• Journal of Korea Water Resources Association
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• v.41 no.5
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• pp.527-544
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• 2008

Generalized Pareto distribution (GPD) is frequently applied in hydrologic extreme value analysis. The main objective of statistics of extremes is the prediction of rare events, and the primary problem has been the estimation of the threshold and the exceedances which were difficult without an accurate method of calculation. In this paper, to obtain the threshold or the exceedances, four methods were considered. For this comparison a GPD model was used to estimate parameters and quantiles for the seven durations (1, 2, 3, 6, 12, 18 and 24 hours) and the ten return periods (2, 3, 5, 10, 20, 30, 50, 70, 80 and 100 years). The parameters and quantiles of the three-parameter generalized Pareto distribution were estimated with three methods (MOM, ML and PWM). To estimate the degree of fit, three methods (K-S, CVM and A-D test) were performed and the relative root mean squared error (RRMSE) was calculated for a Monte Carlo generated sample. Then the performance of these methods were compared with the objective of identifying the best method from their number.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.96-105
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• 1998

The aim of this paper is to propose the method of WDHMM(Weighted DHMM), using the MLP-VQ for the improvement of speaker-independent connect-digit recognition system. MLP neural-network output distribution shows a probability distribution that presents the degree of similarity between each pattern by the non-linear mapping among the input patterns and learning patterns. MLP-VQ is proposed in this paper. It generates codewords by using the output node index which can reach the highest level within MLP neural-network output distribution. Different from the old VQ, the true characteristics of this new MLP-VQ lie in that the degree of similarity between present input patterns and each learned class pattern could be reflected for the recognition model. WDHMM is also proposed. It can use the MLP neural-network output distribution as the way of weighing the symbol generation probability of DHMMs. This newly-suggested method could shorten the time of HMM parameter estimation and recognition. The reason is that it is not necessary to regard symbol generation probability as multi-dimensional normal distribution, as opposed to the old SCHMM. This could also improve the recognition ability by 14.7% higher than DHMM, owing to the increase of small caculation amount. Because it can reflect phone class relations to the recognition model. The result of my research shows that speaker-independent connected-digit recognition, using MLP-VQ and WDHMM, is 84.22%.

• The Korean Journal of Pesticide Science
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• v.10 no.4
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• pp.279-288
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• 2006

Three different experiments were undertaken to investigate the runoff and erosion loss of diazinon and metolachlor from sloped-field by rainfall. The mobility of two pesticides and which phase they were transported by were examined in adsorption study, the influence of rainfall pattern and slope degree on the pesticide losses were evaluated in simulated rainfall study, and the pesticide losses from soybean field comparing with bare soil were measured in field lysimeter study. Freundlich adsorption parameter (K) ranged $1.6{\sim}2.0$ for metolachlor and $4.0{\sim}5.5$ for diazinon. The K values of pesticides by the desorption method were higher than those ones by the adsorption method. Another parameter (1/n) in Freundlich equation for the pesticides tested ranged $0.96{\sim}1.02$ by desorption method and $0.87{\sim}1.02$ by adsorption method. By the SSLRC's classification for pesticide mobility of diazinon and metolachlor were classified as moderately mobile ($75{\leq}Koc$ <500). Runoff and erosion losses of pesticides by three rainfall scenarios were $0.5{\sim}1.0%$ and $0.1{\sim}0.7%$ for metolachlor and $0.1{\sim}0.6%$ and $0.1{\sim}0.2%$ for diazinon. Distribution of pesticides in soil polite were investigated after the simulated rainfall events. Metolachlor was leached to $10{\sim}15$ cm soil layer and diazinon was leached to $5{\sim}10$ cm soil layer. Losses of each pesticide in the 30% of sloping degree treatment were $0.2{\sim}1.9$ times higher than those ones in the 10% of sloping degree treatment. Pesticide losses from a series of lysimeter plots in sloped land by rainfall ranged $1.0{\sim}3.1%$ for metolachlor and $0.23{\sim}0.50%$ for diazinon, and were $1/3{\sim}2.5$ times to the ones in the simulated rainfall study. The erosion rates of pesticides from soybean-plots were $21{\sim}75%$ lower than the ones from bare soil plots. The peak runoff concentration in soybean-plots and bare soil plots were $1{\sim}9{\mu}gL^{-1}$ and $3{\sim}16{\mu}gL^{-1}$ for diazinon, $7{\sim}31{\mu}gL^{-1}$ and $5{\sim}40{\mu}gL^{-1}$ for metolachlor, respectively.

