• 한국전문물리치료학회지
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• 제23권2호
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• pp.93-99
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• 2016

Background: Parametric statistical procedures are typically conducted under the condition in which a sample distribution is statistically identical with its population. In reality, investigators use inferential statistics to estimate parameters based on the sample drawn because population distributions are unknown. The uncertainty of limited data from the sample such as lack of sample size may be a challenge in most rehabilitation studies. Objects: The purpose of this study is to review the bootstrapping method to overcome shortcomings of limited sample size in rehabilitation studies. Methods: Articles were reviewed. Results: Bootstrapping method is a statistical procedure that permits the iterative re-sampling with replacement from a sample when the population distribution is unknown. This statistical procedure is to enhance the representativeness of the population being studied and to determine estimates of the parameters when sample size are too limited to generalize the study outcome to target population. The bootstrapping method would overcome limitations such as type II error resulting from small sample sizes. An application on a typical data of a study represented how to deal with challenges of estimating a parameter from small sample size and enhance the uncertainty with optimal confidence intervals and levels. Conclusion: Bootstrapping method may be an effective statistical procedure reducing the standard error of population parameters under the condition requiring both acceptable confidence intervals and confidence level (i.e., p=.05).

• 한국자동차공학회논문집
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• 제10권4호
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• pp.85-92
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• 2002

To investigate the safety of the in-use vehicles emission against the tail-pipe emission regulation, in-use vehicles emission trend according to vehicle mileage should be known. But it is impossible to collect all vehicles emission data In order to know that. Therefore, it is necessary to establish a statistically meaningful inference method that can be used generally to estimate in-use vehicles emissions distribution according to the vehicle mileage with relatively less in-use vehicles emission data. To do this, a linear regression model that solved the problems of data normality and common variance of error was studied. As a way that can secure the data normality, In(emission) instead of emission itself was used as a sampled data. And a reciprocal of mileage was suggested as a factor to secure common variance of error. As an example, 36 data of FTP-75 test were handled in this study. As a result, using average value and standard deviation at each mileage which were inferred from a linear regression model, probability density distribution and cumulative distribution of emissions according to the vehicle mileage were obtained and it was possible to predict the deterioration factor through full useful life mileage and also possible to decide whether those in-use vehicles will meet the tail-pipe emission regulations or not.

• 대기
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• 제24권4호
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• pp.503-514
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• 2014

Evaluation of predictability of numerical models for tropical cyclone track was performed using along-and cross-track component. The along-and cross-track bias were useful indicators that show the numerical models predictability associated with cause of errors. Since forecast errors, standard deviation and consistency index of along-track component were greater than those of cross-track component, there was some rooms for improvement in alongtrack component. There was an overall slow bias. The most accurate model was JGSM for 24-hour forecast and ECMWF for 48~96-hour forecast in direct position error, along-track error and cross-track error. ECMWF and GFS had a high variability for 24-hour forecast. The results of predictability by track type showed that most significant errors of tropical cyclone track forecast were caused by the failure to estimate the recurvature phenomenon.

• ETRI Journal
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• 제30권4호
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• pp.506-515
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• 2008

The H.264/AVC standard has adopted new coding tools such as intra-prediction, variable block size, motion estimation with quarter-pixel-accuracy, loop filter, and so on. The adoption of these tools enables an H.264/AVC-coded bitstream to have more information than was possible with previous standards. In this paper, we propose an effective spatial error concealment method with low complexity in H.264/AVC intra-frame. From information included in an H.264/AVC-coded bitstream, we use prediction modes of intra-blocks to recover a damaged block. This is because the prediction direction in each prediction mode is highly correlated to the edge direction. We first estimate the edge direction of a damaged block using the prediction modes of the intra-blocks adjacent to a damaged block and classify the area inside the damaged block into edge and flat areas. Our method then recovers pixel values in the edge area using edge-directed interpolation, and recovers pixel values in the flat area using weighted interpolation. Simulation results show that the proposed method yields better video quality than conventional approaches.

• 산업경영시스템학회지
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• 제39권1호
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• pp.64-72
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• 2016

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

• 한국작물학회지
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• 제51권spc1호
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• pp.304-309
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• 2006

Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.711-714
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• 2005

We propose floating point arithmetic units for geometry operation of mobile 3D graphic processor. The proposed arithmetic units conform to the single precision format of IEEE standard 754-1985 that is a standard of floating point arithmetic. The rounding algorithm applies the nearest toward zero form. The proposed adder/subtraction unit and multiplier have one clock cycle latency, and the inversion unit has three clock cycle latency. We estimate the required numbers of arithmetic operation for Viewing transformation. The first stage of geometry operation is composed with translation, rotation and scaling operation. The translation operation requires three addition and the rotation operation needs three addition and six multiplication. The scaling operation requires three multiplication. The viewing transformation is performed in 15 clock cycles. If the adder and the multiplier have their own in/out ports, the viewing transformation can be done in 9 clock cycles. The error margin of proposed arithmetic units is smaller than $10^{-5}$ that is the request in the OpenGL standard. The proposed arithmetic units carry out operations in 100MHz clock frequency.

