• Journal of Life Science
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• v.34 no.3
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• pp.145-152
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• 2024

Seaweeds represent a widely harnessed marine resource that are valued for their abundant supply of essential nutrients, particularly proteins and amino acids. In Korea, where over 500 species of seaweed thrive and more than 50 are utilized for culinary purposes, seaweed has become a staple in regular diets. In this study, we focused on five of the most commonly consumed seaweed species in Korea: Capsosiphon fulvescens, Hizikia fusiforme, Porphyra yezoensis, Saccharina japonica, and Undaria pinnatifida. We closely examined the amino acid compositions of these five species. High-performance liquid chromatography showed that aspartic acid, glutamic acid, alanine, and leucine were the most abundant amino acids in the seaweeds. Principal component analysis revealed that the five seaweed species could be classified into three clusters according to their amino acid composition, partially corroborating findings from the phylogenetic analysis. Among various amino acids, glutamic acid, aspartic acid, and alanine were the primary amino acids driving differentiation. Notably, U. pinnatifida and C. fulvescens, which demonstrated close phylogenetic proximity, exhibited remarkably similar amino acid profiles. Conversely, although P. yezoensis and S. japonica shared a phylogenetic relationship, they displayed distinctly different amino acid compositions. H. fusiforme emerged as a distinct group in both analyses.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.3
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• pp.81-95
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• 2024

This study empirically analyzed the effectiveness of government financial support policies for venture enterprises in the Daejeon region, using raw data obtained from the Small and Medium Venture Business Administration's survey results from 2016 to 2021. Daejeon, considering its economic significance, has a significant proportion of venture enterprises in its economy compared to the national average, with a focus on technological development. Conducting regression analysis yielded several key findings. Firstly, loan and guarantee support is effective for improving sales and market share, while R&D support is effective for technological development. Second, R&D and loan support have the most significant impact on sales in the fourth stage (maturity), while guarantee support is most influential in the third stage. Third, in industry analysis, the coefficients representing the effects of financial support were larger across all performance indicators compared to firm level data analysis. Based on these empirical analysis results, the study proposes several policy implications as follows. First, the government should actively provide funding support to venture companies rather than leaving investments to the capital market. Second, the methods and targets of funding support should vary according to the purpose of the support. Third, it is necessary to establish a platform that connects venture companies with private investors to commercialize developed technologies. Fourth, the funding support of venture capital for technology-intensive venture companies should be expanded.

• Journal of Space Technology and Applications
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• v.4 no.2
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• pp.121-136
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• 2024

Korea Pathfinder Lunar Orbiter (KPLO), launched in August 2022, is successfully carrying out its mission. Korea's lunar lander and rover programs are expected to proceed in the future. To successfully carry out the mission after the lunar lander has landed on the surface, the performance of the equipment to be mounted should be checked in a laboratory environment similar to the Moon. Scientists and engineers of several countries, including the United States and China, use lunar soil simulant which is developed to resemble lunar soil for simulating the surface of the lunar landing site. Several lunar probe landing sites are being discussed in Korea, and lunar soil simulants such as Korea Hanyang Lunar Simulant-1 (KOHLS-1), Korea Aerospace University Mechanical Lunar Simulants (KAUMLS), and Korea Lunar Simulant-1 (KLS-1), which are similar to the characteristics of lunar mare soil, have been developed. However, those simulants are not useful if the landing site is chosen as a highland area. In this study, we introduce the process of developing KIGAM-L1, a lunar highland soil simulant similar to the chemical composition of the Apollo 16 lunar soil sample and the particle size distribution of lunar soil sample 60500-1, in case the lunar lander lands at highland area.

