• Journal of Biosystems Engineering
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• 제30권5호
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• pp.293-298
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• 2005

The purpose of this study was the development of a multi-joint robot manipulator for milking robot system. The multi-joint robot manipulator was controlled by 5 drivers with driver controller through the position information obtained from the image processing system. The robot manipulator to automatically attach each teat cup to the teats of a milking cow was developed and it's motion was accurately measured with error rate. Results were as follows. 1. Maximum errors in position accuracy were 4mm along X-axis, 4.5mm along Y-axis and 0.9mm along Z-axis. Absolute distance errors were maximum 4.8mm, minimum 2.7mm, and average 3.6mm. 2. Errors of repeatability were maximum 3.0mm along X-axis, 3.0mm along Y-axis, and 0.5mm along Z-axis. Distance error values were maximum 3.2mm, minimum 2.2mm, and average 2.5mm. It is envisaged that multi-joint robot manipulator can be applicate to milking robot system being developed in consideration of the experiment results.

• Membrane and Water Treatment
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• 제9권5호
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• pp.363-371
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• 2018

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.

• 무역학회지
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• 제47권3호
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• pp.211-232
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• 2022

Due to the impact of the public health event COVID-19 epidemic, the Chinese futures market showed "Black Swan". This has brought the unpredictable into the economic environment with many commodities falling by the daily limit, while gold performed well and closed in the sunshine(Yan-Li and Rui Qian-Wang, 2020). Volatility is integral part of financial market. As an emerging market and a special precious metal, it is important to forecast return of gold futures price. This study selected data of the SHFE gold futures returns and conducted an empirical analysis based on the generalised autoregressive conditional heteroskedasticity (GARCH)-type model. Comparing the statistics of AIC, SC and H-QC, ARMA (12,9) model was selected as the best model. But serial correlation in the squared returns suggests conditional heteroskedasticity. Next part we established the autoregressive moving average ARMA-GARCH-type model to analysis whether Volatility Clustering and the leverage effect exist in the Chinese gold futures market. we consider three different distributions of innovation to explain fat-tailed features of financial returns. Additionally, the error degree and prediction results of different models were evaluated in terms of mean squared error (MSE), mean absolute error (MAE), Theil inequality coefficient(TIC) and root mean-squared error (RMSE). The results show that the ARMA(12,9)-TGARCH(2,2) model under Student's t-distribution outperforms other models when predicting the Chinese gold futures return series.

• 한국정보통신학회논문지
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• 제20권1호
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• pp.142-152
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• 2016

실내 측위 분야에서는 사용할 수 없는 GPS 의 한계를 극복하기 위해 대두되고 있는 기술들은 대부분 사설 무선 통신망(Private Wireless Network)를 이용한 방법이다. 그러나 이러한 방법들은 설치 및 유지 보수비용이 많이 들고 측위 오차가 수 미터로 실내 주차장 등 정밀한 측위가 필요한 장소에서 사용하기에 부적합하다. 본 논문에서는 QR 코드 인식 기반 차량용 실내 측위 방법을 제안하였다. QR 코드 스캔을 통해 절대 좌표를 얻고 아핀 변환(affine transform)을 통한 기울기(Tilt) 및 회전(Roll) 보정과 스케일 변환 및 삼각함수를 이용한 카메라의 위치 정보(상대좌표)를 획득하여 정밀한 위치 좌표를 계산한다. 결과적으로 13.79cm 의 평균 오차를 달성해 기존 무선 네트워크 기반 기술의 오차 50cm 대비 단지 27.6% 정도 오차율에 해당함을 확인하였다.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
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• pp.500-510
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• 1996

A Direct injection -mixing total -flow -control sprayer was developed and evaluated . The system provided precise application rates and minimized operator exposure to chemicals as well as providing a possibility for recycling container so f unused chemicals that can causes environmental contamination. Chemicals were metered and injected proportionally to the diluent flow rate to provide constant concentrations. The main diluent flow was varied in response to changes in travel speed. Experimental variables of the sprayer were the control interval, the sensitivity of flow regulating valve, the tolerance of control object and the sensitivity of the injection pump system. The optimal performance of the flow control system was with an average response time of 8.5 sec at an absolute steady state of error of 0.067 L/min (0.8% of flow rate). The average response time of the injection rate was -0.53 sec and the coefficient of variation (CV) of concentration was 3.2%.

• 설비공학논문집
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• 제21권11호
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• pp.629-635
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• 2009

In this study, fin surface temperature and frost properties, i.e., frost thickness and frost surface temperature on a heat exchanger, were experimentally analyzed with different fin thicknesses, fin sizes and thermal conductivities of fin. As a result, it is found that fin thickness and thermal conductivity of fin should be considered in order to design an efficient heat exchanger fin. Correlations of dimensionless average frost properties were proposed as functions of dimensionless air temperature, dimensionless fin base temperature, dimensionless fin thickness, absolute air humidity, Reynolds number and Fourier number. The correlations predicted well the average frost thickness with a maximum error of 10.5% and frost surface temperature with a maximum difference of $0.89^{\circ}C$, respectively.

