• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.223-233
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• 2017

The railway turnout system is one of the most important systems that set train routes. Turnout system integrity should be guaranteed for robust train operation. To diagnose the turnout system status, LVDT and accelerometers are installed on a turnout system in a high speed line. The LVDT and accelerometers produce signals containing physical meaning of the turnout systems. The LVDT produces the displacement of the rail gauge and vibration when point moving or a train passes on turnout systems and the accelerometer produces impact forces induced by wheel sets. We performed data extraction from the measured signals and parameterized the extracted signals into meaningful quantities. The parameters are used for classifying whether the turnout status is normal. We proposed two methods for the classification, one uses probabilistic distribution and the other artificial neuron networks. The probabilistic distribution is used for the parameter being classified by the quantities and the artificial neuron networks for the form classification. Finally, we show how to learn the normal status of a turnout system.

• Journal of the Korean Chemical Society
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• v.11 no.4
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• pp.132-137
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• 1967

A spectrophotometric method for the determination of major impurities, such as iron and copper, in high purity of antimony with 8-hydroxyquinoline (oxine) has been studied. The iron-oxinate is stable at the pH range 5.0 to 5.7, and the copper-oxinate at the pH range 3.5 to 4.0. To mask antimony in sulfuric acid solution of sample, author has investigated the effect of tartaric acid on antimony, and found that 10ml of 0.5M tartaric acid solution could mask up to 600mg of antimony. The absorbance of iron-oxinate was measured at 580$m{\mu}$ and iron could be determined, but it is necessary for copper-oxinate to measure at 410 and 580m respectively after removing heavy metals other than copper by back extraction with 15% solution of sodium hydroxide, and copper could be determined by making a correction for the amounts of iron present. Up to 150 ${\mu}g$ of iron (0.005-0.03%), and 100 ${\mu}g$ of copper (0.005-0.016%), in 500mg of antimony could be determined.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.164-169
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• 2009

This paper proposes a road detection method using BP(Back-Propagation) neural network based on texture information of the each candidate road region segmented for satellite images. To segment the candidate road regions, the histogram-based binarization method proposed by N.Otsu is firstly performed and the neighboring regions surrounding road regions are then removed. And after extracting the principal color using the histogram of the segmented foreground, the candidate road regions are classified into the regions within ${\pm}25$ of the principal color. Finally, the road regions are segmented using BP neural network based on texture information of the candidate regions. The texture information in this paper is calculated using co-occurrence matrix and is used as an input data of the BP neural network. The proposed method is based on the fact that the road has the constant intensity and shape. The experiment demonstrated the validity of the proposed method and showed 90% detection accuracy for the various images.

• Bulletin of the Korean Chemical Society
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• v.23 no.8
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• pp.1139-1143
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• 2002

Analysis of lysophosphatidic acids (LPAs) is of clinical importance as they can serve a potential marker for ovarian and other gynecological cancers and obesity. It is critically important to develop a highly sensitive and specific method for the early detection of gynecological cancers to improve the overall outcome of this disease. We have established a novel quantification method of LPAs in human plasma by negative ionization tandem mass spectrometry (MS-MS) using multiple reaction monitoring (MRM) mode without the conventional TLC step. Protein-bound lipids, LPAs in plasma were extracted with methanol : chloroform (2:1) containing LPA C14:0 as an internal standard under acidic condition. Following back extraction with chloroform and water, the centrifuged lower phase was evaporated and reconstituted in methanol. The reconstituted solution was directly injected into electrospray source of MS/MS. For MRM mode, Q1 ions selected were m/z 409, 433, 435, 437 and 457 which corresponds to molecular mass [M-H]- of C16:0, C18:2, C18:1, C18:0 and C20:4 LPA, respectively. Q2 ions selected for MRM were m/z 79, phosphoryl product. Using MS/MS with MRM mode, all the species of LPAs were completely separated from plasma matrix without severe interferences. This method allowed simultaneous detection and quantification of different species of LPAs in a plasma over a linear dynamic range of 0.01-25 ㎛olL-1 . The detection limit of the method was 0.3 pmol/mL, with a correlation coefficient of 0.9983 in most LPAs analyzed. When applied to the plasmas of normal and gynecological cancer patients, this new method differentiated two different groups by way of total LPA level.

• The Korean Journal of Community Living Science
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• v.22 no.4
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• pp.615-621
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• 2011

This study was conducted to evaluate of the protection efficiency in each part of developed pesticide-proof clothes by repeated washings. We investigated the effect of repeated laundering on mechanical properties of pesticide-proof clothes (not washed vs 5 times washed). We also examined pesticide infiltration rate into the pesticide-proof clothes by repeated laundering. The patches(TCL paper, surface area 50cm2)were attached to the inside of pesticide-proof clothes(head, chest, right upper-arm, right forearm, left thigh, left calf, back) which subjects had dressed in during pesticide spraying. The patches were detached from working clothes after work. For the extraction of pesticide in pesticide-proof clothes, sonication was applied for 30 min with methanol. The gas chromatography/mass spectrometry (GC/MS) was applied to identify the pesticide component. The results of this study are as follows: The force strength, water-vapour resistance and surface wetting resistance of pesticide-proof clothes decreased 5 times more in washed clothes. The concentration of pesticide was the highest in the head area of pesticide-proof clothes. In seven parts of TLC paper attached to the pesticide proof clothes, the concentration of pesticide was higher in the left thigh. The penetration part and concentration of pesticide increased as washing was repeated. Therefore the conclusion which can be drawn from this study is this: protection efficiency of pesticide-proof clothes decrease by repeated washings.

