• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.101-114
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• 2023

In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.347-355
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• 2022

The safety valve (PSV) is a safety device that automatically releases a spring when the pressure generated by various causes reaches the set pressure, and is restored to a normal state when the pressure falls below a certain level. Periodic inspection and monitoring of safety valves are essential so that they can operate normally in abnormal conditions such as pressure rise. However, as the current safety inspection is performed only at a set period, it is difficult to ensure the safety of normal operation. Therefore, evaluation items were developed by finding failure modes and causative factors of safety valves required for safety management. In addition, it is intended to provide decision-making information for securing safety by deriving the priority of items. To this end, a Delphi survey was conducted three times to derive evaluation factors that were judged to be important in relation to the Failure Mode Cause Factor (FMCFs) of the safety valve (PSV) targeting 15 experts. As a result, 6 failure modes of the safety valve and 22 evaluation factors of its sub-factors were selected. In order to analyze the priorities of the evaluation factors selected in this way, the hierarchical structure was schematized, and the hierarchical decision-making method (AHP) was applied to the priority calculation. As a result of the analysis, the failure mode priorities of FMCFs were 'Leakage' (0.226), 'Fail to open' (0.201), 'Fail to relieve req'd capacity' (0.152), 'Open above set pressure' (0.149), 'Spuriously' 'open' (0.146) and 'Stuck open' (0.127) were confirmed in the order. The lower priority of FMCFs is 'PSV component rupture' (0.109), 'Fail to PSV size calculation' (0.068), 'PSV Spring aging' (0.065), 'Erratic opening' (0.059), 'Damage caused by improper installation and handling' (0.058), 'Fail to spring' (0.053), etc. were checked in the order. It is expected that through efficient management of FMCFs that have been prioritized, it will be possible to identify vulnerabilities of safety valves and contribute to improving safety.

• Korean small business review
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• v.31 no.1
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• pp.73-88
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• 2009

This study examines the characteristics of 24 Korean hidden champions such as key success factors, core competences, strategic problems, and desirable future directions. The study categorized them into 8 types with Danny Miller's four trajectories and top manager's decision making style(rationality and passion). Danny Miller argued in his book, Icarus paradox, that outstanding firms will extend their orientations until they reach dangerous extremes and their momentum will result in common trajectories of decline. He suggested four very common success types: Craftsmen, Builders, Pioneers, Salesmen. He also suggested common trajectories of decline:Focusing(from Craftsmen to Tinkers), Venturing(from Builders to Imperialists), Inventing(from Pioneers to Escapists), Decoupling(from Salesmen to Drifts). In Korea, successful startups appear to possess three kinds of drive: Technology-drive, Vision-drive, Market-drive. Successful technology-driven firms tend to grow as craftsmen or pioneers. Successful vision-driven and market-driven ones tend to grow as builders and salesmen respectively. Korean top managers or founders seem to have two kinds of decision making style: Passion-based and Rationality-bases. Passion-based(passionate) entrepreneurs are biased towards action or proactiveness in competing and getting things done. Rationality- based ones tend to emphasis the effort devoted to scanning and analysing information to better understand a company's threats, opportunities and options. Consequently this study suggested 4*2 types of Korean hidden champions: (1) passionate craftsmen, (2) rational craftsmen, (3) passionate builders, (4) rational builders, (5) passionate pioneers, (6) rational pioneers, (7) passionate salesmen, (8) rational salesmen. These 8 type firms showed different success stories and appeared to possess different trajectories of decline. These hidden champions have acquired competitive advantage within domestic or globally niche markets in spite of the weak market power and lack of internal resources. They have maintained their sustainable competitiveness by utilizing three types of growth strategy; (1) penetrating into the global market, (2) exploring new service market, (3) occupying the domestic market. According to the types of growth strategy, these firms showed different financial outcomes and possessed different issues for maintaining their competitiveness. This study found that Korean hidden champions were facing serious challenges from the transforming economic structure these days and possessed the decline potential from their success momentum or self-complacence. It argues that they need to take a new growth engine not to decline in the turbulent environment. It also discusses how firms overcome the economic crisis and find a new business area in promising industries for the future. It summarized the recent policy of Korean government called as "Green Growth" and discussed how small firms utilize such benefits and supports from the government. Other implications for firm strategies and governmental policies were discussed.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Journal of Korean Society of Steel Construction
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• v.20 no.5
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• pp.609-616
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• 2008

Recently, many ocean bridges that connect land to island or island to island have been constructed along with the improvement of the nation's economy. Long-span bridges can be categorized as suspension bridge, cable-stayed bridge, arch bridge and truss bridge. In this study, correction with respect to construction error can be presented on site through the monitoring of the cable tension change of real structure for four major construction stages so that construction accuracy, including the management of profiles, can be improved. A vibration method, the so-called indirect method that uses the cable's natural frequency changes from the acceleration sensor installed on the cable, is applied in measuring cable tension. In this study, the estimation formula for the effective length of cable with damper is presented by comparing and analyzing between actual measurement and analysis result for the change of the cable's effective length. By the way, it is known that the reliability of estimating cable tension by applying the former method that uses the net distance from damper to anchorage is low. Therefore, for future reference of the maintenance stage, the presented formula for estimating the effective length of cable can be used as a reference for the rational decision-making, such as the re-tensioning and replacement of cable.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.38
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• pp.327-376
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• 2008

