• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.19-27
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• 2022

Across the world, 'housing' comprises a significant portion of wealth and assets. For this reason, fluctuations in real estate prices are highly sensitive issues to individual households. In Korea, housing prices have steadily increased over the years, and thus many Koreans view the real estate market as an effective channel for their investments. However, if one purchases a real estate property for the purpose of investing, then there are several risks involved when prices begin to fluctuate. The purpose of this study is to design a real estate price 'return rate' prediction model to help mitigate the risks involved with real estate investments and promote reasonable real estate purchases. Various approaches are explored to develop a model capable of predicting real estate prices based on an understanding of the immovability of the real estate market. This study employs the LSTM method, which is based on artificial intelligence and deep learning, to predict real estate prices and validate the model. LSTM networks are based on recurrent neural networks (RNN) but add cell states (which act as a type of conveyer belt) to the hidden states. LSTM networks are able to obtain cell states and hidden states in a recursive manner. Data on the actual trading prices of apartments in autonomous districts between January 2006 and December 2019 are collected from the Actual Trading Price Disclosure System of the Ministry of Land, Infrastructure and Transport (MOLIT). Additionally, basic data on apartments and commercial buildings are collected from the Public Data Portal and Seoul Metropolitan Government's data portal. The collected actual trading price data are scaled to monthly average trading amounts, and each data entry is pre-processed according to address to produce 168 data entries. An LSTM model for return rate prediction is prepared based on a time series dataset where the training period is set as April 2015~August 2017 (29 months), the validation period is set as September 2017~September 2018 (13 months), and the test period is set as December 2018~December 2019 (13 months). The results of the return rate prediction study are as follows. First, the model achieved a prediction similarity level of almost 76%. After collecting time series data and preparing the final prediction model, it was confirmed that 76% of models could be achieved. All in all, the results demonstrate the reliability of the LSTM-based model for return rate prediction.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.270-279
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• 2022

In this paper, system dynamics considering dynamics and time was examined to study the changes in system structure according to reinforcement (policy intervention) of regulation and punishment for fishing boats, and the strategizing directions were analyzed. Until now, regulations and punishments on fishing boats have been conducted temporarily and short-term as a precautionary measure to prevent accidents and imposed penalties. However, due to various anomalous side effects, the expected results were not achieved, negligent accidents occurred constantly, and follow-up measures were repeated. Resultantly, the regulation and punishment of fishing boats is a reinforced safety standard, and there is a necessity to improve facilities, equipment, and industry, and develop technology (including time delay) to prevent accidents. However, as the negative (illegal) activities continue without immediate and significant resistance, the safety blind spot for accident prevention cannot be minimized. Thus, policy intervention based on linear thinking without sufficiently considering variables of the dynamic mechanism and time can distort the basic values pursued by the policy. For the regulation and punishment of fishing boats, a strategy to supplement the mechanism should be prepared prior to the preparation of reinforced safety standards. Improvement and development of related technologies, mandatory training hours for anglers, fishing industry, and related organizations, proposal of specific action plan for Fishing Management and Promotion Act for growing fishing-related industries.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.75-82
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• 2022

Analyzing the psychological and pedagogical literature, we found the researchers' interest in the problem posed. The concept of "culture of professional communication» is considered, which is interpreted as the level of realization of creative abilities, exchange of messages, organization of mutual understanding, mutual knowledge in the process of professionally directed interaction between subjects, in which interpersonal relationships arise, manifest and form. The concept of "professional culture of communication of a teacher" is interpreted. The motives that are socially significant in the professional communication of the teacher are highlighted. The necessity of forming a culture of professional communication among students, in particular by means of information technologies in the present, is clarified. The interactive component of professional communication is considered. The types of interactions between people in everyday life (ritual and entertainment interaction, joint purposeful activity, no interaction, game and interpersonal interaction) are identified. Traditional and specific forms and methods of teaching are written out. All interactive technologies carried out by means of information technologies are conventionally divided into four groups, depending on the form of educational activity appropriate for their use (pair (work of the subject with the teacher or peers one on one by means of Information Technologies); frontal (the teacher simultaneously teaches a group of subjects by means of Information Technologies); group or cooperative (all subjects teach each other by means of Information Technologies); individual (independent work of the subject using Information Technologies)). In the higher education institution, future specialists should learn knowledge, acquire skills on the basic rules of the culture of professional communication and methods of interaction and their effective use, which is possible with the use of Information Technologies. Recommendations for optimal professional communication have been developed that help you express your thoughts easily and beautifully, and conduct a dialogue in a relaxed and harmonious way.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.9-22
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• 2022

