• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.2
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• pp.160-167
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• 2023

An INS is a composite navigation system providing "added value" so defined if work stations provide Multi-Function Displays(MFDs) integrating information and functions for navigational tasks. Even though the minimum requirements for an INS are defined by IMO performance standards, a generic list of the devices and functions that constitute an INS does not exist, so the configuration of the INS is different for each manufacturer, and guidelines based on users' perspectives are also insufficient. This study was conducted to enhance the usability of the INS by analyzing the information required by users according to the ship's operating status and tasks and effectively structuring it in the MFD of the INS. By analyzing INS-related international standards and manufacturers' component equipment lists, mandatory navigation information was selected and card sorting tests were conducted on ship operators with experience in using MFDs to group the information required for each INS task. The results of the study can serve as a basic guideline for manufacturers to structure information based on users' experience when designing products.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.199-206
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• 2023

This study utilizes deep learning algorithms to automatically classify construction waste into three categories: wood waste, plastic waste, and concrete waste. Two models, VGG-16 and ViT (Vision Transformer), which are convolutional neural network image classification algorithms and NLP-based models that sequence images, respectively, were compared for their performance in classifying construction waste. Image data for construction waste was collected by crawling images from search engines worldwide, and 3,000 images, with 1,000 images for each category, were obtained by excluding images that were difficult to distinguish with the naked eye or that were duplicated and would interfere with the experiment. In addition, to improve the accuracy of the models, data augmentation was performed during training with a total of 30,000 images. Despite the unstructured nature of the collected image data, the experimental results showed that VGG-16 achieved an accuracy of 91.5%, and ViT achieved an accuracy of 92.7%. This seems to suggest the possibility of practical application in actual construction waste data management work. If object detection techniques or semantic segmentation techniques are utilized based on this study, more precise classification will be possible even within a single image, resulting in more accurate waste classification

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.7
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• pp.485-496
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• 2018

In this paper, the smoke behavior in an underground station on operation of the fans in the ventiliation of the station was measured by the experimental method when the fire occurred in the underground station platform where the platfrom screen door was installed. The ventilation characteristics were compared when the ventilation system was operated and when the ventilation system was not operated when a fire occurred at the platform where the clean door was closed. To simulate the fire smoke, the smoke generated from the smoke generator was heated using a hot air fan. The transmittance was measured using a smoke density meter to quantitatively measure fire smoke. If the screen door is closed and the ventilation system of the underground station does not work, it is confirmed that if a fire occurs in the platform, smoke accumulates inside the platform, evacuating passengers is very difficult and can lead to a very dangerous situation. On the other hand, under the condition that the ventilation facility of the subway station is operated, the smoke evacuates to the outside through the ventilation facility of the underground station, and airflow is formed in the direction from the waiting room to the waiting area, so that the passenger located on the platform can safely evacuate toward the concourse. In the following paper, we will discuss the concurrent effect of tunnel ventilation through tunnel vent near the platform.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1802-1813
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• 2023

Conjugate heat transfer between liquid metal and solid is a common phenomenon in a liquid-metal-cooled fast reactor's fuel assembly and heat exchanger, dramatically affecting the reactor's safety and economy. Therefore, comprehensively studying the sophisticated conjugate heat transfer in a liquid-metal-cooled fast reactor is profound. However, it has been evidenced that the traditional Simple Gradient Diffusion Hypothesis (SGDH), assuming a constant turbulent Prandtl number (Pr_t,, usually 0.85 - 1.0), is inappropriate in the Computational Fluid Dynamics (CFD) simulations of liquid metal. In recent decades, numerous studies have been performed on the four-equation model, which is expected to improve the precision of liquid metal's CFD simulations but has not been introduced into the conjugate heat transfer calculation between liquid metal and solid. Consequently, a four-equation model, consisting of the Abe k - ε turbulence model and the Manservisi k_𝜃 - ε_𝜃 heat transfer model, is applied to study the conjugate heat transfer concerning liquid metal in the present work. To verify the numerical validity of the four-equation model used in the conjugate heat transfer simulations, we reproduce Johnson's experiments of the liquid lead-bismuth-cooled turbulent pipe flow using the four-equation model and the traditional SGDH model. The simulation results obtained with different models are compared with the available experimental data, revealing that the relative errors of the local Nusselt number and mean heat transfer coefficient obtained with the four-equation model are considerably reduced compared with the SGDH model. Then, the thermal-hydraulic characteristics of liquid metal turbulent pipe flow obtained with the four-equation model are analyzed. Moreover, the impact of the turbulence model used in the four-equation model on overall simulation performance is investigated. At last, the effectiveness of the four-equation model in the CFD simulations of liquid sodium conjugate heat transfer is assessed. This paper mainly proves that it is feasible to use the four-equation model in the study of liquid metal conjugate heat transfer and provides a reference for the research of conjugate heat transfer in a liquid-metal-cooled fast reactor.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2C
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• pp.71-79
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• 2009

This study is to develope the resilient modulus prediction model, which is the function of mean effective principal stress and axial strain, for three types of railroad trackbed materials such as crushed stone, weathered granite soil, and crushed-rock soil mixture. The model consists of the maximum Young's modulus and nonlinear values for higher strain, analogous to dynamic shear modulus. The maximum value is modeled by model parameters, $A_E$ and the power of mean effective principal stress, $n_E$. The nonlinear portion is represented by modified hyperbolic model, with the model parameters of reference strain, ${\varepsilon}_r$ and curvature coefficient, a. To assess the performance of the prediction models proposed herein, the elastic response of a test trackbed near PyeongTaek, Korea, was evaluated using a 3-D elastic multilayer computer program (GEOTRACK). The results were compared with measured elastic vertical displacement during the passages of freight and passenger trains at two locations, whose sub-ballasts were crushed stone and weathered granite soil, respectively. The calculated vertical displacements of the sub-ballasts are within the order of 0.6mm, and agree well with measured values. The prediction models are thus concluded to work properly in the preliminary investigation.

