• Journal of Soil and Groundwater Environment
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• v.29 no.1
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• pp.10-17
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• 2024

In Korea, the common remedial process for reclamation of agricultural soils nearby abandoned mines involves chemical soil stabilization followed by covering with clean soil. This study investigated the chemical properties of cover soils and the validity of HCl extraction method in assessing the degree of As and heavy metal stabilization in stabilized soils collected from 14 plots where mine reclamation had been completed. The results revealed there were no major differences in contaminants extraction rate between the stabilized soils and contaminated soils, suggesting HCl extraction procedure is a less feasible method to determine the efficiency of the stabilization. Soil quality indicators including OM, SiO₂, P₂O₅, etc. of the land-covering soils were generally lower than those of stabilized soils that used to be the cultivation layer before the stabilization. Nonetheless, the value of those indicators didn't meet the regulatry limits of agricultural soil. Therefore, future strategy for mine reclamation should concentrate not only on contaminant concentration but also on soil quality parameters for agricultural use of the reclaimed soil.

• Korean Journal of Microbiology
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• v.46 no.3
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• pp.291-295
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• 2010

A novel bacteriocin produced by Streptococcus parauberis Z49 strain was characterized and efficiently extracted from fermented cultures by use of aqueous two-phase systems. The nisin-like bacteriocin, which was active even after a heat treatment at $121^{\circ}C$ for 15 min and in the broad pH range from 2 to 12, showed inhibition of bacterial growth of Micrococcus luteus, Lactobacillus spp., Lactobacillus fermentum, Enterococcus faecium, Listereia monocytogenes, and Pseudomonas fluorescens. Optimal conditions of PEG 600/$Na_2SO_4$ aqueous two-phase systems for the simple and rapid extraction of a novel bacteriocin were determined to be PEG 600 15%, $Na_2SO_4$ 30%, and NaCl 8%, where the bacteriocin was concentrated in PEG layer.

• Journal of IKEEE
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• v.24 no.1
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• pp.140-146
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• 2020

We investigated light extraction film based on polymer dispersed liquid crystal (PDLC) for application in organic light emitting diodes (OLEDs). At least 30 seconds of direct UV irradiation process for curing PDLC film on a bottom-emitting OLEDs was successfully achieved without damage on the intrinsic properties of the OLED. We demonstrated that high haze and transmittance can be tuned simultaneously by controlling the UV curing time. By adding PDLC as an external layer without any additional treatment, the light scattering and extraction is increased. Consequently, a PDLC scattering film with 89.8% and 59.9 of total transmittance and haze respectively, achieved about 16% of light intensity enhancement from integrating sphere measurement.

• Korean Journal of Medicinal Crop Science
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• v.17 no.6
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• pp.434-438
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• 2009

For the development of a new antidementia functional food or alternative drug using agricultural products, Job's tears (Coix lachrymajobi L.), which shows high acetylcholinesterase (AChE) inhibitory activity (55.1%) was selected and the extraction conditions of AChE inhibitor were optimized. AChE inhibitor of Job's tears was maximally extracted when it was treated with 60% methanol at $40^{\circ}C$ for 6 h. The AChE inhibitor of the methanol extracts was partially purified by systematic solvent extraction, thin layer chromatography, silica gel chromatography and reverse-phase HPLC and the partial purified AChE inhibitor with inhibitory activity ($IC_{50}$) of $0.608\;{\mu}g$ was obtained. The partial purified AChE inhibitor was soluble in methanol and hexane, and insoluble in water. Its maximum absorption spectra was 230 nm and also it was stable in the range of $30^{\circ}C$ and $70^{\circ}C$ and pH 4.0-8.0 for 1 h.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.404-406
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• 1996

The objective of this paper is to present a new feature-vector extraction method for the automatic detection and classification of power quality(PQ) disturbances, where FFT, DWT(Discrete Wavelet Transform), and data compression are utilized to extract an appropriate feature vector. In particular, the proposed classifier consists of three parts: i.e., (i) automatic detection of PQ disturbances, where the wavelet transform and signal power estimation method are utilized to detect each disturbance, (ii) feature vector extraction from the detected disturbance, and (iii) automatic classification, where Multi-Layer Perceptron(MLP) is used to classify each disturbance from the corresponding extracted feature vector. To demonstrate the performance and applicability of the proposed classification algorithm, some test results obtained by analyzing 7-class power quality disturbances generated by the EMTP are also provided.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.119-126
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• 2024

