• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.62-72
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• 2011

Currently, The failure of construction project is increasing to be caused by a changing construction environment. According to this circumstances, Researches of project success factors affecting performance have been presented to develop strategies for efficient construction project management in the construction industry. However, Conducting efficient construction project management is difficult because project manager could not know which project success factors can be improved or not. Especially, although the project characteristics were derived the level of difficulty for performance, research of the project characteristics which could not be improved as influence factor to performance is lacking. Therefore, This paper has developed the Performance Predicting System(PPS) with Fuzzy set theory to establish. PPS has been developed to establish efficient project management strategies and to save time and effort. As Contractor inputs the project characteristics, PPS can predict the level of difficulty of performance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.3
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• pp.10-16
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• 2005

This paper suggested the sulfur lamp power supply using Fuzzy Gain Scheduling(FGS), which was designed and confirmed the performance through manufacturing. it was based on Series Resonant Half Bridge Inverter(SRHBI), so that was applied Pulse Frequency Modulation(PFM), Zero Voltage Switching(ZVS), soft switching and soft start for input power variation and output power compensation. In order to get the lengthened life time of magnetron and stabilized output or power, power ratter and efficiency were improved by fuzzy gain algorism. It also made it possible to get not the existing foxed output power but continuous variable output power$(900\~1250[W])$. The manufactured power supply showed good results in input power $220[V]{\pm}15[\%]$ with stabilized output of power, luminous efficiency 97[1m/W] and power factor $96[\%]$.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.1-12
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• 2020

This study aimed to select and evaluate policy priorities for the expansion of public and semi-public systems for coastwise passenger transport services. For research methodology, the Consistent Fuzzy Preference Relations (CFPR) method was used to effectively extract expert knowledge. First, the result of the analysis on policy tasks for expanding the semi-public system for coastwise passenger transport services showed that "the establishment of public transportation fare system" was the most important task at 0.160. Second, "conversion of the subsidiary routes to a public system by the central government" was ranked next at the importance of 0.136. The factor named "support through proper allocation of budgets between national and local governments" are ranked third (0.119). The results of this study have practical implications in that it proposed the policy priorities for the expansion of the public semi-public systems for coastwise passenger transport services.

• Structural Engineering and Mechanics
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• v.62 no.4
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• pp.507-517
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• 2017

Due to the discontinuous nature of uncertainty quantification in conventional evidence theory(ET), the computational cost of reliability analysis based on ET model is very high. A novel ET model based on fuzzy distribution and the corresponding combination rule to synthesize the judgments of experts are put forward in this paper. The intersection and union of membership functions are defined as belief and plausible membership function respectively, and the Murfhy's average combination rule is adopted to combine the basic probability assignment for focal elements. Then the combined membership functions are transformed to the equivalent probability density function by a normalizing factor. Finally, a reliability analysis procedure for structures with the mixture of epistemic and aleatory uncertainties is presented, in which the equivalent normalization method is adopted to solve the upper and lower bound of reliability. The effectiveness of the procedure is demonstrated by a numerical example and an engineering example. The results also show that the reliability interval calculated by the suggested method is almost identical to that solved by conventional method. Moreover, the results indicate that the computational cost of the suggested procedure is much less than that of conventional method. The suggested ET model provides a new way to flexibly represent epistemic uncertainty, and provides an efficiency method to estimate the reliability of structures with the mixture of epistemic and aleatory uncertainties.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.47-57
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• 2005

In this research, the main theme is the system integration of driving simulator and unmanned vehicle. The total system is composed of the mater system and the slave system. The master system has a cockpit system and the driving simulator. The slave system means an unmanned vehicle, which is composed of the actuator system the sensory system and the vision system. The communication system is composed of RS-232C serial communication system which combines the master system with the slave system. To integrate both systems, the signal classification and system characteristics considered DSP(Digital Signal Processing) filter is designed with signal sampling and measurement theory. In addition, to simulate the motion of tele-operated unmanned vehicle on the driving simulator, the classical washout algorithm is applied to this filter, because the unmanned vehicle does not have a limited working space, while the driving simulator has a narrow working space and it is difficult to cover all the motion of the unmanned vehicle. Because the classical washout algorithm has a defect of fixed high pass later, fuzzy logic is applied to reimburse it through an adaptive filter and scale factor for realistic motion generation on the driving simulator.

