• 산경연구논집
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• 제8권4호
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• pp.15-21
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• 2017

Purpose - In this work, we examined the causal relationship between credit loans from households (CLH), loan collateralized with housing (LCH) and an interest of certificate of deposit (ICD) among others in South Korea. Furthermore, the optimal forecasts on the underlying model will be obtained and have the potential for applications in the economic field. Research design, data, and methodology - A total of 31 realizations sampled from the 4th quarter in 2008 to the 4th quarter in 2016 was chosen for this research. To achieve the purpose of this study, a regression model with correlated errors was exploited. Furthermore, goodness-of-fit measures was used as tools of optimal model-construction. Results - We found that by applying the regression model with errors component ARMA(1,5) to CLH, the steep and lasting rise can be expected over the next year, with moderate increase of LCH and ICD. Conclusions - Based on 2017-2018 forecasts for CLH, the precipitous and lasting increase can be expected over the next two years, with gradual rise of two major explanatory variables. By affording the assumption that the feedback among variables can exist, we can, in the future, consider more generalized models such as vector autoregressive model and structural equation model, to name a few.

• Asian-Australasian Journal of Animal Sciences
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• 제28권4호
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• pp.592-598
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• 2015

Stress adversely affects the wellbeing of commercial chickens, and comes with an economic cost to the industry that cannot be ignored. In this paper, we first develop an inexpensive and non-invasive, automatic online-monitoring prototype that uses sound data to notify producers of a stressful situation in a commercial poultry facility. The proposed system is structured hierarchically with three binary-classifier support vector machines. First, it selects an optimal acoustic feature subset from the sound emitted by the laying hens. The detection and classification module detects the stress from changes in the sound and classifies it into subsidiary sound types, such as physical stress from changes in temperature, and mental stress from fear. Finally, an experimental evaluation was performed using real sound data from an audio-surveillance system. The accuracy in detecting stress approached 96.2%, and the classification model was validated, confirming that the average classification accuracy was 96.7%, and that its recall and precision measures were satisfactory.

• 동력기계공학회지
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• 제11권4호
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• pp.103-108
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• 2007

In general, the swing motion of the crane is controlled and suppressed by activating the trolley motion. In many papers reported by us, we suggested a new type of anti-sway control system of the crane. In the proposed control system, a small auxiliary mass(moving-mass) is installed on the spreader and the swing motion is controlled by moving the auxiliary mass. The actuator reaction against the auxiliary mass applies inertial control forces to the container in order to reduce the swing motion in the desired manner. The measuring system is based on laser sensor or others. However it is not so useful in real world. Especially, in this paper, the image sensor is used to measures the motions of the spreader and the measured data are fed back to the controller in real time. The applied image processing technique is a kind of robust template matching method which is named Vector Code Correlation (VCC) and devised to consider the real environmental conditions. And the $H_{\infty}$ based control technique is applied to suppress swing motion of the crane. And the experimental result shows that the proposed measurement system based on image sensor and control system is useful and robust to disturbances.

• Communications for Statistical Applications and Methods
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• 제16권6호
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• pp.1005-1012
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• 2009

The area under the curve(AUC) is commonly used as a measure of the receiver operating characteristic(ROC) curve which displays the performance of a set of binary classifiers for all feasible ratios of the costs associated with true positive rate(TPR) and false positive rate(FPR). In the bipartite ranking problem where one has to compare two different observations and decide which one is "better", the AUC measures the quantity that ranking score of a randomly chosen sample in one class is larger than that of a randomly chosen sample in the other class and hence, the function which maximizes an AUC of bipartite ranking problem is different to the function which maximizes (minimizes) accuracy (misclassification error rate) of binary classification problem. In this paper, we develop a way to construct the unified framework for AUC maximizer including support vector machines based on maximizing large margin and logistic regression based on estimating posterior probability. Moreover, we develop an efficient algorithm for the proposed unified framework. Numerical results show that the propose unified framework can treat various methodologies successfully.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3611-3634
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• 2015

In this paper, we build a theoretical framework for quantitatively measuring and graphically representing the degrees of closeness centralization among performers assigned to enact a workflow procedure. The degree of closeness centralization of a workflow-performer reflects how near the performer is to the other performers in enacting a corresponding workflow model designed for workflow-supported organizational operations. The proposed framework comprises three procedural phases and four functional transformations, such as discovery, analysis, and quantitation phases, which carry out ICN-to-WsoN, WsoN-to-SocioMatrix, SocioMatrix-to-DistanceMatrix, and DistanceMatrix-to-CCV transformations. We develop a series of algorithmic formalisms for the procedural phases and their transformative functionalities, and verify the proposed framework through an operational example. Finally, we expatiate on the functional expansion of the closeness centralization formulas so as for the theoretical framework to handle a group of workflow procedures (or a workflow package) with organization-wide workflow-performers.

