• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.848-853
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• 2004

Regarding to the project SUAV (Smart Unmanned Aerial Vehicle) in KARI (Korea Aerospace Research Institute), several engine configurations has been evaluated. However it's not an easy task to collect all the necessary data of each engine for the analysis. Usually, some kind of modeling technique is required in order to determine the unknown data. In the present paper a qualitative method for reverse engineering is proposed, in order to identify some design patterns and relationships between parameters. The method can be used to estimate several parameters that usually are not provided by the manufacturer. The method consists of modeling an existing engine and through a simulation, compare its transient behavior with its operating envelope. In the simulation several parameters such as thermodynamics, performance, safety and mechanics concerning to the definition of operation-envelope, have been discussed qualitatively. With the model, all engine parameters can be estimated with acceptable accuracy, making possible the study of dependencies among different parameters such as power-turbine total inertia, TIT, take-off time and part load, in order to check if the engine transient performance is within the design criteria. For more realistic approach and more detailed design requirements, it will be necessary to enhance the compressor map first, and more realistic estimated values must be taken into account for intake-loss, bleed-air and auxiliary power extraction. The relative importance of these “unknown” parameters must be evaluated using sensitivity analysis in the future evaluation. Moreover, fluid dynamics, thermal analysis and stress analysis necessary for the resulting life assessment of en engine, will not be addressed here but in a future paper. With the methodology presented in the paper was possible to infer the relationships between operation-envelope and engine parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.1-19
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• 2021

The graph-based tag recommendation algorithm FolkRank can effectively utilize the relationships between three entities, namely users, items and tags, and achieve better tag recommendation performance. However, FolkRank does not consider the internal relationships of user-user, item-item and tag-tag. This leads to the failure of FolkRank to effectively map the tagging behavior which contains user neighbors and item neighbors to a tripartite graph. For item-item relationships, we can dig out items that are very similar to the target item, even though the target item may not have a strong connection to these similar items in the user-item-tag graph of FolkRank. Hence this paper proposes an improved FolkRank algorithm named FolkRank++, which fully considers the user-user and item-item internal relationships in tag recommendation by adding the correlation information between users or items. Based on the traditional FolkRank algorithm, an initial weight is also given to target user and target item's neighbors to supply the user-user and item-item relationships. The above work is mainly completed from two aspects: (1) Finding items similar to target item according to the attribute information, and obtaining similar users of the target user according to the history behavior of the user tagging items. (2) Calculating the weighted degree of items and users to evaluate their importance, then assigning initial weights to similar items and users. Experimental results show that this method has better recommendation performance.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.132-133
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• 2023

The safe evacuation of people during disasters is of utmost importance. Various life safety evacuation simulation tools have been developed and implemented, with most relying on algorithms that analyze maps to extract the shortest path and guide agents along predetermined routes. While effective in predicting evacuation routes in stable disaster conditions and short timeframes, this approach falls short in dynamic situations where disaster scenarios constantly change. Existing algorithms struggle to respond to such scenarios, prompting the need for a more adaptive evacuation route algorithm that can respond to changing disasters. Artificial intelligence technology based on reinforcement learning holds the potential to develop such an algorithm. As a fundamental step in algorithm development, this study aims to evaluate whether an evacuation algorithm developed by reinforcement learning satisfies the performance conditions of the evacuation simulation tool required by IMO MSC.1/Circ1533.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.5
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• pp.203-220
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• 2020

The purpose of this study is to examine the importance of entrepreneurs' well-being, and to propose several ways to improve it. First, the factors influencing entrepreneurs' well-being were explored via previous literature review, and positive psychological capital based on positive psychology was selected as the main factor. In addition, the hypotheses were formulated and the research model was constructed by selecting authentic leadership, mastery goal orientation, and social support as the antecedents predictably associated with positive psychological capital. To empirically analyze the proposed model, a questionnaire survey was conducted for the entrepreneurs who fulfilled the training/coaching/consulting programs offered by the Youth Startup Academy. By using the collected 133 responses, PLS-Structural Equation Analysis, PLS-Multi Group Analysis(MGA), and PLS-Importance-Performance Map Analysis(IPMA) were performed. As a result, it was found that positive psychological capital had a high causal relationship with the well-being of entrepreneurs; and authentic leadership and mastery goal orientation had a positive effect on positive psychological capital. However, the statistical significance of the impact of social support has not been verified. While differences in causality between early and growing stages of start-ups only acted as sub-factors of positive psychological capital, the aforementioned three antecedents showed a significant difference for hope and optimism, respectively. This study expanded the topic of entrepreneurship-related research, which mostly focuses on identifying the performance factors of start-ups. It is meaningful in that it empirically verified the causality model constructed by exploring the factors with respect to the mental well-being of entrepreneurs, which is a main theme in the entrepreneurship-related research. These results found in the current study will render practical insights to entrepreneurs, researchers, and educators.