Disease caused by the coronavirus (COVID-19) is sweeping the globe. There are numerous methods for identifying this disease using a chest imaging. Computerized Tomography (CT) chest scans are used in this study to detect COVID-19 disease using a pretrain Convolutional Neural Network (CNN) ResNet50. This model is based on image dataset taken from two hospitals and used to identify Covid-19 illnesses. The pre-train CNN (ResNet50) architecture was used for feature extraction, and then fully connected layers were used for classification, yielding 97%, 96%, 96%, 96% for accuracy, precision, recall, and F1-score, respectively. When combining the feature extraction techniques with the Back Propagation Neural Network (BPNN), it produced accuracy, precision, recall, and F1-scores of 92.5%, 83%, 92%, and 87.3%. In our suggested approach, we use a preprocessing phase to improve accuracy. The image was enhanced using the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm, which was followed by cropping the image before feature extraction with ResNet50. Finally, a fully connected layer was added for classification, with results of 99.1%, 98.7%, 99%, 98.8% in terms of accuracy, precision, recall, and F1-score.

• Smart Structures and Systems
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• v.33 no.6
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• pp.385-398
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• 2024

To improve the accuracy of time-frequency analysis (TFA) and instantaneous frequency (IF) extraction of structural dynamic response signals, this paper improves the spline-kernelled chirplet transform, and a new form of modified spline-kernelled chirplet transform (MSCT) based on revised Gaussian window function and energy concentration principle is put forward. The effectiveness of the proposed method is verified by numerical examples of single-component signal, multicomponent signal, single-degree-of-freedom Duffing nonlinear system and two-layer shear frame structure model. Then, a time-varying cable test is designed to collect the acceleration response signals under linear changing tension, and the IF extraction of these signals is performed by using MSCT, which further verifies the effectiveness and accuracy of this method. Through numerical simulation and experimental verification, it is proved that the proposed method can effectively extract the IF of nonlinear structure and time-varying structure.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1347-1355
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• 2019

Deep learning approach based on convolution neural network (CNN) has extensively studied in the field of computer vision. However, periocular feature extraction using CNN was not well studied because it is practically impossible to collect large volume of biometric data. This study uses the ResNet model which was trained with the ImageNet dataset. To overcome the problem of insufficient training data, we focused on the training of multi-layer perception (MLP) having simple structure rather than training the CNN having complex structure. It first extracts features using the pretrained ResNet model and reduces the feature dimension by principle component analysis (PCA), then trains a MLP classifier. Experimental results with the public periocular dataset UBIPr show that the proposed method is effective in person authentication using periocular region. Especially it has the advantage which can be directly applied for other biometric traits.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1224-1230
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• 2007

In this paper, we study the classification of defects at steam generator tube in nuclear power plant using eddy current testing (ECT). We consider 4 defect patterns of SG tube: I-In type, I-Out type, V-In type, and V-Out type. Through numerical analysis program based on finite element modeling, 400 ECT signals are generated by varying width and depth of each defect type. In order to improve the classification performance, we propose new feature extraction technique. After extracting new features from the generated ECT signals, multi-layer perceptron is used to classify the defect patterns. Through the computer simulation study, it is shown that the proposed method achieves 100% classification success rate while the previous method yields 91% success rate.

• Microbiology and Biotechnology Letters
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• v.23 no.2
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• pp.229-235
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• 1995

The surface tension-decreasing biosurfactant was purified from Rhodotorula muciloginosa G-1. The purification procedure was the solvent extraction of culture broth. To ensure complete extraction, the sample was extracted twice with equal volume of ethylacetate. The crude solution was washed with n-hexane to remove unconsumed soybean oil. The crude sample of biosurfactant was applied to Silica gel column chromatography equilibrated with chloroform, and eluted with chloroform : methanol gradient. Serveral solvent system was used to developed the thin layer chromatography (TLC). The purified biosurfactant sample gave one spot (Rf 0.78). It was estimated that biosurfactant was glycolipid about having M.W.1,500 with standard of polyethyleneglycol by Sephadex LH-20 column chromatography.