• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.112-119
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• 2009

Telecare, one of the e-healthcare services with lCT, is a promising technology which aims to monitor the state of patients and then provide the medical services appropriately in remote sites. Virtual telecare team based on the concept of virtual collaborative teams which consist of a patient, a doctor, and a telecare team, operates on a temporary basis in need. Reputation, which means the degree of a patient's belief to a doctor in consideration, is the most important factor to make the virtual telecare team trustable. In this paper, we propose the fuzzy reputation model of a virtual telecare team, which is a reputation-based trust model based on fuzzy set theory. An illustrative example is also given in order to show the applicability of the model to the concept of a virtual telecare team.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.132-136
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• 1994

Presented is the study on design and implementation of a fuzzy system to approximately reason using measured actual storage rate in irrigation reservoirs. To design Fuzzy reasoning systems. Minimum Operation Rule by Mamdani was applied. Fuzzy variable and membership functions are determined after identifying storage-rate affecting factor and followed simulation. Hydrological model to express actual situation within drought areal boundary is generally too complex. Hereby, considering irregularity of time-rate storage change during irrigation, this system uses irrigation water and meteorological data as a IN-data. It was abvious the results were closely corresponding to the actual data observed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.150-155
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• 2011

In an active noise control systems, an IIR filter may cause a problem in stability beacause of its poles. For IIR filter, its poles goes sometimes out of a unit circle in a z-plane in the transition state, where the adaptive algorithm converges to the optimum value, which causes the system to diverge. Fuzzy LMS algorithm has a better convergence property than conventional LMS algorithms, but is not applicable to IIR filter because of the reasons. Stabilized adaptive algorithm could be improves stability by moving the pole of IIR filer toward the origin forcibly in the transient state, and by introducing forgetting factor to maintain the optimum convergence when it reaches to the steady state. In this paper, We proposed stabilized adaptive fuzzy LMS algorithms with IIR filter structures, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithm.

• Journal of Construction Engineering and Project Management
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• v.7 no.3
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• pp.39-55
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• 2017

Preeminent performance of construction industry are unattainable with poor productivity resulting in time and cost over runs. Enhancement in productivity cannot be achieved without identifying and analyzing factors that adversely affect productivity. The objective therefore is to propose a productivity analysis model to quantify the probability of effect of factors influencing productivity by using fuzzy logic incorporated with relative importance index method, for various types of construction projects. To achieve this objective, a questionnaire survey was carried out targeting respondents of Indian construction industry, from four distinct projects, namely, residential, commercial, infrastructure and industrial projects. Based on questionnaire administered, the relative importance and ranks of factors demonstrated using relative importance index method. Probability assessment model to analyze productivity was then developed by using Fuzzy Logic Toolbox of MATLAB. The applicability of the proposed model was tested in seven construction projects and the probability of impact of factors on productivity evaluated. The results of application of model in the construction firms infers that the most contributing factor groups for most of the projects were discerned to be manpower, motivation and time group.

• Journal of the Korea Safety Management & Science
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• v.19 no.4
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• pp.43-52
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• 2017

The purposes of this study are to analyze risks of construction step BIM(Building Information Modeling) applied project and improve it. Recently, construction industry has emphasized an importance of BIM for efficient utilization of various information. In the whole life cycle of huge construction project, there are cases introducing BIM and projects applying BIM are gradually increased to the work of construction step. However, the process of communication is not established, so the contents of BIM process of construction step are just showing rough fields and concepts of working utilization, so it's restrictive to utilize BIM actively on constructions step. Through results of case study in this research, constructor risks of BIM business should be efficiently treated with Fuzzy-FMEA that is more precise than existing danger evaluation.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.353-354
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• 2023

Improving productivity in industries is a very critical issue, and improving labor productivity is especially important in construction industry, which is a labor-intensive industry. However, researches on labor productivity in construction industry are insufficient, and most of previous studies have limitations in terms of specificity and logic. In this study, fuzzy DEMATEL method was used to structural analyze of influence factors for labor productivity in construction industry based on previous researches and expert survey. The result of this study contributes to deriving priorities for improving labor productivity.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Journal of Korean Society of Transportation
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• v.23 no.6 s.84
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• pp.31-40
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• 2005

Main airports in the Intra-Asian market have faced competition not only to attract China-bound transshipment cargoes but also to be hub airport in same region. In spite of such a importance, the previous research has been short of evaluation of airport competitiveness. Implication of the previous research has mainly been focused on evaluation of airport critical factor service qualify and efficiency. The aim of this paper is to present critical points that affect airport competitiveness using an algorithm based on reversed fuzzy evaluation and senario method. The results of senario analysis and reversed fuzzy evaluation shows that Incheon international airport needs to enhance service level of 7% as a result of senario analysis and service level of 5% and brand equity level of 10% at the same time as a result of reversed fuzzy evaluation analysis, to ensure competitiveness in same region.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.71-79
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• 1997

In this paper, a codeword-dependent distance normalization(CDDN) and an instar-formed fuzzy smoothing of output distribution are proposed for robust estimation of output probabilities in the FVQ(fuzzy vector quantization)-DHMM(discrete hidden Markov model). The FVQ-DHMM is a variant of DHMM in which the state output probability is estimated by the sum oft he product of the output probability and its weighting factor for each codeword on an input vector. As the performance of the FVQ-DHMM is influenced by weighting factor and output distribution from a state, it is required to get a method to get robust estimation of weighting factors and output distribution for each state. From experimental results, the proposed CDDN method has reduced 24% of error rate over the conventional FVQ-DHMM, and also reduced 79% of error rate when the smoothing of output distribution is also applied to the computation of an output probability. These results indicate that the use of CDDN and the fuzzy smoothing of output distribution to the FVQ-DHMM lead to improved recognition, and therefore it may be used as an alternative to the robust estimation of output probabilities for HMMs.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.515-521
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• 2015

The purpose of this study was to analyze the weights of obstacle factors against mutual access of towed trailers of car-ferry between South Korea and China using Fuzzy-AHP. To this end, factors were first selected through literature research and finally selected through in-depth interviews with a group of experts in cargoes who are currently in car-ferry companies. Selected high rank obstacle factors included unstable service provision, limited policy support, and additional costs being incurred and among them, unstable service provision was identified as the most serious obstacle factor through analysis. Eleven measurement variables selected include insufficient supply of container yard, trailer insurance and management issues, insufficient special equipment, insufficient specialized manpower, limited input service courses, insufficient marketing and public relations strategies, and increasing transportation costs and among them, increasing equipment returning costs due to unbalanced cargo gathering were identified as the most serious obstacle factor through analysis followed by limited input service courses, insufficient special equipment, delays in procedures, and occurrence of additional procedures in order of precedence.