• Journal of Korea Water Resources Association
• /
• v.39 no.9 s.170
• /
• pp.755-766
• /
• 2006

Since the accuracy of climate forecast information has improved from better understanding of the climatic system, particularly, from the better understanding of ENSO and the improvement in meteorological models, the forecasted climate information is becoming the important clue for streamflow prediction. This study investigated the available climate forecast information to improve the extended streamflow prediction in Korea, such as MIMI(Monthly Industrial Meteorological Information) and GDAPS(Global Data Assimilation and Prediction) and measured their accuracies. Both MIMI and the 10-day forecast of GDAPS were superior to a naive forecasts and peformed better for the flood season than for the dry season, thus it was proved that such climate forecasts would be valuable for the flood season. This study then forecasted the monthly inflows to Chungju Dam by using MIMI and GDAPS. For MIMI, we compared three cases: All, Intersection, Union. The accuracies of all three cases are better than the naive forecast and especially, Extended Streamflow Predictions(ESPs) with the Intersection and with Union scenarios were superior to that with the All scenarios for the flood season. For GDAPS, the 10-day ahead streamflow prediction also has the better accuracy for the flood season than for the dry season. Therefore, this study proved that using the climate information such as MIMI and GDAPS to reduce the meteorologic uncertainty can improve the accuracy of the extended streamflow prediction for the flood season.

• Journal of Intelligence and Information Systems
• /
• v.7 no.1
• /
• pp.81-95
• /
• 2001

Plant construction projects usually take much higher uncertainty and risks than the projects from other domains. This implies the importance of plant construction project management should be more emphasized than the other domain. Especially, the overall successes of the projects often depend on the performance of process planning and scheduling performed at the initial stage of the project. However, most plant construction projects suffer great difficulties in establishing proper process planning and scheduling timely because of unstructureness and dynamicity of environment of the project itself In this paper, we propose a knowledge-based process planning and scheduling approach in a plant construction domain to cope this problem. First, we modulize process planning knowledge and present the knowledge representation scheme. Second, we propose an inferencing mechanism to build a process planning for plant construction based on the represented process planning knowledge. Since our approach automate the initial process planning, which was usually done by manual way, it can improve the correctness and also completeness of the process plan and schedule by reducing the time to plan and allowing simulations on the various situation. We also design and implement this our approach as a real working system, and it is successfully applied to real plant construction cases from a leading construction company in Korea. Based on this success, we expect our approach can be easily applied to the projects of other areas, while contributing to enhancement in productivity and quality of project management.

• Journal of KIISE:Software and Applications
• /
• v.29 no.12
• /
• pp.966-978
• /
• 2002

There are two important problems in improving text classification systems based on machine learning approach. The first one, called "selection problem", is how to select a minimum number of informative documents from a given document collection. The second one, called "composition problem", is how to reorganize selected training documents so that they can fit an adopted learning method. The former problem is addressed in "active learning" algorithms, and the latter is discussed in "boosting" algorithms. This paper proposes a new learning method, called AdaBUS, which proactively solves the above problems in the context of Naive Bayes classification systems. The proposed method constructs more accurate classification hypothesis by increasing the valiance in "weak" hypotheses that determine the final classification hypothesis. Consequently, the proposed algorithm yields perturbation effect makes the boosting algorithm work properly. Through the empirical experiment using the Routers-21578 document collection, we show that the AdaBUS algorithm more significantly improves the Naive Bayes-based classification system than other conventional learning methodson system than other conventional learning methods

• Environmental and Resource Economics Review
• /
• v.23 no.4
• /
• pp.583-615
• /
• 2014

