• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.53-59
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• 2021

The marine transport industry generally applies new technologies later than other transport industries, such as airways and railways. Vessels require efficient operation, and their performance and lifespan depend on the level of maintenance and management. Many studies have shown that corrective maintenance (CM) and time-based maintenance (TBM) have restrictions with respect to enabling efficient maintenance of workload and cost to improve operational efficiency. Predictive maintenance (PdM) is an advanced technology that allows monitoring the condition and performance of a target machine to predict its time of failure and helps maintain the key machinery in optimal working conditions at all times. This study presents the development of a marine predictive maintenance (MPdM; maritime predictive maintenance) method based on applying PdM to the marine environment. The MPdM scheme is designed by considering the special environment of the marine transport industry and the extreme marine conditions. Further, results of the study elaborates upon the concept of MPdM and its necessity to advancing marine transportation in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.239-247
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• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1106-1115
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• 2021

In this study, a fin that controls ship stern flow was attached on stern hull of a 80k bulk carrier to improve resistance performance. The rectangular cross-sectional fin was attached at several locations on the hull, and angle to streamline was changed with constant length, breadth, and thickness. The resistance performance and wake on propeller plane of the hull with and without the fin were analyzed using model-scale computational fluid dynamics simulation. The analysis results were extrapolated to full-scale to compare the performance and wake of the full-scale ship. First, the fin changed path of bilge vortex that flowed into the propeller along the stern hull without the fin to transom stern. This change increased pressure of the stern hull and upper region of the propeller, so pressure resistance and total resistance of the hull were reduced - the nearer the fin location to after perpendicular (AP) and base line of the hull, the larger the reduction of the resistances. Second, nominal wake fraction of the hull with the fin was lower than that without the fin. This dif erence was in proportion to the angle of the fin, but the total resistance reduction was in proportion until a certain angle at which the reduction was maximum. The largest total resistance reduction was approximately 2.1% at 12.5% of length between perpendiculars from the AP, 10% of draft from the base line, and 14° with respect to the streamline.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.83-106
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• 2021

Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.151-168
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• 2021

This study compared and analyzed the effect of the burden of household expenditure in the metropolitan and non-metropolitan areas on the intention to childbirth intention to married women using a panel logit model. To this end, this analysis targeted married women aged 25 to 39 who are highly likely to be fertile. The main results are as follows; First of all, it was confirmed that the economic power of spouse can be an important factor in the childbirth intention regardless of region. Second, it was found that the higher the satisfaction of marriage had a positive effect on the childbirth intention, and also higher the value that children must have, the higher the childbirth intention. Third, it was confirmed that the burden of household expenditure is the most important factor in the willingness to childbirth intention, excluding factors such as the number of existing children. In particular, the burden on education spending in both the capital region and non-capital region was found to be a key reason for the decrease in the childbirth intention. Lastly, the burden of household expenditure showed different effects on childbirth intention on depending on the region. Specifically, in the capital region, medical spending and loans had a greater impact, while, in the non-capital region, transportation and communication costs had a greater impact on childbirth intentions. Through the results, this study confirmed the implication that easing the burden on household expenditure is continuously necessary to enhance childbirth, and that discriminatory policy approaches are required depending on the area of residence.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.14-34
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• 2023

The purpose of this study was to calculate the appropriate yellow-signal time for intersections, to find out the relationship between the approach speed and intersection width when calculating the time, and to secure safety by minimizing conflicts and dilemma sections in intersections that change according to the signal operation. For this purpose, 6,824 data points from 5 intersections were collected and analyzed. The main results of the study are as follows. First, the approach speed of individual vehicles in different lanes was analyzed, and the width of an intersection was defined by considering the conflict in each direction. Second, we developed a multiple regression model based on the approach speed and conflict points, which compensated for the problems of an existing formula. Third, a standard table is presented for applying the appropriate yellow-signal time according to the approach speed and intersection width based on a development formula. A method is also presented to determine the safety of the length of the dilemma according to the change in the yellow-light time by presenting a calculation table that can cross-analyze the yellow-signal time and a dilemma section using the relationship.

• Journal of the Korean Regional Science Association
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• v.39 no.3
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• pp.65-83
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• 2023

The purpose of this study is to conceptually define "spatial inclusivity" and empirically examine the impact of disability severity and spatial inclusivity on social participation among individuals experiencing physical discomfort. The social and spatial environment of the residential area is crucial for individuals with disabilities who face limited activity range and complex barriers due to physical constraints. In this study, spatial inclusivity from the perspective of people with disabilities is defined as establishment of equal relationships with non-disabled individuals within the local community, as well as the availability of basic facilities and services in a safe urban space that allows for access and utilization. This concept consists of three dimensions: individual networks, social environment, and physical environment. The physical environment encompasses safety levels, natural environment, living environment, public transportation conditions, medical services in residential areas. We used the 2019 Community Health Survey to examine the relationship between disability severity, spatial inclusivity, and social participation using a two level regression model. The findings are as follows: Firstly, personal relationships at the individual level and the physical environment at the local level have a positive impact on social participation. Secondly, when identifying dividing the physical environment into five sub-factors, no significant influence of individual factors is found. Thirdly, trustworthy and friendly social environment at the local level has a negative impact on social participation. These results provide empirical evidence that spatial inclusivity has an effect on the social participation of individuals with disabilities and suggest implications for urban planning to create and enhance conditions for the social participation of individuals with disabilities.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.87-96
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• 2022

The Ministry of Land, Infrastructure and Transport has also been promoting the commercialization of land transport technology to commercialize the technologies owned by small and medium-sized venture companies, and to support the transfer and commercialization of public technologies. At this point, in order to improve the investment effect of subsequent new projects and to select excellent research institutes, it is necessary to establish a valid evaluation index system suitable for the purpose of the project. The evaluation index system for subsequent new projects should be linked to the project objectives and goals of the preceding project, and should be selected in consideration of existing evaluation indicators to prevent interruption of research results. Therefore, this thesis sets the evaluation index system into multiple scenarios through hierarchical cluster analysis using the evaluation result data for each evaluation committee for small and medium venture companies participating in the land transportation technology commercialization support project, and then analyzes the structural equation model. As a result of scenario analysis, considering the measurement effect of each path representing the causal relationship between evaluation indicators and the effect of each evaluation index on evaluation items, the scenario with the highest impact on the evaluation result was selected as an improvement plan.

• Journal of the Korean Applied Science and Technology
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• v.40 no.2
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• pp.268-276
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• 2023

The purpose of this study is to investigate how the presence experience of virtual reality sports room class affects the intention to participate in sports activities when pleasure and immersion are experienced. For the survey, a total of 300 people, 60 copies each, were sampled for the upper grades of elementary school, and a total of 276 copies of data were used for the study, excluding 24 copies with insincere answers from among the questionnaires. The data processing used in this study was SPSS ver. 24.0 and AMOS ver. 24.0 Statistical program was used to perform confirmatory factor analysis, frequency analysis, Cronbach's α coefficient calculation, correlation analysis, and structural equation model analysis. Through this procedure, the following results were derived. First, the presence experience of the virtual reality sports room class had a positive effect on enjoyment. Second, the relationship between enjoyment and immersion in virtual reality sports room classes had a positive effect. Third, the enjoyment of the virtual reality sports room class had a positive effect on the intention to participate in sports activities. Fourth, the class immersion of the students who participated in the virtual reality sports room had a positive effect on their intention to participate in future sports activities.