• Korean journal of applied entomology
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• v.48 no.1
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• pp.45-51
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• 2009

This paper presents sequential sampling plans for evaluating the pest density based on complete counts from probe in a rice storage warehouse. Both maize weevil and Indian meal moth population showed negative binomial dispersion patterns in brown rice storage. For cost-effective monitoring and action decision making system, sequential sampling plans by using the sequential probability ratio test (SPRT) were developed for the maize weevil and Indian meal moth in warehouses with 0.8 M/T storage bags. The action threshold for the two insect pests was estimated to 5 insects per kg, which was projected by a matrix model. The results show that, using SPRT methods, managers can make decisions using only 20 probe with a minimum risk of incorrect assessment.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.10a
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• pp.165-196
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• 2001

DNA chip 또는 microarray는 다수의 유전자 또는 유전자 조각을 (보통 수천내지 수만 개)칩상에 고정시켜 놓고 DNA hybridization 반응을 이용하여 유전자들의 발현 양상을 분석할 수 있는 기술이다. 이러한 high-throughput기술은 예전에는 생각하지 못했던 여러가지 분자생물학의 문제에 대한 해답을 제시해 줄 수 있을 뿐 만 아니라, 분자수준에서의 질병 진단, 신약 개발, 환경 오염 문제의 해결 등 그 응용 가능성이 무한하다. 이 기술의 실용적인 적용을 위해서는 DNA chip을 제작하기 위한 하드웨어/웻웨어 기술 외에도 이러한 데이터로부터 최대한 유용하고 새로운 지식을 창출하기 위한 bioinformatics 기술이 핵심이라고 할 수 있다. 유전자 발현 패턴을 데이터마이닝하는 문제는 크게 clustering, classification, dependency analysis로 구분할 수 있으며 이러한 기술은 통계학과인공지능 기계학습에 기반을 두고 있다. 주로 사용된 기법으로는 principal component analysis, hierarchical clustering, k-means, self-organizing maps, decision trees, multilayer perceptron neural networks, association rules 등이다. 본 세미나에서는 이러한 기본적인 기계학습 기술 외에 최근에 연구되고 있는 새로운 학습 기술로서 probabilistic graphical model (PGM)을 소개하고 이를 DNA chip 데이터 분석에 응용하는 연구를 살펴본다. PGM은 인공신경망, 그래프 이론, 확률 이론이 결합되어 형성된 기계학습 모델로서 인간 두뇌의 기억과 학습 기작에 기반을 두고 있으며 다른 기계학습 모델과의 큰 차이점 중의 하나는 generative model이라는 것이다. 즉 일단 모델이 만들어지면 이것으로부터 새로운 데이터를 생성할 수 있는 능력이 있어서, 만들어진 모델을 검증하고 이로부터 새로운 사실을 추론해 낼 수 있어 biological data mining 문제에서와 같이 새로운 지식을 발견하는 exploratory analysis에 적합하다. 또한probabilistic graphical model은 기존의 신경망 모델과는 달리 deterministic한의사결정이 아니라 확률에 기반한 soft inference를 하고 학습된 모델로부터 관련된 요인들간의 인과관계(causal relationship) 또는 상호의존관계(dependency)를 분석하기에 적합한 장점이 있다. 군체적인 PGM 모델의 예로서, Bayesian network, nonnegative matrix factorization (NMF), generative topographic mapping (GTM)의 구조와 학습 및 추론알고리즘을소개하고 이를 DNA칩 데이터 분석 평가 대회인 CAMDA-2000과 CAMDA-2001에서 사용된cancer diagnosis 문제와 gene-drug dependency analysis 문제에 적용한 결과를 살펴본다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.28-38
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• 2013

In this paper, we propose a improved turbo equalizer which generates a feedback signal through a simple calculation to improve performance in single carrier system with the LMS(least mean square) algorithm based equalizer and LDPC(low density parity check) codes. LDPC codes can approach the Shannon limit performance closely. However, computational complexity of LDPC codes is greatly increased by increasing the repetition of the LDPC codes and using a long parity check matrix in harsh environments. Turbo equalization based on LDPC code is used for improvement of system performance. In this system, there is a disadvantage of very large amount of computation due to the increase of the repetition number. To less down the amount of this complicated calculation, The proposed improved turbo equalizer adjusts the adoptive equalizer after the soft decision and the LDPC code. Through the simulation results, it's confirmed that performance of improved turbo equalizer is close to the SISO-MMSE(soft input soft output minimum mean square error) turbo equalizer based on LDPC code with the smaller amount of calculation.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.51-59
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• 2020

In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.

