• Title/Summary/Keyword: error detection

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Determination of secondary aliphatic amines in surface and tap waters as benzenesulfonamide derivatives using GC-MS (Benzenesulfonamide 유도체로 GC-MS를 사용한 지표수 및 수돗물 중 2차 지방족 아민의 분석)

  • Park, Sunyoung;Jung, Sungjin;Kim, Yunjeong;Kim, Hekap
    • Analytical Science and Technology
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    • v.31 no.2
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    • pp.96-105
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    • 2018
  • This study aimed to improve the method for detecting eight secondary aliphatic amines (SAAs), so as to measure their concentrations in fresh water and tap water samples. NaOH (8 mL, 10 M) and benzenesulfonyl chloride (2 mL) were added to a water sample (200 mL), and the mixture was stirred at $80^{\circ}C$ for 30 min. An additional NaOH solution (10 mL) was added and the stirring was continued for another 30 min. The pH of the cooled mixture was adjusted to 5.5-6.0 by adding HCl (35 %), and the SAAs were extracted using dichloromethane (50 mL). This extraction was repeated once. The extract was then washed with $NaHCO_3$ (15 mL, 0.05 M) and dried over $Na_2SO_4$ (4 g). The extract was finally concentrated to 0.1 mL, of which $1{\mu}L$ was analyzed for SAAs by GC-MS. The linearity of the spike calibration curves was high ($r^2=0.9969-0.9996$). The detection limits of the method ranged from 0.01 to $0.20{\mu}g/L$, and its repeatability and reproducibility (expressed as relative standard deviation) were both less than 10 % (6.6-9.4 %). Its accuracy (measured in percentage error) ranged between 2.4 % and 6.1 %. The established method was applied to the analysis of five surface water and 82 tap water samples. Dimethylamine was the only SAA detected in all the water samples, and its average concentration was $0.79{\mu}g/L$ (range: $0.20-2.54{\mu}g/L$). Therefore, this study improved the analytical method for SAAs in surface water and tap water, and the regional and seasonal concentration distributions were obtained.

PCA­based Waveform Classification of Rabbit Retinal Ganglion Cell Activity (주성분분석을 이용한 토끼 망막 신경절세포의 활동전위 파형 분류)

  • 진계환;조현숙;이태수;구용숙
    • Progress in Medical Physics
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    • v.14 no.4
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    • pp.211-217
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    • 2003
  • The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

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The Role of T1-201 Brain SPECT in the Differentiating Recurrent Tumor from Radiation Necrosis (뇌종양의 재발과 방사선 괴사의 감별을 위한 탈륨 SPECT의 역할)

  • Won, Kyoung-Sook;Ryu, Jin-Sook;Moon, Dae-Hyuk;Yang, Seoung-Oh;Lee, Hee-Kyung;Lee, Jung-Kyo;Kwun, Byung-Duk
    • The Korean Journal of Nuclear Medicine
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    • v.30 no.4
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    • pp.476-483
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    • 1996
  • Following radiation therapy for brain tumors, patients often have clinical deterioration due to either radiation necrosis or recurrent tumor progression in the treatment field. The distinction between these entities is important but difficult clinically or even with CT or MRI. T1-201 has been known to accumulate in various tumors and be useful to grade, predict prognosis or detect recurrence of glioma. The aim of this study was to evaluate the usefulness of T1-201 SPECT in the differentiation of recurrent tumor from radiation necrosis. Of 67 patients who did T1-201 brain SPECT imaging with clinically suspected recurrent tumor or radiation necrosis, 20 patients underwent histopathological examination and constituted the study population. T1-201 uptake indices on T1-201 brain SPECT imaging rrere calculated and correlated with histopathological diagnosis. Of 20 patients, 15 were histopathologically confirmed as recurrent original tumor or malignant transformation of benign tumor and 5 were diagnosed as radiation necrosis. On T1-201 SPECT, 18 of 20 had T1-201 index above 2.5 which was regarded as positive indicator for the presence of tumor. Seventeen cases showed concordance, which consisted of 15 true positive and 2 true negative. Discordant 3 cases were all false positive. There was no case of false negative. The sensitivity, specificity, positive and negative predictive value of T1-201 SPECT were 100%, 40%, 83% and 100%. In conclusion, T1-201 brain SPECT is a sensitive diagnostic test in the detection of recurrent tumor following radiation therapy and is useful in the differentiation of recurrent tumor from radiation necrosis. Relatively low specificity should be evaluated further in larger number of patients in consideration of sampling error and referral bias for pathologic examination.