Including the rolling black out in 2011, Korea has suffered from rapid increase of electricity consumption and demand forecasting failure for last five years. In addition, because of the Fukushima disaster, high fuel prices, and introduction of new generation sources such as renewables, the uncertainty on a power supply strategy increases. Consequently, a stable power supply becomes the new agenda and a revisino of strategy for new power generation sources is needed. In the light of this, we appraises the sixth basic plan for long term electricity demand and supply considering the changes of foreign and domestic conditions. We also simulate a strategy for the new power generation sources using a portfolio analysis method. As results, a diversity of power generation sources will increase and the share of renewable power generation will be surged on the assumptions of a cost reduction of renewable power sources and an increase of fuel costs. Particularly, on the range of a risk level(standard deviation) from 0.06 and 0.09, the efficient frontier has the most various power sources. Besides, the existing power plan is not efficient so that an improvement is needed. Lastly, the development of an electricity storage system and energy management system is necessary to make a stable and efficient power supply condition.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.1
• /
• pp.705-713
• /
• 2018

An automotive ball joint connects the suspension system to the steering system and helps to enable rotational and linear motion between the two elements for steering. This study examines a ball joint used in medium and large-sized pickup trucks. Ball joints consist of a stud, socket, bearing, and plug. The main structural performance metrics of ball joints are the pull-out strength and push-out strength. These structural parameters must meet certain criteria to avoid serious accidents. Test and simulation methods are used to investigate the design requirements, but tests are time-consuming and costly. In this study, we modeled ball joints in SolidWorks and performed a finite element analysis in Abaqus to predict structural performance. The analysis was used to obtain the structural performance required for the static analysis of a 2D axisymmetric model. The uncertainties in the manufacturing of the ball joint were assumed to be the manufacturing tolerances, and the dimensional design variables were identified through case studies. The manufacturing tolerances at each level were defined, and the results were compared with experimental results.

• Journal of Korean Society for Atmospheric Environment
• /
• v.33 no.5
• /
• pp.497-514
• /
• 2017

This study quantitatively analyzes the effects of emission inventory choices on the simulated particulate matter (PM) concentrations and the domestic/foreign contributions in the Seoul Metropolitan Area (SMA) with an air quality forecasting system. The forecasting system is composed of Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Community Multi-Scale Air Quality (CMAQ). Different domestic and foreign emission inventories were selectively adopted to set up four sets of emissions inputs for air quality simulations in this study. All modeling cases showed that model performance statistics satisfied the criteria levels (correlation coefficient >0.7, fractional error <50%) suggested by previous studies. Notwithstanding the apparently good model performance of total PM concentrations by all emission cases, annual average concentrations of simulated total PM concentrations varied up to $20{\mu}g/m^3$ (160%) depending on the combination of emission inventories. In detail, the difference in simulated annual average concentrations of the primary PM coarse (PMC) was up to $25.2{\mu}g/m^3$ (6.5 times) compared with other cases. Furthermore, model performance analyses on PM species showed that the difference in the simulated primary PMC led to gross model overestimation in general, which indicates that the primary PMC emissions need to be improved. The contribution analysis using model direct outputs indicated that the domestic contributions to the annual average PM concentrations in the SMA vary from 44% to 67%. To account for the uncertainty of the simulated concentration, the contribution correction factor method proposed by Bae et al. (2017) was applied, which resulted in converged contributions(from 48% to 57%). We believe this study shows that it is necessary to improve the simulated concentrations of PM components in order to enhance the accuracy of the forecasting model. It is deemed that these improvements will provide more accurate contribution results.

