• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.12-22
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• 2019

This study derived the design aspects by carrying out the case study of Neunggok prehistoric remains park, Ansansingil historic park and Yongjuk historic park to which are taken measures to preserve undesignated cultural heritages after studying the related laws & regulations and the systems as the design conditions of historic park preserving buried cultural heritages. The results of the study are as follows. First, according to the laws & regulations related to the historical parks, the historic sites should be preserved and utilized at the same time and can have history-related facility spaces, squares, rest spaces, exercise spaces, education & culture space, and convenience spaces. Second, by the space organization and the circulation system emphasizing only the preservation of buried cultural heritages, the feature-preservation space and the functional space are separated and due to not accepting the usage behavior considering peripheral land use, the effectiveness of the historical park was low. Third, the passive feature-preservation methods such as the preservation of the exposed site in architectural methods, the reproduction of the dugout hut, and the planting Royal azaleas or displaying stone after covering up the location of the pit dwellings with soil and the usage mainly for viewing have weakened the identity of the historical park. Fourth, the fence preventing users' access interferes experiencing the features, and the vertical structure protecting the upper part of the exposed features has overwhelmed the landscape of the historical parks. Fifth, it was difficult to figure out the feature space only by the texts mainly on terminologies and the excavation photographs presented on the information signs which introduce the buried cultural heritages.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.26-34
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• 2021

In the era of the Fourth Industrial Revolution, the future battlefield will carry out multi-area operations with hyper-connected, high-speed and mobile systems. In order to prepare for changes in the future, the Korean military intends to develop various weapons systems and form a multi-layer tactical network to support On The Move communication. However, current tactical networks are limited in support of On The Move communications. In other words, the operation of multi-beam antennas is necessary to efficiently construct a multi-layer tactical network in future warfare. Therefore, in this paper, we look at the need for multi-beam antennas through the operational scenario of a multi-layer tactical network. In addition, based on development consideration factors, features of rotary-wing and fixed-wing aircraft, we present the location and operation of airborne relay drone installations of multi-beam antennas.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.25-48
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• 2014

Increased frequency of climate extremes is another face of climate change confronted by humans, resulting in catastrophic losses in agriculture. While climate extremes take place on many scales, impacts are experienced locally and mitigation tools are a function of local conditions. To address this, agrometeorological early warning systems must be place and location based, incorporating the climate, crop and land attributes at the appropriate scale. Existing services often lack site-specific information on adverse weather and countermeasures relevant to farming activities. Warnings on chronic long term effects of adverse weather or combined effects of two or more weather elements are seldom provided, either. This lecture discusses a field-specific early warning system implemented on a catchment scale agrometeorological service, by which volunteer farmers are provided with face-to-face disaster warnings along with relevant countermeasures. The products are based on core techniques such as scaling down of weather information to a field level and the crop specific risk assessment. Likelihood of a disaster is evaluated by the relative position of current risk on the standardized normal distribution from climatological normal year prepared for 840 catchments in South Korea. A validation study has begun with a 4-year plan for implementing an operational service in Seomjin River Basin, which accommodates over 60,000 farms and orchards. Diverse experiences obtained through this study will certainly be useful in planning and developing the nation-wide disaster early warning system for agricultural sector.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.415-423
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• 2021

Citizen participation and Living Lab are attracting interest as one of the major strategies for the success of smart cities. In a Living Lab, citizens, who are the end-users of technology, participate in the search for alternatives to define and solve problems and repeat experiments to verify alternatives in a circular process. The purpose of this research was to present an operating model of a citizen-participating online community platform to improve urban problems, implement and test it, and show its applicability. To this end, an operation model of a citizen-participating online community platform was proposed to improve urban problems. An online platform was designed and implemented to reflect the functions pursued by the operation model. Finally, a pilot test for the function was performed using the Oma Elementary School case located in Ilsan, Goyang-si, Gyeonggi-do. The operating model was designed with the city's pedestrian environment and children. As a result, the sharing and communicating process of urban issues among community members worked appropriately according to the designed intention. The Living Lab coordinator could visualize and view urban issues posted by users on a map based on location information. Visualizing the urban problem as a heat map confirmed that urban problems were concentrated in a specific area.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1089-1098
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• 2020

In this study, we propose a method to detect red tide Cochlodinium Polykrikoide using by machine learning and geostationary marine satellite images. To learn the machine learning model, GOCI Level 2 data were used, and the red tide location data of the National Fisheries Research and Development Institute was used. The machine learning model used logistic regression model, decision tree model, and random forest model. As a result of the performance evaluation, compared to the traditional GOCI image-based red tide detection algorithm without machine learning (Son et al., 2012) (75%), it was confirmed that the accuracy was improved by about 13~22%p (88~98%). In addition, as a result of comparing and analyzing the detection performance between machine learning models, the random forest model (98%) showed the highest detection accuracy.It is believed that this machine learning-based red tide detection algorithm can be used to detect red tide early in the future and track and monitor its movement and spread.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.373-382
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• 2021

