• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.603-612
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• 2006

Recently the web service area is rapidly growing as the next generation IT paradigm because of increase of concern about SOA(Services-Oriented Architecture) and growth of B2B market. Since a service discovery through UDDI(Universal Description, Discovery and Integration) is limited to a functional requirement, it is not considered an effect on frequency of service using and reliability of mutual relation. That is, a quality as nonfunctional aspect of web service is regarded as important factor for a success between consumer and provider. Therefore, the web service selection method with considering the quality is necessary. This paper suggests the agent-based quality broker architecture and selection process which helps to find a service providing the optimum quality that the consumer needs in a position of service consumer. A theory of agent is accepted widely and suitable for proposed system architecture in the circumstance of distributed and heterogeneous environment like web service. In this paper, we considered the QoS and CoS in the evaluation process to solve the problem of existing researches related to the web service selection and used PROMETHEE(Preference Ranking Organization MeTHod for Enrichment Evaluations) as an evaluation method which is most suitable for the web service selection among MCDM approaches. PROMETHEE has advantages that solve the problem that a pair-wise comparison should be performed again when comparative services are added or deleted. This paper suggested a case study with the service composition scenario in order to verify the selection process. In this case study, the decision making problem was described on the basis of evaluated values for qualities from a consumer's point of view and the defined service level.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.83-93
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• 2012

Technology assessment is one of the most challenging decision making areas that companies face nowadays. According to increase the importance of technology selection, it has been a main issue for the decision makers whether an appropriate technology selection will be successful or not. Therefore, in this study, a technology assessment model using BSC and ANP method was proposed. The technology assessment model consist of three phase. In first phase, various factors, that have an influence on technology assessment, were taken into consideration. Based on the extracted BSC process, the strategies and critical success factors and performance measures were extracted for selecting the technology. And in second phase, the ANP method used to integrate opinions of experts' and evaluate technology alternatives controls tangible and intangible criteria, allows for more complex inter-relationship among decision levels and deals with ambiguity involved in the assessment process. In the lase phase, according to the result of before phase, decision makers select the appropriate technology. Furthermore, the proposed model was applied in the public service for validating the feasibility of the assessment model. The criteria and proposed performance measures informs the method and focus areas for developing the technology. Furthermore, the assessment model can be applied to the other area, and give the objectivity and rationality.

• The Korean Journal of Financial Management
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• v.25 no.3
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• pp.1-32
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• 2008

This study examines the changes and determinants of cash to assets ratios(cash ratios) by analyzing 14,016 Korean manufacturing firms sample for the period of $1999{\sim}2004$. The major findings can be summarized as follows. First, the average cash ratios for Korean manufacturing firms have increased from 4.7 percent of 1999 to 5.2 percent of 2004. In addition, the average cash holdings per firm also have increased from 4.3 billion Won to 8.0 billion Won during the same period. However, the capital expenditures relative to cash ratios or operating cash flow have decreased significantly, confirming the notion that physical investment of Korean manufacturing sector has been shrinking recently. Second, in regression tests with panel data, the coefficients of target adjustment variables show the expected negative signs, but coefficients of the deficit of fund variables show the unexpected positive signs. Thus, the evidence seems to be supportive of static tradeoff model of cash holdings. Third, in regression tests to find the determinants of cash ratios, most of the variables show similar results as the previous studies. However, in terms of adjusted coefficient of determination and F-statistic, the firm-characteristic variables suggested by static trade-off theory have more explanatory power than the variables suggested by pecking order theory.

• Journal of Broadcast Engineering
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• v.12 no.6
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• pp.611-623
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• 2007

The H.264|AVC standard incorporates an intra prediction tool into inter frame coding. However, this leads to excessive amount of increase in encoding time, thus resulting in the difficulty in real-time implementation of software encoders. In this paper, we first propose an early decision on intra prediction coding and a fast intra prediction method using the characteristics of block contents and the context of neighboring block modes for the intra prediction in the inter frame coding of H.264/AVC. Basically, the proposed methods determine a skip condition on whether the $4{\times}4$ intra prediction is to be used in the inter frame coding by considering the content characteristics of each block to be encoded and the context of its neighboring blocks. The performance of our proposed methods is compared with the Joint Model reference software version 11.0 of H.264|AVC. The experimental results show that our proposed methods allow for 41.63% reduction in the total encoding time with negligible amounts of PSNR drops and bitrate increases, compared to the original Joint Model reference software version 11.0.

• Journal of Distribution Research
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• v.10 no.3
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• pp.59-86
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• 2005

This study examined whether the efforts of department store for recovering services may be perceived fairly from the standpoint of customers upon any occurrence of service failure, whether such perceived justice contributes to higher customer satisfaction and trust, and whether such customer satisfaction and trust have positive influence on store loyalty of customers, respectively. For this sake, this study investigated relevant literatures, set up some hypotheses to solve main questionable considerations and made a corresponding empirical analysis. For empirical analysis, a questionnaire survey was applied to total 204 customers who experienced in service recovery around domestic major department stores in the last one(1) year. With regard to empirical analysis to verify some hypotheses hereof, this study verified the reliability and validity of each questionnaire item by means of statistical programs like SPSS 10,0 and AMOS 4.0, followed by verifying hypotheses through SEM(structural equation modeling) analysis. These results indicate that positive efforts of department stores for service recovery upon their service failure may bring customer satisfaction and trust in department store, which result in boosting up store loyalty of customers. In this empirical study, it was notably demonstrated that despite any occurrence of service failure, the corresponding efforts of department stores to improve the level of justice perceived by customers in course of service recovery, had positive effects on better customer satisfaction, trust and store loyalty, and these effects induced customer's continuous repurchase, positive WOM(word of mouth) and recommendation about the use of appropriate department store, which may contribute to better its competitive edge.