• 전자공학회논문지
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• 제52권8호
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• pp.89-96
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• 2015

인간의 시각은 색순응을 통해서 사물의 색을 광원의 색에 영향 없이 인지 할 수 있다. 반면에, 카메라는 입력 값을 그대로 기록하기 때문에, 광원에 따라 물체의 색이 다르게 나타난다. 최근에 희박성 제약조건의 비음수 행렬 분해(nonnegative matrix factorization with sparseness constraint; NMFsc)를 이용한 광원추정 방법이 제안되었다. 이 방법은 낮은 희박성 제약조건을 사용해서 광원을 추정하고, 높은 희박성 제약조건을 사용해서 반사율을 추정한다. 하지만, 희박성 제약조건의 비음수 행렬분해를 이용한 광원 추정 방법은, 영상의 전역적인 정보를 사용하므로, 영상에서 동일한 색이 넓은 영역에 존재하는 경우, 추정된 광원이 큰 오차를 가진다. 이러한 단점을 보완하기 위해, 영상에서 주색도 분석과 희박성 제약조건의 비음수 행렬 분해를 이용한 광원 추정 방법을 제안하였다. 먼저 주색도를 분석하기 위해 영상을 색도 좌표계로 옮기고 색도 히스토그램을 이용하여 유사한 색도를 가지는 영역들로 영상을 분할한다. 다음으로 영상의 주색도는 분할된 영상들 중 색도의 표준편차가 가장 적은 영상의 색도로 선택한다. 마지막으로 주색도 분석 결과와 희박성 제약조건의 비음수 행렬 분해를 이용해 입력 영상에서 주색도 성분을 제거하고 최종적인 광원을 추정한다. 실제 촬영 영상에 대한 평균 각오차를 사용하여 기존의 방법과의 성능을 비교하였고, 그 결과 제안하는 방법의 평균 각 오차는 5.5를 나타내어 영상의 주 색도를 포함하여 광원을 추정한 기존 방법의 평균 각 오차 5.7 보다 우수한 성능을 나타내었다.

• Smart Structures and Systems
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• 제20권5호
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• pp.549-562
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• 2017

The US railroad network carries 40% of the nation's total freight. Railroad bridges are the most critical part of the network infrastructure and, therefore, must be properly maintained for the operational safety. Railroad managers inspect bridges by measuring displacements under train crossing events to assess their structural condition and prioritize bridge management and safety decisions accordingly. The displacement of a railroad bridge under train crossings is one parameter of interest to railroad bridge owners, as it quantifies a bridge's ability to perform safely and addresses its serviceability. Railroad bridges with poor track conditions will have amplified displacements under heavy loads due to impacts between the wheels and rail joints. Under these circumstances, vehicle-track-bridge interactions could cause excessive bridge displacements, and hence, unsafe train crossings. If displacements during train crossings could be measured objectively, owners could repair or replace less safe bridges first. However, data on bridge displacements is difficult to collect in the field as a fixed point of reference is required for measurement. Accelerations can be used to estimate dynamic displacements, but to date, the pseudo-static displacements cannot be measured using reference-free sensors. This study proposes a method to estimate total transverse displacements of a railroad bridge under live train loads using acceleration and tilt data at the top of the exterior pile bent of a standard timber trestle, where train derailment due to excessive lateral movement is the main concern. Researchers used real bridge transverse displacement data under train traffic from varying bridge serviceability levels. This study explores the design of a new bridge deck-pier experimental model that simulates the vibrations of railroad bridges under traffic using a shake table for the input of train crossing data collected from the field into a laboratory model of a standard timber railroad pile bent. Reference-free sensors measured both the inclination angle and accelerations of the pile cap. Various readings are used to estimate the total displacements of the bridge using data filtering. The estimated displacements are then compared to the true responses of the model measured with displacement sensors. An average peak error of 10% and a root mean square error average of 5% resulted, concluding that this method can cost-effectively measure the total displacement of railroad bridges without a fixed reference.

• 방송공학회논문지
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• 제16권2호
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• pp.207-215
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• 2011

SC-FDE(Single Carrier with Frequency Domain Equalizer) 전송 방식에서 채널의 다중경로를 통과한 신호들은 채널 지연 확산과 노이즈 영향으로 심하게 왜곡이 되거나 ISI(Inter-Symbol Interference)가 발생된다. 기존 UW(Unique-Word) 기반 SC-FDE 전송 방식중 하나인 반복적 채널 추정은 채널 길이를 안다고 가정하여 추정한 CIR(Channel Impulse Response)의 채널 길이 밖에 있는 노이즈 성분을 시간 영역에서 스무딩을 함으로써 노이즈 성분을 제거한다. 또한, 주파수 영역에서 채널 추정에 사용하는 UW를 복원하여 잔재하는 ISI 성분을 제거함으로써 채널 추정 성능을 향상시킨다. 본 논문은 채널 길이 안으로 있는 노이즈 성분 억압을 통한 채널 추정기법을 제안한다. 노이즈 성분을 억압하기 위해 시간 영역에서 추정된 CIR로 채널 길이 밖에 있는 노이즈 성분을 이용하여 노이즈의 표준편차를 추정하고 본래 신호 샘플에 영향이 안가도록 노이즈 표준편차 이득의 기준을 만든다. 추정된 노이즈의 표준편차와 이득을 이용하여 CIR 샘플들이 기준값 이하 일 때 채널 길이 안에 있는 노이즈 성분을 스무딩을 한다. 시뮬레이션 결과는 채널의 MSE(Mean Square Error)와 BER(Bit Error Rate)을 통하여 제안된 기법을 적용할 때 성능 개선이 나타남을 확인 할 수 있었다.