• Anxiety and mood
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• v.13 no.2
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• pp.53-59
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• 2017

Reliable and valid diagnostic screening tools in the primary care setting enable accurate estimation of depression in individuals at risk or in need of treatment, and provide patients with an opportunity to receive optimal treatments. Although there have been extensive studies on screening tools for depression used in domestic mental health settings, there is little consideration and lack of a thorough review of the diagnostic validity of screening tools. In the current review, we selected 13 representative screening tools for depression which were evaluated in a total of 19 validation studies conducted in Korea. We summarized DSM-5 target domains, diagnostic indices, sensitivity, specificity, cut-off scores, and diagnostic validity information for each tool. Finally, the depression measurement expert group was constituted to evaluate the current status of screening tools for depression, and their recommendations for a new screening tool were summarized. This study was conducted as part of the Mental Health Technology Development project to develop the Korean screening tool for depression (K-DEP).

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.9
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• pp.1226-1234
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• 2015

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.1
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• pp.42-48
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• 2003

LPG has been a broad concern of pro-environmental alternative fuel for vehicles. Recently, the new Liquid Phase LPG Injection(LPLI) system extends the limit of power of LPG engine and gives a chance to substitute LPG engine for diesel engine of heavy duty vehicles that are the main resources of air pollution in urban area. Large bore size of heavy duty LPG engine derives a serious knock problem. To find an optimal MBT conditions, it is necessary to know how the flame develops in the combustion chamber and find where the knock positions are. In this study. the ion-probe head gasket was used to estimate the knock position. Inverse operation of the ion-probe signal provides the flame developing characteristics. The further the position is from the spark plug, the later the flame arrives and the more times knock occurs. The main factor that effects knock position is inferred a flor situation of mixed gas in the combustion chamber.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.711-716
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• 2003

This paper proposes the method to select the number of optimal mixtures in each state in Continuous Density HMM (Hidden Markov Models), Previously, researchers used the same number of mixture components in each state of HMM regardless spectral characteristic of speaker, To model each speaker as accurately as possible, we propose to use a different number of mixture components for each state, Selection of mixture components considered the probability value of mixture by each state that affects much parameter estimation of continuous density HMM, Also, we use PCA (principal component analysis) to reduce the correlation and obtain the system' stability when it is reduced the number of mixture components, We experiment it when the proposed method used average 10% small mixture components than the conventional HMM, When experiment result is only applied selection of mixture components, the proposed method could get the similar performance, When we used principal component analysis, the feature vector of the 16 order could get the performance decrease of average 0,35% and the 25 order performance improvement of average 0.65%.

• Journal of Korean Neurosurgical Society
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• v.58 no.2
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• pp.93-100
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• 2015

Objective : Optimal treatment decision and estimation of the prognosis in traumatic brain injury (TBI) is currently based on demographic and clinical predictors. But sometimes, there are limitations in these factors. In this study, we analyzed three central nervous system biomarkers in TBI patients, will discuss the roles and clinical applications of biomarkers in TBI. Methods : From July on 2013 to August on 2014, a total of 45 patients were included. The serum was obtained at the time of hospital admission, and biomarkers were extracted with centrifugal process. It was analyzed for the level of S-100 beta (S100B), glial fibrillary acidic protein (GFAP), and ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1). Results : This study included 33 males and 12 females with a mean age of 58.5 (19-84) years. TBI patients were classified into two groups. Group A was severe TBI with Glasgow Coma Scale (GCS) score 3-5 and Group B was mild TBI with GCS score 13-15. The median serum concentration of S100B, GFAP, and UCH-L1 in severe TBI were raised 5.1 fold, 5.5 fold, and 439.1 fold compared to mild injury, respectively. The serum levels of these markers correlated significantly with the injury severity and clinical outcome (p<0.001). Increased level of markers was strongly predicted poor outcomes. Conclusion : S100B, GFAP, and UCH-L1 serum level of were significantly increased in TBI according to severity and associated clinical outcomes. Biomarkers have potential utility as diagnostic, prognostic, and therapeutic adjuncts in the setting of TBI.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1454-1464
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• 2013

In this paper, we propose a rapid rigid registration method for the fusion visualization of intra-operative 2D XA and pre-operative 3D CTA images. In this paper, we propose a global movement estimation based on a trilateration for the fast and robust initial registration. In addition, the principal axis of each image is generated and aligned, and the bounding box of the vascular shape is compared for more accurate initial registration. For the fine registration, two images are registered where the distance between two vascular structures is minimized by selective distance measure. In the experiment, we evaluate a speed, accuracy and robustness using five patients' data by comparing the previous registration method. Our proposed method shows that two volumes can be registered at optimal location rapidly, and robustly comparing with the previous method.

