher educational institutions are determined. Competitiveness, professional mobility, professionalism and competence of a specialist are qualities that determine a person's life and work success. Professional mobility is interpreted as a systemic quality of a specialist's personality, which includes a whole range of knowledge, skills, abilities, personal qualities, value orientations, and so on. The vision of mobility of specialists by foreign scientists is presented. It is noted that the classification of professional mobility presented in the article makes it possible to organize various movements from a single position, to present them as separate manifestations of the general process of professional and pedagogical mobility, to determine which type of mobility ensures the performance of certain social functions. It was found that mobility can be differentiated into differentiated and intergeneration. According to the subject, individual and group mobility are distinguished; according to the direction - internal and external. The classification of employees according to their attitude to mobility is shown, which can be divided into the following groups: actually mobile; potentially mobile; actually stable; potentially stable.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.7-13
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• 2023

This study investigated the criteria for evaluating the impact of artificial intelligence services. The study classified AI evaluation targets into two areas: AI service and AI technology, and identified influence, sustainability, efficiency, effectiveness, and appropriateness as potential evaluation criteria. The time aspect of AI service evaluation was divided into pre-evaluation and post-evaluation, with pre-evaluation focused on reviewing items during development and design. The AI service area was classified into public, private, and mixed forms, and the impact assessment was classified as vertical or horizontal. The application of AI services was divided into normative and regulatory aspects, and the purpose of the evaluation could be impact or process evaluation. The subject and field of the AI service could also be used for classification purposes. The results of this study can be used to support the creation of AI service impact policies and countermeasures. However, further research is needed to develop specific indicators based on the criteria identified in this study to evaluate the impact of AI services.

• Korean Journal of Childcare and Education
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• v.19 no.1
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• pp.111-126
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• 2023

Objective: The purpose of the current research is to collect basic data to diagnose the current status and to foresee the future research trends of young children's parent education programs published in South Korea from 2001 to 2020. Methods: Data collection was made out of RISS of Korea. Excel 2016 was used to categorize 210 finally filtered and collected data which included academic journal articles, MA/PhD dissertations, and funded research reports according to analysis criteria by publication year/5-year-term, research theme, research method, and researchers' academic area. Results: Annual/5-year-term analysis shows increasing trends of parent education programs for young children. Quantitative research was the most frequently implemented method, followed by literature reviews, qualitative research, and mixed research method in order. In research theme, parent-competency reinforcement program was the most frequently implemented theme followed by parent education, socio-emotional issue, special education for young children with special needs, family support, early childhood sex education, and program analysis in order. Education area showed the most active participation in parent education program for young children in comparing with other academic areas in research field. Conclusion/Implications: Research trends of young children's parent education programs showed steady increase in their amount, frequency, and diversity as well. Minority parents need more attentions for providing the next young generation's educational equality. Parent programs during COVID-19 need to gain more research attentions as well as care-giving grandparents, social workers, and public health care helpers in child caring service areas in order to alleviate low-birth rate.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.307-315
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• 2022

The purpose of this study was to design a training program for pre-service elementary teachers, incorporating the concepts of extended reality technologies. This program contained the basic skills necessary for them to utilize in their future classrooms. To accomplish this, 12 undergraduate students of various majors enrolled in one of Korea's national universities of education were selected as research subjects. For a total of 6 times over 6 weeks, they participated in a training program learning the basic concepts of virtual, augmented, and mixed reality, as well as creating their own education software to use in simulated classes. To improve the quality of future research efforts, this study found it would be beneficial to: 1) expand the relevant support equipment, 2) provide students with preliminary, background knowledge of text-based programming, 3) introduce short-term, more intensive training, and 4) improve the survey methods for this research.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.2-5
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• 2022

With the advent of deep learning and the rapid development of ICT (Information and Communication Technology), research using artificial intelligence is being actively conducted in various fields of society such as politics, economy, and culture and so on. Deep learning-based artificial intelligence technology is subdivided into various domains such as natural language processing, image processing, speech processing, and recommendation system. In particular, as the industry is advanced, the need for a recommendation system that analyzes market trends and individual characteristics and recommends them to consumers is increasingly required. In line with these technological developments, this paper extracts and classifies attribute information from structured or unstructured text and image big data through deep learning-based technology development of 'language processing intelligence' and 'image processing intelligence', and We propose an artificial intelligence-based 'customized fashion advisor' service integration system that analyzes trends and new materials, discovers 'market-consumer' insights through consumer taste analysis, and can recommend style, virtual fitting, and design support.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.701-716
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• 2022