• Journal of Platform Technology
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• v.12 no.3
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• pp.41-54
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• 2024

Recently, support for various types of entrepreneurship has been increasing. At the same time, interest in entrepreneurship education is increasing to expand support for entrepreneurship and improve entrepreneurship performance. Therefore, the scope and interest of entrepreneurship education and support is expanding beyond college students and the general public to include high school students. Accordingly, this study seeks to investigate in more depth the relationship between entrepreneurship competency, entrepreneurship attitude, and intention to start a business in order to increase the intention to start a business. As a result of the analysis, entrepreneurship capabilities (creativity, risk-taking, and innovation) had a positive effect on attitude toward entrepreneurship, and attitude toward entrepreneurship had a positive effect on the will to start a business. In addition, the results of the analysis of the mediating effect of entrepreneurship attitude in the relationship between entrepreneurship capabilities (creativity, risk-taking, and innovation) and entrepreneurship will are as follows. First, in the relationship between creativity and entrepreneurial will, entrepreneurial attitude played a partial mediating role. Additionally, in the relationship between risk tolerance and entrepreneurial intention, entrepreneurial attitude played a partial mediating role. Lastly, in the relationship between innovation and entrepreneurial will, entrepreneurial attitude played a complete mediating role. The research conclusion summarizes the results of this study, suggests implications for entrepreneurs and start-ups, as well as limitations of this study and directions for future research..

• Applied Chemistry for Engineering
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• v.35 no.3
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• pp.200-208
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• 2024

Chung's equations-IX and Chung's equation-XII were utilized to predict the fire risk and evaluate fire risk ratings for four types of wood: camphor, cherry, rubber, and elm trees. The combustion tests were conducted using a cone calorimeter test method by ISO 5660-1 standards. The fire risk and fire risk rating (FRR) were compared for Fire Risk Index-IX (FRI-IX) and Fire Risk Index-XII (FRI-XII). The results yielded Fire Performance Index-XI (FPI-XI) ranging from 0.08 to 11.48 and Fire Growth Index-XI (FGI-XI) ranging from 0.67 to 111.89. The Fire Risk Index-XII (FRI-XII), indicating fire risk rating, exhibited an increasing order of cherry (0.45): Grade A (Ranking 5) < PMMA (1): Grade A (Ranking 4) < elm (1.23): Grade A (Ranking 3) < rubber (1.56): Grade A (Ranking 2) << camphor (148.23): Grade G (Ranking 1). Additionally, the fire risk index-IX (FRI-IX) was cherry (0): Grade A (Ranking 3) ≈ rubber (0): Grade A (Ranking 3) ≈ elm tree (0): Grade A (Ranking 3) < PMMA (1): Grade A (Ranking 2) << camphor tree (66.67): Grade G (Ranking 1). In general, camphor was found to have the highest fire risk. In conclusion, although the expression of the index is different as shown based on the standards of FRI-IX and FRI-XII, predictions based on fire risk assessment of combustible materials showed similar trends.

• Journal of Platform Technology
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• v.11 no.5
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• pp.59-71
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• 2023

This paper proposes a method of estimating the illumination chromaticity of a scene in which an image is taken. Storring and Bianco proposed a method of estimating illuminant chromaticity using skin color. Storring et al. used skin color distribution characteristics and black body locus, but there is a problem that the link between the locus and CIE-xy data is reduced. Bianco et al. estimated the illuminant chromaticity by comparing the skin color distribution in standard lighting with the skin color distribution in the input image. This method is difficult to measure and secure as much skin color as possible in various illumination. The proposed method can estimate the illuminant chromaticity for any input image by analyzing the relationship between the skin color information and the illuminant chromaticity. The estimation method is divided into an analysis stage and a test stage, and the data set was classified into an analysis group and a test group and used. Skin chromaticity is calculated by obtaining skin color areas from all input images of the analysis group, respectively. A mapping is obtained by analyzing the correlation between the average set of skin chromaticity and the reference illuminant chromaticity set. The calculated mapping is applied to all input images of the analysis group to estimate the illuminant chromaticity, calculate the error with the reference illuminant chromaticity, and repeat the above process until there is no change in the error to obtain a stable mapping. The obtained mapping is applied to the test group images similar to the analysis stage to estimate the illuminant chromaticity. Since there is no independent data set containing skin area and illuminant reference information, the experimental data set was made using some of the images of the Intel TAU data set. Compared to Finlayson, a similar theory-based existing method, it showed performance improvement of more than 40%, Zhang 11%, and Kim 16%.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.23-41
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• 2024