• Journal of Korean Society for Quality Management
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• v.44 no.2
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• pp.389-408
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• 2016

Purpose: This study was designed to analyze the behavioral change of knowledge structures and the trends of research topics in the quality management field. Methods: The network structure and knowledge structure of the words were visualized in map form using co-word analysis, cluster analysis and strategic diagram. Results: Summarizing the research results obtained in this study are as follows. First, the word network derived from co-occurrence matrix had 106 nodes and 5,314 links and its density was analyzed to 0.95. Average betweenness centrality of word network was 2.37. In addition, average closeness centrality and average eigenvector centrality of word network were 0.01. Second, by applying optimal criteria of cluster decision and K-means algorithm to word co-occurrence matrix, 106 words were grouped into seven clusters such as standard & efficiency, product design, reliability, control chart, quality model, 6 sigma, and service quality. Conclusion: According to the results of strategic diagram analysis over time, the traditional research topics of quality management field related to reliability, 6 sigma, control chart topics in the third quadrant were revealed to be declined for their study importance. Research topics related to product design and customer satisfaction were found to be an important research topic over analysis periods. Research topic related to management innovation was emerging state and the scope of research topics related to process model was extended to research topics with system performance. Research topic related to service quality located in the first quadrant was analyzed as the key research topic.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.239-250
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• 2020

This study was conducted to elicit the competencies of college faculties and their educational needs depending on the careers. 110 full-time professors from A college in Gyeonggi-do participated in this study from November 27 to December 7, 2018. The findings are that competencies of college faculties were found as 10 teaching competencies and 7 general competencies, and most of the competencies showed differences in importance and performance. In addition, according to the t-test and Borich needs analysis, there were differences in the educational needs of faculties depending on the three careers: a group with less than five years of experience, a group with six to ten years of experience, and a group with more than 11 years of experience. The results of this study suggest the systematic education and training program to improve the competencies of college faculties are necessary and show designing a concrete road map and training manual is needed.

• Progress in Medical Physics
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• v.29 no.4
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• pp.123-136
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• 2018

The complex dose distribution and dose transfer characteristics of intensity-modulated radiotherapy increase the importance of precise beam data measurement and review in the acceptance inspection and preparation stages. In this study, we propose a process map for the introduction and installation of high-precision radiotherapy devices and present items and guidelines for risk management at the acceptance test procedure (ATP) and commissioning stages. Based on the ATP of the Varian and Elekta linear accelerators, the ATP items were checked step by step and compared with the quality assurance (QA) test items of the AAPM TG-142 described for the medical accelerator QA. Based on the commissioning procedure, dose quality control protocol, and mechanical quality control protocol presented at international conferences, step-by-step check items and commissioning guidelines were derived. The risk management items at each stage were (1) 21 ionization chamber performance test items and 9 electrometer, cable, and connector inspection items related to the dosimetry system; (2) 34 mechanical and dose-checking items during ATP, 22 multileaf collimator (MLC) items, and 36 imaging system items; and (3) 28 items in the measurement preparation stage and 32 items in the measurement stage after commissioning. Because the items presented in these guidelines are limited in terms of special treatment, items and practitioners can be modified to reflect the clinical needs of the institution. During the system installation, it is recommended that at least two clinically qualified medical physicists (CQMP) perform a double check in compliance with the two-person rule. We expect that this result will be useful as a radiation safety management tool that can prevent radiation accidents at each stage during the introduction of radiotherapy and the system installation process.

• Journal of the Korean Applied Science and Technology
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• v.40 no.5
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• pp.1043-1054
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• 2023

Amidst the rapid growth of the vegan cosmetics market, consumer orientation towards environmental and ethical values has been intensifying. However, research on this subject remains limited. This study delves into the relationship between consumer value perception, environmental motivations, and perceived barriers influencing the purchase intentions of vegan cosmetics. Conducting a PLS-SEM analysis on a sample of 300 women with experience using vegan cosmetics, it was discerned that monetary value, social value, brand value, emotional value, quality value, and environmental knowledge play significant roles in influencing purchase intentions. The moderating effect analysis highlighted image barriers and value barriers as crucial factors. Through Importance-Performance Map Analysis, emotional value emerged as a pivotal element in strategizing to strengthen the purchasing intentions for vegan cosmetics. This research contributes both theoretically and practically to enhancing the competitive edge of the vegan cosmetics market and promoting sustainable consumption behavior.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.655-665
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• 2016

Considering the importance of SMEs, which account for 88% of employment and 99% of domestic businesses, the government has implemented informatization policy support. On the other hand, due to budget limitations and the ability of the private market, it is time to transition to the new policy of the informatization support paradigm. This study evaluated the informatization policy support of SMBA by a comparison with the stage model to determine the future direction. The informatization development model is a step model divided into five levels ranging from the informatization initiation level to the strategic innovation level. The informatization policy of SMBA was focused on the development of automation and in-house integration, and business-to-business integration and strategic innovation step was found to be lacking. Based on these results, there are three implications for the informatization policy of the next SMEs. First, there is a need for a movement of the center of the support in the informatization step to the strategic innovative step. Second, by establishing an informatization road map, it is necessary to develop their own informatization capabilities according to the road map. Finally, it is important to improve the effectiveness of informatization support based on performance rather than policy providers.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.