This study investigated the distribution behaviors of PM2.5 and PM10 at two air quality monitoring sites, Go-eup (GO) and Backseokeup (BS), located in Yangju City, South Korea. The amounts of emissions sources of pollutants were analyzed based on the Clean Air Policy Support System (CAPSS), and the contribution rates of neighboring cities were enumerated in Yangju. Yangju has a geological basin structure, and it is a city with mixed urban and rural characteristics. The emission concentration of particulate matter was affected by geological and seasonal factors for all sites observed in this study. Therefore, these factors should be considered when establishing policies related to particulate matter. Because the official GO and BS station sites in Yangju are both situated in the southern part of the city, the representativeness of both stations was checked using correlation analysis for the measurement of PM2.5 and PM10 by considering two more sites-those of Bongyang-dong (BY) and the Gumjun (GJ) industrial complex. The data included discharge amounts for business types 4 and 5, which were not sufficiently considered in the CAPSS estimates. Because the 4 and 5 types of businesses represent over 92.6% of businesses in this city, they are workplaces in Yangju that have a significant effect on the total air pollutant emission. These types of businesses should be re-inspected as the main discharge sources in industry, and basic data accumulation should be carried out. Moreover, to manage the emission of particulate matter, attainable countermeasures for the main sources of these emissions should be prepared in a prioritized fashion; such countermeasures include prohibition of backyard burning, supervision of charcoal kilns, and management of livestock excretions and fugitive dust in construction sites and on roads. The contribution rates by neighboring cities was enumerated between 6.3% and 10.9% for PM2.5. Cooperation policies are thought to be required with neighboring cites to reduce particulate matter.

• Geomechanics and Engineering
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• v.29 no.4
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• pp.421-434
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• 2022

In the present study, reference samples were prepared using ore preparation facility tailings taken from the copper mine (Kure, Kastamonu), Portland cement (PC) in certain proportions (3 wt%, 5 wt%, 7 wt%, 9wt% and 11 wt%), and water. Then natural zeolite taken from the Bigadic Region was mixed in certain proportions (10 wt%, 20 wt%, 30 wt% and 40 wt%) for each cement ratio, instead of the PC, to prepare zeolite-substituted CPB samples. Thus, the effect of using Zeolite instead of PC on CPB's strength was investigated. The obtained CPB samples were kept in the curing cabinet at a temperature of 25℃ and at least 80% humidity, and they were subjected to the Uniaxial Compressive Strength (UCS) test at the end of the curing periods of 3, 7, 14, 28, 56, and 90 days. Except for the 3 wt% cement ratio, zeolite substitution was observed to increase the compressive strength in all mixtures. Also, the liquefaction risk limit for paste backfill was achieved for all mixtures, and the desired strength limit value (0.7 MPa) was achieved for all mixtures with 28 days of curing time and 7 wt%, 9 wt%, 11 wt% cement ratios and 5% cement - 10% zeolite substituted mixture. Moreover, the limit value (4 MPa) required for use as roof support was obtained only for mixtures with 11% cement - 10% and 20% zeolite content. Generally, zeolite substitution seems to be more effective in early strength (up to 28th day). It has been determined that the long-term strength losses of zeolite-substituted paste backfill mixtures were caused by the reaction of sulfate and hydration products to form secondary gypsum, ettringite, and iron sulfate.

• Computers and Concrete
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• v.33 no.2
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• pp.175-193
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• 2024

Researchers have embarked on an active investigation into the feasibility of adopting alternative materials as a solution to the mounting environmental and economic challenges associated with traditional concrete-based construction materials, such as reinforced concrete. The examination of concrete's mechanical properties using laboratory methods is a complex, time-consuming, and costly endeavor. Consequently, the need for models that can overcome these drawbacks is urgent. Fortunately, the ever-increasing availability of data has paved the way for the utilization of machine learning methods, which can provide powerful, efficient, and cost-effective models. This study aims to explore the potential of twelve machine learning algorithms in predicting the tensile strength of geopolymer concrete (GPC) under various curing conditions. To fulfill this objective, 221 datasets, comprising tensile strength test results of GPC with diverse mix ratios and curing conditions, were employed. Additionally, a number of unseen datasets were used to assess the overall performance of the machine learning models. Through a comprehensive analysis of statistical indices and a comparison of the models' behavior with laboratory tests, it was determined that nearly all the models exhibited satisfactory potential in estimating the tensile strength of GPC. Nevertheless, the artificial neural networks and support vector regression models demonstrated the highest robustness. Both the laboratory tests and machine learning outcomes revealed that GPC composed of 30% fly ash and 70% ground granulated blast slag, mixed with 14 mol of NaOH, and cured in an oven at 300°F for 28 days exhibited superior tensile strength.

• Safety and Health at Work
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• v.14 no.4
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• pp.445-450
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• 2023

Background: The impact of COVID-19 infection on workers' work function persists even after the acute phase of the infection. We studied this phenomenon in Japanese workers. Methods: We conducted a one-year prospective cohort study online, starting with a baseline survey in December 2020. We tracked workers without baseline work functioning impairment and incorporated data from 14,421 eligible individuals into the analysis. We estimated the incidence rate ratio for new onset of work functioning impairment due to COVID-19 infection during follow-up, using mixed-effects Poisson regression analysis with robust variance. Results: Participants reporting infection between January and December 2021 showed a significantly higher incidence of new work functioning impairment (adjusted incidence rate ratio: 2.18, 95% confidence interval: 1.75-2.71, p < 0.001). The formality of the recuperation environment correlated with a higher risk of work functioning deterioration in infected individuals (p for trend <0.001). Conclusion: COVID-19-infected workers may continue to experience work difficulties due to persistent, post-acute infection symptoms. Companies and society must urgently provide rehabilitation and social support for people with persistent symptoms, recognizing that COVID-19 is not just a transient acute infection.