• 정보과학회 논문지
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• 제44권4호
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• pp.433-438
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• 2017

오늘날의 네트워크는 고속화와 유비쿼터스 환경으로 인해 다양한 응용이 급속도로 생성되고 있으며 네트워크 트래픽도 매우 복잡해지고 있다. 이에 효율적인 네트워크 운용 및 관리를 위한 구체적인 단위의 트래픽 분류가 필수적이다. 다양한 트래픽 분류 방법이 연구되고 있는 가운데 아직 트래픽을 완벽하게 분류해내는 방법론은 개발되지 않은 실정이다. 이에 본 논문에서는 네트워크 플로우의 연관성 모델을 정의하고 이를 기반으로 트래픽을 분류하는 방법을 제안한다. 트래픽 분류를 위한 네트워크 플로우의 연관성 모델은 크게 유사성 모델과 연결성 모델로 이루어진다. 제안하는 방법론을 효과적으로 적용하기 위한 방안을 제시하며 실험을 통해 본 분류 방법론이 높은 정확도와 분석률의 방법론이라는 것을 증명한다.

• 한국도로학회논문집
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• 제12권2호
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• pp.115-121
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• 2010

입도조정기층 재료의 역학적 특성평가를 위하여 15개 시료에 대해 반복재하 삼축압축시험, CBR 시험, 투수계수시험을 수행하였다. 입도조정기층 재료의 CBR 값은 32~110 범위(평균 81)에서 매우 폭넓게 결정되었으며, 수침조건에서 팽창량은 0.04mm 이하로 나타났다. 입도조정기층 재료의 탄성계수는 체적응력의 영향을 매우 크게 받았으며 선형체적응력모델의 적용성이 가장 뛰어남을 확인하였다. 입도조정기층 재료의 탄성계수는 100MPa~600MPa, 모델계수 $k_1$은 80~270, 모델계수 $k_2$는 0.1~0.6 사이에서 결정 되었다. 체가름시험과 다짐시험에서 결정된 지수물성치로부터 입도조정기층 재료의 탄성계수를 결정하는 경험모형을 제안하였다. 제안된 경험모형의 결정계수는 모델계수 $k_1$ 결정에 있어서는 0.423, 모델계수 $k_2$ 결정에 있어서는 0.920, 응력단계별 탄성계수 결정에 있어서는 0.872로 평가되었다.

• 대한수학회지
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• 제57권5호
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• pp.1167-1186
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• 2020

This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility model, and the stochastic interest rate is driven by the Cox-Ingersoll-Ross (CIR) process with full correlation structure imposed among the state variables. This full correlation structure possesses the limitation to have fully analytical pricing formula for hybrid models of variance swaps, due to the non-affinity property embedded in the model itself. We address this issue by obtaining an efficient semi-closed form pricing formula of variance swaps for an approximation of the hybrid model via the derivation of characteristic functions. Subsequently, we implement numerical experiments to evaluate the accuracy of our pricing formula. Our findings confirm that the impact of the correlation between the underlying and the interest rate is significant for pricing discretely-sampled variance swaps.

• 한국물환경학회지
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• 제35권5호
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• pp.425-431
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• 2019

Recently, people have been attracting attention to the good quality of water resources as well as water welfare. to improve the quality of life. This study is a papers on the prediction of benthic macroinvertebrate index (BMI), which is a aquatic ecological health, using the machine learning based CFS (Correlation-based Feature Selection) method and the random forest model to compare the measured and predicted values of the BMI. The data collected from the Han River's branch for 10 years are extracted and utilized in 1312 data. Through the utilized data, Pearson correlation analysis showed a lack of correlation between single factor and BMI. The CFS method for multiple regression analysis was introduced. This study calculated 10 factors(water temperature, DO, electrical conductivity, turbidity, BOD, $NH_3-N$, T-N, $PO_4-P$, T-P, Average flow rate) that are considered to be related to the BMI. The random forest model was used based on the ten factors. In order to prove the validity of the model, $R^2$, %Difference, NSE (Nash-Sutcliffe Efficiency) and RMSE (Root Mean Square Error) were used. Each factor was 0.9438, -0.997, and 0,992, and accuracy rate was 71.6% level. As a result, These results can suggest the future direction of water resource management and Pre-review function for water ecological prediction.

• 한국음향학회지
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• 제31권2호
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• pp.93-99
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• 2012

음성코딩 시 성도는 Linear Predictive Coding (LPC) 계수를 이용해서 모델링 한다. 일반적으로 LPC 계수는 양자화와 선형보간 관점에서 유리한 Line Spectral Frequency (LSF) 파라미터로 변경하여 사용한다. 10차 이상의 다차원 LSF 데이터를 벡터 양자화를 이용하여 직접 코딩하게 되면 벡터 내 상관관계 (intra-frame correlation)를 모두 이용할 수 있으므로 rate-distortion 관점에서는 높은 효율을 기대할 수 있다. 하지만, 계산량과 메모리 요구량이 높아져서 실제 코딩 시스템에서는 사용할 수 없게 되므로, 차원을 나누어 압축하는 Split Vector Quantization (SVQ)이 이용된다. 또한, LSF 데이터는 과거 벡터와의 벡터 간 상관관계 (inter-frame correlation)가 높으므로, 이를 이용한 Predictive Split Vector Quantization (PSVQ)이 사용되고 있다. PSVQ는 SVQ 보다 높은 rate-distortion 성능을 보인다. 본 논문에서는 음성 저장 장치를 위한 최적의 PSVQ를 구현하기 위해서 다수의 과거 프레임 정보와의 벡터 간상관관계 (inter-frame correlation)를 고려한 Multi-Frame AR-model 기반 SVQ (MF-AR-SVQ)를 제안하였다. 기존 PSVQ와 비교해 보았을 때, MF-AR-SVQ는 계산량과 메모리 요구량의 큰 증가 없이, 평균 spectral distortion 관점에서 약 1비트의 성능 향상을 보였다.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.313-322
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• 2005