• Korean Journal of Psychosomatic Medicine
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• v.28 no.1
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• pp.81-88
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• 2020

Objectives : This study aimed to compare autonomic nervous system (ANS) dysregulation and differential relationships with clinical severities between anxiety disorder, depressive disorder, and trauma·stressor related disorder using heart rate variability (HRV) parameters. Methods : We conducted a retrospective chart review of outpatients from 2017 to 2018 in Stress Clinic of National Center for Mental Health. Total 473 patients were included; 166 anxiety disorder; 184 depressive disorder ; 123 trauma·stressor related disorder. Parameters of 5-min analysis of HRV were compared in three groups. Additionally, we investigated the differential association of each parameters with Clinical Global Impression-Severity Scale (CGI-S) across each group. Results : No significant differences were found in all HRV parameters between the three groups. However, significant group interactions by CGI-S were found in standard deviation of all RR intervals (SDNN) and the square root of the mean squared differences of successive normal-to-normal intervals (RMSSD) (SDNN, p=0.017 ; RMSSD, p=0.034). A negative relationship between CGI-S and SDNN, RMSSD has been found in anxiety disorder and depressive disorder. However, a positive relationship between CGI-S and SDNN, RMSSD has been found in trauma·stressor related disorder. Conclusions : Despite of no significant differences of each HRV parameter, our findings suggested the differential associations of HRV parameters with clinical severity among anxiety disorder, depressive disorder and trauma·stressor related disorder. In trauma·stressor related disorder, the clinical severity and degree of ANS dysregulation may differ, so more aggressive treatment is suggested.

• Korean Journal of Environmental Agriculture
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• v.26 no.4
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• pp.343-350
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• 2007

Three different experiments were carried out to investigate the runoff and erosion losses of endosulfan from sloped-field by rainfall. The mobility of endosulfan and which phase it was transported by were examined in adsorption study, the influence of rainfall pattern and slope degree on the pesticide loss were evaluated in simulated rainfall study, and the pesticide losses from soybean-grown field comparing with bare soil were measured in field lysimeter study. Adsorption parameter (K) of endosulfan ranged from 77 to 131 by adsorption method and K values by the desorption method were higher than those by the adsorption method. By the SSLRC's classification for pesticide mobility endosulfan was classified as non-mobile class ($K_{oc}>4,000$). Runoff and erosion loss of endosulfan by three rainfall scenarios ranged from 3.4 to 5.6%and from 4.4 to 15.6%of the amount treated. Endosulfan residues were mainly remained at the top 5 cm of soil depth after the simulated rainfall study. Pesticide loss in case of 30%-slope degree ranged from 0.6 to 0.9 times higher than those in case of 10%-slope degree. The difference of pesticide runoff loss was related with its concentration in runoff water and the difference of pesticide erosion loss would related closely with the quantity of soil eroded. Endosulfan losses from a series of lysimeter plots in sloped land by rainfall ranged from 5 to 35% of the amount treated. The erosion rate of endosulfan from soybean-plots was 66% of that from bare soil plots. The effect of slope conditions was not great for runoff loss, but was great for erosion loss as increasing to maximum $4{\sim}12$ times with slope degree and slope length. The peak runoff concentration of endosulfan in soybean-plots and bare soil plots ranged from 8 to 10 and from 7 to $9{\mu}gL^{-1}$ on nine plots with different slope degree and slope length. Therefore the difference of the peak runoff concentrations between bare soil plots and soybean-plots were not great.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.6
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• pp.868-872
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• 2005

Individual management of the animal is the first step towards reaching the goal of precision livestock farming that aids animal welfare. Accurate recognition of each individual animal is important for precise management. Electronic identification of cattle, usually referred to as RFID (Radio Frequency Identification), has many advantages for farm management. In practice, however, RFID implementations can cause several problems. Reading speed and distance must be optimized for specific applications. Image processing is more effective than RFID for the development of precision farming system in livestock. Therefore, the aim of this paper is to attempt the identification of cattle by using image processing. The majority of the research on the identification of cattle by using image processing has been for the black-and-white patterns of the Holstein. But, native Japanese and Korean cattle do not have a consistent pattern on the body, so that identification by pattern is impossible. This research aims to identify to Japanese black cattle, which does not have a black-white pattern on the body, by using image processing and a neural network algorithm. 12 Japanese black cattle were tested. Values of input parameter were calculated by using the face image values of 12 cows. The face was identified by the associate neural memory algorithm, and the algorithm was verified by the transformed face image, for example, of brightness, distortion, noise and angle. As a result, there was difference due to a transformation ratio of the brightness, distortion, noise, and angle. The algorithm could identify 100% in the range from -30 to +30 degrees of brightness, -20 to +40 degrees of distortion, 0 to 60% of noise and -20 to +30 degree of angle transformed images.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.1003-1007
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• 2013

Objective: This work aimed to investigate the correlations of tumor-associated macrophages (TAMs) and their subtypes M1 and M2 with liver metastasis of colorectal cancer, and provide useful references for seeking predictors of liver metastasis and studying mechanisms. Methods: 120 patients with colorectal cancer from 2000 to 2009 were divided into low, middle and high liver metastasis groups (group A, B and C, respectively). S-P immunohistochemical staining and microscopic observation were conducted to compare expression in CD68-positive cells (TAMs), CD80-positive cells (M1) and CD163-positive cells (M2) in three groups. Correlations of TAMs, M1, M2, and M2/M1 ratio with clinical and pathological parameters were analyzed. Results: With increase of liver metastatic ability, the number of TAMs decreased gradually, with no significant difference between any two of the three groups (P > 0.05), while the numbers of M1 and M2 were significantly decreased and increased, respectively, with significant difference between any two of three groups (P < 0.05 or P < 0.01). In addition, the M2/M1 ratio increased with increase of liver metastatic ability (P < 0.01). There was no statistical significance of correlation of TAMs with each clinical and pathological parameter. M1 was negatively related with lymphatic metastasis and liver metastatic ability. M2 was positively correlated with preoperative CEA level, lymphatic metastasis, tumor differentiation degree and liver metastatic ability. The same was the case for the M2/M1 ratio. Conclusions: Effects of TAMs on liver metastasis of colorectal cancer do not depend on the total number of TAMs, but on the number and proportion of functional subtypes M1 and M2. M2 number and M2/M1 ratio are more accurate predictors for liver metastasis of colorectal cancer.

