• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.1
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• pp.125-143
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• 2018

The study consisted of a survey of the residential satisfaction level of the 3rd grade students and a survey of accessibility from farms for practical field training to public facilities. According to the geographical location of the farms on the map, the average distance to facilities related to convenience or safety and health that students complained was about 12km. And that to social and public facilities was about 4.4km. Students pointed out the convenience of using transportation, commercial and convenient facilities, and the safety of anti-crime security facilities as complaints during the practice session. Residential satisfaction levels in five realms, such as facility and structure, convenience, safety, comfort and sociality, were not all reached at the satisfaction level. In particular, the satisfaction level of female students was sub-normal in the safety and convenience realms. The average satisfaction levels reviewed by department were sub-normal for horse industry and floriculture departments. By residential patterns, satisfaction with sharing with the farmers was higher than with other patterns. And satisfaction level by housing structure was much lower in the assembly and container structures Since residential satisfaction level is determined by the inside and outside environment of the dwelling, college should provide students with accurate and vivid data using information communication technologies.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.175-183
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• 2023

This study examines differences in satisfaction, intention to revisit, and word-of-mouth recommendations among foreign tourists, based on their nationality and factors influencing their decision to visit Korea. The study utilizes the data collected from foreign tourists who visited Korea in 2021, including information on their country of origin, factors influencing their decision to visit, satisfaction levels, intention to revisit, and willingness to recommend Korea to others. While the survey data comprises a large sample of over 8,000 respondents, only 1,398 without missing values are used for analysis. According to the analysis results, there were significant differences in satisfaction, intention to revisit, and word-of-mouth recommendations among foreign tourists based on their nationality and factors influencing their decision to visit. Notably, leisure and sports activities and distance from their home country are significant factors in making a decision to visit Korea. Countries with relatively lower tourism decision mechanisms are Japan, Singapore, China, Taiwan, Malaysia, Canada, Mongolia, and India. Based on these analysis results, this study presents strategic improvement measures to revitalize Korean tourism industry, particularly after the pandemic.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.73-89
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• 2023

This study aims to analyze the frequency of keywords used in Korean abstracts, which are unstructured text data in the domestic record management research field, using text mining techniques to identify domestic record management research trends through distance analysis between keywords. To this end, 1,157 keywords of 77,578 journals were visualized by extracting 1,157 articles from 7 journal types (28 types) searched by major category (complex study) and middle category (literature informatics) from the institutional statistics (registered site, candidate site) of the Korean Citation Index (KCI). Analysis of t-Distributed Stochastic Neighbor Embedding (t-SNE) and Scattertext using Word2vec was performed. As a result of the analysis, first, it was confirmed that keywords such as "record management" (889 times), "analysis" (888 times), "archive" (742 times), "record" (562 times), and "utilization" (449 times) were treated as significant topics by researchers. Second, Word2vec analysis generated vector representations between keywords, and similarity distances were investigated and visualized using t-SNE and Scattertext. In the visualization results, the research area for record management was divided into two groups, with keywords such as "archiving," "national record management," "standardization," "official documents," and "record management systems" occurring frequently in the first group (past). On the other hand, keywords such as "community," "data," "record information service," "online," and "digital archives" in the second group (current) were garnering substantial focus.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.5
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1321-1330
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• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• Journal of the Korean Regional Science Association
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• v.40 no.1
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• pp.89-110
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• 2024

REITs are very closely related to real estate management, but there have been no prior studies analyzing the location of REITs assets. Therefore, this study analyzed the location characteristics of REITs assets in two aspects to clarify the location characteristics by using spatial information of REITs assets. First, the characteristics of the type of city where REITs assets are distributed were analyzed, and second, the characteristics of the zoning where REITs assets are distributed were analyzed. As a result of analyzing the characteristics of the city where REITs assets are distributed by type, it was analyzed that in the case of the capital area, both the ratio of cities with REITs assets location and the intensity of REITs assets location (number of REITs assets per city) have location characteristics by city hierarchy in the order of metropolitan city > big city > small and medium-sized city. In the case of non-capital area's metropolitan and large cities, the ratio of REITs assets location cities is similar to that of the capital area, but the location intensity of REITs assets was analyzed to be significantly lower than that of the capital area. As a result of the analysis of REITs assets by type, housing REITs assets tend to be located in the old downtown commercial zoning and the new downtown residential zoning, office REITs assets are characterized by concentration of location in specific commercial zoning of Seoul, and retail REITs assets are located mainly in the old downtown station area. In addition, it was found that logistics REITs assets tend to be located in management zoning, centering on key logistics hub cities in the region.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.119-131
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• 2024

