• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.268-279
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• 2021

The geospatial schemes based on topo-climatology have been developed to produce digital climate maps at a site-specific scale. Their development processes are reviewed here to derive the needs for new schemes in the future. Agricultural and forestry villages in Korea are characterized by complexity and diversity in topography, which results in considerably large spatial variations in weather and climate over a small area. Hence, the data collected at a mesoscale through the Automated Synoptic Observing System (ASOS) operated by the Korea Meteorological Administration (KMA) are of limited use. The geospatial schemes have been developed to estimate climate conditions at a local scale, e.g., 30 m, lowering the barriers to deal with the processes associated with production in agricultural and forestry industries. Rapid enhancement of computing technologies allows for near real-time production of climate information at a high-resolution even in small catchment areas and the application to future climate change scenarios. Recent establishment of the early warning service for agricultural weather disasters can provide growth progress and disaster forecasts for cultivated crops on a farm basis. The early warning system is being expanded worldwide, requiring further advancement in geospatial schemes and digital climate mapping.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.1
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• pp.56-61
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• 2022

In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.61-70
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• 2022

General users who use smartphone apps often use the Vault app to protect personal information such as photos and videos owned by individuals. However, there are increasing cases of criminals using the Vault app function for anti-forensic purposes to hide illegal videos. These apps are one of the apps registered on Google Play. This paper proposes a methodology for extracting feature points through XML-based keyword frequency analysis to explore Vault apps used by criminals, and text mining techniques are applied to extract feature points. In this paper, XML syntax was compared and analyzed using strings.xml files included in the app for 15 hidden Vault anti-forensics apps and non-hidden Vault apps, respectively. In hidden Vault anti-forensics apps, more hidden-related words are found at a higher frequency in the first and second rounds of terminology processing. Unlike most conventional methods of static analysis of APK files from an engineering point of view, this paper is meaningful in that it approached from a humanities and sociological point of view to find a feature of classifying anti-forensics apps. In conclusion, applying text mining techniques through XML parsing can be used as basic data for exploring hidden Vault anti-forensics apps.

• Journal of the Korea Institute of Building Construction
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• v.22 no.3
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• pp.281-291
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• 2022

This study attempts to use big data to determine the indicators necessary for a fire risk assessment of buildings. Because most of the causes affecting the fire risk of buildings are fixed as indicators considering only the building itself, previously only limited and subjective assessment has been performed. Therefore, if various internal and external indicators can be considered using big data, effective measures can be taken to reduce the fire risk of buildings. To collect the data necessary to determine indicators, a query language was first selected, and professional literature was collected in the form of unstructured data using a web crawling technique. To collect the words in the literature, pre-processing was performed such as user dictionary registration, duplicate literature, and stopwords. Then, through a review of previous research, words were classified into four components, and representative keywords related to risk were selected from each component. Risk-related indicators were collected through analysis of related words of representative keywords. By examining the indicators according to their selection criteria, 20 indicators could be determined. This research methodology indicates the applicability of big data analysis for establishing measures to reduce fire risk in buildings, and the determined risk indicators can be used as reference materials for assessment.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.49-55
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• 2022

In this paper, we propose an obstacle detection method that can operate robustly even in external environmental factors such as weather. In particular, we propose an obstacle detection system that can accurately inform dangerous situations in AR through DB-based feature matching and RANSAC-based multiplane method. Since the approach to detecting obstacles based on images obtained by RGB cameras relies on images, the feature detection according to lighting is inaccurate, and it becomes difficult to detect obstacles because they are affected by lighting, natural light, or weather. In addition, it causes a large error in detecting obstacles on a number of planes generated due to complex terrain. To alleviate this problem, this paper efficiently and accurately detects obstacles regardless of lighting through DB-based feature matching. In addition, a criterion for classifying feature points is newly calculated by normalizing multiple planes to a single plane through RANSAC. As a result, the proposed method can efficiently detect obstacles regardless of lighting, natural light, and weather, and it is expected that it can be used to secure user safety because it can reliably detect surfaces in high and low or other terrains. In the proposed method, most of the experimental results on mobile devices reliably recognized indoor/outdoor obstacles.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.325-335
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• 2021

Chronic diseases have been increasing recently as the average life expectancy of humans has been extended, and this trend has caused problems such as the widespread demand for health and rehabilitation services and rising medical costs. In order to solve this problem, the community-based rehabilitation has been developed and strengthened in Korea and gradually promoted since 2019. It is important to secure access to clients who want to use services to revitalize community-based rehabilitation. So in this study, as part of the community-based rehabilitation, intends to devise smartphone applications designs and develop a prototype to secure access to community-based occupational therapy services based on occupation and activities. For Occupational Therapy Practice Framework (OTPF), International Classification of Functioning, Disability and Health (ICF), and Allen Diagnostic Module-2 (ADM-2) were used to devise and categorize occupation and activity based application content, and link OTPF, ICF, and ADM-2 through prior research analysis and expert meetings. The derived content was visualized through literature review and activity analysis, and was implemented to enable direct playback within the application using the YouTube API, and finally developed a prototype application. The Android Studio 3.5.2 for Windows 64-bit was used to build the application prototype. In further research, converging various digital technologies for user convenience and additionally researching community-based occupational therapy service providers opinions and service user satisfaction will improve accessibility to community-based occupational therapy services for clients who have difficulty occupational performance in the community.