• 한국멀티미디어학회논문지
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• 제13권11호
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• pp.1698-1705
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• 2010

본 논문에서는 자기 공명 영상에서 고속의 간 분할 기법을 제안한다. 제안 기법은 MR 영상을 정규화된 기울기 크기 정보를 바탕으로 효율적으로 객체와 경계로 구분한다. 다음으로 간 영역에 해당하는 객체를 직전에 분할된 슬라이스의 간 영역에서 추출된 씨앗점들로 2차원 씨앗점 영역 성장법을 이용하여 검출한다. 마지막으로 롤링 볼 알고리즘과 연결 요소 분석 기법을 사용하여 간 경계 부근의 위양성 오차를 최소화한다. 20명의 환자 데이터에 대하여 제안 기법으로 분할한 결과와 수작업으로 분할한 결과를 비교하여 정확성을 검증하였다. 평균 볼륨 오버랩 오차 5.2%였고, 평균 절대값 볼륨 측정 오차는 1.9%였다. 제안 기법으로 한 환자 데이터를 분할하는 데 소요되는 평균 시간은 약 3초 정도였다. 제안 기법은 빠르고, 정확한 간 분할을 필요로 하는 컴퓨터 보조 간 진단 기법에 사용될 수 있다.

• 한국가스학회지
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• 제23권5호
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• pp.52-58
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• 2019

본 연구에서는 국내 도시가스 인수량에 대한 예측 모델을 개발하였다. 국내의 도시가스 회사는 KOGAS에 차년도 수요를 예측하여 보고해야 하므로 도시가스 인수량 예측은 도시가스 회사에 중요한 사안이다. 도시가스 사용량에 영향을 미치는 요인은 용도구분에 따라 다소 상이하나, 인수량 데이터는 용도별 구분이 어렵기 때문에 특정 용도에 관계없이 영향을 주는 요인으로 외기온도를 고려하여 모델개발을 실시하였다.실험 및 검증은 JB주식회사의 2008년부터 2018년까지 총 11년 치 도시가스 인수량 데이터를 사용하였으며, 전통적인 시계열 분석 중 하나인 ARIMA(Auto-Regressive Integrated Moving Average)와 딥러닝 기법인 LSTM(Long Short-Term Memory)을 이용하여 각각 예측 모델을 구축하고 두 방법의 단점을 최소화하기 위하여 다양한 앙상블(Ensemble) 기법을 사용하였다. 본 연구에서 제안한 일별 예측의 오차율 절댓값 평균은 Ensemble LSTM 기준 0.48%, 월별 예측의 오차율 절댓값 평균은 2.46%, 1년 예측의 오차율 절댓값 평균은 5.24%임을 확인하였다.

• Steel and Composite Structures
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• 제21권4호
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• pp.921-947
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• 2016

Concrete Filled Fibre Reinforced Polymer Tube (CFFT) for new columns construction has attracted significant research attention in recent years. The CFFT acts as a formwork for new columns and a barrier to corrosion accelerating agents. It significantly increases both the strength capacity (Strength enhancement ratio) and the ductility (Strain enhancement ratio) of reinforced concrete columns. In this study, based on predefined selection criteria, experimental investigation results of 134 circular CFFT columns under axial compression have been compiled and analysed from 599 CFFT specimens available in the literature. It has been observed that actual confinement ratio (expressed as a function of material properties of fibres, diameter of CFFT and compressive strength of concrete) has significant influence on the strength and ductility of circular CFFT columns. Design oriented models have been proposed to compute the strength and strain enhancement ratios of circular CFFT columns. The proposed strength and strain enhancement ratio models have significantly reduced Average Absolute Error (AAE), Mean Square Error (MSE), Relative Standard Error of Estimate (RSEE) and Standard Deviation (SD) as compared to other available strength and strain enhancement ratios of circular CFFT column models. The predictions of the proposed strength and strain enhancement ratio models match well with the experimental strength and strain enhancement ratios investigation results in the compiled database.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.349-363
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• 2020

Penalized spline is a suitable nonparametric approach in estimating mean model in small area. However, application of the approach in informative sampling in a published article is uncommon. We propose a semiparametric mixed-model using penalized spline under informative sampling to estimate mean of small area. The response variable is explained in terms of mean model, informative sample effect, area random effect and unit error. We approach the mean model by penalized spline and utilize a penalized spline function of the inclusion probability to account for the informative sample effect. We determine the best and unbiased estimators for coefficient model and derive the restricted maximum likelihood estimators for the variance components. A simulation study shows a decrease in the average absolute bias produced by the proposed model. A decrease in the root mean square error also occurred except in some quadratic cases. The use of linear and quadratic penalized spline to approach the function of the inclusion probability provides no significant difference distribution of root mean square error, except for few smaller samples.