• Clinical and Experimental Pediatrics
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• v.53 no.3
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• pp.397-407
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• 2010

Purpose : The F9 gene is known to be the causative gene for hemophilia B, but unfortunately the detection rate for restriction fragment length polymorphism-based linkage analysis is only 55.6%. Direct DNA sequencing can detect 98% of mutations, but this alternative procedure is very costly. Here, we conducted multiplex polymerase chain reactions (PCRs) and conformation sensitive gel electrophoresis (CSGE) to perform a screened DNA sequencing for the F9 gene, and we compared the results with direct sequencing in terms of accuracy, cost, simplicity, and time consumption. Methods : A total of 27 unrelated hemophilia B patients were enrolled. Direct DNA sequencing was performed for 27 patients by a separate institute, and multiplex PCR-CSGE screened sequencing was done in our laboratory. Results of the direct DNA sequencing were used as a reference, to which the results of the multiplex PCR-CSGE screened sequencing were compared. For the patients whose mutation was not detected by the 2 methods, multiplex ligation-dependent probe amplification (MLPA) was conducted. Results : With direct sequencing, the mutations could be identified from 26 patients (96.3%), whereas for multiplex PCRCSGE screened sequencing, the mutations could be detected in 23 (85.2%). One patient's mutation was identified by MLPA. A total of 21 different mutations were found among the 27 patients. Conclusion : Multiplex PCR-CSGE screened DNA sequencing detected 88.9% of mutations and reduced costs by 55.7% compared with direct DNA sequencing. However, it was more labor-intensive and time-consuming.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.3
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• pp.95-100
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• 2009

Fine fuel moisture code (FFMC), a main component of forest fire weather index(FWI) in the Canadian forest fire danger rating system(CFFDRS), indicated a probability of ignition through expecting a dryness of fine fuels. According to this code, a rising of temperature and wind velocity, a decreasing of precipitation and decline of humidity in a weather condition showed a rising of a danger rate for the forest fire. In this study, we analyzed a weather condition during 5 years in Kangwon province, calculated a FFMC and examined an application of FFMC. Very low humidity and little precipitation was a characteristic during spring and fall fire season in Kangwon province. 75% of forest fires during 5 years occurred in this season and especially 90% of forest fire during fire season occurred in spring. For developing of the prediction model for a forest fire occurrence probability, we used a logistic regression function with forest fire occurrence data and classified mean FFMC during 10 days. Accuracy of a developed model was 63.6%. To improve this model, we need to deal with more meteorological data during overall seasons and to associate a meteorological condition with a forest fire occurrence with more research results.

• Journal of Biomedical Engineering Research
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• v.34 no.1
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• pp.8-13
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• 2013

Persons with sensorineural hearing impairment have troubles in hearing at noisy environments because of their deteriorated hearing levels and low-spectral resolution of the auditory system and therefore, they use hearing aids to compensate weakened hearing abilities. Various algorithms for hearing loss compensation and environmental noise reduction have been implemented in the hearing aid; however, the performance of these algorithms vary in accordance with external sound situations and therefore, it is important to tune the operation of the hearing aid appropriately in accordance with a wide variety of sound situations. In this study, a sound classification algorithm that can be applied to the hearing aid was suggested. The proposed algorithm can classify the different types of speech situations into four categories: 1) speech-only, 2) noise-only, 3) speech-in-noise, and 4) music-only. The proposed classification algorithm consists of two sub-parts: a feature extractor and a speech situation classifier. The former extracts seven characteristic features - short time energy and zero crossing rate in the time domain; spectral centroid, spectral flux and spectral roll-off in the frequency domain; mel frequency cepstral coefficients and power values of mel bands - from the recent input signals of two microphones, and the latter classifies the current speech situation. The experimental results showed that the proposed algorithm could classify the kinds of speech situations with an accuracy of over 94.4%. Based on these results, we believe that the proposed algorithm can be applied to the hearing aid to improve speech intelligibility in noisy environments.