Understanding accurate traffic performance is crucial for ensuring efficient highway operation and providing a sustainable mobility environment. On the other hand, an immediate and precise estimation of highway traffic performance faces challenges because of infrastructure and technological constraints, data processing complexities, and limitations in using integrated big data. This paper introduces a framework for estimating traffic performance by analyzing real-time data sourced from toll collection systems and dedicated short-range communications used on highways. In particular, this study addresses the data errors arising from segmented information in data, influencing the individual travel trajectories of vehicles and establishing a more reliable Origin-Destination (OD) framework. The study revealed the necessity of trip linkage for accurate estimations when consecutive segments of individual vehicle travel within the OD occur within a 20-minute window. By linking these trip ODs, the daily average highway traffic performance for South Korea was estimated to be248,624 thousand vehicle kilometers per day. This value shows an increase of approximately 458 thousand vehicle kilometers per day compared to the 248,166 thousand vehicle kilometers per day reported in the highway operations manual. This outcome highlights the potential for supplementing previously omitted traffic performance data through the methodology proposed in this study.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.49-62
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• 2024

Reckless development of the underground by rapid urbanization causes inspection delay on replacement of existing structure and installation new facilities. However, frequent accidents occur due to deviation in construction design planned by inaccurate location information of underground structure. Meanwhile, the electrical resistivity survey, knowns as non-destructive method, is based on the difference in the electric potential of electrodes to measure the electrical resistance of ground. This method is significantly advanced with multi-electrode and deep learning for analyzing strata. However, there is no study to quantitatively assess change in electrical resistance according to geometric conditions of structures. This study evaluates changes in electrical resistance through geometric parameters of electrodes and structure. Firstly, electrical resistance numerical module is developed using generalized mesh occurring minimal errors between theoretical and numerical resistance values. Then, changes in resistances are quantitatively compared on geometric parameters including burial depth, diameter of structure, and distance electrode and structure under steady current condition. The results show that higher electrical resistance is measured for shallow depth, larger size, and proximity to the electrode. Additionally, electric potential and current density distributions are analyzed to discuss the measured electrical resistance around the terminal electrode and structure.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.358-366
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• 2023

This study aimed to provide a solution for improving ship collision alert of the 'accident vulnerable ship monitoring service' among the 'intelligent marine traffic information system' services of the Ministry of Oceans and Fisheries. The current ship collision alert uses a supervised learning (SL) model with survey labels based on large ship-oriented data and its operators. Consequently, the small ship data and the operator's opinion are not reflected in the current collision-supervised learning model, and the effect is insufficient because the alarm is provided from a longer distance than the small ship operator feels. In addition, the supervised learning (SL) method requires a large number of labeled data, and the labeling process requires a lot of resources and time. To overcome these limitations, in this paper, the classification model of collision alerts for small ships using unlabeled data with the semi-supervised learning (SSL) algorithms (Label Propagation and TabNet) was studied. Results of real-time experiments on small ship operators using the classification model of collision alerts showed that the satisfaction of operators increased.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.124-140
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• 2023

The rapid growth in shared E-scooters worldwide has led to many studies on the topic. The results of these studies are still in the early stages, and the main factors affecting trips are being identified. In particular, the development of trip-generation models is very important for transportation planning, and a new transportation mode for developing the models for shared E-scooters is lacking both domestically and internationally. This study aims to develop a trip generation model for shared E-scooters using significant variables by thoroughly reviewing previous studies. The trip characteristics of major service areas and other areas may differ owing to the trip characteristics of the mode. The trip generation models were developed based on the service trip density by dividing the areas by service level. The factors affecting shared E-scooter trips in major service areas included the presence of universities, closeness centrality, and cultural areas, while factors affecting the trips in minor service areas included the presence of universities, betweenness centrality, and trip distance. The developed models provide basic information that can be used to establish transport policies for introducing shared E-scooters in cities in the future.