China is marking 9.4% annual growth rate in average since 1978. GDP reached $1090 in 2003 as the first time and China ranked at 4th with their economy size in 2006. One of the remarkable change in China is the extension of foreign open-door policy. China joined WTO in the end of 2001 and it strengthen the foundation of Chinese market economy structure and encouraged the inflow of foreign capital. While 400 of the 500 global corporations advanced into China, the economy trade has been rapidly increasing between Korea and China. The economy trade in both countries has been regularized since 1992 and the annual trade is tending upwards in last 15 years. Korean trade toward China reached 134,400 million which is increased 27 times compared with the total of 1982. In this period, Korean trade toward China marked 24.5% in Export increasing rate and 16.7% in import increasing rate. China became the 2nd biggest export country of Korea in 2001 and became the top in 2003. As the China foreign direct investment has been increasing rapidly, the number of Korean companies advanced into China has been remarkably increasing. By focusing on a thorough review of the nationally published documents of Korean-Chinese business management research during more than two decades (1981-2004), the present paper has been systematically classified and analyzed the current status of Korean-Chinese business management research. The paper raised some important issues regarding Korean-Chinese business management research and predominantly, its future prospects are outlined. In the paper, the documents which are registered in the Korean Academic Processing Foundation registration of journals and candidate registration of journals have been classified by: research purpose, main subject, research method and the results. Careful analysis among the research clarified the active and inactive business management research fields. This clarification enables us to get a better understanding of the current research of Korean-Chinese business management, and more importantly, it pointed out to the direction of future development of research. In addition, the systematic classification made by this paper may contribute to the decision making of subject index of Korean-Chinese business management research since there has been no classification standard of it until now.

• Korean Journal of Construction Engineering and Management
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• v.15 no.5
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• pp.103-114
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• 2014

Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple performance factors that are grouped into outputs and inputs. DEA has proven to be superior to simple aggregation of performance measures, and is also useful for evaluating the performance of construction companies for comparison with competitor performance. The purpose of this study was to survey literatures on the application of DEA methodology and to propose a methodological scheme to measure the performance of construction organizations. Articles on previous studies were surveyed and examined as part of a comprehensive review. The survey revealed that the application of DEA in the construction industry was li mited. Further, the survey indicated that there is a need for the development of a methodological framework on the special goals and subjects of performance measurement, methods of data structure and collection, selection of appropriate DEA models, analysis of results, and post-test. Based on the survey, this study identified and discussed the types of major issues and topics for future studies from a methodological perspective, which could be helpful to researchers interested in using DEA to study performance issues in construction organizations.

• International Commerce and Information Review
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• v.18 no.4
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• pp.3-29
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• 2016

Recently, the market size of the global electronic-commerce is rapidly growing. The global market size of an overseas direct-purchase is expected to reach 1 trillion won by 2020. This study intends to determine the decision making factors of B2B overseas direct-purchase(DP) and reverse direct-purchase(RDP), and the impact on the vitalization of the small to middle-sized companies'(SMC) overseas DP and RDP. Ultimately, the purpose of this study is to provide a policy insight on the expansion of exports by SMC. For this, we determined the necessary elements for getting good results by Korean SCM in the overseas DP and RDP market through a preceding research based on resource-based theory and industry structure theory. Afterwards, we used the multiple regression model for positive analysis of the survey documents. We were able to confirm through analysis that the company information, logistics delivery, customs process, law and regulations have positive effects on the overseas DP and RDP. This study surveyed the entire overseas DP market, rather than focusing on the cases of harm and responses of the overseas DP, which was the topic for the preceding research, and can be differentiated from the previous study by deducting influence factors for the Korean SMC to succeed in the overseas DP and RDP market. Moreover, the results of this study is meaningful in proposing a strategic direction for the SMC participating in the overseas DP market and the government enacting policies.

• Management & Information Systems Review
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• v.39 no.2
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• pp.145-162
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• 2020

This study examines problems with using the conventional analytic hierarchy process (AHP) method and proposes a method of weight adjustment as a modification of AHP. AHP is a method for transforming complex decision problems into a hierarchal structure, which is composed of elements in the upper and lower levels and then using pairwise comparisons to evaluate these elements and subsequently to obtain their relative weights. The elements' relative importance is reliable if the elements in the lower hierarchical levels (sub factors) that comprise each element in the upper hierarchical level (primary factor) are equal in number. In other words, if the number of sub factors is different for each primary factor, a serious error is expected as a result. Therefore, this study proposes a modification of AHP that can avoid such an error when AHP is used. Specifically, an error that arises from different number of sub factors (matrix size) can be overcome by making the number of sub factors identical for each primary factor. The resulting model has been validated through the applications in different AHP hierarchical structures.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.545-557
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• 2017

The study is about the efficient alternative to concrete surface in the field of visual inspection technology for deteriorated infrastructure. By combining industrial drones and deep learning based image analysis techniques with traditional visual inspection and research, we tried to reduce manpowers, time requirements and costs, and to overcome the height and dome structures. On board device mounted on drones is consisting of a high resolution camera for detecting cracks of more than 0.3 mm, a lidar sensor and a embeded image processor module. It was mounted on an industrial drones, took sample images of damage from the site specimen through automatic flight navigation. In addition, the damege parts of the site specimen was used to measure not only the width and length of cracks but white rust also, and tried up compare them with the final image analysis detected results. Using the image analysis techniques, the damages of 54ea sample images were analyzed by the segmentation - feature extraction - decision making process, and extracted the analysis parameters using supervised mode of the deep learning platform. The image analysis of newly added non-supervised 60ea image samples was performed based on the extracted parameters. The result presented in 90.5 % of the damage detection rate.