• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.483-490
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• 2021

Due to the recent increase in various problems from underground development in urbanized areas, accurate underground facility information management is highly needed. Therefore, in this study, in order to utilize the Integration Map of Underground Goespatial Information in real time on-site, the function of comparing the mutual location of the GPR (Ground Penetration Radar) sensing data and the Integration Map of Underground Goespatial Information, and function of analyze underground facilities, and function of converting surveying data into a shape file through position correction & attribute editing in a 3D space, and the function of submitting the shape file to the Integration Map of Underground Goespatial Information mobile center was defined and developed as a program. In addition, for the on-site application test of the development program, scenarios used at the underground facility real-time survey site and GPR exploration site were derived, and four sites in Seoul were tested to confirm that the use scenario worked properly. Through this, the on-site utilization of the program developed in this study could be confirmed, and it would contribute to the confirmation of the quality of Shape-file and the "update automation" of "Integration Map of Underground Goespatial Information". In addition, it is expected that the development program will be further applied to the Underground Facility Map's Accuracy Improvement Diffusion Project' promoted by the MOLIT (Ministry of Land, Infrastructure, and Transport).

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.519-524
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• 2022

Domestic building finishing materials are being evaluated according to KS F 2271 standards according to the notification of the Ministry of Land, Infrastructure and Transport, and this test is evaluated using laboratory animals. In this study, experiments were conducted on highly combustible organic insulation materials such as EPS, urethane, and phenolic foam. The purpose of this study was to analyze the cause of the behavioral suspension of the experimental mice by measuring the average behavioral suspension time of the mice caused by the harmful gas generated when these three types of insulation materials were burned. FTIR analysis and smoke density experiment were performed as a cause analysis method for the behavioral suspension of mice, and the experimental results were analyzed by dividing the causes of behavioral suspension into suffocation by particulate matter and toxic inhalation by gaseous substances. As a result of the test, urethane was evaluated as the most harmful insulation material, and as a result of FTIR analysis and smoke density test as a cause analysis for the gas toxicity test results, it is judged that the behavioral stop of the rats by suffocation is higher than the effect of toxic inhalation. This study is a basic study on the cause analysis of harmful gases, and it will be necessary to prepare the toxicity basis and analyze various materials and gases.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.413-419
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• 2022

As the development of the underground space becomes active, safety accidents related to the underground are frequently occurring in recent years. In this regard, the Ministry of Land, Infrastructure and Transport is enforcing the 『Special Act on Underground Safety Management』 (enforced on January 1, 2018, hereafter referred to as the Underground Safety Act). Among the core contents of the Underground Safety Act, underground facilities(water supply, sewage, gas, power, communication, heating) buried underground, underground structures(subway, underpass, underpass, underground parking lot, underground shopping mall, common area), ground (Drilling, wells, geology) of 15 types of underground information can be checked at a glance on a three-dimensional basis by constructing an integrated underground spatial map and using it. The purpose of this study is to develop a program that can quickly inspect the three-dimensional model after creating a three-dimensional underground structure data among the underground spatial integration maps. To this end, we first investigated and reviewed the domestic and foreign status of technology that generates and automatically inspects 3D underground structure data. A quality inspection program was developed. Through this study, it is judged that it will be meaningful as a basic research for improving the quality of underground structures on the integrated map of underground space by automating more than 98% of the 3D model inspection process, which is currently being conducted manually.

• Journal of Industrial Convergence
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• v.20 no.2
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• pp.1-9
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• 2022

As the need for improvement of transparency and fairness in the selection of national R&D projects has been continuously raised, we analyzed the impact on the evaluation selection results by evaluation indexes for The land transportation technology commercialization support project and searched for ways to improve indexes using the analysis results. As for the research data, it were applied as selection results of new R&D projects and evaluation indexes in two fields(SME innovation and start-up) in 2021. Logistic regression analysis is used for the influence of each evaluation indexes on the evaluation result, and for the regression model, evaluation indexes with low influence are removed in advance through artificial neural network multiple perceptron analysis to improve the reliability of the analysis results. As a result of the analysis, in the field of SME innovation, the influence of the evaluation index on the workforce planning was the lowest and the influence of the appropriateness of commercialization promotion plan was the highest. In the start-up field, the influence of the evaluation indexes for technology development suitability, marketability, and suitability for carrying out the project were estimated to be similar to each other, and the influence of the technology evaluation index was found to be the lowest. The analysis results of this thesis suggest the need for continuous improvement of selection and evaluation indexes, and by using the analysis results to select a fair R&D institution according to the selection of appropriate indexes, it will be possible to contribute to deriving excellent research results and fostering excellent companies in the field of land transportation.

• 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 Korea Institute of Building Construction
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• v.21 no.6
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• pp.701-712
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• 2021

As the domestic housing supply problem has been resolved, the apartment construction market has shifted to a consumer-oriented market that wants high quality, and in particular, expectations in the area of finishing quality have increased. Looking at the status of complaints regarding apartment housing defects supplied by Korea Land and Housing Corporation, tile-related complaints are the type occurring the most frequently. While the Ministry of Land, Infrastructure and Transport(MOLIT) is making an ongoing effort to reduce complaints related to defects, through approaches such as drafting amendments to 「Investigation of defects in apartment houses, calculation of repair costs, and standards for determining defects」, the provision of preventive measures has been insufficient. In addition, by reviewing studies, there has been insufficient research to construct a classification system after deriving the characteristics of each type using the qualitative knowledge of experts, various quantitative indicators, and suggesting measures for reduction according to the causes of each type. Therefore, this study will reflect qualitative indicators to use the AHP analysis that makes it easy to identify the relationship between defects by surveying construction experts. Then, by visualizing the weight of 'Possibility of recurrence after repair,' 'Degree of difficulty in repairing defects' and 'Fault frequency' using a radial graph, we will analyze the characteristics of each type of tile construction defect and establish measures for reduction according to the cause. This will improve the quality of the living environment and contribute to the establishment of a system for smooth defect management and reduction of defects in apartment tile construction.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.79-101
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• 2023