• 반도체디스플레이기술학회지
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• 제12권2호
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• pp.67-72
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• 2013

Temperature is a critical parameter in yield improvement for wafer manufacturing. In chemical vapor deposition (CVD) equipment, crack defect in ceramic heater leads to yield reduction, however, there is no suitable ceramic heater fault detection system for conventional CVD equipment. This paper proposes a short-time zero-crossing rate based fault detection method for the ceramic heater in CVD equipment. The proposed method measures the output signal ($V_{pp}$) of RF filter and extracts the zero-crossing rate (ZCR) as feature vector. The extracted feature vectors have a discriminant power and Gaussian mixture model (GMM) based fault detection method can detect fault in ceramic heater. Experimental results, carried out by measured signals provided by a CVD equipment manufacturer, indicate that the proposed method detects effectively faults in various process conditions.

• 한국전자거래학회지
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• 제18권1호
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• pp.97-105
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• 2013

방대한 량의 전자상거래 데이터 객체를 다루는데 같거나 유사한 객체들을 찾는 유사도 측정은 중요하다. 객체간 유사도 측정은 객체 쌍의 유사도 측정값을 비교하므로 객체 량이 많아질수록 오랜 시간이 걸린다. 최근의 여러 유사도 측정 연구에선 이를 더 효율적으로 수행하는 기법을 제시하고 실제 데이터 셋에서 그 성능을 평가해왔다. 본 논문에서는 이들 연구에서 사용하는 데이터 셋의 특성과 실험에서 사용되는 쓰레숄드 값이 가지는 의미에 대해 분석해본다. 이러한 분석은 새로운 유사도 측정 기법의 성능 평가 실험의 참조 기준을 제시하는 역할을 한다.

• 한국통신학회논문지
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• 제33권1C호
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• pp.94-101
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• 2008

본 논문에서는 실시간으로 빛의 편광상태(SOP)를 파악할 수 있는 장치를 소개한다. 소개하는 장치는 광파를 수평 선형편광과 수직 선형편광 성분으로 분리하고, 각각을 기준 광원의 수평 선형편광 및 수직 선형편광 성분들과 중첩시키고 이로부터 발생한 비트신호들을 시간 영역에서 측정하여 비교함으로써 광파의 SOP를 파악해 내는 순방향(feed-forward) 측정 시스템으로서 귀환(feedback) 방식을 이용하는 기존의 방식들에 비해 SOP 측정시간을 실시간으로 단축시키는 장점을 갖고 있다. 본 논문에서는 또한 SOP 측정 과정에서 수반될 수 있는 광소자의 복굴절 변화에 의한 측정 오차를 매우 간편하고 정확하게 제거할 수 있는 새로운 오차 보정 방식을 소개한다. 제안하는 시스템의 동작과 성능을 모의실험 및 광학 실험을 통해 입증하였다.

• 한국IT서비스학회지
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• 제11권1호
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• pp.211-221
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• 2012

Many metric-based classification models have been proposed to predict fault-proneness of software module. This paper presents two prediction models using Bayesian classifier which is one of the most popular modern classification algorithms. Bayesian model based on Bayesian probability theory can be a promising technique for software quality prediction. This is due to the ability to represent uncertainty using probabilities and the ability to partly incorporate expert's knowledge into training data. The two models, Na$\ddot{i}$veBayes(NB) and Bayesian Belief Network(BBN), are constructed and dimensionality reduction of training data and test data are performed before model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I error and Type II error, and compared with well-known prediction models, backpropagation neural network model and support vector machine model. The results show that the prediction performance of BBN model is slightly better than that of NB. For the data set with ambiguity, although the BBN model's prediction accuracy is not as good as the compared models, it achieves better performance than the compared models for the data set without ambiguity.

• Journal of Information Processing Systems
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• 제10권4호
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• pp.589-601
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• 2014

The performance of edge detection often relies on its ability to correctly determine the dissimilarities of connected pixels. For grayscale images, the dissimilarity of two pixels is estimated by a scalar difference of their intensities and for color images, this is done by using the vector difference (color distance) of the three-color components. The Euclidean distance in the RGB color space typically measures a color distance. However, the RGB space is not suitable for edge detection since its color components do not coincide with the information human perception uses to separate objects from backgrounds. In this paper, we propose a novel method for color edge detection by taking advantage of the HSV color space and the Mahalanobis distance. The HSV space models colors in a manner similar to human perception. The Mahalanobis distance independently considers the hue, saturation, and lightness and gives them different degrees of contribution for the measurement of color distances. Therefore, our method is robust against the change of lightness as compared to previous approaches. Furthermore, we will introduce a noise-resistant technique for determining image gradients. Various experiments on simulated and real-world images show that our approach outperforms several existing methods, especially when the images vary in lightness or are corrupted by noise.