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A Study on GPU-based Iterative ML-EM Reconstruction Algorithm for Emission Computed Tomographic Imaging Systems (방출단층촬영 시스템을 위한 GPU 기반 반복적 기댓값 최대화 재구성 알고리즘 연구)

  • Ha, Woo-Seok;Kim, Soo-Mee;Park, Min-Jae;Lee, Dong-Soo;Lee, Jae-Sung
    • Nuclear Medicine and Molecular Imaging
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    • v.43 no.5
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    • pp.459-467
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    • 2009
  • Purpose: The maximum likelihood-expectation maximization (ML-EM) is the statistical reconstruction algorithm derived from probabilistic model of the emission and detection processes. Although the ML-EM has many advantages in accuracy and utility, the use of the ML-EM is limited due to the computational burden of iterating processing on a CPU (central processing unit). In this study, we developed a parallel computing technique on GPU (graphic processing unit) for ML-EM algorithm. Materials and Methods: Using Geforce 9800 GTX+ graphic card and CUDA (compute unified device architecture) the projection and backprojection in ML-EM algorithm were parallelized by NVIDIA's technology. The time delay on computations for projection, errors between measured and estimated data and backprojection in an iteration were measured. Total time included the latency in data transmission between RAM and GPU memory. Results: The total computation time of the CPU- and GPU-based ML-EM with 32 iterations were 3.83 and 0.26 see, respectively. In this case, the computing speed was improved about 15 times on GPU. When the number of iterations increased into 1024, the CPU- and GPU-based computing took totally 18 min and 8 see, respectively. The improvement was about 135 times and was caused by delay on CPU-based computing after certain iterations. On the other hand, the GPU-based computation provided very small variation on time delay per iteration due to use of shared memory. Conclusion: The GPU-based parallel computation for ML-EM improved significantly the computing speed and stability. The developed GPU-based ML-EM algorithm could be easily modified for some other imaging geometries.

Treatment of Reproductive Dysfunctions and Reproductive Monitoring Using Ultrasonography in Dairy Cow (초음파 검사에 의한 젖소 번식 검진과 번식 장애 치료)

  • Lim, W.H.;Oh, K.S.;Seo, G.J.;Hwang, S.S.;Kim, B.S.;Bae, C.S.;Kim, S.H.;Kim, J.T.;Park, I.C.;Park, S.G.;Son, C.H.
    • Journal of Embryo Transfer
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    • v.21 no.3
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    • pp.217-223
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    • 2006
  • This study was carried out principally to obtain the basic data for the improvement of the reproductive performance and production using plasma progesterone assay and ultrasonography in dairy cow. The results obtained from this studies were as follows. The results of reproductive examination in 85,983 cows were ovarian diseases 40,399 (47.0%), uterine diseases 11,912 (13.9%), pregnancy or pregnant failures 26,587 (30.9%), adhesion of reproductive tracts 172 (0.2%), freemartin 8 (0.01%), and others 6,905 (8.3%), respectively. The treatment status of reproductive dysfunction in 30,241 cows were silent heat or error of estrus detection 14,909 (49.3%), follicular cysts 3,750 (12.4%), luteal cysts 907 (3.0%), inactive ovaries 665 (2.2%), granulosa cell tumor of ovary 3 (0.01%) and endometritis 6,986 (23.1%), respectively. The indices of reproductive efficiency after the periodical examination of reproductive status were as follows; the mean intercalving inteual was reduced from 475 days at the first examination to 381 days at the last examination of reproductive status, the mean interval calving to conception was reduced from 186 to 98 days, the mean interval calving to first service was reduced from 106 to 66 days, the cows showing heat by 60 days postpartum were increased from 32 to 90%, the mean conception rate to first service was increased from 42 to 64%, and the mean service per conception was reduced from 2.6 to 1.8 times, respectively.

A study on the location of fire fighting appliances in cargo ships (화물선 소화설비 비치에 대한 연구)

  • Ha, Weon-Jae
    • Journal of Advanced Marine Engineering and Technology
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    • v.40 no.9
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    • pp.852-858
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    • 2016
  • To safeguard the accommodation spaces on cargo ships from fire, structural fire protection provisions introduced by SOLAS and these measures retard the propagation of flames and smoke. SOLAS also specifies provisions for fire fighting drills. These provisions are a combination of regulations regarding structure and equipment and those dealing with the human element for the fire protection and effective responses in the event of fire. Requirements related to the human element play a supporting role to the requirements for structure and equipment because the present accommodation structure and equipment are insufficient for extinguishing a fire, therefore, fire-extinguishing activity performed by crew members is essential. To reduce human error and ensure effective fire fighting, it is necessary to install a fire-fighting system and improve the fire fighting process. The fundamental concept of fire fighting exercises is to commence fire fighting before the fire grows too big to extinguish. It is essential to relocate the storage place of fire fighting equipment to expedite the fire-fighting exercise. This study was carried out to reduce human risk for this purpose, the fire control station was relocated to a site that could be accessed from the open deck. Further, two sets of a fire fighter's outfit were stored at the same site. This relocation eliminated the risk of the crew reentering to operate the fire fighting system in the fire control station and allowed the crew to pick up the fire fighters' outfits quickly in the event of a fire. In addition, it was proposed that the IIC method be made mandatory. This method is combination of automatic fire detection system and sprinkler system which can reduce the risk of the fire fighting exercises for the crew and to suppress fire in the initial stage. This study was carried out to provide a foundation to the possible amendment of the relevant SOLAS regulations and national legislation.