• 한국사회정책
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• v.25 no.4
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• pp.301-321
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• 2018

The purpose of this paper is to analyze whether any combination of the quantitative and qualitative aspects of the public pension system is a causal factor for the elderly poverty reduction rate. For this, fuzzy-set qualitative comparison analysis was conducted with the poverty reduction rate as the outcome condition variable, the public pension expenditure ratio, the redistributive index, the first floor public pension weight, the second floor public pension weight and the second floor forced private pension weight did. As a result of the analysis, the combination of high public pension expenditure ratio, low two - tier public pension share and high two - tier compulsory private pension share has become a cause of high poverty reduction rate of the elderly. And more various forms of association were found as the cause of low poverty reduction rate of the elderly. This paper suggests policy proposals based on the above findings.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.127-135
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• 2023

Nowadays, the number of patients committing suicide due to depression and stress is rapidly increasing. In addition, if stress and depression last for a long time, they are dangerous factors that can cause heart disease, brain disease, and high blood pressure. However, no matter how modern medicine has developed, it is a very difficult situation for patients with depression and heart disease without special drugs or treatments. Therefore, in many countries around the world, studies are being actively conducted to determine patients at risk of depression and patients at risk of suicide at an early stage using electrocardiogram, oxygen saturation, and brain wave analysis functions. In this paper, in order to analyze these problems, a computer simulation was performed to determine heart disease risk patients by establishing heart disease hypothesis data. In particular, in order to improve the predictive rate of heart disease by more than 10%, a simulation using fuzzy inference was performed.

• Computers and Concrete
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• v.32 no.2
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• pp.119-138
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• 2023

Concrete carbonation is a prevalent phenomenon that leads to steel reinforcement corrosion in reinforced concrete (RC) structures, thereby decreasing their service life as well as durability. The process of carbonation results in a lower pH level of concrete, resulting in an acidic environment with a pH value below 12. This acidic environment initiates and accelerates the corrosion of steel reinforcement in concrete, rendering it more susceptible to damage and ultimately weakening the overall structural integrity of the RC system. Lower pH values might cause damage to the protective coating of steel, also known as the passive film, thus speeding up the process of corrosion. It is essential to estimate the carbonation factor to reduce the deterioration in concrete structures. A lot of work has gone into developing a carbonation model that is precise and efficient that takes both internal and external factors into account. This study presents an ML-based adaptive-neuro fuzzy inference system (ANFIS) approach to predict the carbonation depth of fly ash (FA)-based concrete structures. Cement content, FA, water-cement ratio, relative humidity, duration, and CO2 level have been used as input parameters to develop the ANFIS model. Six performance indices have been used for finding the accuracy of the developed model and two analytical models. The outcome of the ANFIS model has also been compared with the other models used in this study. The prediction results show that the ANFIS model outperforms analytical models with R-value, MAE, RMSE, and Nash-Sutcliffe efficiency index values of 0.9951, 0.7255 mm, 1.2346 mm, and 0.9957, respectively. Surface plots and sensitivity analysis have also been performed to identify the repercussion of individual features on the carbonation depth of FA-based concrete structures. The developed ANFIS-based model is simple, easy to use, and cost-effective with good accuracy as compared to existing models.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.35-43
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• 2013

As texture images have become prevalent throughout a variety of industrial applications, copyright protection of these images has become important issues. For this reason, this paper proposes a color-texture image watermarking algorithm utilizing texture properties inherent in the image. The proposed algorithm selects suitable blocks to embed a watermark using the energy and homogeneity properties of the grey level co-occurrence matrices as inputs for the fuzzy c-means clustering algorithm. To embed the watermark, we first perform a discrete wavelet transform (DWT) on the selected blocks and choose one of DWT subbands. Then, we embed the watermark into discrete cosine transformed blocks with a gain factor. In this study, we also explore the effects of the DWT subbands and gain factors with respect to the imperceptibility and robustness against various watermarking attacks. Experimental results show that the proposed algorithm achieves higher peak signal-to-noise ratio values (47.66 dB to 48.04 dB) and lower M-SVD values (8.84 to 15.6) when we embedded a watermark into the HH band with a gain factor of 42, which means the proposed algorithm is good enough in terms of imperceptibility. In addition, the proposed algorithm guarantees robustness against various image processing attacks, such as noise addition, filtering, cropping, and JPEG compression yielding higher normalized correlation values (0.7193 to 1).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.273-282
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• 2016

There has been growing social interest recently in the movement rights of people with reduced mobility. However, it simply eliminates the temporary inconvenience of walking of people with reduced mobility because it focuses only on supply of institutional facilities. Therefore, we look forward to improving movement welfare by proposing an optimized path finding algorithm for people with reduced mobility that takes into consideration physical elements affecting their movement, such as slope, steps etc. We selected Walking barrier factor by analyzing previous studies and calculated the relative importance of Walking barrier factors using an Analytic Hierarchy Process(AHP). Next, through the fuzzy system, the Walking disturbance level of link, which integrates the weights of Walking barrier factors and the attributes of each link, is derived. Then, Walking path cost that takes into consideration the ‘length’ factors is calculated and an optimized path for people with reduced mobility is searched using Dijkstra’s Algorithm. Nineteen different paths were searched and we confirmed that the derived paths are meaningful in terms of improving the mobility of people with reduced mobility by conducting a field test. We look forward to improving movement welfare by providing a navigation service using the path finding algorithm proposed in this study.