• Asian Journal of Innovation and Policy
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• v.9 no.2
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• pp.187-206
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• 2020

Under the on-going evolution of the COVID-19 pandemic, estimating the economic impact of the pandemic is highly uncertain and challenging. This situation makes it difficult for policymakers, governors, and economic entities to formulate appropriate responses and decision makings. To provide useful information about the effect of the COVID-19 pandemic on the Korean economy, this study examined macroeconomic impact analysis stemming from the pandemic shocks with different scenarios for the Korean economy. Based on three scenarios using the growth rate of 2020 GDP and consumer expenditure patterns, the 2021 GDP by industry sector was forecast with two new approaches. First, the recovering process of the Korean economy from the shock was analyzed by applying a Flex-IO method. Second, a new forecasting approach combined with an IO coefficient matrix was applied to forecast the future GDP changes. The findings of this study are summarized as follows: First, the total GDP growth rate under the Pessimistic Scenario demonstrates less rebound from the shock than that of the Base Scenario. Second, agriculture, culture, and tourism-related sectors that are suffering from the severe losses of COVID-19 showed lower resilience than other different industries. Third, information and communications technology (ICT) industry maintains a stable growth trend and is expected to take the leading role for the Korean economy in the post-COVID-19 and the Industry 4.0 eras. The findings deliver that it needs to analyze how government expenditure responding the shock into the forecasting model, which can be more useful and reliable to simulate the resilience from the pandemic.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.10
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• pp.936-942
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• 2015

This paper suggests the significant strategies and their priority to deal with space transportation market trends. First, market trends related with technical improvement and change in demand are analyzed by the literature research. The three key trends are obtained: 'Increasing Demand of High-Performance Launch Vehicles', 'Rising of Low-Price Launch Vehicles', and 'Rising of Dual/Multi-Launch'. And then, strategies for developing the launch vehicle industry in Korea are selected from several studies about commercialization of Korean launch vehicle. The strategies are evaluated by the experts through pairwise comparison matrix and the criteria for this process is how significantly does the strategy effect on the launch vehicle industry through market assessment. As a result, reliable order of priority among the strategies are obtained. Under the three key trends, strategy to enhance reliability is most important. And, strategy to have price competitiveness has secondary priority to deal with 'Rising of Low-Price Launch Vehicles' trend and 'Rising of Dual/Multi-Launch' trend. On the contrary, strategy of government's support is secondary under 'Increasing Demand of High-Performance Launch Vehicles' trend.

• Journal of Korea Technology Innovation Society
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• v.14 no.1
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• pp.60-84
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• 2011

This study accomplished technology improvement assessment of Gashydrate R&D project using ANP method which can deal with the sophisticated decisions involving a variety of interactions and dependencies. Criteria were selected by consultation and questionnaires with experts in four technology parts of gas hydrate project, and then the network was formed from relation with criteria and alternatives. As the result of analysis, the weight matrix was derived and the various relation in the network was able to be verified. The analysis was accomplished with four technology parts - geophysical exploration technology, geological and geochemical technology, analysis of deep-drill cores and stability technology, production technology - and the 'reliability' criterion ranked the highest of all parts. The rank of other criteria and the result of technology improvement assessment reflected the level of each technology. Thus, the result of this study will contribute to policy decision-making for developing and evaluating gas hydrate technology and other R&D projects.

• Korean Business Review
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• v.14
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• pp.63-76
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• 2001

The purchase of business services is a growing activity among finns but with little appreciation that the purchase of a service requires a modification of the decision process developed for the purchase of material goods. A taxonomy for purchasing business services is developed to create a matrix with company involvement and focus of service as dimensions. Business services are classified according to their focus on three aspects of the finn: property, people, and core business. Business services are also classified according to the degree of company involvement: high company involvement and low company involvement. A number of propositions are formulated based on insights derived from this taxonomy. The taxonomy results in six business service cells: facility support, equipment support, employee support, employee development, core business facilitator, and professional. Implications for managers considering a purchase in each category are explored. This study tests the research hypotheses delineated from the classification model and the purchasing process of business services. The strategic implications are suggested based on the findings for each cell of the classification model. This study concludes with a research agenda for further studies.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.6
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• pp.94-101
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• 1994

About vibration model of Six-degrees-of-freedom(DOF), in mass load, examined results for knowing dynamic interference and response variation is as follows; In case of putting mass load upon the object, experimented results on two-degrees-of-freedom of the translation-1 direction and the rotation-1 direction at open-loop-control system, about 0.19 arcsed in input of the translation-$0.1{\mu}m$ and $0.022{\mu}m$ on input of the rotation-0.5 arcsec, the justicse of motion equation is acknowledged as confirming the appearance of the interference-$0.022{\mu}m$. In establishing calculation of transformation matrix by using analogue circuit, as simulating results that used incomplete differentiation, interference is $1.7{\times}10^{-3}$ arcsec on input of the translation-$0.1{\mu}m$ and $1.4{\times}10^{4}{\mu}m$ on input of the rotation-0.5 arcsec in open-loop-control system. Also it is $4.2{\times}10^{-4}$ arcsec on input of the translation-$0.1{\mu}m$ and $5.6{\times}10^{-5}{\mu}m$ on input of the rotation-0.5 arcesc in closed-loop-control system. As closed-loop-control system is better than open-loop-control system, equivalent accordance is confirmed on original response. Finally, fundamental validity of this theory is acknowledged.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.255-266
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• 2009

In this study, a robust aerospace system design process for the aerospace system is developed by considering the uncertainties of user requirements, manufacturing errors, and operational environment variation. User requirements are analyzed and quantified by decision making models and system engineering methods to select alternative concepts which satisfies the various requirements. Robust design and optimization method is applied to derive the robust solution of the selected system. First, a variance of objective function is calculated, and a mean value and a variance of target value are determined by the deterministic design optimization results of the system. A robust optimum design formulation is then needed to derive the robust solution that minimizes the variance of the response and moves the mean values to the target value. It is applied to Very Light Jet (VLJ) aircraft to which much attention is paid recently in civil aerospace market.