• Journal of the Korea Institute of Building Construction
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• v.21 no.6
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• pp.689-700
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• 2021

Due to the COVID-19 pandemic, higher education in South Korea has rapidly shifted online. In addition, the advent of the Fourth Industrial Revolution has highlighted the need to introduce innovation teaching methods. To cope with these changes and demands, the learning management system used by domestic universities must therefore be improved. This study developed a learning management system for the application of team-based learning to improve and develop the learning management system of domestic universities. The major research findings are as follows. The analysis results showed that there is not sufficient function to apply new innovation teaching methods, such as team-based learning, in the current learning management system of domestic universities. Therefore, a learning management system capable of supporting team-based learning courses was developed in this study. The system consisted of 'pre-class learning,' 'team activities' and 'participation learning,' which were further classified into nine sub-items. In the future, a survey of system users is planned in order to further improve the system. It is believed that if the proposed learning management system were introduced to domestic universities, it would improve the educational environment and contribute to the spread and use of innovative teaching methods.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.55-65
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• 2022

The purpose of this paper was to investigate the relationship between cybersickness symptoms and visual function and to determine whether visual perception training is effective in reducing symptoms of cybersickness. The study subjects were healthy adult males who experienced the same virtual reality program for 15 minutes. Afterwards, the VR satisfaction score and cybersickness level were measured and classified into a comfortable virtual reality program viewer group (CVR group, 20 people) and an uncomfortable virtual reality program viewer group (UVR group, 20 people). Visual function test was performed on all subjects, and the vision therapy training program was applied to the UVR group once a week for 40 minutes 12 times, and then the visual function and SSQ questionnaire were re-evaluated. Subjects with diplopia were 55% in the UVR group and 5% in the CVR group, which was significantly higher in the UVR group, there were differences in stereopsis, exophoria, near point convergence(p<.01) and vergence function(p<.001) between the two groups. After vision therapy, changes in SSQ, stereopsis, near point convergence, and vergence function of UVR user group were positively changed(p<.01). Therefore, cybersickness symptoms are related to visual function, it seems that the vision therapy can be used as a way to alleviate the symptoms of cybersickness.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1097-1104
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• 2021

Online game-bots are already known for a lot of persons by various ways. It leads to problems such as declining game player's interest, in-game financial crisis, etc. Detecting and restricting of game-bot is now essential. Because both publishers and players get disadvantages from their long term abnormal working. But it is not easy to restrict, because of false restriction risks. Game publishers need to distinguish game-bot from server-side game logs. At last, it should can make reasons for game-bot restriction. In this paper, we classified game-bot users by using daily separated game logs for testing data. For daily-driven detection, we separated total dataset into one day logs. Preliminary detects game-bots with one day logs, and determines total results by using these data. Daily driven detection advantages on detection which contains combined game playing style. Which shows like normal user and game-bot. These methodology shows better F1-score, which one of indicator which demonstrate classification accuracy. It increases from 0.898 to 0.945 by using Random Forest classifier.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.365-385
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• 2022

The easy payment service is a payment and remittance service that uses a simple authentication method. As online transactions have increased due to COVID-19, the use of an easy payment service is increasing. At the same time, electronic financial industries such as Naver Pay, Kakao Pay, and Toss are diversifying the competition structure of the easy payment market; meanwhile overseas fintech companies PayPal and Alibaba have a unique market share in their own countries, while competition is intensifying in the domestic easy payment market, as there is no unique market share. In this study, the participants in the easy payment market were classified as electronic financial companies, mobile phone manufacturers, and financial companies, and a SWOT analysis was conducted on the representative services in each industry. The analysis examined the user reviews of Google Play Store via a topic modeling analysis, and it employed positive topics as strengths and negative topics as weaknesses. In addition, topic modeling was conducted by dividing news articles into political, economic, social, and technology (PEST) articles to derive the opportunities and threats to easy payment services. Through this research, we intend to confirm the service capabilities of easy payment companies and propose a service activation strategy that allows gaining the upper hand in the market.