• Journal of International Academy of Physical Therapy Research
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• v.11 no.2
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• pp.2096-2101
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• 2020

Background: The effect of mobilization on lumbar back pain has been fully described in several clinical aspects, but evidence for muscle strength would be still less clear. Objective: To assess the effect of lumbar mobilization on lower limb strength in healthy individuals. Methods and Analysis: Healthy people aged 18-65 will be included regardless of race or sex. Original peer-reviewed primary reporting randomized controlled trials (RCTs) will be included. Electronic databases, such as MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Web of Science, Pedro, CINAHL, ClinicalTrials.gov will be searched from inception until July 30. Only studies published in English will be included in this review. Two reviewers will complete the screening for eligibility independently, and the other two reviewers will also complete the risks of data extraction and bias assessment independently. Lower Limb strength will be assessed as primary outcome, and particular intervention or participant characteristics will be assessed as the secondary outcomes. Meta-analysis will be conducted using Review Manager 5.3.3, and evidence level will be assessed using the method for Grading of Recommendations Assessment, Development and Evaluation. Outcomes will be presented as the weighted mean difference or standardized mean difference with 95% CI. If I² ≤ 50%, P>.1, the fixed effect model will be used, otherwise, random-effects model will be used. Ethics and dissemination: This review might not be necessary ethical approval because it does not require individual patient's data; these findings will be published in conference presentations or peer-reviewed journal articles. PROSPERO registration number: CRD42020150144.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.267-274
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• 2017

Recently, there is a new trend about internet of things (IoT) such as shops with smart mirror around the fashion and beauty industry. Since smart mirror can display a content through a monitor which is attached to back of mirror system while looking through a mirror, it can be applied to various industries such as fashion, beauty and health care. This paper proposes an efficient learning system requiring no assistance from others for the hearing deaf who atrophy verbal skill and are inaccurate in pronunciation by using features of smart mirror. Also, this system proposes an efficient and simple lip reading method which can be applied to an embedded system and improves a learning efficiency by employing previously verified pronunciation training data.

• Archives of Pharmacal Research
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• v.19 no.6
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• pp.529-534
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• 1996

A high-performance liquid chromatographic (HPLC) assay has been developed for the determination of ketorolac in human serum using a new extraction method with a good recovery. Human serum samples (1.0 ml) spiked with known concentrations of ketorolac tromethamine and 10${\mu}g$ of ketoprofen as the internal standard (IS) were acidified with 200${\mu}l$ of 1 N HCl and extracted with 7 ml of n-hexane-ether (7:3 v/v). Extracts were centrifuged and organic layer was back-extracted with 400${\mu}l$ of 0.1% tromethamine solution. Twenty .mu.l of centrifuged aqueous layer was injected onto a reversed-phase octyl column and eluted with a mixture of acetonitrile, water, methanol, and triethylamine [35:55:10:0.1 (v/v), pH 3.0] at a flow rate of 1.0 ml/min. Ultraviolet detection of ketorolac and IS was carried out at 300 nm. The calibration curve obtained using peak area ratios showed a good linearity (in concentration range 10-150 ng/ml $r^2$=O.9944; in range 50-2000 ng/ml, r$^{2}$=0.9998). The mean intra-day accuracy and precision for this HPLC method were found to be 3.6 and 3.7%, respectively. The mean inter-day accuracy and precision were found to be 4.0 and 3.7%, respectively, in the concentration range 50-2000 ng/ml. The recovery of ketorolac from serum was 92.0 $({\pm}5.7)$ % at the concentration of 100 ng/ml. This method proved to be readily applicable to the assay of ketorolac in human serum.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.1 s.116
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• pp.96-104
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• 2007

Currently, there is a lack of suitable prediction model and measurement data for vegetation loss. So in this paper, vegetation loss measurement has been performed for seven different tree-species, including dawn-redwood tree, plane tree, pine tree and hymalaya cedar in the frequency range of $1.0{\sim}6.0\;GHz$, for the two years, from 2005 to 2006 years. And then, extraction and revision for the proposed RET model input parameters in ITU-R P.833 has been performed. The key results of measurement and RET modeling has been presented in this paper. The results of this study have been adapted for ITU-R recommendation at the ITU-R meeting in 2005 and 2006.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.54-61
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• 2001

A software package to classify acoustic emission (AE) signals using the wavelet transform and the neural network was developed Both of the continuous and the discrete wavelet transforms are considered, and the error back-propagation neural network is adopted as m artificial neural network algorithm. The signals acquired during the 3-point bending test of specimens which have artificial defects on weld zone are used for the classification of the defects. Features are extracted from the time-frequency plane which is the result of the wavelet transform of signals, and the neural network classifier is tamed using the extracted features to classify the signals. It has been shown that the developed software package is useful to classify AE signals. The difference between the classification results by the continuous and the discrete wavelet transforms is also discussed.