• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.479-482
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• 2001

Construction industry included speciality compare with others industry. Systemically approach and enterprise cultural approach is required in order to perform Knowledge Management in construction industry. But, most of construction enterprise immersed in system approach to perform Knowledge Management, in this reason caused failure of Knowledge Management. To resolve the structural contradiction, Learning organization based the Community of Practice(CoP) is studied in this paper.

• Journal of the Korea Institute of Building Construction
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• v.2 no.4
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• pp.105-112
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• 2002

The EVMS(Earned Value Management System) comes from C/SCSC which was first released by the United States Department of Defense in December 1967, and preyed very powerful and efficient project management tool from a lot of practices. Although it is an excellent tool, we can not be succeed appling foreign system due to the differences of construction culture and law between the Korean and US construction industries. EAC(Estimate at Completion) is one of the most important functions in the EVMS. The purpose of this study is to propose the improved EAC method according to the performance indices better than old that and to prove from examples. In advance, the improved EAC method is to estimate more exactly costs and to promote efficiency in construction projects.

• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.7-32
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• 2016

This study has measured interdisciplinarity using a topic modeling, which automatically extracts sub-topics based on term information appeared in documents group unlike the traditional top-down approach employing the references and classification system as a basis. We used titles and abstracts of the articles published in top 20 journals for the past five years by the 5-year impact factor under the category of 'Information & Library Science' in JCR 2013. We applied 'Discipline Diversity' and 'Network Coherence' as factors in measuring interdisciplinarity; 'Shannon Entropy Index' and 'Stirling Diversity Index' were used as indices to gauge diversity of fields while topic network's average path length was employed as an index representing network cohesion. After classifying the types of interdisciplinarity with the diversity and cohesion indices produced, we compared the topic networks of journals that represent each type. As a result, we found that the text-based diversity index showed different ranking when compared to the reference-based diversity index. This signifies that those two indices can be utilized complimentarily. It was also confirmed that the characteristics and interconnectedness of the sub-topics dealt with in each journal can be intuitively understood through the topic networks classified by considering both the diversity and cohesion. In conclusion, the topic modeling-based measurement of interdisciplinarity that this study proposed was confirmed to be applicable serving multiple roles in showing the interdisciplinarity of the journals.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Korean Journal of Social Welfare Studies
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• v.43 no.2
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• pp.5-29
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• 2012

Previous performance evaluation focusing on objective data of service agency has the limitations that did not reflect user-centered evaluation. With the expansion of voucher service, importance of perspective of service user such as satisfaction index is increasing. As voucher service has been delivered by the financial burden of government and user, we need the performance evaluation system that reflects the both performance indices to meet the accountability of two stake-holders. So this study focuses on deriving integrated evaluation system developing systems what mixed objective and subjective performance. Data used in this study is collected form 70 social service agencies that deliver voucher service and 1445 service users. Using General Satisfaction Index and Efficiency Index by DEA, this study analysed the correlation between efficiency and satisfaction index, and integrated performance evaluation model is constructed through portfolio map. This study has the following implication. This study theoretically explains the relation of objective performance and subjective performance and gives practical guidance in performance evaluation criterion and interpretation of performance.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2179-2181
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• 2004

Model-free Method들 중에 반복 피트백 조절 알고리즘(Iterative Feedback Tuning, IFT)는 특정한 성능지수를 정의하고, 이를 최소화하도록 제어기의 게인들을 조절하는 방법을 제시하였다. PID와 같은 고전적인 제어이론에 근거한 제어기 설계 과정과는 달리, IFT 알고리즘은 반복 실험을 통해 성능지수의 Gradient를 구하여 이로부터 필터 게인들 조정하는 방법을 채택하고 있다. 수학적 증명과 실험적 실증을 통하여 IFT의 수렴성과 유용성이 보여짐에도 불구하고 IFT 알고리즘의 한계점은 단일 성능지수의 사용이라는데 있다. 이를 개선하기 위해서는 단일 제어 목적을 위한 단일 성능지수의 사용이 아닌 복수의 제어 목적을 위한 복수의 성능지수의 사용이 필요하다. 본 논문에서는 두 개의 성능지수를 가지는 IFT를 이용해서 위상 여유가 크고, 대역폭이 넓은 제어기를 설계하기 위해서 제어기 게인을 자동 조절하는 알고리즘을 제안하고 ODD에서 사용되는 플랜트에 적용한 모의실험을 통하여 그 유용성을 보였다.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2005.04a
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• pp.80-84
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• 2005

