• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1068-1069
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• 2012

시계열 데이타는 일정 시간 간격으로 측정한 값의 시퀀스를 뜻하는데, 사용자에 의해 주어진 질의 시퀀스와 유사한 데이타 시퀀스를 검색하는 방법을 유사 시퀀스 매칭이라고 한다. 본 논문에서는 유사 시퀀스 매칭 시, 질의 시퀀스로 MBR을 구성할 때 한 개의 MBR이 아닌 다수의 MBR로 구성하는 방법을 제안하였다. 다수의 MBR로 구성하여 질의 처리를 하면 질의 시퀀스의 길이가 길 경우 적은 비용으로 질의 처리를 수행할 수 있다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.95-98
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete -time system have proper reason. Sufficiently conditions for the global state -matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMls). Finally, we prove the effectiveness and stabilization of the proposed intelligent digital redesign method by applying the chaotic Lorentz system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2833-2850
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• 2014

This paper proposes a novel framework for traffic video classification based on chaotic features. First, each pixel intensity series in the video is modeled as a time series. Second, the chaos theory is employed to generate chaotic features. Each video is then represented by a feature vector matrix. Third, the mean shift clustering algorithm is used to cluster the feature vectors. Finally, the earth mover's distance (EMD) is employed to obtain a distance matrix by comparing the similarity based on the segmentation results. The distance matrix is transformed into a matching matrix, which is evaluated in the classification task. Experimental results show good traffic video classification performance, with robustness to environmental conditions, such as occlusions and variable lighting.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.623-632
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• 2009

In this paper, we propose a pulmonary nodule registration for the tracking of lung nodules in sequential CT scans. Our method consists of following five steps. First, a translational mismatch is corrected by aligning the center of optimal bounding volumes including each segmented lung. Second, coronal maximum intensity projection(MIP) images including a rib structure which has the highest intensity region in baseline and follow-up CT series are generated. Third, rigid transformations are optimized by normalized average density differences between coronal MIP images. Forth, corresponding nodule candidates are defined by Euclidean distance measure after rigid registration. Finally, template matching is performed between the nodule template in baseline CT image and the search volume in follow-up CT image for the nodule matching. To evaluate the result of our method, we performed the visual inspection, accuracy and processing time. The experimental results show that nodules in serial CT scans can be rapidly and correctly registered by coronal MIP-based rigid registration and local template matching.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.279-286
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• 2000

The objective of this research is to detect the papaya fruits on tree in an orchard. The detection of papaya on natural background is difficult because colors of fruits and background such as leaves are similarly green. We cannot separate it from leaves by color information. Therefore, this research will use shape information instead. First, we detect an interested object by detecting its boundary using edge detection technique. However, the edge detection will detect every objects boundary in the image. Therefore, shape description technique will be used to describe which one is the interested object boundary. The good shape description should be invariant in scaling, rotating, and translating. The successful concept is to use Fourier series, which is called "Fourier Descriptors". Elliptic Fourier Descriptors can completely represent any shape, which is selected to describe the shape of papaya. From the edge detection image, it takes a long time to match every boundary directly. The pre-processing task will reduce non-papaya edge to speed up matching time. The deformable template is used to optimize the matching. Then, clustering the similar shapes by the distance between each centroid, papaya can be completely detected from the background.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.949-954
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• 2010

Computing the rotation-invariant distance between image time-series is a time-consuming process that incurs a lot of Euclidean distances for all possible rotations. In this paper we propose an innovative solution that significantly reduces the number of Euclidean distances using the triangular inequality. To this end, we first present the notion of self rotation distance and show that, by using the self rotation distance with the triangular inequality, we can prune many unnecessary distance computations. We next present that only one self-rotation is enough for all self-rotation distances required. Experimental results show that our self rotation distance-based methods outperform the existing methods by up to an order of magnitude.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.173-184
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• 2002

This paper discuss an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, Kim et al. suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multidimensional index using a feature vector as indexing attributes. For query processing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verify the superiority of our approach, we perform extensive experiments. The results reveal that our approach achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.881-886
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.69-78
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• 2010

Spectral modeling synthesis (SMS) has been used as a powerful tool for musical sound modeling. This technique considers a sound as a combination of a deterministic plus a stochastic component. The deterministic component is represented by the series of sinusoids that are described by amplitude, frequency, and phase functions and the stochastic component is represented by a series of magnitude spectrum envelopes that functions as a time varying filter excited by white noise. These representations make it possible for a synthesized sound to attain all the perceptual characteristics of the original sound. However, sometimes considerable phase variations occur in the deterministic component by using the conventional SMS for the complex sound such as whale sounds when the partial frequencies in successive frames differ. This is because it utilizes the calculated phase to synthesize deterministic component of the sound. As a result, it does not provide a good spectrum matching between original and synthesized spectrum in higher frequency region. To overcome this problem, we propose a modified SMS that provides good spectrum matching of original and synthesized sound by calculating complex residual spectrum in frequency domain and utilizing original phase information to synthesize the deterministic component of the sound. Analysis and simulation results for synthesizing whale sounds suggest that the proposed method is comparable to the conventional SMS in both time and frequency domain. However, the proposed method outperforms the SMS in better spectrum matching.

• Knowledge Management Research
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• v.22 no.2
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• pp.1-17
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• 2021

In this study, we predicted the bitcoin prices of Bithum and Coinbase, a leading exchange in Korea and USA, using ARIMA and Recurrent Neural Networks(RNNs). And we used news articles from each country to suggest a separated RNN model. The suggested model identifies the datasets based on the changing trend of prices in the training data, and then applies time series prediction technique(RNNs) to create multiple models. Then we used daily news data to create a term-based dictionary for each trend change point. We explored trend change points in the test data using the daily news keyword data of testset and term-based dictionary, and apply a matching model to produce prediction results. With this approach we obtained higher accuracy than the model which predicted price by applying just time series prediction technique. This study presents that the limitations of the time series prediction techniques could be overcome by exploring trend change points using news data and various time series prediction techniques with text mining techniques could be applied to improve the performance of the model in the further research.