• Journal of Korea Water Resources Association
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• v.53 no.4
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• pp.273-283
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• 2020

Quantitative forecasting of groundwater levels for the assessment of groundwater variation and vulnerability is very important. To achieve this purpose, various time series analysis and machine learning techniques have been used. In this study, we developed a prediction model based on LSTM (Long short term memory), one of the artificial neural network (ANN) algorithms, for predicting the daily groundwater level of 11 groundwater wells in Hankyung-myeon, Jeju Island. In general, the groundwater level in Jeju Island is highly autocorrelated with tides and reflected the effects of precipitation. In order to construct an input and output variables based on the characteristics of addressing data, the precipitation data of the corresponding period was added to the groundwater level data. The LSTM neural network was trained using the initial 365-day data showing the four seasons and the remaining data were used for verification to evaluate the fitness of the predictive model. The model was developed using Keras, a Python-based deep learning framework, and the NVIDIA CUDA architecture was implemented to enhance the learning speed. As a result of learning and verifying the groundwater level variation using the LSTM neural network, the coefficient of determination (R²) was 0.98 on average, indicating that the predictive model developed was very accurate.

• Journal of the Korean Geographical Society
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• v.50 no.3
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• pp.355-373
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• 2015

In this study the factors of fire damage are analyzed through previous research reviews. Local environmental factors as well as those factors attributed to fire damage (number of fire events, number of injured, number of death, economic loss) were selected to compose mutual relationship model. In order to verify this relationship model, official statistics concerning fire damage were collected from 228 local governments and compared with results from previous research. As a result of this comparison four dependent variables and 22 independent variables that affect fire damage were analyzed. Independent variables are divided into human vulnerability factors, physical vulnerability factors, economic vulnerability factors, mitigating factors and local characteristics. To analyze a relationship between selected dependent variables and independent variables, we applied a semi-logarithm model and performed regression analysis. Among the 22 independent variables, the number of the weak to disaster, social welfare service workers, workers in manufacturing industry, and the number of workers in restaurants and bars per 10,000 people show the significant correlation with the number of fire incidence. The number of death from fire is significantly related to two variables which are the number of social welfare service workers per 10,000 and the ratio of commercial area. Damage cost is significantly dependent on the property taxes per 10,000 people. These factors were included in the research model as vulnerability factors (human, physical, economic) and mitigating factors and local characteristics, and the validity of research model was verified. The result could contribute to fire-fighting resource allocation in Korea or they can be utilized in establishing fire prevention policy, which will enhance the national level of fire safety.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6925-6931
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• 2015

LED(Light Emitting Diode) is used in various filed like a display because of low power consuming, long life span, high brightness, rapid response time and environmental-friendly characteristic. General fabrication method is combination blue light LED chip with yellow fluorescent substance. Because this way is suitable for industry field in terms of convenience, economic, efficiency. In white light LED packaging process, encapsulation process that is dispensing fluorescent substance with silicon to blue light LED chip is most important. So, in this paper we develop EHD pump system using voice coil motor and electrostatic pump for dispensing fluorescent substance. For these things we conduct basic test about liquid surface profiles by voltage and process time. Through this data we decide optimal process condition and verify the optimal condition using design of experiment method. And to confirm uniformity of the condition, we conduct repeat dispensing test.

• Journal of Korean Society for Geospatial Information Science
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• v.1 no.1 s.1
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• pp.127-140
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• 1993

The purpose of this paper is to examine the possible benefits of combining transportation planning models with geographic information systems (GIS) in the hope that intergrating these systems can alleviate the inherent problems of transportation planning models such as user unfriendliness, labor intensiveness, and theoretical limitations. Specially, this paper focuses on the issue of incompatiblity between GIS and the conventional transportation planning models in dealing with network topologies. Resolving this conflict in topologies is a conerstone for eliminating the user-unfriendliness and labor-intensiveness issues. This paper presents the development of an algorithm that converts GIS topology into transportation network topology. The FORTRAN-based topology conversion algorithm generates transportation networks from the GIS cartographic file and establishes a communication charmel between the two systems.

• Journal of Korean Society of Steel Construction
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• v.20 no.1
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• pp.21-31
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• 2008

response surface method (RSM) is widely used to evaluate th e extremely smal probability of ocurence or toanalyze the reliability of very complicated structures. Althoug h Monte-Carlo Simulation (MCS) technique can evaluate any system, the procesing time of MCS dependson the reciprocal num ber of the probability of failure. The stochastic finite element method could solve thislimitation. However, it is limit ed to the specific program, in which the mean and coeficient o f random variables are programed by a perturbation or by a weigh ted integral method. Therefore, it is not aplicable when erequisite programing. In a few number of stage analyses, RSM can construct a regresion model from the response of the c omplicated structural system, thus, saving time and efort significantly. However, the acuracy of RSM depends on the dist ance of the axial points and on the linearity of the limit stat e functions. To improve the convergence in exact solution regardl es of the linearity limit of state functions, an improved adaptive response surface method is developed. The analyzed res ults have ben verified using linear and quadratic forms of response surface functions in two examples. As a result, the be st combination of the improved RSM techniques is determined and programed in a numerical code. The developed linear adapti ve weighted response surface method (LAW-RSM) shows the closest converged reliability indices, compared with quadratic form or non-adaptive or non-weighted RSMs.