• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.116-119
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• 2018

In this paper, we propose a new single-image dehazing method. The proposed method constructs color ellipsoids that are statistically fitted to haze pixel clusters in RGB space and then calculates the transmission values through color ellipsoid geometry. The transmission values generated by the proposed method maximize the contrast of dehazed pixels, while preventing over-saturated pixels. The values are also statistically robust because they are calculated from the averages of the haze pixel values. Furthermore, rather than apply a highly complex refinement process to reduce halo or unnatural artifacts, we embed a fuzzy segmentation process into the construction of the color ellipsoid so that the proposed method simultaneously executes the transmission calculation and the refinement process. The results of an experimental performance evaluation verify that compared to prevailing dehazing methods the proposed method performs effectively across a wide range of haze and noise levels without causing any visible artifacts. Moreover, the relatively low complexity of the proposed method will facilitate its real-time applications.

• Journal of Construction Engineering and Project Management
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• v.8 no.4
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• pp.1-24
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• 2018

In the last decade, the use of Building Information Modeling (BIM) as a new technology has been applied with traditional Computer-aided design implementations in an increasing number of architecture, engineering, and construction projects and applications. Its employment alongside construction management, can be a valuable tool in helping move these activities and projects forward in a more efficient and time-effective manner. The traditional stakeholders, i.e., Owner, A/E and the Contractor are involved in this BIM system that is used in almost every activity of construction projects, such as design, cost estimate and scheduling. This article extracts major features of the application of BIM from perspective of participating BIM components, along with the different phrases, and applies to them a logistic analysis using a fuzzy performance tree, quantifying these phrases to judge the effectiveness of the BIM techniques employed. That is to say, these fuzzy performance trees with fuzzy logic concepts can properly translate the linguistic rating into numeric expressions, and are thus employed in evaluating the influence of BIM applications as a mathematical process. The rotational fuzzy models are used to represent the membership functions of the performance values and their corresponding weights. Illustrations of the use of this fuzzy BIM performance tree are presented in the study for the uninitiated users. The results of these processes are an evaluation of BIM project performance as highly positive. The quantification of the performance ratings for the individual factors is a significant contributor to this assessment, capable of parsing vernacular language into numerical data for a more accurate and precise use in performance analysis. It is hoped that fuzzy performance trees and fuzzy set analysis can be used as a tool for the quality and risk analysis for other construction techniques in the future. Baldwin's rotational models are used to represent the membership functions of the fuzzy sets. Three scenarios are presented using fuzzy MEAN, AND and OR gates from the lowest to intermediate levels of the tree, and fuzzy SUM gate to relate the intermediate level to the top component of the tree, i.e., BIM application final performance. The use of fuzzy MEAN for lower levels and fuzzy SUM gates to reach the top level suggests the most realistic and accurate results. The methodology (fuzzy performance tree) described in this paper is appropriate to implement in today's construction industry when limited objective data is presented and it is heavily relied on experts' subjective judgment.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.2
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• pp.144-150
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• 2013

The purpose of this study was to evaluate the competence level of the caregiver and verify empirically the evaluated score of the competence level of the caregiver depending on the type of career and employment to propose a measure to improve the quality of care services. To more accurately evaluate the competence level of caregiver, the collected data were analyzed using fuzzy relationships for identifying the extent of relationship, after setting weighted values for the evaluation factors for working levels and service qualities. Such approach has a significance in that individual evaluation factors and individual's competence levels for caregivers may be more suitably and exactly identified. The analysis results are as follows. Care skill, reliability, assurance, typicality were statistically significant according to the caregiver's career. Also, according to the types of employment, job consciousness, responsiveness, empathy, typicality were statistically significant. To improve the competence level of the caregiver, it may be seen that improvement of job consciousness considering the career and employment types and making environments for acquiring the care skills should be done, while providing stability of the employment types rather than careers is more meaningful to improve the quality of services.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.526-537
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• 1999

In the paper. we propose an evaluation model based the adaptive fuzzy systems, which can transform the physical features of a color pattern to the emotional features. The model is motivated by the Soen's psychological experiments, in which he found the physical features such as average hue, saturation, intensity and the dynamic components of the color patterns affects to the emotional features represented by a pair of adjective words having the opposite meanings. Our proposed model consists of two adaptive fuzzy rule-bases and the y-model, a l i r ~ r ys et operator, to fuze the evaluation values produced by them. The model shows con~parablep erformances to the neural network for the approximation of the nonlinear transforms, and it has the advantage to obtain the linbwistic interpretation from the trained results. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.737-744
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• 2000

