• Horticultural Science & Technology
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• v.29 no.6
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• pp.549-554
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• 2011

The effect of full bloom date and growing season weather on harvesting date of 'Niitaka' pear (Pyrus pyrifolia) in Naju province and the model of multiple linear regression for predicting the fruit growing days was studied. Earlier year in full bloom date, the harvesting date tended earlier but fruit growing days tended longer. Mean and coefficient of variation of fruit growing degree days (GDD) accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ from full bloom date to harvesting date was 3,565, 2.9% and 4,463, 2.5%, respectively. Fruit growing days was not correlated with the fruit GDD accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ in each month but highly correlated with GDD accumulated daily meteorological factors at days after full bloom date. Especially, it was highly negatively correlated with GDD accumulated daily mean and maximum temperature at the base of $0^{\circ}C$ from $1^{st}$ day after full bloom to $60^{th}$ day. The determination coefficient ($r^2$) of multiple linear regression model by full bloom date, GDD accumulated daily mean and maximum temperature from $1^{st}$ day after full bloom to $60^{th}$ day for predicting fruit growing days was 0.7212. As a result, the fruit growing days of 'Niitaka' pear in Naju province can predict with 72% accuracy by the model of multiple linear regression.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.265-274
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• 1998

본 논문은 도로를 주행하는 차량의 지점속도에 대하여 단기간(short-term)으로 예측하는 네 가지의 모형들에 대한 개발 및 결과의 비교하고 평가했다. 사용된 기법들로는 다중회귀분석, 시계열분석(ARIMA), 인공 신경망, 칼만필터링 등이며, 모형의 구출을 위하여 다수의 독립변수 및 입력변수가 요구되는 다중회귀분석과 인공 신경망에서는 연속방정식에서 고려되는 변수들간의 단순상관계수 및 편상관계수의 계산을 통해서 입력변수가 설정이 되었으며, 시계열분석(ARIMA)과 칼만필터링 등 단일 입력 변수만을 요하는 모형에서는 바로 전 시간대와 현재시간대의간격동안 속도의 변화량을 입력변수로 설정하였다. 속도를 비롯해서 교통 데이터는 현장자료를 사용하였는데, 이는 서울의 한강 옆에 위치한 올림픽대로 중 한강대로에 위치한 검지기 3개를 통해서 천호동 방면으로 이동하는 교통류에 대해서 17시간 (00시~17시)동안 수집했다. 17시간 수집했는데 그중에 검지된 속도는 14km/h에서 98km/h까지 변하는 등, 수집된 자료에는 다양한 교통상태가 포함되어 있는데 이는 각 모형들의 정확한 예측력과 적응성을 평가하기 위함이었다. 각 모형은 예측하고자 하는 시점으로부터 1, 5, 10, 15분 후의 속도를 예측하는 것으로 총 4가지의 예측시간간격으로 각각 실험되었다. 결과는 전반적으로 신뢰성 있게 나왔으나 그중에서도 정확성면에서는 인공신경망과 칼만필터링이 우수했고 적응성면에서는 칼만필터리딩 탁월했다. 또한 1분 후의 속도를 예측하는 결과들은 모형들간에 거의 비슷한 정확도를 보여주었는데 이는 입력변수의 설정이 중요한 것임을 보여주는 것이라 판단된다. 있는 기법이다.적으로 세부적 차종분류로 접근한다.의 영향들을 고려함으로써 가로망 설계 과정에서 가로망의 상반된 역할인 이동성과 접근성의 비교가 가능한 보다 현실적인 가로망 설계 모형을 구축하고자 한다. 지금까지 소개된 가로망 설계모형들은 용량변화에 대한 설계변수의 형태에 따라 이산적 가로망 설계 모형과 연속적 가로망 설계모형으로 나뉘어지게 된다. 본 논문의 경우, 계산속도의 향상 측면에서는 연속적 가로망 설계 모형을 도입할 수 있지만, 이때 요구되는 도로용량이 이산적인 변수(차선 수)로 결정되어야만 신호제어 변수를 결정할 수 있기 때문에, 이산적 가로망 설계 모형이 사용된다. 하지만, 이산적 설계모형의 경우 조합최적화 문제이므로 정확한 최적해를 구하기 위해서는 상당한 시간이 소요되며, 경우에 따라서는 국부 최적해에 빠지게 된다. 이러한 문제를 극복하기 위해, 우선 이상적 모형의 근사화, 혹은 조합최적화문제를 위해 개발된 Simulated Annealing기법의 적용, 연속적 모형의 변수를 이산화하는 방법 등 다양한 모형들을 고려해 본 뒤, 적절한 모형을 적용할 것이다. 가로망 설계 모형에서 신호제어를 고려하기 위해서는 주어진 가로망에 대한 통행 배정과정에서 고려되는 통행시간을 링크통행시간과 교차로 지체시간을 동시에 고려해야 하는데, 이러한 문제의 해결을 위해서 최근 활발히 논의되고 있는 교차로에서의 신호제어에 대응하는 통행배정 모형을 도입하여 고려하고자 한다. 이를 위해서 지금까지 연구되어온 Global Solution Approach와 Iterative Approach를 비교, 검토한 뒤 모형에 보다 알맞은 방법을 선택한다. 차량의