This study conducted a survey to find out the opinions on oral health behavior and oral health education according to gender in health and non-health college students. According to the research results, there were many girls in the health-realted field and boys in the non-health-related college students. Among the oral health behaviors, brushing in school was common in both boys and girls in the health-related college students, and professional oral health education experiences were also found in the health-related college students. The need for oral health education among male students was 76.4% for healh-related college students, 48.3% for non-health-related college students, whereas female health-related college students showed 80.3%, and non-health -related college students were 60.4%. Participation in oral health education in order of male health-related students, male non-health-related students, female health-related students, and female non-health-related students were 81.9%, 68.1%, 84.8% and 73.3% respectively. The preferred method of oral health education was experiential education such as brushing for both male and female in the health-related college students, and lectures by dentists or dental hygienist were the highest reponse for non-health-related college students. The preferred location for oral health education was highest in schools. Through the results of this study, it was considered necessary to develop and disseminate appropriate oral health education programs according to college students' majors and gender, and to form correct oral health knowledge, attitudes and behaviors for oral health through oral health education.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1277-1290
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• 2020

Water resources which is formed of surface and groundwater, are considered as one of the pivotal natural resources worldwide. Since last century, the rapid population growth as well as accelerated industrialization and explosive urbanization lead to boost demand for groundwater for domestic, industrial and agricultural use. In fact, better management of groundwater can play crucial role in sustainable development; therefore, determining accurate location of groundwater based groundwater potential mapping is indispensable. In recent years, integration of machine learning techniques, Geographical Information System (GIS) and Remote Sensing (RS) are popular and effective methods employed for groundwater potential mapping. For determining the status of the integrated approach, a systematic review of 94 directly relevant papers were carried out over the six previous years (2015-2020). According to the literature review, the number of studies published annually increased rapidly over time. The total study area spanned 15 countries, and 85.1% of studies focused on Iran, India, China, South Korea, and Iraq. 20 variables were found to be frequently involved in groundwater potential investigations, of which 9 factors are almost always present namely slope, lithology (geology), land use/land cover (LU/LC), drainage/river density, altitude (elevation), topographic wetness index (TWI), distance from river, rainfall, and aspect. The data integration was carried random forest, support vector machine and boost regression tree among the machine learning techniques. Our study shows that for optimal results, groundwater mapping must be used as a tool to complement field work, rather than a low-cost substitute. Consequently, more study should be conducted to enhance the generalization and precision of groundwater potential map.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1367-1377
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• 2020

The purpose of this study is to assess the seismic vulnerability of buildings in Gyeongju city starting with the earthquake that occurred in the city on September 12, 2016, and produce a seismic vulnerability map. 11 influence factors related to geotechnical, physical, and structural indicators were selected to assess the seismic vulnerability, and these were applied as independent variables. For a dependent variable, location data of the buildings that were actually damaged in the 9.12 Gyeongju Earthquake was used. The assessment model was constructed based on random forest (RF) as a mechanic study method and support vector machine (SVM), and the training and test dataset were randomly selected with a ratio of 70:30. For accuracy verification, the receiver operating characteristic (ROC) curve was used to select an optimum model, and the accuracy of each model appeared to be 1.000 for RF and 0.998 for SVM, respectively. In addition, the prediction accuracy was shown as 0.947 and 0.926 for RF and SVM, respectively. The prediction values of the entire buildings in Gyeongju were derived on the basis of the RF model, and these were graded and used to produce the seismic vulnerability map. As a result of reviewing the distribution of building classes as an administrative unit, Hwangnam, Wolseong, Seondo, and Naenam turned out to be highly vulnerable regions, and Yangbuk, Gangdong, Yangnam, and Gampo turned out to be relatively safer regions.

• Journal of Industrial Convergence
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• v.20 no.3
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• pp.33-40
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• 2022

Recently, IoT-linked services have been used in various environments, and IoT and artificial intelligence technologies are being fused. However, since technologies that process IoT data stably are not fully supported, research is needed for this. In this paper, we propose a processing technique that can optimize IoT data after generating embedded vectors based on machine learning for IoT data. In the proposed technique, for processing efficiency, embedded vectorization is performed based on QR such as index of IoT data, collection location (binary values of X and Y axis coordinates), group index, type, and type. In addition, data generated by various IoT devices are integrated and managed so that load balancing can be performed in the IoT data collection process to asymmetrically link IoT data. The proposed technique processes IoT data to be orthogonalized based on hash so that IoT data can be asymmetrically grouped. In addition, interference between IoT data may be minimized because it is periodically generated and grouped according to IoT data types and characteristics. Future research plans to compare and evaluate proposed techniques in various environments that provide IoT services.