• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.527-536
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• 2017

With the recent development of smart grid industry, the necessity for efficient EMS(Energy Management System) has been increased. In particular, in order to reduce electric load and energy cost, sophisticated electric load forecasting and efficient smart grid operation strategy are required. In this paper, for more accurate electric load forecasting, we extend the data collected at demand time into high time resolution and construct an artificial neural network-based forecasting model appropriate for the high time resolution data. Furthermore, to improve the accuracy of electric load forecasting, time series data of sequence form are transformed into continuous data of two-dimensional space to solve that problem that machine learning methods cannot reflect the periodicity of time series data. In addition, to consider external factors such as temperature and humidity in accordance with the time resolution, we estimate their value at the time resolution using linear interpolation method. Finally, we apply the PCA(Principal Component Analysis) algorithm to the feature vector composed of external factors to remove data which have little correlation with the power data. Finally, we perform the evaluation of our model through 5-fold cross-validation. The results show that forecasting based on higher time resolution improve the accuracy and the best error rate of 3.71% was achieved at the 3-min resolution.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.333-340
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• 2011

KJJVC(Korea-Japan Joint VLBI Correlator) was installed at the KJCC(Korea-Japan Correlation Center) and has been operated by KASI(Korea Astronomy and Space Science Institute) from 2009. KJNC is able to correlate the VLBI observed data through KVN(Korean VLBI Network), VERA(VLBI Exploration of Radio Astrometry), and JVN(Japanese VLBI Network) and its joint network array. And it is used exclusively as computer in order to process the observed data for the scientific purpose KJJVC used the VSI(VLBI Standard Interface) as the VLBI international standard at the data input-output specification between each component. Especially, for correlating the observed data, the data is transmitted with 1024Mbps speed between Mark5B high-speed playback and RVDB(Raw VLBI Data Buffer). The EMI(Electromagnetic lnterference), which is occurred by data transmission with high-speed, cause the data loss and the loss occurrence is frequently often for long transmission cable. Finally it will be caused the data recognition error by decreasing the voltage level of digital data signal. In this paper, in order to minimize the data loss by measuring the EMI noise level in transmission of the VSI specification, the 3 methods such as 1) RC filtering method, 2) lmpedance matching using Microstrip line, and 3) Signal buffering method using Differential line driver, were proposed. To verify the effectiveness of each proposed method, the performance evaluation was conducted by implementing and simulations for each method. Each proposed method was effectively confirmed as the high-speed data transmission of the VSI specification.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• The Journal of the Petrological Society of Korea
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• v.4 no.1
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• pp.49-58
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• 1995

Staurolite-biotite-andalusite-garnet (SBAG) assemblage and its sub-assemblages (SBA and SBG) commonly occur in the Dueumri Formation near the Chunyang granite, belonging to andalusite and sillimanite zones. The occurrence of the SBAG mineral assemblage is unusual because it is univariant in the $K_2O-FeO-MgO-Al_2O_3-SiO_2-H_2O$ (KFMASH) model system. We used projection and singular value decomposition (SVD) methods to investigate the equilibrium relationship between SBAG and its sub-assemblage. The SVD modelling of single specimen containing the SBAG assemblage suggests no reaction relationship with respect to mass-balance. Thus, the SBAG assemblages are stabilized by non-KFMASH component. On the other hand, the AFM-Mn projection suggests a reaction relationship between SBAG and its sub-assemblage because they intersect each other in this composition space. The SVD modelling, however, suggests no reaction relationship between these assemblages. Thus, the SBAG assemblages are likely to be stabilized by the variation in bulk-rock composition and/or 1.1~2,. The stable occurrence of staurolite in the sillimanite zone is compatible with pressure estimates from the garnet-plagioclase-biotite-muscovite geobarometer.

• Tunnel and Underground Space
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• v.28 no.1
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• pp.97-110
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• 2018

The application of sprayed waterproofing membrane with high adhesion and ductility is considered to be promising as a measure for repair and reinforcement of a tunnel structure. Therefore, a powder-type and one-component membrane prototype with high tensile and bond strengths was made in this study. Then, its reinforcement effect on a shield segment was evaluated by carrying out a series of full-scale loading tests of segment specimens on which the membrane was sprayed. From the tests, it was confirmed that the initial cracking loads increased by approximately 34% due to cracking retardation by membrane coating. Even though the increase of failure loads were not so high as cracking loads, the strain-softening behaviors were observed from specimens coated by the membrane. Therefore, it is expected that the membrane coated on the inner surface of a lining might be effective in preventing its brittle failure.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.823-832
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• 2006

Precipitation is the most important component to the study of water and energy cycle in hydrology. In this study we investigate rainfall retrieval uncertainty from different sources of remotely sensed precipitation field and then probable error propagation in the simulation of hydrologic variables especially, runoff on different vegetation cover. Two remotely sensed rainfall retrievals (space-borne IR-only and ground radar rainfall) are explored and compared visually and statistically. Then, an offline Community Land Model (CLM) is forced with in situ meteorological data to simulate the amount of runoff and determine their impact on model predictions. A fundamental assumption made in this study is that CLM can adequately represent the physical land surface processes. Results show there are big differences between different sources of precipitation fields in terms of the magnitude and temporal variability. The study provides some intuitions on the uncertainty of hydrologic prediction via the interaction between the land surface and near atmosphere fluxes in the modelling approach. Eventually it will contribute to the understanding of water resources redistribution to the climate change in Korean Peninsula.