• Journal of Korean Society of Environmental Engineers
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• v.37 no.5
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• pp.262-268
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• 2015

This study established an analytical method to simultaneously determine six organophosphorous pesticides [methyldemetone-S, diazinon, fenitrothion, parathion, phentoate, and O-ethyl O-(4-nitrophenyl) phenylphosphonothioate (EPN)] and carbaryl in water using a gas chromatography/mass spectrometry (GC/MS) system coupled with on-line micro extraction by packed sorbent (MEPS) and programmed temperature vaporizer (PTV) injector. Polystyrene divinylbenzene (PDVB) was used as a sorbent of MEPS. The effects of elution solvents, pH, elution volume and draw-eject cycles of samples on sample pretreatment process were investigated. Also, quality assurance and quality control (QA/QC) and the recovery of the pesticides in environmental samples were evaluated. The elution was performed using $30{\mu}L$ of a mixed solvent (acetone : dichloromethane = 80 : 20 (v/v)). Sample pretreatment processes were optimized with seven cycles of draw-eject of sample (1 mL) spiking an internal standard and sulfuric acid. At lower pH, the analytical sensitivity of diazinon decreased, but that of carbaryl increased. The method detection limit and the limit of quantification for this method were 0.02~0.18 and $0.08{\sim}0.59{\mu}g/L$, respectively. The method precision and accuracy were 1.5~11.5% and 83.3~129.8%, respectively, at concentrations of $0.5{\sim}5.0{\mu}g/L$. The recovery rates for all the pesticides except carbaryl in various environmental samples ranged 75.7~129.3%. The recovery rate of carbaryl in effluent sample was over 200% whereas carbaryl in drinking water, groundwater, and river water were in the acceptable range.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.786-792
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• 2010

This paper presents a real-time lane detection method which can accurately find the lane-mark boundaries in complex road environment. Unlike many existing methods that pay much attention on the post-processing stage to fit lane-mark position among a great deal of outliers, the proposed method aims at removing those outliers as much as possible at feature extraction stage, so that the searching space at post-processing stage can be greatly reduced. To achieve this goal, a grid-based morphology operation is firstly used to generate the regions of interest (ROI) dynamically, in which a directional edge-linking algorithm with directional edge-gap closing is proposed to link edge-pixels into edge-links which lie in the valid directions, these directional edge-links are then grouped into pairs by checking the valid lane-mark width at certain height of the image. Finally, lane-mark colors are checked inside edge-link pairs in the YUV color space, and lane-mark types are estimated employing a Bayesian probability model. Experimental results show that the proposed method is effective in identifying lane-mark edges among heavy clutter edges in complex road environment, and the whole algorithm can achieve an accuracy rate around 92% at an average speed of 10ms/frame at the image size of $320{\times}240$.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.11
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• pp.1682-1686
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• 2015

This study was conducted to establish an HPLC analysis method for determination of marker compounds as part of materials standardization for development of health functional food materials from pear pomace. The quantitative determination method of caffeic acid and chlorogenic acid as marker compounds of pear pomace extract (PPE) was optimized by HPLC analysis using a C18 column ($5{\times}250mm$, $5{\mu}m$) with a 0.2% elution gradient of acetic acid and methanol as the mobile phase at a flow rate of 0.8 mL/min and detection wavelength of 330 nm. The HPLC/UV method was applied successfully to the quantification of marker compounds in PPE after validation of the method with linearity, accuracy, and precision. The method showed high linearity of the calibration curve with a coefficient of correlation ($R^2$) of 0.9999, and limit of detection and limit of quantification were $1.14{\mu}g/mL$ (caffeic acid) and $1.61{\mu}g/mL$ (chlorogenic acid) as well as $4.9{\mu}g/mL$ (caffeic acid) and $4.9{\mu}g/mL$ (chlorogenic acid), respectively. Relative standard deviation values from intra- and inter-day precision were less than 3.1% (caffeic acid) and 4.0% (chlorogenic acid), respectively. Recovery rates of caffeic acid and chlorogenic acid at 12.5, 25, and $50{\mu}g/mL$ were 93.66~106.32% and 97.33~105.68%, respectively. An optimized method for extraction of caffeic acid and chlorogenic acid in PPE was established through diverse extraction conditions, and the validation indicated that the method is very useful for evaluation of marker compounds in PPE to develop a health functional food material.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.21-32
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• 2006

