• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.106-123
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• 2019

Demand for performance analysis is increasing for efficient use of limited budgets such as improving investment efficiency and strategic budget allocation in accordance with the continuous increase demand of R&D budget for developing advanced weapon systems in the future battlefields. In accordance with the Act on the Performance Evaluation and Performance Management of the National R&D Projects established in March 2006, the performance analysis has been conducted for the systematic management and utilization of the R&D project performance. It was recognized as a project to achieve self-defense through strengthening the weapons system development capability, however, efficiency evaluation of Defense R&D projects was not much emphasized. Research on the efficiency analysis of defense R&D projects has been conducted in recent years, but most studies focused on corporate efficiency and productivity of defense companies. In this study, we analyzed the three-stage performance of defence R&D projects based on the logical model using the data envelope analysis(DEA) model. We also analyzed performance analysis from various perspectives through R&D type, technology classification and performance model. This study is expected to help defense department improve defense R&D projects and make decision.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.21-46
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• 1990

This paper, a sequel to Yoo and Lee (1990), attempts to investigate the interindustry determinants of technical efficiency in Korea's manufacturing industries, and also to conduct an exploratory analysis on the stability of technical efficiency over time. The hypotheses set forth in this paper are most found in the existing literature on technical efficiency. They are, however, revised and shed a new light upon, whenever possible, to accommodate any Korea-specific conditions. The set of regressors used in the cross-sectional analysis are chosen and the hypotheses are posed in such a way that our result can be made comparable to those of similar studies conducted for the U.S. and Japan by Caves and Barton (1990) and Uekusa and Torii (1987), respectively. It is interesting to observe a certain degree of similarity as well as differentiation between the cross-section evidence on Korea's manufacturing industries and that on the U.S. and Japanese industries. As for the similarities, we can find positive and significant effects on technical efficiency of relative size of production and the extent of specialization in production, and negative and significant effect of the variations in capital-labor ratio within industries. The curvature influence of concentration ratio on technical efficiency is also confirmed in the Korean case. There are differences, too. We cannot find any significant effects of capital vintage, R&D and foreign competition on technical efficiency, all of which were shown to be robust determinants of technical efficiency in the U.S. case. We note, however, that the variables measuring capital vintage effect, R&D and the degree of foreign competition in Korean markets are suspected to suffer from serious measurement errors incurred in data collection and/or conversion of industrial classification system into the KSIC (Korea Standard Industrial Classification) system. Thus, we are reluctant to accept the findings on the effects of these variables as definitive conclusions on Korea's industrial organization. Another finding that interests us is that the cross-industry evidence becomes consistently strong when we use the efficiency estimates based on gross output instead of value added, which provides us with an ex post empirical criterion to choose an output measure between the two in estimating the production frontier. We also conduct exploratory analyses on the stability of the estimates of technical efficiency in Korea's manufacturing industries. Though the method of testing stability employed in this paper is never a complete one, we cannot find strong evidence that our efficiency estimates are stable over time. The outcome is both surprising and disappointing. We can also show that the instability of technical efficiency over time is partly explained by the way we constructed our measures of technical efficiency. To the extent that our efficiency estimates depend on the shape of the empirical distribution of plants in the input-output space, any movements of the production frontier over time are not reflected in the estimates, and possibilities exist of associating a higher level of technical efficiency with a downward movement of the production frontier over time, and so on. Thus, we find that efficiency measures that take into account not only the distributional changes, but also the shifts of the production frontier over time, increase the extent of stability, and are more appropriate for use in a dynamic context. The remaining portion of the instability of technical efficiency over time is not explained satisfactorily in this paper, and future research should address this question.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.648-654
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• 2018

Currently, the Defense Agency for Technology and Quality (DTaQ), which is responsible for the quality assurance of military supplies, divides munitions into four categories, in order to conduct its governmental quality assurance activities, including product examination, process review and system audit. However, these 4 categories may differ depending on the related organizations' (e.g. Defense Acquisition Program Administration, munitions manufacturing) military requirements. Therefore, in this study, appropriate classification criteria for munitions are suggested for the sake of the efficient procurement, production and quality assurance of military supplies. We investigated the item classification system of the Public Procurement Service, which is a similar organization to the DTaQ. We also compared the appropriate classification criteria with those of related organizations and identified the current status of munitions classification data according to the current standard. In addition, application samples are presented using the proposed quality assurance classification criteria. Finally, the classification criteria of military supplies proposed in this paper will contribute to improving the efficiency of government quality assurance activities.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.811-822
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• 2005