• Restorative Dentistry and Endodontics
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• v.23 no.2
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• pp.701-709
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• 1998

Many dental composites are Bis-GMA based resin which diluted with the more fluid monomer triethylenglycol dimethacrylate(TEGDMA). TEGDMA is often present in exess so that some quantity remains unreacted following photo-initiated polymerization. TEGDMA is a component of some resin composites which contributes to their cytotoxicity. The presence of dentin between resin composite and pulp space reduce the cytotoxicity in vitro. The root system from extrcted human third molar was removed and then a circular occlusal cavity 4mm in diameter was prepared, leaving a remaining dentinal thickness to the roof of the pulpal chamber within the range 1.0-1.5mm. Dentine was treated with 37% phosphoric acid prior to Z 100 placement without using bonding resin(group 1). In group 2, SMP(Scotchbond Multi Purpose) primer, bonding resin prior to Z 100 placement were applied sequently. In group 3, moulds with internal dimensions 4mm diameter by 2mm depth were used to contain the composite alone with an equvalent mass on tooth model, and then they were immersed directly into water. The purpose of this study is to evaluate the release rate and quantity of TEGDMA with or without the application of bonding resin. Both release rate and total cumulative amount of TEGDMA for the three groups were determined using reversed-phase HPLC at times up to 10 days. The results were as follows: 1. All experimental groups showed the highest rate of release was in the first sample period(0-4.32 min) and the rate of release declined exponentially thereafter. 2. The maximum release rate and total cumulative account of TEGDMA in the tooth model of group 1 and group 2 with the use of SMP bonding resin were reduced however ther were no significant differences between these groups(P>0.05). 3. In the first sample period(0-4.32 min), the rate of release of TEGDMA from composite resin in group 3 immersed directly into water was significantly higher than that in group 1 and group 2 of tooth model(P<0.05). Conclusively, TEGDMA diffusion from Z 100 resin was not effectively prevented by the presence of dentin in spite of using the SMP bonding resin.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.298-308
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• 2020

This study was designed to verify reliability and feasibility by analyzing elderly drivers' ability test tools for older drivers aged 65 or older, which were improved in 2018 and are currently being conducted by the Korea Highway Traffic Authority. Only those aged 65 or older who voluntarily applied to the elderly driving ability evaluation system implemented by the Seoul branch of the Korea Highway Traffic Authority. The research was conducted for about 50 days until Aug. 31, 2018, starting with the registration and inspection of the first study subjects. The analysis performed a correlation analysis with existing tools and cognitive testing tools (MMSE_K) to determine their feasibility and reliability as an improved tool in 2018. As a result, the first, the speed distance, time-space memory, and dispersionism of each sub-component of the old version showed statistically significant static correlation with the sub-factor of the current version. Persistence, on the other hand, was not statistically significant to the current version. The limitations of this study were as follows. Most of the people in the study were highly educated and residents in the metropolitan area. Therefore, it is likely that the results of MSE_K, which checks cognitive and judgment skills, have been upgraded. Also, cognitive tools that are measured by computers are likely to have real measurement errors for generations who are not familiar with computers. Therefore, it is expected that improvement and development of tools for improving the limit points at the site and assessing actual operation capability will be required.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.5
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• pp.316-325
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• 2012

In this study, we suggested adequate control technology by analyzing emission process and main chemical of VOC/HAPs generated from four paint factories in Busan area. And we estimated whether Kapok fiber, which is a natural material, can be commercially used for an absorbent by testing adsorption ability. As a result of this sturdy, above 60% of VOC/HAPs was volatilized and dispersed inside the working place without conducting control system of facilities during manufacturing paints. Concentration profile of VOC/HAPs, which is volatile naturally outside the factories, is surveyed above 70% at Toluene, Ethylbenzene, and Xylene. And a result of evaluation of odor attribution level about the component whose Odor Threshold is known, it is estimated that major cause material of A, B, C factories is Toluene and that of D factory is m/p-Xylene. And that result presented design arguments such as facilities specifications, activated carbon filling volume, and replace cycle of activated carbon as control technology. Also, that result presented emission process improvement such as adsorption of central-controlled ventilation device, installation of inlet flenge, and potable cleaning process. The rate of pollutant adsorption of Kapok fiber, which is natural material, is indicated about 91.9%, 66.7%. That result validated the possibility as replacement of activated carbon.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.27-36
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• 2004

Detection and recognition of human faces in images can be considered as an important aspect for applications that involve interaction between human and computer. In this paper, we propose a face recognition method using eigenfaces and fuzzy neural networks. The Principal Components Analysis (PCA) is one of the most successful technique that have been used to recognize faces in images. In this technique the eigenvectors (eigenfaces) and eigenvalues of an image is extracted from a covariance matrix which is constructed form image database. Face recognition is Performed by projecting an unknown image into the subspace spanned by the eigenfaces and by comparing its position in the face space with the positions of known indivisuals. Based on this technique, we propose a new algorithm for face recognition consisting of 5 steps including preprocessing, eigenfaces generation, design of fuzzy membership function, training of neural network, and recognition. First, each face image in the face database is preprocessed and eigenfaces are created. Fuzzy membership degrees are assigned to 135 eigenface weights, and these membership degrees are then inputted to a neural network to be trained. After training, the output value of the neural network is intupreted as the degree of face closeness to each face in the training database.