• Journal of KIISE:Databases
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• v.33 no.1
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• pp.42-55
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• 2006

We propose a single Index approach for subsequence matching that supports moving average transform of arbitrary order in time-series databases. Using the single index approach, we can reduce both storage space overhead and index maintenance overhead. Moving average transform is known to reduce the effect of noise and has been used in many areas such as econometrics since it is useful in finding overall trends. However, the previous research results have a problem of occurring index overhead both in storage space and in update maintenance since tile methods build several indexes to support arbitrary orders. In this paper, we first propose the concept of poly-order moving average transform, which uses a set of order values rather than one order value, by extending the original definition of moving average transform. That is, the poly-order transform makes a set of transformed windows from each original window since it transforms each window not for just one order value but for a set of order values. We then present theorems to formally prove the correctness of the poly-order transform based subsequence matching methods. Moreover, we propose two different subsequence matching methods supporting moving average transform of arbitrary order by applying the poly-order transform to the previous subsequence matching methods. Experimental results show that, for all the cases, the proposed methods improve performance significantly over the sequential scan. For real stock data, the proposed methods improve average performance by 22.4${\~}$33.8 times over the sequential scan. And, when comparing with the cases of building each index for all moving average orders, the proposed methods reduce the storage space required for indexes significantly by sacrificing only a little performance degradation(when we use 7 orders, the methods reduce the space by up to 1/7.0 while the performance degradation is only $9\%{\~}42\%$ on the average). In addition to the superiority in performance, index space, and index maintenance, the proposed methods have an advantage of being generalized to many sorts of other transforms including moving average transform. Therefore, we believe that our work can be widely and practically used in many sort of transform based subsequence matching methods.

• The Journal of the Korea Contents Association
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• v.3 no.3
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• pp.85-97
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• 2003

Medical tomography images like CT, MRI, PET, SPECT, fMRI, ett have been widely used for diagnosis and treatment of a patient and for clinical study in hospital. In many cases, tomography images are scanned in several different modalities or with time intervals for a single subject for extracting complementary information and comparing one another. 3D image registration is mapping two sets of images for comparison onto common 3D coordinate space, and may be categorized to marker -based matching and feature-based matching. 3D registration of brain images has an important role for visual and quantitative analysis in localization of treatment area of a brain, brain functional research, brain mapping research, and so on. In this article, marker-based and feature-based matching methods which are often used are introduced.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.357-364
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• 1997

The early detection of breast cancer is clearly a key ingredient for reducing breast cancer mortality. Microcalcification is the only visible feature of the DCIS's(ductal carcinoma in situ) which consist 15 ~ 20% of screening-detected breast cancer. Therefore, the analysis of the shapes and distributions of microcalcifications is very significant for the early detection. The automatic detection procedures have b(:on the concern of digital image processing for many years. We proposed here one efficient method which is essentially statistical pattern classification accelerated by one representative feature, correlation coefficient. We compared the results by this additional feature with results by a simple gray level thresholding. The average detection rate was increased from 48% by gray level feature only to 83% by the proposed method The performances were evaluated with TP rates and FP counts, and also with Bayes errors.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.19-24
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• 2022

"Know thyself" is one of the most famous ancient proverbs. We need to know ourselves to understand others and find true ourselves. Enneagram is one of the tools we can use to do it. It has drawn more and more attention from people by its effectiveness and spiritual depth. It has been widely promoted in both business management and spirituality contexts. It has many concepts to be understood. Holy ideas and virtues are understood to be restored to find our true self which is the purpose of using the Enneagram. Actually, holy ideas and virtues are similar with character qualities which comprise character. In this paper, holy ideas and virtues are matched with corresponding character qualities. To promote transformative process of character development through Enneagram, an app was designed. It has 2 levels. Level 1 is to find personality type and show corresponding character qualities of 9 personality types to users. Level 2 is to find subtypes and Enneagram Levels of Development for further purpose.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.2
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• pp.3-9
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• 2009

When washing machine is rotated in the laundry, it tends to lean toward one side. This tendency causes a serious vibration. The balance of washing machine plays an important role in order to reduce the vibration by injecting the sand or the salt water into the balance of washing machine. The hot plate welder is used to prevent from outflow of contents. The hot plate welder brings about many problems which is concerned with accidents. The direction recognition and location information of the balance are required in this system. In this paper, the recognition direction of balance in washing machine using machine vision system is studied. The template matching algorithm compares sub-image with original image acquired in real-time to obtain a center point of balance image. The mid points and the edges of balance are estimated by the edge detection and gauging algorithms. The data acquired by these results is used for recognition direction of balance. The automation software for image processing is developed by using LabVIEW.