Automated text categorization is to classify free text documents into predefined categories automatically and whose main goals is to reduce considerable manual process required to the task. The researches to improving the text categorization performance(efficiency) in recent years, focused on enhancing existing classification models and algorithms itself, but, whose range had been limited by feature based statistical methodology. In this paper, we propose RTPost system of different style from i.ny traditional method, which takes fault tolerant system approach and data mining strategy. The 2 important parts of RTPost system are reinforcement training and post-processing part. First, the main point of training method deals with the problem of defining category to be classified before selecting training sample documents. And post-processing method deals with the problem of assigning category, not performance of classification algorithms. In experiments, we applied our system to documents getting low classification accuracy which were laid on a decision boundary nearby. Through the experiments, we shows that our system has high accuracy and stability in actual conditions. It wholly did not depend on some variables which are important influence to classification power such as number of training documents, selection problem and performance of classification algorithms. In addition, we can expect self learning effect which decrease the training cost and increase the training power with employing active learning advantage.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.1
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• pp.285-291
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• 1991

A two-stage slit type virtual impactor based on the concept of the single stage virtual impactor has been designed, fabricated, and evaluated for the purpose of concentrating the suspended particles in the air with the size range of 1.8-4.5 .mu.m and handling large flow volume. Monodisperse methylene blue particles have been generated with vibrating orifice aerosol generator (VOAG). The separation efficiency and concentration efficiency have been measured by the UV-visible absorption spectrometry. Previous study for a single stage virtual impactor were used to determine the design parameters such as 50% cut-off sizes and dimensions of the two stage virtual impactor. The separation efficiency curve and 50% cut-off Stokes number(cut-off sizes) are not sensitive to the nozzle Reynolds number, but sensitive to the ratio between the minor flow rate and the total flow rate, The measured concentration efficiency was compared with the maximum concentration efficiency determined by the separation efficiencies of the first and the second stages. The differences between the measured and the maximum concentration efficiencies result from the wall loss due to the deposited particles on the internal walls inside the impactor.

• The Journal of Information Systems
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• v.29 no.3
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• pp.145-157
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• 2020

Purpose This study proposed an approach for predicting the efficiency rating of the cultural tourism festivals using DEA and machine learning techniques. The cultural tourism festivals are selected for the best festivals through peer reviews by tourism experts. However, only 10% of the festivals which are held in a year could be evaluated in the view of effectiveness without considering the efficiency of festivals. Design/methodology/approach Efficiency scores were derived from the results of DEA for the prediction of efficiency ratings. This study utilized BCC models to reflect the size effect of festivals and classified the festivals into four ratings according the efficiency scores. Multi-classification method were considered to build the prediction of four ratings for the festivals in this study. We utilized neural networks and SVMs with OAO(one-against-one), OAR(one-against-rest), C&S(crammer & singer) with Korea festival data from 2013 to 2018. Findings The number of total visitors in low efficient rating of DEA is more larger than the number of total visitors in high efficient ratings although the total expenditure of visitors is the highest in the most efficient rating when we analyzed the results of DEA for the characteristics of four ratings. SVM with OAO model showed the most superior performance in accuracy as SVM with OAR model was not trained well because of the imbalanced distribution between efficient rating and the other ratings. Our approach could predict the efficiency of festivals which were not included in the review process of culture tourism festivals without rebuilding DEA models each time. This enables us to manage the festivals efficiently with the proposed machine learning models.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.98-107
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• 2007