• The Journal of Bigdata
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• v.7 no.1
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• pp.173-185
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• 2022

Nowadays, Korean webtoons are leading the global digital comic market. Webtoons are being serviced in various languages around the world, and dramas or movies produced with Webtoons' IP (Intellectual Property Rights) have become a big hit, and more and more webtoons are being visualized. However, with the success of these webtoons, the working environment of webtoon creators is emerging as an important issue. According to the 2021 Cartoon User Survey, webtoon creators spend 10.5 hours a day on creative activities on average. Creators have to draw large amount of pictures every week, and competition among webtoons is getting fiercer, and the amount of paintings that creators have to draw per episode is increasing. Therefore, this study proposes to generate webtoon background images using deep learning algorithms and use them for webtoon production. The main character in webtoon is an area that needs much of the originality of the creator, but the background picture is relatively repetitive and does not require originality, so it can be useful for webtoon production if it can create a background picture similar to the creator's drawing style. Background generation uses CycleGAN, which shows good performance in image-to-image translation, and CartoonGAN, which is specialized in the Cartoon style image generation. This deep learning-based image generation is expected to shorten the working hours of creators in an excessive work environment and contribute to the convergence of webtoons and technologies.

• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

• Journal of the Korean Society for information Management
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• v.39 no.4
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• pp.269-306
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• 2022

This study aimed to develop indicators that can measure the digital transformation performance of science and technology information construction and sharing systems by utilizing the Digital Curation Maturity Models. For digital transformation, it is necessary to consider not only simple service improvement but also organizational and business changes. In this study, we aimed to develop a model for measuring the digital transformation of KISTI, Korea's representative science and technology information service organization. KISTI has already carried out BPR work for digital transformation and borrowed the concept of a maturity model. However, in BPR, there is no method to measure the result. Therefore, in this paper, we developed an index to measure digital transformation based on the maturity model. Indicator development was carried out in two ways: model development and evaluation. Cases for model construction were made through a comprehensive review of existing KISTI and various domestic and foreign cases. The models before verification were technology (37), data (45), strategy (18), organization (36), and (social)influence (14) based on the major categories. After verification using confirmatory factor analysis, the model is classified as technology (20 / 17 indicators dropped), data (36 / 9 indicators dropped), strategy (18 / maintenance), organization(30 / 6 indicators dropped), and (social) influence (13 indicators / 1 indicator dropped).

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.214-222
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• 2022

It is important to realize employment equality to fulfill corporate social responsibility. The most suitable indicator for assessing its performance is the gender wage gap. Korea is considered the country with the most severe gender wage gap among OECD member countries, however, studies on the gender wage gap have been mainly attempted to explain in terms of the structure of the labor market, government policies, etc. This study focus on the characteristics of CEO and HR systems among the characteristics of organizations affecting the gender wage gap. The management philosophy sets the direction of organizational decision-making and activates the system. In addition, the HR system enables fair and objective organizational management for members through rules and procedures. However, even in organizations seeking rationalization, minority people may experience discrimination. Moreover, the rational HR system may act as a mechanism to justify discrimination, contrary to existing intentions. This study proposes that in order for the rational HR system to work positively, it must be based on the management philosophy. In other words, it is intended to derive a mechanism that can alleviate the gender wage gap from the integrated perspective of the characteristics of the CEO and the rational HR system. In particular, it aims to provide specific implications for how the organization should operate the HR system by examining the gender wage gap based on internal factors of companies that utilize manpower.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.469-478
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• 2019

This study is an empirical survey of the job status and job satisfaction of early childhood teachers. The subjects of this study were teachers of early childhood education in (the province of) Chungcheongnam-do. The Early Childhood Education Institution was conducted with 255 teachers for teachers working in public day care centers, private day care centers, public kindergartens and private kindergartens. o carry out this study, we analyzed the collected questionnaires by using the SPSS statistical package program. T-test, χ²-validation and ANOVA analysis were used for this study, and Scheffé analysis was applied as a post hoc analysis. As a result of this study, job status was examined by type, age, educational attainment, and educational experience. The satisfaction level of educational institutions was highest in the national public day care centers, and the age was 50 years or older, and the education level was high in graduate school. In addition, the job satisfaction of early childhood teachers was significantly analyzed in relation to fellow teacher, relationship with the director, self-identity and teaching environment. Through this study, understanding the current job status and satisfaction of early childhood education teachers can be used as an important data in preparing a plan to raise their job performance and work efficiency.