The purpose of this study was to provide basic data on pre-service teacher's education based on cooperative learning-oriented teaching and learning methods by applying cooperative learning to verify the effectiveness of pre-service early childhood teacher's communication and problem-solving ability. In the first semester of 2021, 4th grade students who took the teaching method by subject class opened by department of early childhood education at C university were taught for 11 weeks from March 1st week to May 2nd week in 2021 for 4 hours a week. The results of this study were as follows: First, the average score of interpretive ability was the highest in the sub-areas of communication ability of pre-service early childhood teachers, followed by message conversion ability, role performance ability, self-presentation ability, and goal setting ability in the cooperative learning-oriented teaching method by subject class. Second, in terms of the overall average score of pre-service teacher's problem-solving ability, the average score of post-test was increased compared to the average score of pre-test. Through the cooperative learning-oriented class experience in the university's early childhood teacher training course, it is possible to cultivate the practical ability that can be used variously for the children such as communication ability and problem-solving ability in the early childhood education field. Therefore, it is necessary to provide opportunities for cooperative learning-oriented teaching methods in the teacher's education curriculum.

• Human Ecology Research
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• v.60 no.3
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• pp.331-344
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• 2022

The purpose of this study was to identify a support method for the introduction of metaverse-based classes (MBC) in home economics (HE) education. This was achieved by diagnosing the stages of concern and levels of use exhibited by HE teachers applying the concerns-based adoption model (CBAM). Questionnaires were sent to a convenience sample of middle- and high-school HE teachers using the KSDC (Korea Social Science Data Center). Overall, 271 responses were received, and the data were analyzed using KSDC E-STAT 3.0 and SPSS 28.0.1.1. The results were as follows: First, regarding the level of knowledge of MBC, the introductory level was the most common (139 respondents, 51.3%,), followed by the beginner level (81, 29.9%), the intermediate level (28, 10.3%,), the advanced level (12, 4.4%), and the master level (11, 4.1%). Average responses on a 5-point Likert scale to questions about the use of metaverse in HE classes were as follows: possibility (4.02), necessity (3.82), and usefulness (3.90). Second, HE teachers' stages of concern in MBC were as follows (in descending order): unconcerned - stage 0, and information - stage 1 (86.9), personal - stage 2 (85.6), management - stage 3 (80.9), collaboration - stage 5 (57.5), consequence - stage 4 (57.4), and refocusing - stage 6 (55.2). Third, the use of MBC was highest for orientation - level 1 (173 respondents, 63.8%), followed by non-use - level 0 (34, 12.5%), preparation - level 2 (29, 10.7%), mechanical - level 3 (15, 5.5%), refinement - level 5 (8, 3.0%), renewal - level 7 (8, 3.0%), routine - level 4 (3, 1.1%), and integration - level 6 (1, 0.4%). Many HE teachers had heard about MBC but were in the introductory level of not knowing what it is, and at the stage of being unconcerned or wanting to know about MBC. Of the 271 respondents, only 35 used metaverse in classes. Therefore, it is necessary to provide teacher training opportunities that provide basic information on the significance and implementation of MBC for HE teachers. Also, an MBC guideline book should be developed and distributed to HE teachers. Finally, a teacher community meeting is needed to share the expertise of teachers with substantial experience in using MBC.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.794-801
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• 2021