This paper resorts to rock mass rating and rock mass quality to draw value based on the evaluation of rock and to draw interrelation formula in relation to rock mass quality, A comparative analysis was given of survey values reported in the existing documents. This paper has tried to find out the relationship between RMR and Q System for the sake of choosing rational reinforcing patterns and of the safety of tunnels. The results run as follow: RMR=8.251n(Q)+43.83. This paper has also tried to find out the relationship between RMR and Q System by using Fuzzy Approximate Reasoning Concept. We suggest that those in charge should not depend on a single system only after evaluating the classification of rocks, and compare one result with another for the good of keeping track of the condition of base rocks in a better way.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.410-413
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• 1998

A passive approach for enhancing fault detection and isolation performance of multiple observer based fault detection isolation schemes(FDIS) is proposed. The FDIS has a hierarchical framework to perform detection and isolation of faults of interest, and diagnosis of process faults. The decision unit comprises of a rule base and fuzzy inference engine and removes some difficulties of conventional decision unit which includes crisp logic and threshold values. Emphasis is placed on the design and evaluation methods of the diagnostic rule base. The suggested scheme is applied for the FDIS design for a DC motor driven centrifugal pump system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.5-8
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• 2003

This paper presents a methodology to be able to select an appropriate RP system that suits the end use of a part. Evaluation factors used in process selection include major attributes such as accuracy, roughness, strength, elongation, part cost and build time that greatly affect the performance of RP systems. Crisp values such as accuracy and surface roughness are obtained with a new test part developed. The test part is designed with conjoint analysis to reflect users' preference. The part cost and build time that have approximate ranges due to cost and many variable parameters are presented by linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application is selected by using the modified TOPSIS(Technique of Order Preference by Similarity to Ideal Solution) method. It uses crisp data as well as linguistic variables, and each weight on the alternatives is assigned by using pair-wise comparison matrix. The ranking order helps the decision making of the selection of RP systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.138-149
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• 2016

Quality function deployment (QFD) is a widely adopted customer-oriented product development methodology by translating customer requirements (CRs) into technical attributes (TAs), and subsequently into parts characteristics, process plans, and manufacturing operations. A main activity in QFD planning process is the determination of the target levels of TAs of a product so as to achieve a high level of customer satisfaction using the data or information included in the houses of quality (HoQ). Gathering the information or data for a HoQ may involve various inputs in the form of linguistic data which are inherently vague, or human perception, judgement and evaluation for the information and data. This research focuses on how to deal with this kind of impreciseness in QFD optimization. In this paper, it is assumed as more realistic situation that the values of TAs are taken as discrete, which means each TA has a few alternatives, as well as the customer satisfaction level acquired by each alternative of TAs and related cost are determined based on subjective or imprecise information and/or data. To handle these imprecise information and/or data, an approach using some basic definitions of fuzzy sets and the signed distance method for ranking fuzzy numbers is proposed. An example of a washing machine under two-segment market is provided for illustrating the proposed approach, and in this example, the difference between the optimal solution from the fuzzy model and that from the crisp model is compared as well as the advantage of using the fuzzy model is drawn.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1320-1326
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• 2010

In this paper, we develop a design methodology of granular-based neurocomputing networks realized with the aid of the clustering techniques. The objective of this paper is modeling and evaluation of approximation and generalization capability of the Linear-Type Superconducting Power Supply (LTSPS). In contrast with the plethora of existing approaches, here we promote a development strategy in which a topology of the network is predominantly based upon a collection of information granules formed on a basis of available experimental data. The underlying design tool guiding the development of the granular-based neurocomputing networks revolves around the Fuzzy C-Means (FCM) clustering method and the Radial Basis Function (RBF) neural network. In contrast to "standard" Radial Basis Function neural networks, the output neuron of the network exhibits a certain functional nature as its connections are realized as local linear whose location is determined by the membership values of the input space with the aid of FCM clustering. To modeling and evaluation of performance of the linear-type superconducting power supply using the proposed network, we describe a detailed characteristic of the proposed model using a well-known NASA software project data.

• Journal of Korean Society of Transportation
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• v.12 no.4
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• pp.5-19
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• 1994

The new concept of level of service for the airport system indicates that there must be strong stimulation to proceed with the current stereotyped service standards which are being criticised due to their being based on, either physical capacity/volume or temporal/spatial standards that directly incorporates the perception of passengers. Quantitative factors have been dealt with the main service measurements when evaluating level of service. However, the passenger's perception for the provision service at the airport system is definitely important consideration to assess level of service. To enhance the reliability of service level evaluation from the passenger's point of view, this study has adopted three main evaluation factors ; temporal/spatial factors as quantitative measurements and comfort and reasonable service factors as qualitative measurements. The multi-decision model was constructed using Fuzzy Set Theory and applied to a case study at Seoul Kimpo International Airport. Results are presented in terms of passenger satisfaction with a variety of different values.