Recently, various virtual avatar music content that showcases singing and dancing have been produced, and as virtual artists gain popularity, offline virtual avatar concerts have also emerged. However, there are few examples of virtual avatar band content where avatars play instruments. In addition, offline virtual avatar concerts using large screens at the front are limited in their ability to utilize the fantastical effects and high degree of freedom unique to virtual reality. In this paper, inspired by these limitations of virtual avatar music content, we introduce the production case of virtual avatar band content and immersive interactive concert of virtual band idol Verse'day. Firstly, we present a case study on creating band performance animations and music videos using motion capture systems and real-time engines. Then, we introduce a production case of an immersive interactive concert using projection mapping technology and a light stick that allows real-time interaction in an offline concert. Finally, based on these production cases, we discussed the future research directions of developing virtual avatar music content creation. We expect that our production cases will inspire the creation of diverse virtual avatar music content and the development of immersive interactive offline virtual avatar concerts in the future.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.4
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• pp.267-277
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• 2024

The Sortie Generation Rate (SGR) is a critical performance indicator for carrier-based aircraft and is a key factor for the carrier design process. This study aims to analyze the factors that affect SGR and establish a representative Sortie Generation Process (SGP) along with simulation results to calculate SGR for a naval ship equipped to carry aircraft. Detailed SGR factors are identified from the perspectives of the aircraft, aviation personnel, and aircraft carrier during the flight preparation stage, and the SGP is established accordingly. As a representative, Korean Navy's CVX basic design is chosen for detailed analysis. The physical dimension and spots for the deck design with time and probabilistic data of SGP are considered to develop a queueing network model for SGR calculation. To consider the specific probabilistic features, the model was solved with discrete event simulation tools(SimPy and AnyLogic) where the results show great agreement. Such findings on SGR factors and calculation are expected to be incorporated in the future development of SGR calculation algorithms and also present guidelines for proper design of aircraft carrier based on concrete operation concept.

• Journal of the Korean Society of Radiology
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• v.18 no.4
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• pp.317-325
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• 2024

This study aimed to classify normal and nodule images in thyroid ultrasound images using GLCM and machine learning. The research was conducted on 600 patients who visited S Hospital in Busan and were diagnosed with thyroid nodules using thyroid ultrasound. In the thyroid ultrasound images, the ROI was set to a size of 50x50 pixels, and 21 parameters and 4 angles were used with GLCM to analyze the normal thyroid patterns and thyroid nodule patterns. The analyzed data was used to distinguish between normal and nodule diagnostic results using the SVM model and KNN model in MATLAB. As a result, the accuracy of the thyroid nodule classification rate was 94% for SVM model and 91% for the KNN model. Both models showed an accuracy of over 90%, indicating that the classification rate is excellent when using machine learning for the classification of normal thyroid and thyroid nodules. In the ROC curve, the ROC curve for the SVM model was generally higher compared to the KNN model, indicating that the SVM model has higher within-sample performance than the KNN model. Based on these results, the SVM model showed high accuracy in diagnosing thyroid nodules. This result can be used as basic data for future research as an auxiliary tool for medical diagnosis and is expected to contribute to the qualitative improvement of medical services through machine learning technology.

• Journal of the Korea Society of Computer and Information
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• v.29 no.8
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• pp.11-21
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• 2024

This study explores the use of virtual reality (VR) technology to identify and label key segments of the golf swing. To address the limitations of existing VR devices, we developed a platform to collect kinematic data from various VR devices using the OpenVR SDK (Software Development Kit) and SteamVR, and developed a semi-automated labeling technique to identify and label temporal changes in kinematic behavior through LSTM (Long Short-Term Memory)-based time series data analysis. The experiment consisted of 80 participants, 20 from each of the following age groups: teenage, young-adult, middle-aged, and elderly, collecting data from five swings each to build a total of 400 kinematic datasets. The proposed technique achieved consistently high accuracy (≥0.94) and F1 Score (≥0.95) across all age groups for the seven main phases of the golf swing. This work aims to lay the groundwork for segmenting exercise data and precisely assessing athletic performance on a segment-by-segment basis, thereby providing personalized feedback to individual users during future education and training.