• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1625-1631
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• 2020

With the development of IoT technology, various digital equipment is being spread, and accordingly, the importance of data processing is increasing. The importance of data processing is increasing as it greatly affects the reliability of equipment, and various studies are being conducted. In this paper, we propose an algorithm to remove AWGN according to the characteristics of the fuzzy membership function. The proposed algorithm calculates the estimated value according to the correlation between the value of the fuzzy membership function between the input image and the pixel value inside the filtering mask, and obtains the final output by adding or subtracting the output of the spatial weight filter. In order to evaluate the proposed algorithm, it was simulated with existing AWGN removal algorithms, and analyzed using difference image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves the important characteristics of the image, and shows the performance of efficiently removing noise.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.207-213
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• 2022

Recently, with the improvement of the performance of IoT technology and AI, automation and unmanned work are progressing in a wide range of fields, and interest in image processing, which is the basis of automation such as object recognition and object classification, is increasing. Image noise removal is an important process used as a preprocessing step in an image processing system, and various studies have been conducted. However, in most cases, it is difficult to preserve detailed information due to the smoothing effect in high-frequency components such as edges. In this paper, we propose an algorithm to restore damaged images in AWGN(additive white Gaussian noise) using fuzzy weights based on Gaussian distribution. The proposed algorithm switched the filtering process by comparing the filtering mask and the noise estimate with each other, and reconstructed the image by calculating the fuzzy weights according to the low-frequency and high-frequency components of the image.

• Steel and Composite Structures
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• v.51 no.1
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• pp.25-41
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• 2024

The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence of several suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (ANFIS) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (FHO) and equilibrium optimizer (EO) with the ANFIS, referred to as ANFIS_FHO and ANFIS_EO, respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that ANFIS_FHO and ANFIS_EO both have amazing potential for precisely calculating pile bearing capacity. The R² values obtained for ANFIS_FHO were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the ANFIS_FHO system had less uncertainty than the ANFIS_EO model. The research found that the ANFIS_FHO model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.139-144
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• 2009

The leveling of technical internet domain term with its aim to accumulate knowledge that machine can comprehend, which has been used widely in recent years. If stratify domain term weight, we believe that machine can manage and analyze in formation on its own using the ontology. In this paper, we propose an algorithm that allows us to extract properties of ontology weight from structured information already existing in web documents. In particular by stratification of the domain knowledge that is composed of property information, we were able to make the algorithm better and improve the quality of extraction results. In our experiments with 50 thousands targeted documents, we were able to extract property information with 94% confidence.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3472-3482
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• 2024

This study proposes a modified extended cognitive reliability and error analysis method (CREAM) for achieving a more accurate human error probability (HEP) in advanced control rooms. The traditional approach lacks failure data and does not consider the common performance condition (CPC) weights in different cognitive functions. The modified extended CREAM decomposes tasks using a method that combines structured information analysis (SIA) and the extended CREAM. The modified extended CREAM performs the weight analysis of CPCs in different cognitive functions, and the weights include cognitive, correlative, and important weights. We used the extended CREAM to obtain the cognitive weight. We determined the correlative weights of the CPCs for different cognitive functions using the triangular fuzzy decision-making trial and evaluation laboratory (TF-DEMATEL), and evaluated the importance weight of CPCs based on the interval 2-tuple linguistic approach and ensured the value of the importance weight using the entropy method in the different cognitive functions. Finally, we obtained the comprehensive weights of the different cognitive functions and calculated the HEPs. The accuracy and sensitivity of the modified extended CREAM were compared with those of the basic CREAM. The results demonstrate that the modified extended CREAM calculates the HEP more effectively in advanced control rooms.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.198-207
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• 1996

Electro sensitive traffic system can't consider passenger car unit, so, it causes start up delay time and passenger waiting time. In this paper, it antecedently creates optimal traffic cycle of passenger car unit at the bottom traffic intersection. But, sometimes it can make mistakes due to changes in car weight, car speed, and control of feed-back data. Moreover, to prevent spillback, it can adapt control even though upper traffic intersection has a different saturation rate, road length, road slope and road width.

• Proceedings of the ESK Conference
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• 1994.04a
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• pp.52-63
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• 1994

산업현장에서 산업재해의 주요한 요인이 되는 중량물 수운반 활동시 작업자가 안전 하게 작업을 행하면서도 최적허용중량을 결정하기위한 연구는 주어진 작업조건하에 서 인양되는 최대중량을 결정하기 위한 기준으로서 척추에 가해지는 압력을 이용하는 생체역학적 접근법, 주어진 작업조건하에서 인양되는 최대중량을 결정하기 위한 기준 으로서 에너지 소모량을 이용하는 생리학적 접근법, 주어진 작업조건하에서사람이 인 양할 수 있는 최대중량을 결정하는 기준으로서 피실험자에의해서 인지되는 힘든 정도를 이용하는 정신물리학적 접근법 등으로수행하여 왔다.

• The Journal of the Korea Contents Association
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• v.17 no.10
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• pp.231-240
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• 2017

Although the value of technology is evaluated by various methods, the result of technology valuation is different from evaluator and evaluation methods. Also the uncertainty on the result occurs with respect to the evaluation factors and evaluation model which should be considered. In the case of lack of data or comparison target, the credibility of the technology valuation result could be unsure. To decrease uncertainty of the technology valuation, Fuzzy concept and Fuzzy Comprehensive Evaluation method are applied instead of using existing methods which evaluate technology value(level) by the number. In the research, we firstly devide evaluation criteria into technology value factor and business value factor and evaluate the technology level for micro pressure wave reduction technology which has been developed in Korea. Technology value factor is marked as high level with 46%, and business value factor is very high with 44%, and the overall level of technology is evaluated between very high and high. It helps to compare to other technology in the rivalry by the factors as it can evaluate the value of technology by factors. The technology valuation method which is applied in this research is expected to use on analyzing technology level of new technology or alternative technology in many different field.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.305-309
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• 2011

A sparse reconfigurable adaptive filter (SRAF) based on a photonic switch determines the appropriate time delays and weight values for an optical switch implementation of tapped-delay-line (TDL) systems. It is well known that the choice of switch delays is significantly important for efficiently implementing the SRAF. If the same values exist as calculating the sum of weight magnitudes for implementing the connection constraint required by the SRAF, conventional connection algorithm based on sequentially selection the maximum elements might not work perfectly. In an effort to increase the effectiveness of system identification, an upgraded connection algorithm used progressive calculation to obtain the better solution is considered in this paper. The performance of the proposed connection constraint algorithm is illustrated by computer simulation for a system identification application.

• Advances in materials Research
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• v.5 no.4
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• pp.263-277
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• 2016

Mechanical properties of $Al/Al_2O_3$ and $Al/B_4C$ composites prepared through powder metallurgy are estimated up to 50% $Al_2O_3$ and 35% $B_4C$ weight fractions using micromechanics models and experiments. The experimental Young's modulus up to 0.40 weight fraction of ceramic is found to lie closely between Ravichandran's/Hashin-Shtrikman lower/upper bounds, and close to self consistent method/Miller and Lannutti method/modified rule of mixture/fuzzy logic method single value predictions. Measured Poisson's ratio lies between rule of mixture/Ravichandran lower and upper bound/modified Ravichandran upper bounds. Experimental Charpy energy lies between Hopkin-chamis method/equivalent charpy energy/Ravichandran lower limit up to 20%, and close to the reciprocal rule of mixture for higher $Al_2O_3$ content. Rockwell hardness (RB) and Micro-hardness of $Al/Al_2O_3$ are closer to modified rule of mixture predictions.