In this paper, we discuss suppression for logistic regression model. Suppression for linear regression model was defined as the relationship among sums of squared for regression as well as correlation coefficients of. variables. Since it is not common to obtain simple correlation coefficient for binary response variable of logistic model, we consider cumulative logistic models with multinomial and ordinal response variables rather than usual logistic model. As number of category of a response variable for the cumulative logistic model gets collapsed into binary, it is found that suppressions for these logistic models are changed. These suppression results for cumulative logistic models are discussed and compared with those of linear model.

• Journal of Advanced Marine Engineering and Technology
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• 제25권1호
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• pp.139-145
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• 2001

The objective of experimental study is to apply simultaneous measurement by PIV(Particle Image Velocimetry) to high_speed flow characteristics within ginseng cleaner model. Three different kinds of flow rate(15. 20, 27l/min) are selected as experimental condition. Optimized cross correlation identification to obtain velocity distribution, time-mean velocity distribution, velocity, profile, kinetic energy and turbulence intensity are represented quantitatively for the deeped understanding of the flow characteristics in a ginseng cleaner model.

• 한국항만학회지
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• 제13권1호
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• pp.101-112
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• 1999

Traffic accidents increase with the increase of the vehicles in operation on the street. Especially big traffic accidents composed of over 3 killed or 20 injured accidents with the property damage become one of the serious problems to be solved in most of the cities. The purpose of this study is to build the discrimination model on big traffic accidents using the Quantification II theory for establishing the countermeasures to reduce the big traffic accidents. The results are summarized as follows. 1)The existing traffic accident related model could not explain the phenomena of the current traffic accident appropriately. 2) Based on the big traffic accident types vehicle-vehicle, vehicle-alone, vehicle-pedestrian and vehicle-train accident rates 73%, 20.5% 5.6% and two cases respectively. Based on the law violation types safety driving non-fulfillment center line invasion excess speed and signal disobedience were 48.8%, 38.1% 2.8% and 2.8% respectively. 3) Based on the law violation types major factors in big traffic accidents were road and environment, human, and vehicle in order. Those factors were vehicle, road and environment, and human in order based on types of injured driver’s death. 4) Based on the law violation types total hitting and correlation rates of the model were 53.57% and 0.97853. Based on the types of injured driver’s death total hitting and correlation rates of the model were also 71.4% and 0.59583.

• 한국도로학회논문집
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• 제15권4호
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• pp.21-29
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• 2013

PURPOSES : The objective of this study is to provide for the overall SPL (Sound Pressure Level) prediction model by using the NCPX (Noble Close Proximity) measurement method in terms of regression equations. METHODS: Many methods can be used to measure the traffic noise. However, NCPX measurement can powerfully measure the friction noise originated somewhere between tire and pavement by attaching the microphone at the proximity location of tire. The overall SPL(Sound Pressure Level) calculated by NCPX method depends on the vehicle speed, and the basic equation form of the prediction model for overall SPL was used, according to the previous studies (Bloemhof, 1986; Cho and Mun, 2008a; Cho and Mun, 2008b; Cho and Mun, 2008c). RESULTS : After developing the prediction model, the prediction model was verified by the correlation analysis and RMSE (Root Mean Squared Error). Furthermore, the correlation was resulted in good agreement. CONCLUSIONS: If the polynomial overall SPL prediction model can be used, the special cautions are required in terms of considering the interpolation points between vehicle speeds as well as overall SPLs.

• Journal of Korea Trade
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• 제26권1호
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• pp.99-112
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• 2022

Purpose - This paper empirically investigates via a spatial lag model from the perspective of space economy to find the influencing factors of South Korea's OFDI along with 60 countries. Design/methodology - In the study of regional economic phenomena, we must first test the corresponding spatial correlation, and on this basis, complete the construction of the spatial model. For the target research object, after testing the spatial correlation, if there is spatial correlation, a spatial measurement model is needed. This paper uses the global Moran's I index for calculation. Based on the characteristics and research needs of the research object, this paper selects the spatial lag model to verify the existence of the spatial effect and factors affecting OFDI. Findings - Our results show that export scale, infrastructure, technology level, political stability, resource endowment, market size, distance and labor cost have a certain impact on Korea's OFDI, but at present the distance and market size factors are the most important influencing factors for South Korea's OFDI, The technical level and political stability have little effect on South Korea's OFDI, and are not main factors determining South Korea's OFDI. Originality/value - Through spatial measurement verification, it was found that the spatial effect has a significant impact on OFDI, along with more than 60 countries. On this basis, relevant suggestions are put forward, which have strong practical significance for South Korea's OFDI to achieve healthy and sustainable development.