• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.33-42
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• 2022

One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.163-171
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• 2023

The intelligent transportation system has made a huge leap in the level of human services, which has had a positive impact on the quality of life of users. On the other hand, these services are becoming a new source of risk due to the use of data collected from vehicles, on which intelligent systems rely to create automatic contextual adaptation. Most of the popular privacy protection methods, such as Dummy and obfuscation, cannot be used with many services because of their impact on the accuracy of the service provided itself, they depend on changing the number of vehicles or their physical locations. This research presents a new approach based on the shuffling Nicknames of vehicles. It fully maintains the quality of the service and prevents tracking users permanently, penetrating their privacy, revealing their whereabouts, or discovering additional details about the nature of their behavior and movements. Our approach is based on creating a central Nicknames Pool in the cloud as well as distributed subpools in fog nodes to avoid intelligent delays and overloading of the central architecture. Finally, we will prove by simulation and discussion by examples the superiority of the proposed approach and its ability to adapt to new services and provide an effective level of protection. In the comparison, we will rely on the wellknown privacy criteria: Entropy, Ubiquity, and Performance.

• Advances in concrete construction
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• v.17 no.5
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• pp.257-271
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• 2024

During any construction involving mass concrete, it is crucial to control cracking during the placement and curing process. This study develops an intelligent cooling control system that regulates water temperature and flow based on concrete hydration heat, effectively preventing cracking in bridge construction. The system consists of hardware, a neural network-based control algorithm, and an information management system. An optimal cooling control strategy is proposed to dynamically regulate water flow and temperature, preventing cracking by utilizing real-time temperature data, target control curves, neural network algorithms, and cloud-based computing. The intelligent cooling control system has been successfully implemented in controlling cracking risks during bridge construction. It not only mitigates the risk but also provides a convenient management strategy for bridge construction projects. The optimal cooling control strategy ensures high accuracy and stability under unsupervised learning conditions. This intelligent cooling control system can be applied to similar constructions such as bridge, dam, and building that involve the use of mass concrete.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.168-178
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• 2017

In order to prevent major and chemical accidents, some of the plants which would like to install and operate hazard chemicals handling facilities must submit Off-site Consequence Analysis due to recent arisen leak accidents since 2015. A lot of chemical industrials choose gas detectors as mitigation equipment to early detect gas vapor. The way of placement of gas detectors has two methods; Code-based Design(CBD) and Performance-based Design. The CBD has principles for gas detectors to be installed with consideration for the place that is expected to accumulate gas, and the leak locations according to legal standards and technical guidelines, and has a possibility to be unable to detect by these rules to locate gas detectors by vapor density information. The PBD has two methods; a Geographic Method and Scenario based Method. The Scenario-based Method has been suggested to make up for the Geographic Coverage Method. This Scenario-based Method draw the best optimum placement of gas detectors by considering leak locations, leak speed information, leak directions and etc. However, the domestic placement guidelines just refers to the CBD. Therefore, this study is to compare existing placement location of gas detectors by the domestic CBD with placement locations, coverages and the number of gas detectors in accordance with the Scenario-based Method. Also this study has measures for early detecting interest of Vapor Cloud and suitable placement of gas detectors to prevent chemical accidents. The Phast software was selected to simulate vapor cloud dispersion to predict the consequence. There are two cases; an accident hole size of leak(8 mm) from API which is the highst accident hole size less than 24.5 mm, and a normal leak hole size from KOSHA Guide (1.8 mm). Detect3D was also selected to locate gas detectors efficiently and compare CBD results and PBD results. Currently, domestic methods of gas detectors do not consider any risk, but just depend on domestic code methods which lead to placement of gas detectors not to make personnels recognize tolerable or intolerable risks. The results of the Scenario-based Method, however, analyze the leak estimated range by simulating leak dispersion, and then it is able to tell tolerable risks. Thus it is considered that individuals will be able to place gas detectors reasonably by making objectives and roles flexibly according to situations in a specific plant.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.43-53
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• 2019

In recent years, there have been many cases of damage to indoor air hazardous materials, and major damage due to the lack of quick action. In this regard, the system is intended to establish for sending push messages to the user's mobile when the concentration of hazardous substances is exceeded. This system extracts data with IoT system such as Arduino and Raspberry Pi and then constructs database through MongoDB and MySQL in cloud computing system. The database is imported through the application server using NodeJS and sent to the application for visualization. Also, when receiving signals about a dangerous situation in IoT system, push message is sent using Google FCM library. Mobile application is developed using Android Web view, and page to enter Web view is developed using HTML5 (HTML, Javascript CSS). The application of this system enables real-time monitoring of indoor air-dangerous substances. In addition, real-time information on indoor/outdoor detection location and concentration can be sent to the user's mobile in case of a risk situation, which can be expected to help the user respond quickly.

