• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.75-83
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• 2011

This research explores the relative importance of factors and service items that influence the air cargo service quality for provision services by the Skyteam Cargo in the Korean market. In general, the Skyteam Cargo provides a package of services which are different functions and operations of service such item as Equation Heavy (heavy and large express freight), Equation (small express freight), Variation (special freight), and Dimension (general freight). To carry out the research, the expert questionnaire survey, the Analytic Hierarchy Process (AHP) analysis had adopted to evaluate the level of quality for the provision air cargo operation services by the Skyteam Cargo at Incheon International Airport. Based on an expert survey and the AHP, five core service factors, namely, infrastructure as installed facilities, reliability, promptness, efficiency, and safety are defined.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.171-181
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• 2000

Many Studies of tunnel and tunnelling safety have been developed continuously based on the increasing social interests in underground space since 1990's in Korea. Because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities, underground facilities have been created as a great extent in view of less land space available. In this study, a lot of types of tunnel failure were surveyed and the detail causes were studied after many cases of tunnel failure were collected. There were suggested brief countermeasure of tunnel failure through case study. An expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Tunnel and Underground Space
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• v.10 no.3
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• pp.418-429
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• 2000

Many Studies of tunnel and tunnelling safety have been developed continuously based on the increasing social interests in underground space since 1990's in Korea. Because the growth of population in metropolitan has been accelerated at a faster pace than the development of the cities, underground facilities have been created as a great extent in view of less land space available. In this study, a lot of types of tunnel failure were surveyed and the detail causes were studied after many cases of tunnel failure were collected. There were suggested brief countermeasure of tunnel failure through case study. An expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river. This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.67-72
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• 2005

Most of image binarization algorithms analyzes the intensity distribution using the histogram for the determination of threshold value. When the intensity difference between the foreground object and the background is great, the histogram shows the tendency to be bimodal and the selection of the histogram valley as the threshold value shows the good result. On the other side. when the intensity difference is not great and the histogram doesn't show the bimodal property, the histogram analysis doesn't support the selection of the proper threshold value. This Paper Proposed the novel binarization method that applies the fuzzy membership function to each color value on the RGB color model and, by using the operation results, separates the features having the great readability from the background. The proposed method prevents the loss of information incurred by the gray scale conversion by using the RGB color model and extracts effectively the readable features by using the fuzzy inference Compared with the traditional binarization methods, the proposed method is able to remove the majority of noise areas and show the improved results on the image of transport containers , etc.

• 한국사회정책
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• v.19 no.3
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• pp.119-147
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• 2012

This paper aims to explore whether the trilemma of welfare states has been a valid argument about the recent change of welfare states. Based on fuzzy-set ideal type analysis of data from seventeen OECD countries, it examines that welfare states have achieved three core policy objectives -income equality, employment growth and fiscal discipline- in the service economy during the period between 1981 and 2010. The evidence presented in this paper does not support the trilemma of the service economy where only two goals can be pursued successfully at one time, at a cost of the other remained goal. The trilemma has been effective only to the countries in liberal welfare regime where employment growth and fiscal discipline has been achieved at a cost of higher levels of income equality. However, conservative welfare-state regimes have experienced the deterioration of income equality and fiscal restraint after the mid 1980s and it seems that they have diverged into various models. In the countries of the social democratic welfare regime, the goals of equality and employment have been achieved simultaneously together with fiscal discipline since the early 2000s. While they are classified as the perfect model in the research, Southern European welfare states including Greece and Italy, classified as 'the crisis model', have not performed well in all the three aspects. On the evidence presented in this paper, it can be said that the trilemma of welfare states in the service economy is not effective to explain the policy goals of welfare state as well as the result of redistributive politics in the service economy.

• Information Systems Review
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• v.12 no.2
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• pp.189-203
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• 2010

Is presenting guidance of information performance measurement as government PRM version 2.0 these common reference models in public sector. Government PRM is consisted of assessment classification system and standard line of sight and performance management standard form. Through this, is sorting performance element and define cause-and effect. Government PRM is supplying measurement categories at assessment classification system, but relative importance for application standard by measurement categories is not presenting. In this study, importance for government PRM's measurement categories been applying by commonness Test of information performance measurement of public sector wishes to deduce estimation and priority. Research model used Fuzzy QFD, and designed so that can reflect well PRM's development purpose. I applied Fuzzy AHP and FPP method that graft together fuzzy theory to minimize uncertainty and ambiguity in that expert opinion. Is drawn to element that "Standard model offer for information department and management" is the most important in government PRM's development purpose. "Quality of service" is showing the highest priority in customer results in measurement category. Importance for government PRM's measurement categories can offer common valuation basis in government and public institution. Hereafter if examine closely quantitative cause-and effect for structure model of measurement classification system when study government PRM more objective and efficient reference model become.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.2
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• pp.75-87
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• 2013

This study developed a GIS-based suitability assessment model of coastal zoning system that is needed in the substantial classification of coastal zoning system according to the establishment of law about coastal zoning system. First, this study investigated several kinds of regulations, GIS database and application system related coastal area. Also, grid data model was selected as the GIS analytical model for calculating items of suitability assessment of coastal zoning system. And Grid-based analytical method was suggested for calculating items composing of sea and spatial location characteristics including physical one. Critical values of items were presented using standards that were suggested in coastal regulations and land suitability assessment. Especially, this study presented a calculation method of continuous pattern as fuzzy set function for reflecting the characteristics of GIS data. And this study classified the suitability grade using Z-score and developed model designating coastal zone as conservation management priority, utilization management priority, and planning management priority. This study is judged that very efficient business performance is possible if we consider the spatial coverage of study area and GIS database when the suitability assessment model of coastal zoning system that is suggested in this study, is applied to business works.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1413-1424
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• 2013

Recently, the frequency of severe storms increases in Korea. Severe storms occurring in a short time cause huge losses of both life and property. A considerable research has been performed for the flood control system development based on an accurate stream discharge prediction. A physical model is mainly used for flood forecasting and warning. Physical rainfall-runoff models used for the conventional flood forecasting process require extensive information and data, and include uncertainties which can possibly accumulate errors during modelling processes. ANFIS, a data driven model combining neural network and fuzzy technique, can decrease the amount of physical data required for the construction of a conventional physical models and easily construct and evaluate a flood forecasting model by utilizing only rainfall and water level data. A data driven model, however, has a disadvantage that it does not provide the mathematical and physical correlations between input and output data of the model. The characteristics of a data driven model according to functional options and input data such as the change of clustering radius and training data length used in the ANFIS model were analyzed in this study. In addition, the applicability of ANFIS was evaluated through comparison with the results of HEC-HMS which is widely used for rainfall-runoff model in Korea. The neuro-fuzzy technique was applied to a Cheongmicheon Basin in the South Han River using the observed precipitation and stream level data from 2007 to 2011.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.261-274
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• 1997

Most of the data sets to which the conventional discriminant rules have been applied contain only those which belong to one and only one class among the classes of interest. However the extension of the bivalence to multivlaence like Fuzzy concepts strongly influence the traditional view that an object must belong to only class. Thus the goal of this paper is to develop new discriminant rules which can handle the data each object of which may belong to moer than two classes with certain degrees of belongings. A calibration model is used for the relationship between the feature vector of an object and the degree of belongings and a Bayesian inference is made with the Metropolis algorithm on the degree of belongings when a feature vector of an object whose membership is unknown is given. An evalution criterion is suggested for the rules developed in this paper and comparision study is carried using two training data sets.