• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.4D
• /
• pp.339-349
• /
• 2010

The objective of this paper is to develop a structural equations model system for the purpose of tourists' excursion behaviour analysis with their information usage. A tourist' excursion behavior defined as activities in the sightseeing region between arriving and leaving time includes indexes with respect to activity' time use and the number of spots. Additionally, such indexes can be modeled as endogenous variables in the structural equation model system on the assumption that they are influenced by the degree of familarity on the sightseeing region, the degree of information usage, and individual attributes. The case study application involves excursion behaviour data such as one-day excursion activity and information usage diary that are observed in the Fuji Five Lakes, Japan. Since the models presented in the paper are available to statistically analyze the covariance among the endogenous variables, they have the advantage of effectiveness analysis on information usage in the excursion area, compared to the prior approaches such as discrete choice models.

• Proceedings of the Korea Database Society Conference
• /
• 1999.06a
• /
• pp.175-186
• /
• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 1999.03a
• /
• pp.175-186
• /
• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Environmental and Resource Economics Review
• /
• v.13 no.2
• /
• pp.219-243
• /
• 2004

Generally, electricity market has monopoly market structure because of need of enormous investment for infrastructure. However, the introduction of competition in network industry as electricity is a tendency of the world with decreasing the effects of economy of scale due to the advancement of technology. Now, electricity industry restructuring is in progress but the competition in electricity retail market is not in force yet in Korea. Whether a effective competition exist or not is very important to policy decision maker who drive restructuring, but there are small numbers of quantitative researches on that. In this study, we estimated the effectiveness of competition in the electricity retail market through switching costs. If switching costs are high, consumers actually can be locked in incumbent firm in spite of introduction of competition. Therefore switching is a critical factor to determine effectiveness of competition and to estimate the size of switching costs quantitatively can proffer the information about whether the competition in the electricity retail market is effective or not in the future. We estimated switching costs using consumer' stated-preference data by conjoint analysis. In according to estimation results, the cost of switching process is not so high, but the relative brand loyalty of an incumbent company is significantly high. And the price is considered as the most important factor choosing an electric service commodity. Based on the empirical results, it is possible to analyze the relationship between suppliers' competitiveness resulted from management efficiency and customers' switching possibilities. The paper therefore provides guidance for suppliers in deciding to enter into retail competition and for policy makers in introducing retail competition. And it has a significance of estimating the switching costs directly.

• Archives of Plastic Surgery
• /
• v.36 no.5
• /
• pp.565-570
• /
• 2009

Purpose: Numerous techniques have been introduced to reconstruct the perineal area in order to preserve function of both the recipient and the donor site while satisfying aesthetic results. There are several advantages of using the pudendal aretery perforator based flap in that it provides thin coverage of defect area and a relatively excellent circulation through perforators. The perineal region can be divided into two areas : the urogenital triangle and the anal triangle. Since each area differs in structure and function so does its reconstructive plan. The authors of this article report clinical results obtained from pudendal artery perforator based reconstructed cases according to each differrent triangles. Methods: A total of 15 patients who underwent perineal reconstruction were enrolled in our study between the year 2002 and 2006. There were 4 cases of vaginal cancer, 4 cases of extramammary Paget's disease, 1 case of rectovaginal fistula in females and 2 cases of Paget's disease and 4 cases of Fournier's gangrene in male cases. The follow up period was on average 6 month. In female, superfical pudendal artery perforator based local flap were used to reconstruct the urogenital triangle defects, while internal pudendal artery perfoator based local flaps were used to reconstruct the anal traingle defects. In males the gracilis myocutaneous flap and internal pudendal artery perforator based local flaps were used in reconstruction of the scrotum and perineal defect. Result: In females, there was 1 case of partial flap necorsis that employed the superficial pudendal artery perforator but secondary repair through the internal pudendal artery perforator based local flap was done. In addition, there were 4 wound dehiscence cases in females and 2 cases in males. Conclusion: We believe that a better aesthetic and functional outcome can be achieved in perineal reconstruction if discrete surgical planning is carried out systematically categorizing the choice of flap employed acccording to distinct anatomical regions : the urogenital and the anal triangle.

• International Area Studies Review
• /
• v.12 no.3
• /
• pp.321-339
• /
• 2008

The purpose of this study to the analyze characteristics and purchasing activities of consumers by using the Multinomial Logit model, which is a well-known discrete selection model to explain and forecast consumers' selection activities(patterns). The study aims to determine the state of competition between National Brand and Private Band and how some demographic characters and marketing variables influence consumers' brand selections within the facial tissue market. Our analysis process includes reorganization of panel data(individuals' purchasing record at each point) to fit the purpose of our study as well as analysis of probability and influencing factors of consumers' brand selection at each point of purchases. The result showed that consumers at higher age and with higher income hold better probability to purchase National Brand. Likewise, locations also had considerable effect on selecting brand, and Private Brand was preferred in department store and discount stores. On the other hand, consumers loyal to National Brand reported higher probability to purchase if the product prices were higher while Private Brand buyers were more promoted the purchase under price discount.

• Korean Journal of Social Welfare
• /
• v.60 no.2
• /
• pp.99-129
• /
• 2008

This study analyzed the resilience process of persons with disabilities using the grounded theory approach. To conduct this study, the researcher conducted in-depth interviews with 8 persons with disabilities. In data analysis, this study identified 393 concepts on the resilience process of persons with disabilities and the concepts were categorized into 45 sub-categories and 18 primary categories. In the paradigm model on the resilience process of persons with disabilities, it was identified that casual conditions included 'unawareness of disability before being disability', 'extreme pain', 'repressing psychological pain', and the contingent conditions were 'dis-empowerment by staying in home', 'isolation by himself with difficulty in accepting the disability', 'experience of frustration from social barriers with prejudice against persons with disabilities'. Also, it was identified that the resilience process could be dependent on the type and the degree of the disability, the gender, and the length of time being disability. In spite of the casual and contingent conditions, the central way in which persons with disabilities could acquire resilience was identified as 'enhancement of the power of positive thinking'. The control conditions which accelerate or retard central phenomenon were 'the awareness of not being alone through family, friends, neighborhood and the social system' externally and 'finding purpose in life through religion and help from other persons with disabilities', internally. The action/interactional sequences enhanced the efforts, self searching and active acting, and as a result, persons with disabilities could find comfort in life, participate in society and change the perspective of disability in society. The core categories of resilience process in persons with disabilities were a belief in affirmation and choice of life by initiative. In the process analysis, stages developed in the following: 'pain', 'strangeness', 'reflection', 'daily life'. This stage was more continuous and causal than discrete and complete. In this process, the types of resilience of persons with disabilities are divided into 'existence reflection', 'course development', 'implicit endeavor', and 'active execution'. This study showed the details of the paradigm models, the process and types with an in-depth understanding of the resilience process of persons with disabilities using grounded theory as well as theory construction and policy and clinical involvement on the study of persons with disabilities.