• The Korea Journal of Herbology
• /
• v.29 no.1
• /
• pp.13-18
• /
• 2014

Objectives : Iridoid glycoside, swertiamarin is a well known bioactive component found in Swertia japonica Makino (SJ). In this study, we tried to optimize a suitable method which would extract swertiamarin effectively. Methods : Extraction of SJ was carried out by various conditions of time (5 - 60 min), temperature ($30-70^{\circ}C$), solvent (from non-polar to polar), and ratio of solvnet / sample (10 : 1 - 40 : 1) using ultrasonic extractor. Swertiamarin in SJ extracts was quantified by high performance liquid chromatography - Phtodiode array detector (HPLC-PDA) using C18 column and the analytical procedure was validated by evaluation of specificity, range, linearity, accuracy (recovery), precision (intra- and inter day variability), limit of detection (LOD), and limit of quantification (LOQ). Results : An efficient extraction condition for swertiamarin in SJ was optimized using sonicator extraction (temperature $40^{\circ}C$, solvent 20% methanol, solvent / sample (20 : 1), and time 10 min. Analytical procedure was optimized by HPLC-PDA using isocratic solvent system of acetonitrile and water (9 : 91), and the method was validated in regard to linearity (correlation coefficient, $R^2$ > 0.9999), range ($50-1000{\mu}g/mL$), intra- and inter-precision (RSD < 5.0 %), and recovery (99 -103 %). LOD and LOQ were 0.051 and $0.155{\mu}g/mL$, respectively. Conclusion : An optimized method of extraction for swertiamarin in SJ was established through conditions of diverse extraction and the validation result indicated that the method is suited for the determination of swertiamarin in SJ.

• The Journal of the Korean dental association
• /
• v.41 no.6 s.409
• /
• pp.442-449
• /
• 2003

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.488-491
• /
• 1987

In this paper. a heuristic multi-thresholding algorithm is proposed to extract objects from background. Specifically the proposed algorithm finds out multi valleys from gray level histogram automatically and non-recursively. Some experimental result for various types of image. are presented, to show the effectiveness of the proposed algorithm.

• Proceedings of the Korean Radioactive Waste Society Conference
• /
• 2018.11a
• /
• pp.392-393
• /
• 2018

• Economic and Environmental Geology
• /
• v.46 no.5
• /
• pp.425-444
• /
• 2013

This study was carried out in order to determine the remediation of total petroleum hydrocarbons (TPHs), trichloroethylene (TCE), perchloroethylene (PCE), benzene, toluene, ethylbenzene and xylenes (BTEX) compounds for non-aqueous phase liquids (NAPLs) using in-situ air sparging (IAS) / vapor extraction (VE) with the marine sediments of Mandol, Hajeon, Sangam and Busan, South Korea. Surface sediment of Mandol area had sand characteristics (average particle size, 1.789 ${\Phi}$), and sandy silt characteristics (average particle size, 5.503 ${\Phi}$), respectively. Sangam surface sediment had silt characteristics (average particle size, 5.835 ${\Phi}$). Sediment characteristics before experiment in the Busan area showed clay characteristics (average particle size, 8.528 ${\Phi}$). TPHs level in the B1 column of Mandol, Hajeon, Sangam, and Busan sediments were 2,459, 6,712, 4,348, and 14,279 ppm. B2 (3 L/min) to B5 (5 L/min) columns reduced 99.5% to 100.0% of TCE and 93.2% to 100.0% of PCE. Removal rates of TCE, PCE, and BTEX are closely correlated (0.90-0.99) with particle sizes and organic carbon concentrations. However, TPHs (0.76) and benzene (0.71) showed the poorer but moderate correlations with the same parameters.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.4 s.310
• /
• pp.46-54
• /
• 2006