• Structural Engineering and Mechanics
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• v.37 no.6
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• pp.671-684
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• 2011

Deciding on an optimal sensor placement (OSP) is a common problem encountered in many engineering applications and is also a critical issue in the construction and implementation of an effective structural health monitoring (SHM) system. The present study focuses with techniques for selecting optimal sensor locations in a sensor network designed to monitor the health condition of Dalian World Trade Building which is the tallest in the northeast of China. Since the number of degree-of-freedom (DOF) of the building structure is too large, multi-modes should be selected to describe the dynamic behavior of a structural system with sufficient accuracy to allow its health state to be determined effectively. However, it's difficult to accurately distinguish the translational and rotational modes for the flexible structures with closely spaced modes by the modal participation mass ratios. In this paper, a new method of the OSP that computing the mode shape matrix in the weak axis of structure by the simplified multi-DOF system was presented based on the equivalent rigidity parameter identification method. The initial sensor assignment was obtained by the QR-factorization of the structural mode shape matrix. Taking the maximum off-diagonal element of the modal assurance criterion (MAC) matrix as a target function, one more sensor was added each time until the maximum off-diagonal element of the MAC reaches the threshold. Considering the economic factors, the final plan of sensor placement was determined. The numerical example demonstrated the feasibility and effectiveness of the proposed scheme.

• Journal of Korean Society of Transportation
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• v.11 no.1
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• pp.87-103
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• 1993

The subject this paper is the signal control strategy under oversaturated conditions. The nature of traffic control for oversaturation is essentially different from the standard control modes. While under non-saturated situation traffic control is needed for the sake of safety and efficiency, the throughput is essential under oversaturated conditions. Therefore berth objective and strategies differ. For an oversaturated stream the cycle time and the signal offset are thought to be of rather secondary importance. For this case the green split may well be the most important control variable to serve the excessive demand. Up to now, however, most efforts have concentrated on the strategy with the concept which lies just on the extension of Webster's. "Green-split Coordination Strategy for Over-Saturated Networks", presents newly contrived three types of strategies named Forward-coordination, Backward-coordination and Network-coordination respectively and describes the algorithms with the evaluations. The forward coordination strategy treats the forward wave of flow between two signals. The aim is to prevent the outbreak of queue due to the accumulation of temporary excess of demand in near-saturation or saturation flow. The backward coordination strategy treats the backward rave of flow between two signals. The goal is to prevent the waste of green time caused by the exit block at the upstream signal. for this purpose a feedback regulation is provided of the upstream green-split so that the inflow-outflow balance is kept zero. The resultant surplus of green time is alloted to other signal stages. Also here the examination is made of the appropriate value of the feedback control parameter. The network coordination strategy is operated to maximize the network throughput in a specific direction applying a bang-bang control at the bottleneck intersection. This is a type of intervenient control for policy reasons. For this strategy the green-split coordinations, particuarly the backward coordination, are essential as the tactical elements. In order to evaluate the preposed strategies those are compared with the latest existing strategy called saturation-degree-ratio control by the simulation experiments in an assumed 4$\times$4 grid network. The results are satisfactory showing a 10-15% reduction in delays and a 15% increase in network capacity.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.1
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• pp.146-159
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• 2011

The continuous increase in the production of metals and their subsequent release into the environment has lead to increased concentration of these elements in agricultural soils. Because microbes are involved in almost every chemical transformations taking place in the soil, considerable attention has been given to assessing their responses to metal contaminants. Short-term and long-term exposures to toxic metals have been shown to reduce microbial diversity, biomass and activities in the soil. Several studies show that microbial parameters like basal respiration, metabolic quotient, and enzymatic activities, including those of oxidoreductases and those involved in the cycle of C, N, P and other elements, exhibit sensitivity to soil metal concentrations. These have been therefore, regarded as good indices for assessing the impact of metal contaminants to the soil. Metal contamination has also been extensively shown to decrease species diversity and cause shifts in microbial community structure. Biochemical and molecular techniques that are currently being employed to detect these changes are continuously challenged by several limiting factors, although showing some degree of sensitivity and efficiency. Variations and inconsistencies in the responses of bioindicators to metal stress in the soil can also be explained by differences in bioavailability of the metal to the microorganisms. This, in turn, is influenced by soil characteristics such as CEC, pH, soil particles and other factors. Therefore, aside from selecting the appropriate techniques to better understand microbial responses to metals, it is also important to understand the prevalent environmental conditions that interplay to bring about observed changes in any given soil parameter.