가뭄의 정도를 정량화하고 예측하기 위하여 다양한 가뭄지수중 가장 일반적으로 사용되는 것들로는 PDSI(Palmer Drought Severity Index), SWSI(Surface Water Supply Index) 및 SPI(Standard Precipitation Index) 등이 있다. 본 연구에서는 가뭄을 평가하는 방법 중 표준강수지수(SPI)를 활용한 가뭄도 산정 결과와 지하수위 관측자료간의 상관성을 평가함으로써 향후 지하수위 자료를 활용한 가뭄 평가의 가능성을 제시하고자 하였다. 본 연구 결과, 충주가금, 양평개군, 문경문경 및 영주문정 관측소 지역에서 가뭄 평가 인자인 표준강수지수와 지하수위는 비교적 상관성을 갖고 있는 것으로 분석되었으나, 표준강수지수 보다 지하수위 변동이 가뭄에 민감하지 않고 지속성과 영속성을 갖는 것으로 평가되어 가뭄 평가 인자로서 활용성이 높을 것으로 평가되었다. 이들 지역의 표준강수지수 및 지하수 수위 관측자료 간의 교차상관계수는 충주 0.750, 양평 0.533 및 영주 0.607 둥으로 분석되어 상관성이 높은 것으로 나타났다. 가뭄 평가를 위한 가뭄 관측정(DIW, Drought-Index Well)은 주변의 영향을 최소화할 수 있는 지점으로서 가뭄을 정확히 평가 예측할 수 있는 지점에 선정되어 가뭄 평가 및 예측에 활용될 수 있도록 하여야 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.209-214
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• 2004

Time Domain Reflectometry with multiplex system has been installed to configure the spatial and temporal characteristics of soil moisture in a mountainous hillslope. An intensive surveying was performed to build a refined digital elevation model and flow determination algorithms with inverse surveying have been applied to establish an efficient soil monitoring system. Steady state wetness index, quasi-dynamic wetness index and fully dynamic wetness index have been calculated. Continuous monitoring of soil moisture data were analyized with wetness indices. Limitations and hydrological interpretations of this approach have beer discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.408-408
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• 2012

최근 기후변화 때문에 태풍, 호우 등 자연재해로 수방시설물의 피해규모가 커지고 있으며 이러한 피해는 단일 재해요인이 아닌 여러 재해요인이 복합적으로 작용하여 발생하고 있다. 그러므로 도시의 안전성과 방재기능을 확보하기 위해서는 복합위험요소를 고려한 재해위험도의 진단 기술 및 종합적인 재해경감대책 수립을 위한 연구가 필요한 실정이다. 복합위험요소를 고려한 재해위험도 및 재해경감대책을 수립하기 위해서는 도시재해를 유발하는 다양한 요인들이 도시재해에 미치는 영향과 재해요인 중에서 어떠한 재해요인이 도시재해에 더 큰 영향을 미치는지에 대한 검토가 필요하다. 이에 본 연구에서는 정보전달 이론 중의 하나인 엔트로피 방법을 이용하여 복합위험요소를 고려하여 도시지역에 대한 재해위험도를 나타내는 복합위험지수의 가중치를 산정하고자 하였다. 복합위험지수의 가중치는 지표별 속성정보를 추출하여 정규화 과정을 거친 후, 속성별 엔트로피를 산정하여 지표별로 산정된다. 엔트로피 방법에 따라 산정된 가중치는 다른 가중치 산정 방법에 따라 산정된 가중치와의 비교 분석을 통하여 타당성을 검토할 것이며, 이렇게 산정된 가중치를 복합위험지수 산정에 적용한다면, 보다 현실성 있는 도시재해 위험성 또는 취약성 지수로 활용될 수 있을 것으로 판단된다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1717-1722
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• 2008

A number of tools and equipment can measure the degree of stress. Stress measurement includes both psychological and physiological measurements. Considering only one of these elicits subjective or objective deficiency. Overcoming this problem requires a new stress index that combines these two measurements. Following people's personal traits, the measurement results also appear in diverse ways, but we can consider and study the general case obtained on the basis of the measurement tool. By using the index obtained by the psychological and physiological measurement tools, we obtain an integrated stress index. Therefore, we choose to use four stress measurement tools. The index of the result of each measurement tools is referred to as the multi-index. These indices are plotted on coordinates to analyze and diagnose the balance and tendency of the stress.