The current status of local road pavement management in Jeollabuk-do only relies on the accomplishments of the site construction company's pavement repair and is only managed through Microsoft Excel and word documents. Furthermore, the budget is irregular each year. Accordingly, a systematic maintenance plan for local roads is necessary. In this paper, data related to road damage and road environment were collected and processed to derive possible areas which could suffer from road damage. The effectiveness of the methodology was reviewed through the on-site inspection of the area. According to the Ministry of Land, Infrastructure and Transport, in 2018, the number of damages on general national roads were about 47,000. In 2019, it reached around 38,000. Furthermore, the number of lawsuits regarding the road damages were about 93 in 2018 and it increased to 119 in 2019. In the case of national roads, the number of damages decreased compared to 2018 due to pavement repairs. To measure the priorities in maintenance of local roads at Jeollabuk-do, data on maintenance history, local port hole occurrence site, overlapping business section, and emergency maintenance section were transformed into data. Eventually, it led to improvements in maintenance of local roads. Furthermore, spatial data were constructed using various current status data related to roads, and finally the data was processed into a new form that could be utilized in machine learning and predictions. Using the spatial data, areas requiring maintenance on pavement were predicted and the results were used to establish new budgets and policies on road management.

• Journal of Practical Agriculture & Fisheries Research
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• v.13 no.1
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• pp.173-183
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• 2011

Gabensis village is one of the biggest village In the Wampar Local Level Government area within the Huon Gulf District of Morobe Province with a population of around 3,000. The major staple food is banana which is well complemented by minor staples yam, cassava, Singapore/Chinese taro and sweet potato. Apart from gardening for own consumption, the villagers engage in selling of vegetables, garden staples, cocoa beans, coconuts, timber, chicken, fish and pig meat to supplement their livelihood. Livestock like pigs and chickens are also kept for meat and for commercial purpose. Bettlenut which was once one of the main cash crops has now been overtaken by cocoa due to a disease that had attacked almost the entire bettlenut tree population in the area. Even though the Wau-Bulolo highway cuts through the village and all have access to transport infrastructure, the majority of the population still encounter problems in communication due to poor telecommunication coverage. On average most people earn not more than K50 per week due to constrains in production and marketing among others. Gabensis village has the potential to develop a tourism industry given its natural attraction of Lake Wanam. Beside there is also the natural eel farming and the fish pond at the nearby Potsie village. These natural attractions pose huge tourism potential for the community. As part of government services delivery and development, education and health issues is very much important in the community however there is lack of infrastructural development and poor service delivery especially in the area of health. However, the responsibility is on the community to organize themselves to realize that potential. A well developed agro-ecotourism investments would have positive spillover effects to the community thus contributing towards improving the livelihoods of the many farming families.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.225-227
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• 2022

Now In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office in Seoul has built a control center for CCTV control and is building information such as people, vehicle types, license plate recognition and color classification into big data through 24-hour artificial intelligence intelligent image analysis. Seoul Metropolitan Government has signed MOUs with the Ministry of Land, Infrastructure and Transport, the National Police Agency, the Fire Service, the Ministry of Justice, and the military base to enable rapid response to emergency/emergency situations. In other words, we are building a smart city that is safe and can prevent disasters by providing CCTV images of each ward office. In this paper, the CCTV image is designed to extract the characteristics of the vehicle and personnel when an incident occurs through artificial intelligence, and based on this, predict the escape route and enable continuous tracking. It is designed so that the AI automatically selects and displays the CCTV image of the route. It is designed to expand the smart city integration platform by providing image information and extracted information to the adjacent ward office when the escape route of a person or vehicle related to an incident is expected to an area other than the relevant jurisdiction. This paper will contribute as basic data to the development of smart city integrated platform research.

• Journal of Korea Port Economic Association
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• v.39 no.3
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• pp.191-210
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• 2023

The Covid-19 pandemic has had a significant impact on global logistics and supply chains, leading to major discrepancies in logistics performance across countries worldwide. Through an examination of logistics performance index and supply chain tracking data, this study aimed to identify the changes in global supply chains and logistics environments during the pandemic. The analysis of the logistics performance index showed that overall, countries around the world, especially developed nations, showed improvements in metrics such as customs and border management efficiency, the quality of trade and transport infrastructure, capability and quality of logistics services, and cargo tracking abilities. However, the competitive pricing feasibility of international transportation and the on-time delivery frequency of goods saw a decline due to the pandemic's effects. The supply chain tracking data revealed that ports in Asian countries demonstrated high processing efficiency. In contrast, the U.S. and European countries took comparatively more time. Particularly for air cargo, parcels, and express shipments, the U.S. showed relatively longer processing times, leading to logistical delays. In conclusion, during the Covid-19 pandemic, Asian countries maintained relatively high efficiency in their logistics and trade environments. Conversely, the U.S. and some European countries showed delays and decreased efficiency in various metrics. In the future, efforts should be made to address delays and congestion, namely, the deceleration of logistics processes.