The NCAM Land-Atmosphere Modeling Package (LAMP) Version 1: Implementation and Evaluation (국가농림기상센터 지면대기모델링패키지(NCAM-LAMP) 버전 1: 구축 및 평가)

  • Lee, Seung-Jae;Song, Jiae;Kim, Yu-Jung
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.18 no.4
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    • pp.307-319
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    • 2016
  • A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

A Case Study: Improvement of Wind Risk Prediction by Reclassifying the Detection Results (풍해 예측 결과 재분류를 통한 위험 감지확률의 개선 연구)

  • Kim, Soo-ock;Hwang, Kyu-Hong
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.3
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    • pp.149-155
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    • 2021
  • Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

Characterization of compounds and quantitative analysis of oleuropein in commercial olive leaf extracts (상업용 올리브 잎 추출물의 화합물 특성과 이들의 oleuropein 함량 비교분석)

  • Park, Mi Hyeon;Kim, Doo-Young;Arbianto, Alfan Danny;Kim, Jung-Hee;Lee, Seong Mi;Ryu, Hyung Won;Oh, Sei-Ryang
    • Journal of Applied Biological Chemistry
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    • v.64 no.2
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    • pp.113-119
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    • 2021
  • Olive (Olea europaea L.) leaves, a raw material for health functional foods and cosmetics have abundant polyphenols including oleuropein (major bioactive compound) with various biological activities: antioxidant, antibacterial, antiviral, anticancer activity, and inhibit platelet activation. Oleuropein has been reported as skin protectant, antioxidant, anti-ageing, anti-cancer, anti-inflammation, anti-atherogenic, anti-viral, and anti-microbial activity. Despite oleuropein is the important compound in olive leaves, there is still no quantitative approach to reveal oleuropein content in commercial products. Therefore, a validated method of analysis has to develop for oleuropein. In this study, the components and oleuropein content in 10 types of products were analyzed using a developed method with ultra-performance liquid chromatography to quadrupole time-of-flight mass spectrometry, charge of aerosol detector, and photodiode array. The total of 18 compounds including iridoids (1, 3, 4, 14, and 16-18), coumarin (2), phenylethanoids (5, 9, and 11), flavonoids (6-8, 10, 12, and 13), lignan (15), were tentatively identified in the leaves extract based high resolution mass spectrometry data, and the content of oleuropein in each product was almost identical between two detection methods. The oleuropein in three commercial product (A, G, H) was contained more over the suggested content, and it of five products (B, E, H, I, J) were analyzed within 5-10% error range. However, the two products (C, D) were found far lower than suggested contents. This study provides that analytical results of oleuropein could be a potential information for the quality control of leaf extract for a manufactured functional food.

A study on the calibration characteristics of organic fatty acids designated as new offensive odorants by cryogenic trapping-thermal desorption technique (유기지방산 신규악취물질에 대한 저온농축 열탈착방식 (Thermal desorber)의 검량특성 연구)

  • Ahn, Ji-Won;Kim, Ki-Hyun;Im, Moon-Soon;Ju, Do-Weon
    • Analytical Science and Technology
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    • v.22 no.6
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    • pp.488-497
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    • 2009
  • In this study, analytical methodology for several organic fatty acids (OFA: propionic acid (PA), butyric acid (BA), isovaleric acid (IA), and valeric acid (VA)) designated as new offensive odorants in Korea (as of year 2010) was investigated along with some odorous VOCs (styrene, toluene, xylene, methyl ethyl ketone, methyl isobutyl ketone, butyl acetate, and isobutyl alcohol). For this purpose, working standards (WS) containing all of these 13 compounds were loaded into adsorption tube filled with Tenax TA, and analyzed by gas chromatography (GC) system thermal desorber interfaced with. The analytical sensitivities of organic fatty acids expressed in terms of detection limit (both in absolute mass (ng) and concentration (ppb)) were lower by 1.5-2 times than other compounds (PA: 0.24 ng (0.16 ppb), BA: 0.19 ng (0.11 ppb), IA: 0.15 ng (0.07 ppb), and VA: 0.28 ng (0.13 ppb)). The precision of BA, IA, and VA, if assessed in terms of relative standard error (RSE), maintained above 5%, while the precison of other compounds were below 5%. The reproducibility of analysis improved with the aid of internal standard calibration (PA: $1.1{\pm}0.4%$, BA: $10{\pm}0.46$, IA; $12{\pm}0.3%$, VA: $4{\pm}0.1%$), respectively. The results of this study showed that organic fatty acid can be analyzed using adsorption tube and thermal desorber in a more reliable way to replace alkali absorption method introduced in the odor prevention law of the Korea Ministry of Environment (KMOE).