• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.228-237
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• 2021

In those day, the Busan local government had instituted a rule to support and enhance competition as well as improve respect for the ship management industry. This study aims to extract the cause factors to enhance such competition using intuitionistic decision making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) methods. First, eight factors were extracted from the specifications in the Ship Management Industry Development Act. Second, the intuitionistic fuzzy number was converted to a crisp number using the standard fuzzy number. Third, the influence relationship was analyzed using DEMATEL, and the priority ranks for the factors are determined using ISM. From the results of the impact relationship analysis, the three main cause factors were determined as improvement of technical ship management capability, improvement of expertise of manpower for onshore management, and improvement of the quality of the Korean seafarer. The priorities under the ISM method, in descending order, were as follows: improvement of the quality of Korean seafarers, improvement of professionalism among the manpower for shore management, improvement of technical ship management capability, improvement of commercial ship management capability, establishment of a comprehensive information system, improvement of the working conditions and employment environment for seafarers, financial support such as overseas orders, and strengthening the availability of foreign seafarers. Therefore, it is necessary to prioritize policy promotion based on these factors, especially the top three, as these have the highest impact.

• Journal of The Korean Association For Science Education
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• v.42 no.5
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• pp.525-542
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• 2022

The purpose of this study is to comparatively analyze the internal and external frameworks of elementary science textbooks, which first appeared as the authorization system of elementary science textbooks changed from the national government system. In order to confirm the purpose of the authorization system to support the development of diverse and creative textbooks, this study compared 7 authorized textbooks with the national textbook developed as the 'Use of Magnets' unit of the 2015 revised science curriculum. In this study, the textbook's framework was largely divided into an external framework and an internal framework for the 'Use of Magnets' unit of elementary science textbooks, and quantitative and qualitative analyses were conducted in parallel according to each subcategory. According to the research results, in the external framework of textbook units, all textbooks had the same structure: unit introduction, scientific inquiry, creative convergence, unit arrangement, and scientific reading materials. The framework in the 'Use of Magnets' unit of the 7 types of authorized textbooks was found to have some differences according to the textbook development team's interpretation of the curriculum achievement standards and many commonalities that maintained the framework in the national textbooks. In addition, the characteristics of each textbook were clearly revealed in some areas not specified in curriculum such as unit introduction activities and science reading materials, a meaningful change was also found in that the level of inquiry activity was classified and operated in response to the uniform inquiry activity operation of the existing government textbooks.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.51-58
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• 2023

In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.32 no.6
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• pp.219-224
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• 2022

CaF₂ single crystal has a large band gap (12 eV), and it is used for optical windows, prisms, and lenses due to its excellent transmittance in a wide wavelength range and low refractive index. Moreover, it is expected to be one of the materials for ultraviolet transmissive laser optical components. CaF₂ belongs to the fluoride compounds and has a face-centered cubic (FCC) structure with three sub-lattices. The representative method for CaF₂ single crystal growth is Czochralski, which method has the advantages of high production efficiency and the ability to make large crystals. In this study, X-ray diffraction (XRD), X-ray rocking curves (XRC) measurement, and chemical etching were performed to analyze the crystallinity and defect density of the CaF₂ single crystals, grown by the Czochralski method. Fourier-transform infrared spectroscopy (FT-IR) and UV-VIS-NIR spectroscopy systems were used to investigate the optical properties of the CaF₂ crystal. The provability of various applications, including UV application, was systematically investigated with various analysis results.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.49-55
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• 2022

The role of drones has been expanded to various fields such as agriculture, construction, and logistics. In particular, agriculture drones are emerging as an effective alternative to solve the problem of labor shortage and reduce the input cost. In this study therefore, we proposed the fruit recognition algorithm and harvesting mechanism for fruit harvesting drone system that can safely harvest fruits at high positions. In the fruit recognition algorithm, we employ "You-Only-Look-Once" which is a deep learning-based object detection algorithm and verify its feasibility by establishing a virtual simulation environment. In addition, we propose the fruit harvesting mechanism which can be operated by a single driving motor. The rotational motion of the motor is converted into a linear motion by the scotch yoke, and the opened gripper moves forward, grips a fruit and rotates it for harvesting. The feasibility of the proposed mechanism is verified by performing Multi-body dynamics analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4C
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• pp.163-174
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• 2009