Recently, the important of a personal identification is increasing according to expansion using each on-line commercial transaction and personal ID-card. Although a personal ID-card embedded RFID(Radio Frequency Identification) tag is gradually increased, the way for a person's identification is deficiency. So we need automatic methods. Because RFID tag is vary small storage capacity of memory, it needs effective feature extraction method to store personal biometrics information. We need new recognition method to compare each feature. In this paper, we studied the face verification system using Hippocampal neuron modeling algorithm which can remodel the hippocampal neuron as a principle of a man's brain in engineering, then it can learn the feature vector of the face images very fast. and construct the optimized feature each image. The system is composed of two parts mainly. One is feature extraction using NMF(Non-negative Matrix Factorization) and LDA(Linear Discriminants Analysis) mixture algorithm and the other is hippocampal neuron modeling and recognition simulation experiments confirm the each recognition rate, that are face changes, pose changes and low-level quality image. The results of experiments, we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to the existing method.

• Resources Recycling
• /
• v.28 no.2
• /
• pp.46-53
• /
• 2019

In this study, the extraction and reduction behavior of platinum group metals in a non-aqueous solvent based on ionic liquids was investigated in order to confirm a new extraction technology of platinum group metals. Platinum was selectively extracted using an ionic liquid $[C_4mim]PF_6$ from a mixed solution of $PdCl_2$, $PtCl_4$ and $RhCl_3$ dissolved with concentration ratio of 10:1:0.5 M. After stripping of the metals by 1 M $HNO_3$ solution, the platinum was preferentially reduced by aqueous electrolysis on gold electrode at -0.8 V (vs. Pt-QRE). The residual palladium and rhodium were transferred to ionic liquid of $[C_4mim]Cl$. The metallic palladium and rhodium could be sequentially reduced on gold and STS304 as working electrodes by non-aqueous electrolysis, respectively.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2010.11a
• /
• pp.184-187
• /
• 2010

본 논문에서는 움직임 추정(Motion Estimation, ME), 색상 라벨링(Labeling) 그리고 Non-Local means 필터 등을 이용하여 2D 영상을 3D 입체 영상으로 변환하는 기법을 제안한다. 제안하는 기법에서는 프레임 간의 움직임 추정 방법을 사용하여 물체의 움직임 벡터를 추출하며 색상 라벨링 작업을 통해 세밀한 객체를 추출한다. 객체를 추출한 후 영상을 이동시켜서 우영상을 생성한다. 우 영상을 생성하는 과정에서 채워지지 않은 화소들이 발생하는데 전체 화소의 상관도를 고려하는 Non-local means 필터를 사용하여 이 부분을 처리한다. 생성된 우 영상과 원본 영상인 좌 영상으로 비월주사(interlace)하여 최종 3D 입체 영상을 생성한다.

• International Journal of Contents
• /
• v.4 no.2
• /
• pp.24-28
• /
• 2008

In this paper, we propose a new approach for content-based video retrieval using non-parametric based motion classification in the shot-based video indexing structure. Our system proposed in this paper has supported the real-time video retrieval using spatio-temporal feature comparison by measuring the similarity between visual features and between motion features, respectively, after extracting representative frame and non-parametric motion information from shot-based video clips segmented by scene change detection method. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. To obtain visual feature in representative frame, we use the edge-based spatial descriptor. Experimental results show that our approach is superior to conventional methods with regard to the performance for video indexing and retrieval.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.96-99
• /
• 2003

Land cover map is a typical GIS database which shows the Earth's physical surface differentiated by standardized homogeneous land cover types. Satellite images acquired by Landsat TM were primarily used to produce a land cover map of 7 land cover classes; however, it now becomes to produce a more accurate land cover classification dataset of 23 classes thanks to higher resolution satellite images, such as SPOT-5 and IKONOS. The use of the newly produced high resolution land cover map of 23 classes for such activities to estimate non-point sources of pollution like water pollution modeling and atmospheric dispersion modeling is expected to result a higher level of accuracy and validity in various environmental monitoring results. The estimation of pollution from non-point sources using GIS-based modeling with land cover dataset shows fairly accurate and consistent results.