The license plate recognition (LPR) unit consists of the following core components: plate region segmentation, individual character extraction, and character recognition. Out of the above three components, accuracy in the performance of plate region segmentation determines the overall recognition rate of the LPR unit. This paper proposes an algorithm for segmenting the license plate region on the front or rear of a vehicle in a fast and accurate manner. In the case of the proposed algorithm images are captured on the spot where unmanned monitoring of illegal parking and stowage is performed with a variety of roadway environments taken into account. As a means of enhancing the segmentation performance of the on-the-spot-captured images of license plate regions, the proposed algorithm uses a mathematical model for license plate colors to convert color images into digital data. In addition, this algorithm uses Gaussian smoothing and double threshold to eliminate image noises, one-pass boundary tracing to do region labeling, and MBR to determine license plate region candidates and extract individual characters from the determined license plate region candidates, thereby segmenting the license plate region on the front or rear of a vehicle through a verification process. This study contributed to addressing the inability of conventional techniques to segment the license plate region on the front or rear of a vehicle where the frame of the license plate is damaged, through processing images in a real-time manner, thereby allowing for the practical application of the proposed algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.137-143
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• 2015

A delay-line type time-to-digital converter (TDC) implemented in a field-programmable gate array (FPGA) is most widely owing due to its simple structure and high conversion rate. However, the delay-line type TDC suffers from nonlinearity error caused by the long delay-line because its time interval measurement range is determined by the length of the used delay line. In this study, a new TDC structure with a shorter delay line by taking a pulse train as an input is proposed for improved time accuracy and efficient use of resources. The proposed TDC utilizes a pulse-train with four transitions and a transition state detector that identifies the used transition among four transitions and prevents the meta-stable state without a synchronizer. With 72 delay cells, the measured resolution and maximum non-linearity were 20.53 ps, and 1.46 LSB, respectively, and the time interval measurement range was 5070 ps which was enhanced by approximately 343 % compared to the conventional delay-line type TDC.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.126-134
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• 2015

A sleep disorder is being recognized as one of the major health issues related to high levels of stress. At the same time, interests about quality of sleep are rapidly increasing. However, diagnosing sleep disorder is not a simple task because patients should undergo polysomnography test, which requires a long time and high cost. To solve this problem, an accelerometer embedded wrist-worn device is being considered as a simple and low cost solution. However, conventional methods determine a state of user to "sleep" or "wake" according to whether values of individual section's accelerometer data exceed a certain threshold or not. As a result, a high miss-classification rate is observed due to user's intermittent movements while sleeping and tiny movements while awake. In this paper, we propose a novel method that resolves the above problems by employing a dynamic classifier which evaluates a similarity between the neighboring data scores obtained from SVM classifier. A performance of the proposed method is evaluated using 50 data sets and its superiority is verified by achieving 88.9% accuracy, 88.9% sensitivity, and 88.5% specificity.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.761-771
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• 2016

The GloSea5 (Global Seasonal forecasting system version 5) is provided and operated by the KMA (Korea Meteorological Administration). GloSea5 provides Forecast (FCST) and Hindcast (HCST) data and its horizontal resolution is about 60km ($0.83^{\circ}{\times}0.56^{\circ}$) in the mid-latitudes. In order to use this data in watershed-scale water management, GloSea5 needs spatial-temporal downscaling. As such, statistical downscaling was used to correct for systematic biases of variables and to improve data reliability. HCST data is provided in ensemble format, and the highest statistical correlation ($R^2=0.60$, RMSE = 88.92, NSE = 0.57) of ensemble precipitation was reported for the Yongdam Dam watershed on the #6 grid. Additionally, the original GloSea5 (600.1 mm) showed the greatest difference (-26.5%) compared to observations (816.1 mm) during the summer flood season. However, downscaled GloSea5 was shown to have only a -3.1% error rate. Most of the underestimated results corresponded to precipitation levels during the flood season and the downscaled GloSea5 showed important results of restoration in precipitation levels. Per the analysis results of spatial autocorrelation using seasonal Moran's I, the spatial distribution was shown to be statistically significant. These results can improve the uncertainty of original GloSea5 and substantiate its spatial-temporal accuracy and validity. The spatial-temporal reproducibility assessment will play a very important role as basic data for watershed-scale water management.