• Journal of Distribution Research
• /
• v.16 no.3
• /
• pp.33-75
• /
• 2011

The ownership structure of a franchise system is determined by the franchisor's strategic choice. A close look at the extant theories and perspectives in economics and management such as resource scarcity theory, agency theory, transaction cost analysis, and mixed ownership theory reveals that firms choose their ownership structure for the sake of economic efficiency, profit potentials, the chance of survival, and other strategic concerns. The present study, on the basis of strategic choice perspective, reviews the divergent theories of a franchise system's ownership structure and its determinants, thus providing a theoretical framework for comparing the contradictory arguments along the several critical dimensions. We also developed and tested the conflicting hypotheses regarding key determinants of ownership structure including firm's age, size, transaction-specific investments, uncertainty, and risk-sharing propensity. Using a FDD (Franchise Disclosure Document) data set of 543 Korean franchisors, we found that the years in business, the total number of employees, days of training, the inverse of the years of franchising, and the requirement of royalty payment have positive relationships with the proportion of company-owned outlets to total number of outlets. On the other hand, the proportion of company-owned outlets was found to have negative relationships with the total number of outlets and the extent of geographic dispersion of outlets, but to have no significant relationships with the initial investment required and the inverse of contract length. Based on the findings, we provide several theoretical and managerial implications for studying ownership structure of franchise systems.

• Journal of the military operations research society of Korea
• /
• v.32 no.2
• /
• pp.188-211
• /
• 2006

This study aims to empirically investigate the effects of the individual-level characteristics on their timing decisions for their enlistments even though military services are their duties under a draft system. The individual characteristics considered include five psychological factors, such as attitude, uncertainty, information search level, future expectation, and perceived risk towards army, and other several demographic variables. Measurement scales for these psychological variables are developed and a duration model for individuals' enrollment timing decisions is also proposed. The proposed model is fitted to a survey data set collected from both those who have completed military service and those who have not. The estimation results show that two of five psychological variables, negative attitude and perceived risk, and several demographic variables, including education level, income level, residence area, and the number of family members serving the army, have meaningful impacts on the timing decisions for military service. Specifically, the enlistment timings are found to be more delayed as negative attitude towards army is stronger, perceived risk on army is higher, education level is higher, academic performance is better, income level is either low or high, residence area is either Seoul or big cities, and the proportion of family members enlisted is smaller. Several important managerial implications for alleviating problems resulting from enrollment postponements are also discussed.

• International Commerce and Information Review
• /
• v.14 no.1
• /
• pp.345-366
• /
• 2012

The country using factoring actively today is England. The history of factoring could throw back to the Middle Ages, but modern factoring was developed in colonial age of the United States and it was known throughout England in 1960s. At the beginning, it performed mercantile agent who works in local area in order to get rid of uncertainty and inconvenience of a distant trade, but it was getting developed into a today's factoring system which focusing more on financial function. The factoring is called 'account receivable financing' in the United States and it is started out as sales agent and getting developed to 'del credere agent' who guarantee the payment. The activities of factors have been expanded to not only consignment sale and payment guarantees but also advance financing service. However, at the end of the 19th century, the direct sales(direct marketing) was expanded by the development of telecommunication and transportation technology, and then the marketing service by factor was degraded, but the collection of payment and advance finance had been maintained until now and developed into today's factoring system. Especially, the establishment of Uniform Commercial Code in 1931 had formed the basis for activating factoring in the United States through preparing a legal basis of factoring. Due to changes of international trade environment, most of commercial bank in Korea have to deal with export factoring as a trade finance service and it is desirable to specialize as a financing for small and medium company.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.5
• /
• pp.137-146
• /
• 2012

In SCM(Supply Chain Management), a management paradigm where the customer satisfaction is to be achieved by minimizing the cost, reducing the uncertainty, and obtaining the overall optimization. As it performs the integrated operation of the paths of information, assets, and knowledge from the raw material providers to the retailers, the adoption of RFID(Radio Frequency Identification) in SCM could be expected to magnify the effectiveness of the system. However, there is a huge risk by deciding whether or not RFID system is adopted without the objective analysis under the uncertain circumstances. This research paper presents the statistical analysis methodologies for the comparison of RFID with Barcode on the aspect of utility and the statistical analysis tool, RUSAT, which was programmed for nonstatisticians' convenience. Assuming a pharmaceutical industry, this paper illustrates how the data were entered and analyzed in RUSAT. The results of this research are expected to be used not only for the pharmaceutical related company but also for the manufacturer, the whole-saler, and the retailer in the other logistic industries.