• Journal of the Korean Society of Safety
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• v.35 no.6
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• pp.15-24
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• 2020

With the development of the chemical industry, the chemical accident is increasing every year, thereby increasing the risk of accidents caused by chemicals. The Ministry of Environment provides the criteria for determining shelter-in-place or outdoor evacuation by material, duration of accident, and distance from the toxic substance leak. However, it is hard to say that the criteria for determining the transition point are not clear. Transition point mean the time that evacuation method is switched from shelter-in-place to outdoor evacuation. So, the purpose of this study was to calculate appropriate transition point by comparing the cumulative toxic load. Namdong-gu in Incheon Metropolitan City was finally selected as the target area, considering the current status of the population of Incheon Metropolitan City in 2016 and the statistical survey of chemicals in 2016. The target materials were HCl, HF, and NH₃. Modeling was simulated by ALOHA and performed assuming that the entire amount would be leaked for 10 min. Residents' evacuation scenarios were assumed to be shelter-in-place, immediate outdoor evacuation, and outdoor evacuation at an appropriate time after shelter-in-place. Based on the above method, the appropriate transition point from residents located in A(800 m away), B(1,200 m away), C(1,400 m away) and D(2,200 m away) was identified. In HCl, appropriate transition point was after 15 min, after 16 min, after 17 min, after 20 min in order by A, B, C and D. In HF, appropriate transition point was before 1 min or after 16 min, before 4 min or after 19 min, before 5 min or after 20 min, before 14 min or after 26 min in order by A, B, C and D. In NH₃, appropriate transition point at A was before 4 min or after 16. Others are not in chemical cloud. This study confirmed the transition point to minimize the cumulative toxic load can be obtained by quantitative method. Through this, it might be possible to select evacuation method quantitatively that cumulative toxic load are minimal. In addition, if the shelter-in-place is maintained without transition to outdoor evacuation, the cumulative toxic load will increase more than outdoor evacuation. Therefore, it was confirmed that actions to reduce the concentration of chemicals in the room were necessary, such as conducting ventilation after the chemical cloud passed through the site.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.34-44
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• 2024

Recently, due to abnormal climate caused by climate change, natural disasters such as floods, landslides, and soil outflows are rapidly increasing. In Korea, more than 63% of the land is vulnerable to slope disasters due to the geographical characteristics of mountainous areas, and in particular, Quarry mines soil and rocks, so there is a high risk of landslides not only inside the workplace but also outside.Accordingly, this study built a DEM using UAV and aviation LiDAR for monitoring the quarry, conducted a time series change analysis, and proposed an optimal DEM construction method for monitoring the soil collection site. For DEM construction, UAV and LiDAR-based Point Cloud were built, and the ground was extracted using three algorithms: Aggressive Classification (AC), Conservative Classification (CC), and Standard Classification (SC). UAV and LiDAR-based DEM constructed according to the algorithm evaluated accuracy through comparison with digital map-based DEM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.602-607
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• 2018

The destruction of forests requires continuous management due to the risk of disasters such as landslides and landslides. However, existing forest inspection methods are inefficient as they require a lot of manpower and time. Recently, drones are attracting attention as an effective way to construct and utilize spatial information. The size of the drone-related industrial market is rapidly increasing. In this study, we attempted to increase the efficiency of forest investigation utilizing drones. The study area was photographed through the use of drones, and ortho image and DSM were generated through data processing. Study results found that it was possible to calculate the area and the volume for the forest damaged area effectively by employing drones, and suggested the applicability of drones. In the future, it is expected that the method of analyzing the forested area using drones can save manpower and time compared to existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1797-1804
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• 2015

Integrated log management system can help to predict the risk of security and contributes to improve the security level of the organization, and leads to prepare an appropriate security policy. In this paper, we have designed and implemented a Hadoop-based log analysis system by using distributed database model which can store large amount of data and reduce analysis time by automating log collecting procedure. In the proposed system, we use the HBase in order to store a large amount of data efficiently in the scale-out fashion and propose an easy data storing scheme for analysing data using a Hadoop-based normal expression, which results in improving data processing speed compared to the existing system.