• Journal of Construction Engineering and Project Management
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• v.3 no.1
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• pp.35-38
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• 2013

No single project is identical to one another in the construction industry. Furthermore, many construction projects are suffering from tighter budget, shortened schedule and higher client satisfaction level. To overcome these, project managers and engineers are willing to apply various best management practices to their projects. However, it is non-trivial to select the most appropriate practices for their projects. In many cases, it is much more important to find the appropriateness of the management practices than just to use the practices. Although many researchers are focusing on the development of new management practices, there is little research on matching between the circumstances of projects and the developed management practices. The objective of this study is to provide a structured process to suggest the best management practices for individual construction projects by developing a computerized system where an individual project is matched with the most optimal management practices to increase the value of the project. At this stage of writing, the authors have developed a computerized system to effectively find out the best suitable management practices for individual projects. By maximizing the usages of this system, it would facilitate the application of the best management practices in the industry.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.624-627
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• 2013

No single project is identical to one another in the construction industry. Furthermore, many construction projects are suffering from tighter budget, shortened schedule and higher client satisfaction level. To overcome these, project managers and engineers are willing to apply various best management practices to their projects. However, it is non-trivial to select the most appropriate practices for their projects. In many cases, it is much more important to find the appropriateness of the management practices than just to use the practices. Although many researchers are focusing on the development of new management practices, there is little research on matching between the circumstances of projects and the developed management practices. The objective of this study is to provide a structured process to suggest the best management practices for individual construction projects by developing a computerized system where an individual project is matched with the most optimal management practices to increase the value of the project. At this stage of writing, the authors have developed a computerized system to effectively find out the best suitable management practices for individual projects. By maximizing the usages of this system, it would facilitate the application of the best management practices in the industry.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.509-516
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• 2001

As results of many genome projects, genomic sequences of many organisms are revealed. Various methods such as global alignment, local alignment are used to analyze the sequences of the organisms, and k -mer analysis is one of the methods for analyzing the genomic sequences. The k -mer analysis explores the frequencies of all k-mers or the symmetry of them where the k -mer is the sequenced base with the length of k. However, existing on-memory algorithms are not applicable to the k -mer analysis because a whole genomic sequence is usually a large text. Therefore, efficient data structures and algorithms are needed. String B-tree is a good data structure that supports external memory and fits into pattern matching. In this paper, we improve the string B-tree in order to efficiently apply the data structure to k -mer analysis, and the results of k -mer analysis for C. elegans and other 30 genomic sequences are shown. We present a visualization system which enables users to investigate the distribution and symmetry of the frequencies of all k -mers using CGR (Chaotic Game Representation). We also describe the method to find the signature which is the part of the sequence that is similar to the whole genomic sequence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2619-2625
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• 2011

The GPS technique widely used recently in car navigation system has two problems that are unavailability in urban canyons and inherent positional error rate. The one has been studied and solved in many literatures. However, the other still leads to incorrect locational information in some area, especially parallel roads. This paper proposes and implements a system to recognize lane of moving vehicle based on images obtained from in-vehicle networks or other devices. The proposed system utilizes a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. It also employs a method for accuracy improvement. The results obtained from experimental test on real-time navigation show that the proposed systems works well and the accuracy increases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2346-2362
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• 2016

As one of the most important issues in computer vision and image processing, online object tracking plays a key role in numerous areas of research and in many real applications. In this study, we present a novel tracking method based on the proposed structured sparse representation model, in which the tracked object is assumed to be sparsely represented by a set of object and background templates. The contributions of this work are threefold. First, the structure information of all the candidate samples is utilized by a joint sparse representation model, where the representation coefficients of these candidates are promoted to share the same sparse patterns. This representation model can be effectively solved by the simultaneous orthogonal matching pursuit method. In addition, we develop a tracking algorithm based on the proposed representation model, a discriminative candidate selection scheme, and a simple model updating method. Finally, we conduct numerous experiments on several challenging video clips to evaluate the proposed tracker in comparison with various state-of-the-art tracking algorithms. Both qualitative and quantitative evaluations on a number of challenging video clips show that our tracker achieves better performance than the other state-of-the-art methods.