For high-dimensional pattern recognition, such as face classification, the small number of training samples leads to the Small Sample Size problem when the number of pattern samples is smaller than the number of dimensionality. Recently, various LDA-extensions have been developed, including LDA, PCA+LDA, and Direct-LDA, to address the problem. This paper proposes a method of improving the classification efficiency by increasing the number of (sub)-classes through pre-clustering a training set prior to the execution of Direct-LDA. In LDA (or Direct-LDA), since the number of classes of the training set puts a limit to the dimensionality to be reduced, it is increased to the number of sub-classes that is obtained through clustering so that the classification performance of LDA-extensions can be improved. In other words, the eigen space of the training set consists of the range space and the null space, and the dimensionality of the range space increases as the number of classes increases. Therefore, when constructing the transformation matrix, through minimizing the null space, the loss of discriminatve information resulted from this space can be minimized. Experimental results for the artificial data of X-OR samples as well as the bench mark face databases of AT&T and Yale demonstrate that the classification efficiency of the proposed method could be improved.

• Resources Recycling
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• v.12 no.3
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• pp.3-12
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• 2003

Physical separation containing grinding, sieving, dry magnetic separation and air classification were carried out in order to recover Ta anode from waste Ta condenser. Roll crusher wat used for the liberation of resin and metals in closed circuit system. The liberation between Ta anode and resin was easily achieved, whereat some of metals did not liberated from the Ta anode when the waste condenser was crushed below 8 mesh. When the crushed sample were divided into 8/10 mesh, 10/18 mesh and -18 mesh, metals was mainly remained in 8/10 mesh in contrast to Ta anode was in +18 mesh. It was shown that resin was more easily crushed rather than metals from the result of that resin content was 71.5％ in -18 mesh. The liberation efficiency was different with the input size of the crushed sample and average efficiency was 62.3% due to the locked Ta anode particles. The results of air classification test for the crushed samples showed that optimal air flow are 39㎥/h, 32㎥/h, 20㎥/h. respectively. When the sample were separated with optimal condition, 94.45％ Ta anode containing 97.47 wt.％ Ta anode, 0.93 wt.％ resin. 1.61 wt.％ metal was recovered with 49.39 wt.％ yield.

• International Area Studies Review
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• v.15 no.3
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• pp.583-603
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• 2011

This study was designed to comprehensively understand and separate the characteristics of recreation forests of Korea through the multi-variate analysis for the provision of fundamental materials for recreation forests development policies and planning, and attempted to evaluate on the validity of classification of recreation forests, which has never been performed before. According to analysis results, recreation forests could be divided into 4 types; type I(recreation forests whose ecological nature status is not good, but the risk of calamity is low and accessibility is good), type II(recreation forests whose the risk of calamity is low, but ecological nature status is not good, slope is steep, and accessibility is poor), type III(recreation forests that have charming vegetation and landscape, various rest opportunity, and a gentle slope, but poor accessibility), and type IV(recreation forests that ecological nature status is good, but have poor landscape, less rest opportunity, and a steep slope). Also, each type was adjusted as follows; type I($25{\rightarrow}24$ reviews), type II($25{\rightarrow}26$ reviews), type III($17{\rightarrow}16$ reviews), and type IV($25{\rightarrow}25$ reviews). This study can be said to show the usability of validation of classified types, which was not done before. It is clear that the classification of recreation forests increases the efficiency in policy making and performance. Furthermore, by validating the separated types, we could expect high efficiency in policy making and performance on planned recreation forests in the future.

• Journal of KIISE:Information Networking
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• v.32 no.4
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• pp.543-550
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• 2005

Demand for better services in the Internet has been increasing due to the rapid growth of the Internet, and hence next generation routers are required to perform intelligent packet classification. For a given classifier defining packet attributes or contents, packet classification is the process of identifying the highest priority rule to which a packet conforms. A notable characteristic of real classifiers is that a packet matches only a small number of distinct source-destination prefix pairs. Therefore, a lot of schemes have been proposed to filter rules based on source and destination prefix pairs. However, most of the schemes are based on sequential one-dimensional searches using trio which requires huge memory. In this paper, we proposea memory-efficient two-dimensional search scheme using source and destination prefix pairs. By constructing binary prefix tree, source prefix search and destination prefix search are simultaneously performed in a binary tree. Moreover, the proposed two-dimensional binary prefix tree does not include any empty internal nodes, and hence memory waste of previous trio-based structures is completely eliminated.