• Journal of the Korean Solar Energy Society
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• v.30 no.4
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• pp.92-99
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• 2010

The purpose of this study is to apply pressurized plenum under floor air conditioning system to office areas to understand characteristics of indoor thermal environment based on forms of diffusers. For doing this, the author conducted experiment of module measurement, and based on the results, analyzed indoor temperature distribution and velocity distribution based on direction of diffusion by using Computational Fluid Dynamics(CFD), and estimated the Predicted Mean Vote(PMV) of residents based on forms of diffusers to present the optimal air conditioning of the pressurized plenum under floor air conditioning system in heating. The results of this study are as follows. First, as for forms of diffusers, distributed diffusers rather than conical and grill diffusers were favorable in maintaining $24^{\circ}C$, the established temperature in heating, were active in velocity flowing, and were wide in a radius of diffusion. Second, as for position of pressurizing, the difference between upper and lower temperature was wider in center, lateral, and dispersed pressurizing (in order). As for velocity distribution, the velocity was more increased in lateral, center, and dispersed pressurizing(in order), indicating that dispersed pressurizing maintained uniform thermal environment. Third, as for diffusion direction, mixed direction showed less difference between upper and lower temperature and the difference in velocity between center and lateral part was 0.01m/1, indicating that it maintained uniform thermal environment. Fourth, as for the PMV of residents based on the forms of diffusers, the dispersed type showed(+) values above (0) when applied variably based on the position of diffuser, presenting thermal feeling of "being comfortable" to residents.

• Journal of Korea Water Resources Association
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• v.34 no.6
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• pp.713-724
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• 2001

Hydrologists have tried to develop monthly runoff simulation models which are important factor in wafer resources planning. One of the models called Kajiyama formu]a is widely used for monthly runoff simulation in Korea. In recent work by Xiong and Guo (1999), they suggested Two-parameter monthly water balance model to simulate the runoff and showed that the model can be used for the water resources planning program and the climate impact studies. However, they estimated two parameters of transformation of time scale, c and of the field capacity, SC by the trial and error method. Therefore, the purpose of this study is to suggest the estimation methodologies of c and SC, and compare Kajiyama formula with a Two-parameter monthly water balance model to simulate the runoff in Han river and IHP representative basins in Korea. The c is estimated by using the relationship of actual and potential evaporations, and SC is estimated from association with CN. We show that the estimated c and SC can be used as the initial or optimal values in the model.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.175-184
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• 2008

Uncertainties are unavoidable in engineering applications. In this paper we propose an alpha reliable multi-variable network design problem under demand uncertainty. In order to decide the optimal capacity enhancement, three performance measures based on 3E(Efficiency, Equity, and Environmental) are considered. The objective is to minimize the total budget required to satisfy alpha reliability constraint of total travel time, equity ratio, and total emission, while considering the route choice behavior of network users. The problem is formulated as the chance-constrained model for application of alpha confidence level and solved as a lexicographic optimization problem to consider the multi-variable. A simulation-based genetic algorithm procedure is developed to solve this complex network design problem(NDP). A simple numerical example ispresented to illustrate the features of the proposed NDP model.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.145-152
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• 2003

In this paper, assuming that the score of speech utterance is the product of HMM log likelihood and HMM weight, we propose a new method that HMM weights are adapted iteratively like the general MCE training. The proposed method adjusts HMM weights for better performance using delta coefficient defined in terms of misclassification measure. Therefore, the parameter estimation and the Viterbi algorithms of conventional 1:.um can be easily applied to the proposed model by constraining the sum of HMM weights to the number of HMMs in an HMM set. Comparing with the general segmental MCE training approach, computing time decreases by reducing the number of parameters to estimate and avoiding gradient calculation through the optimal state sequence. To evaluate the performance of HMM-based speech recognizer by weighting HMM likelihood, we perform Korean isolated digit recognition experiments. The experimental results show better performance than the MCE algorithm with state weighting.