• Korean Journal of Psychosomatic Medicine
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• v.28 no.1
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• pp.29-35
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• 2020

Objectives : Evidence regarding the association between untreated depression in adolescence and suicidal risk in male young adults is scarce. We aimed to assess the effect of untreated illness during adolescence on the suicidal risk and attempt after that first episode. Methods : As part of a cross-sectional study, between May 2017 and April 2018, a total of 260 patients with currently unipolar or bipolar depression were included in the final analysis. Multiple linear and logistic regression analysis were performed to evaluate the association between untreated mood disorder in adolescence and its effect on the suicidal risk and attempt. Results : In total 260 patients, 189 were classified as untreated group. The proportion of suicide attempts, total depression score, suicidal risk and number of suicide attempts were significantly higher in the untreated group. The most predictive factors of suicide attempts were history of untreated depression [Adjusted Odds Ratio (AOR)=4.19, 95% Confidence Interval (CI)=2.25-7.81, p<0.001] and diagnosis of bipolar depression (AOR=2.60, 95% CI=1.52-4.46, p<0.001). Conclusions : Although the untreated depression suggests higher rates of suicidality, a significant proportion (86.7%) of adolescent depression in this study did not receive psychiatric treatment. Future research should be needed to find better ways to decrease barriers in using mental health treatment and its contribution to reduction and prevention of adverse outcome.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.89-96
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• 2000

ABR service is defined by ATM Forum and ITU for the efficient use of link bandwidth, and 2-pass service policing is proposed for this service. 2-pass service policing is effective by the real-time measurement of the used bandwidth, and this scheme obtains multiplexing gam and control efficiently ABR traffic as dynamically allocating rate by residual bandwidth information. In this study, we propose the real-time bandwidth prediction scheme for ABR traffic control, as using dynamic rate allocation by available bandwidth information. This study can obtain the simple hardware structure by means of as predicting available bandwidth by the total link bandwidth and the sum of transmission rate on the backlogged state connections.

• Nuclear Engineering and Technology
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• v.24 no.1
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• pp.30-39
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• 1992

In this study, an integrated boration and dilution (INBAD) model is proposed to predict the required makeup flowrate for RCS boron concentration change and to analyze the boron concentration behavior at each subsystem within the RCS including CVCS during boration and dilution operation. The INBAD model is constructed by integrating an existing neutronic code and a boration and dilution model. The boration and dilution model has been developed for our specific purpose using the one-cell model and multi-cell model. In addition, in order to assess the boron concentration behavior more realistically, two important features such as variable pressurizer heater output and optional makeup mode (either direct or indirect injection) are implemented in this model. In order to demonstrate the usefulness of this model, the boron concentration behavior analysis at each subsystem were performed for both direct and indirect injection mode using YGN 3 and 4 design data. Also, the effect of pressurizer heater output on the primary loop boron concentration was investigated. The results showed that the boron concentration changes can be predicted accurately at each subsystem during boration and dilution operation.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.4
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• pp.561-568
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• 2017