Purpose: The effectiveness of the transport vehicle management system of the Chemical Substances Control Act will be studies and used as basic data for future system improvement plans. Method: After the enforcement of the Chemical Substances Control Act, the effectiveness for the transport vehicle management system was studies by comparing the transport plan, guidance and inspection status, safety training completion management, ect., and the reduction rate of chemical accidents. Results: The average number of chemical accidents in transport vehicles nationwide is 20 each year. And It is decreasing with the stabilization of the Chemical Substances Control Act('15.1.1). The first reason for the decrease in chemical accidents is the increase in submission of transport plans. Second, as the guidance and inspection rate increased every year, the shipper company's management of transport companies was naturally strengthened. Finally, it is judged that chemical accident caused by transport vehicles decrease through safety education. Conclusion: The current tranport vehicle management system of the Chemical Substances Control Act is effective. However, further research is needed to improve the practical and efficient transport vehicle management system.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.1-10
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• 2022

As the importance of ICT use in education grows, this study analyzes the differences and characteristics of perceptions of educational fields and industries on the use of Edutech, and proposes policy suggestions for revitalizing Edutech by deriving requirements. Accordingly, a survey was conducted on 201 teachers and 100 companies, and IPA analysis, Borich's needs, basic statistics, and t-test were conducted to find out the necessity and utilization of Edutech. As a result, they were highly aware of the need for the use of Edutech, and perceived that the support or accessibility for Edutech was insufficient. Accordingly, direct exchange between on-site teachers and companies from the product development stage to utilization and follow-up management, professional support for the introduction of Edutech, simplification of the purchase process and deregulation, customized support and training programs according to the characteristics of teachers are required. In the future, it is necessary to consider the changes in education that will occur after COVID-19 and establish appropriate product development and spread strategies.

• Journal of Korean society of Dental Hygiene
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• v.22 no.5
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• pp.323-332
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• 2022

Objectives: This study aims to confirm the educational necessity and utilization of VR media. And it was conducted to prepare basic data necessary for the use of VR in various dental hygiene education in the future and the development of innovative practical training courses. Methods: Before and after using VR in oral radiology practice classes, learning interest (4 items), learning commitment (9 items), learning motivation (5 items), educational media preference (4 items), and satisfaction (10 items) were investigated and analyzed. Friedman two way ANOVA by ran a nonparametric analysis corresponding to repeated measures ANOVA was performed. The statistical significance level was 0.05. Results: It was found that there were statistically significant differences in learning interest, learning immersion, and learning motivation according to the type of oral radiology practice education medium (p<0.05). Conclusions: VR is expected that the use of learning media using VR will lead to students' interest, immersion, and learning motivation in class, and that positive learning effects on VR education media can be sufficiently obtained.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.325-330
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• 2022

This paper conducts the collection and experiment of datasets for deep learning research on sign language such as sign language recognition, sign language translation, and sign language segmentation for Korean sign language. There exist difficulties for deep learning research of sign language. First, it is difficult to recognize sign languages since they contain multiple modalities including hand movements, hand directions, and facial expressions. Second, it is the absence of training data to conduct deep learning research. Currently, KETI dataset is the only known dataset for Korean sign language for deep learning. Sign language datasets for deep learning research are classified into two categories: Isolated sign language and Continuous sign language. Although several foreign sign language datasets have been collected over time. they are also insufficient for deep learning research of sign language. Therefore, we attempted to collect a large-scale Korean sign language dataset and evaluate it using a baseline model named TSPNet which has the performance of SOTA in the field of sign language translation. The collected dataset consists of a total of 11,402 image and text. Our experimental result with the baseline model using the dataset shows BLEU-4 score 3.63, which would be used as a basic performance of a baseline model for Korean sign language dataset. We hope that our experience of collecting Korean sign language dataset helps facilitate further research directions on Korean sign language.