Mechanical device using the load cell or strain gage sensor can be influenced by tempearute changes because temperature change can cause a shift in the load cell or straing gage output at zero loading. In this paper, micro cone penetrometers with 1~7mm in diameter, are developed by using an optical fiber sensor (FBG: Fiber Bragg Grating) to compensate the continous temperature change during cone penetration test. Note the temperature compensated method using optical fiber sensor which has hair-size in diameter, and is not affected by environmental conditions because the measured data is the wavelength shifting of the light instead of the intensity of the electric voltage. Temperature effect test shows that the output voltage of strain gage changes and increases with an increase in the temperature. A developed FBG cone penetrometer, however, achieves excellent temperature compensation during penetration, and produces continuous change of underground temperature. In addition, the temperature compensated FBG cone shows the excellent sensitivity and detects the interface of the layered soils with higher resolution. This study demonstrates that the fiber optic sensor renders the possibility of the ultra small size cone and the new fiber optic cone may produce more reliable temperature compensated tip resistance.

• Membrane Journal
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• v.33 no.6
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• pp.325-343
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• 2023

Direct methanol fuel cells (DMFCs) have been attracting attention as energy conversion devices that can directly supply methanol liquid fuel without a fuel reforming process. The commercial polymer electrolyte membranes (PEMs) currently applied to DMFC are perfluorosulfonic acid ionomer-based PEMs, which exhibit high proton conductivity and physicochemical stability during the operation. However, problems such as high methanol permeability and environmental pollutants generated during decomposition require the development of PEMs for DMFCs using novel ionomers. Recently, studies have been reported to develop PEMs using hydrocarbon-based ionomers that exhibit low fuel permeability and high physicochemical stability. This review introduces the following studies on hydrocarbon-based PEMs for DMFC applications: 1) synthesis of grafting copolymers that exhibit distinct hydrophilic/hydrophobic phase-separated structure to improve both proton conductivity and methanol selectivity, 2) introduction of cross-linked structure during PEM fabrication to reduce the methanol permeability and improve dimensional stability, and 3) incorporation of organic/inorganic composites or reinforcing substrates to develop reinforced composite membranes showing improved PEM performances and durability.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.229-237
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• 2023

The use of artificial sources such as explosives and mechanical vibrations for seismic exploration in urban areas poses challenges, as the vibrations and noise generated can lead to complaints. As an alternative to artificial sources, the surface waves generated by traffic noise can be used to investigate the subsurface properties of urban areas. However, traffic noise takes the form of plane waves moving continuously at a constant speed. To apply existing surface wave processing/inversion techniques to traffic noise, the recorded data need to be transformed into a virtual shot gather format using seismic interferometry. In this study, various seismic interferometry methods were applied to traffic noise data, and the optimal method was derived by comparing the results in the Radon and F-K domains. Additionally, the data acquired using various receiver arrays were processed using seismic interferometry, and the results were compared and analyzed to determine the most optimal receiver array direction for exploration.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1679-1692
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• 2023

South Korea is a country that emits a large amount of pollutants as a result of population growth and industrial development and is also severely affected by transboundary air pollution due to its geographical location. As pollutants from both domestic and foreign sources contribute to air pollution in Korea, the location of air pollutant emission sources is crucial for understanding the movement and distribution of pollutants in the atmosphere and establishing national-level air pollution management and response strategies. Based on this background, this study aims to effectively acquire spatial information on domestic and international air pollutant emission sources, which is essential for analyzing air pollution status, by utilizing high-resolution optical satellite images and deep learning-based image segmentation models. In particular, industrial parks and quarries, which have been evaluated as contributing significantly to transboundary air pollution, were selected as the main research subjects, and images of these areas from multi-purpose satellites 3 and 3A were collected, preprocessed, and converted into input and label data for model training. As a result of training the U-Net model using this data, the overall accuracy of 0.8484 and mean Intersection over Union (mIoU) of 0.6490 were achieved, and the predicted maps showed significant results in extracting object boundaries more accurately than the label data created by course annotations.