In order to effectively utilize the Coarse Wavelength Division Multiplexing(CWDM) technology in optical integrated devices, a design of a wavelength selective coupler structure between an optical fiber and an optical waveguide in a flat substrate is can be considered. In this paper, we consider the coupling between a silicon waveguide with an air trench and a single mode fiber. We investigated the tendency of coupling efficiency and its limitations according to the grating depth. For this purpose, the coupling efficiency of coupler structure designed through modeling based on coupled mode theory is predicted and quantitatively compared with simulation results using finite element method.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.155-163
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• 2009

In text-to-speech systems, the conversion of text into prosodic parameters is necessarily composed of three steps. These are the placement of prosodic boundaries. the determination of segmental durations, and the specification of fundamental frequency contours. Prosodic boundaries. as the most important and basic parameter. affect the estimation of durations and fundamental frequency. Break prediction is an important step in text-to-speech systems as break indices (BIs) have a great influence on how to correctly represent prosodic phrase boundaries, However. an accurate prediction is difficult since BIs are often chosen according to the meaning of a sentence or the reading style of the speaker. In Japanese, the prediction of an accentual phrase boundary (APB) and major phrase boundary (MPB) is particularly difficult. Thus, this paper presents a method to complement the prediction errors of an APB and MPB. First, we define a subtle BI in which it is difficult to decide between an APB and MPB clearly as a variable break (VB), and an explicit BI as a fixed break (FB). The VB is chosen using the classification and regression tree, and multiple prosodic targets in relation to the pith and duration are then generated. Finally. unit-selection is conducted using multiple prosodic targets. In the MOS test result. the original speech scored a 4,99. while proposed method scored a 4.25 and conventional method scored a 4.01. The experimental results show that the proposed method improves the naturalness of synthesized speech.

• Journal of KIISE
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• v.44 no.10
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• pp.1026-1033
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• 2017

In this paper a Bayesian modeling and duration-based prediction method is proposed for health clinic time series data using the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM). HDP-HMM is a Bayesian extension of HMM which can find the optimal number of health states, a number which is highly uncertain and even difficult to estimate under the context of health dynamics. Test results of HDP-HMM using simulated data and real health clinic data have shown interesting modeling behaviors and promising prediction performance over the span of up to five years. The future of health change is uncertain and its prediction is inherently difficult, but experimental results on health clinic data suggests that practical long-term prediction is possible and can be made useful if we present multiple hypotheses given dynamic contexts as defined by HMM states.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.2
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• pp.189-195
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• 2011

In this paper, prediction and comparison on COP(coefficient of performance) of R744-R404A cascade refrigeration system are presented to offer the basic design data for the operating parameters of the system. The operating parameters considered in this study include subcooling and superheating degree, compressor efficiency, and condensing and evaporating temperature in the R404A high- and R744 low-temperature cycle, respectively. The main results were summarized as follows : The prediction for performance of R744-R404A cascade refrigeration system have been proposed through multiple regression analysis and compared with other researcher's correlations. As a result, prediction proposed in the study shows disagreement with existing equations. Therefore, it is necessary to propose the more accurate correlation predicting the COP of R744-R404A cascade refrigeration system through an addition experiments.

• The Journal of the Acoustical Society of Korea
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• v.27 no.3
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• pp.111-118
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• 2008

In this paper, we propose a new automatic taxonomy generation algorithm for the audio genre classification. The proposed algorithm automatically generates hierarchical taxonomy based on the estimated classification accuracy at all possible nodes. The estimation of classification accuracy in the proposed algorithm is conducted by applying the training data to classifier using k-fold cross validation. Subsequent classification accuracy is then to be tested at every node which consists of two clusters by applying one-versus-one support vector machine. In order to assess the performance of the proposed algorithm, we extracted various features which represent characteristics such as timbre, rhythm, pitch and so on. Then, we investigated classification performance using the proposed algorithm and previous flat classifiers. The classification accuracy reaches to 89 percent with proposed scheme, which is 5 to 25 percent higher than the previous flat classification methods. Using low-dimensional feature vectors, in particular, it is 10 to 25 percent higher than previous algorithms for classification experiments.