• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1311-1321
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• 1997

In multibody dynamics, differential and algebraic equations which can satisfy both equation of motion and kinematic constraint equation should be solved. To solve these equations, coordinate partitioning method and constraint stabilization method are commonly used. In the coordinate partitioning method, the coordinates are divided into independent and dependent and coordinates. The most typical coordinate partitioning method are LU decomposition, QR decomposition, and SVD (singular value decomposition). The objective of this research is to find an efficient coordinate partitioning method in the dynamic analysis of flexible multibody systems. Comparing two coordinate partitioning methods, i.e. LU and QR decomposition in the flexible multibody systems, a new hybrid coordinate partitioning method is suggested for the flexible multibody analysis.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.47-53
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• 2018

This paper proposes a method to express an MP3 audio file by a series of color QR codes which can be printed on the paper. Moreover, the method can compress the data considerably. Firstly, an MP3 file is divided into many small files which have maximum capacity of binary file of a QR code. Secondly, the multiple files are converted to multiple black-and-white QR codes. Lastly, every three QR codes are combined into color QR codes. When combining, each of three black-and-white QR codes are regarded as red, green, blue components respectively. In this method, the areas of a color QR code where two QR codes are overlapped are expressed by the colors Cyan, Magenta and Yellow. And the areas where three components are overlapped are expressed by white color. Contrarily, the areas that no components are overlapped are expressed by white color. Experimentation result shows that an MP3 file with 8.5MB the original MP3 files are compressed with the compression rate around 15.7. This method has the advantage that can be used in the environments that the internet access is impossible.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.867-878
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• 2006

In the past few years, the research of sensor networks is forced dramatically. Specially, while the research for maintaining the power of a sensor is focused, we are also concerned nth query processing related with the optimization of multiple continuous queries for decreasing in unnecessary energy consumption of sensor networks. We present the fragmentation algorithm to solve the redundancy problem in multiple continuous queries that increases in the count or the amount of transmitting data in sensor networks. The fragmentation algorithm splits one query into more than two queries using the query index (QR-4ree) in order to reduce the redundant query region between a newly created query and the existing queries. The R*-tree should be reorganized to the QR-tree right to the structure suggested. In the result, we preserve 20 percentage of the total energy in the sensor networks.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.43-46
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• 2006

최근 센서네트워크에 관련된 많은 연구가 진행되고 있다. 특히, 센서의 전력 보전을 위한 많은 기술들이 개발되고 있는데, 본 논문에서는 센서 네트워크의 불필요한 전력 소비를 줄이는 다중 연속질의 최적화에 관련된 방법을 제시한다. 우리는 센서 네트워크에서 전송되는 데이터의 횟수나 전송량의 원천적 문제가 되는 다중 연속 질의의 중복성 문제를 해결하는 분할 알고리즘을 제안한다. 분할 알고리즘은 새롭게 생성된 사용자 질의와 기존의 질의 들 사이에 질의 중첩 질의 영역을 제거하기 위해, QR-트리 기반의 질의 인덱스를 통해 하나의 질의를 둘 이상의 질의로 분할하는 알고리즘이다. QR-트리는 효율적인 질의 분할을 위해, $R^*$-트리를 본 논문의 구조에 맞게 개량한 것이다.

• The Research Journal of the Costume Culture
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• v.17 no.4
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• pp.723-732
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• 2009

The quick response(QR) system is very popular in Korean apparel companies. However, the usage of QR system was not known well. The purpose of this study is to identify the usage of the quick response decision support system(QR DSS) and postponement manufacturing in the Korean apparel company. The researched company was the only one which used the QR DSS. The researchers carried out the depth interview with the QR decision makers of the company. This company had 14 brands, and had used the QR DSS since January, 2008. The results are as follows: The QR DSS was supportive computer software program, and it helped the staffs to make agile decision about QR repeat production of clothing. The QR DSS automatically calculated the related data, and suggested the expected sales volume and the proper supply amounts of the styles. There were four functions in QR DSS : 'QR Alert', 'Proper Supply Amount Simulation', 'Sensible QR', and 'Supply/Sales Simulation by Item'. The men's clothing brands effectively used 'Supply/Sales Simulation by Item' function. And the women's clothing brands effectively used 'QR Alert' function. This company also used the postponement production system for QR repeat production. The postponement production was conducted with four methods : the yarn stocking, the grey fabric stocking, the dyed fabric stocking, and the fabric sourcing. The men's clothing brands usually used of the yarn stocking methods and the dyed fabric stocking methods. The women's clothing brands usually used the grey fabric stocking methods. By using QR DSS and postponement production system the company was able to shorten the lead time for QR decision making.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.267-275
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• 2019

Currently, due to the widespread use of a smartphone, QR codes allow users to access a variety of added services. However, the QR codes posted on curved surfaces tend to be non-uniformly illuminated and bring about the decline of recognition rate. So, in this paper, the block-adaptive binarization policy is adopted to find an optimal threshold appropriate for bimodal image like QR codes. For a large block, its histogram distribution is found to get an initial threshold and then the block is partitioned to reflect the local characteristics of small blocks. Also, morphological operation is applied to their neighboring boundary at the discontinuous at the QR code junction. This paper proposes an authentication method based on the color code, uniquely painted within QR code. Through a variety of practical experiments, it is shown that the proposed algorithm outperforms the conventional method in detecting QR code and also maintains good recognition rate up to 40 degrees on curved surfaces.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.67-76
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• 2018

This paper addresses the problem of efficient processing of region monitoring queries. The centralized methods used for existing region monitoring query processing assumes that the mobile object periodically sends location-updates to the server and the server continues to update the query results. However, a large amount of location updates seriously degrade the system performance. Recently, some distributed methods have been proposed for region monitoring query processing. In the distributed methods, the server allocates to all objects i) a resident domain that is a subspace of the workspace, and ii) a number of nearby query regions. All moving objects send location updates to the server only when they leave the resident domain or cross the boundary of the query region. In order to allocate the resident domain to the moving object along with the nearby query region, we use a query index structure that is constructed by splitting the workspace recursively into equal halves. However, However, the above index structure causes unnecessary division, resulting in deterioration of system performance. In this paper, we propose an adaptive split method to reduce unnecessary splitting. The workspace splitting is dynamically allocated i) considering the spatial relationship between the query region and the resultant subspace, and ii) the distribution of the query region. We proposed an enhanced QR-tree with a new splitting method. Through a set of simulations, we verify the efficiency of the proposed split methods.

• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.435-442
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• 1999

A fuzzy-ART(adaptive resonance theory) network for the PVC(premature ventricular contraction) classification using wavelet coefficient is designed. This network consists of the feature extraction and learning of the fuzzy-ART network. In the first step, we have detected the QRS from the ECG signal in order to set the threshold range for feature extraction and the detected QRS was divided into several frequency bands by wavelet transformation using Haar wavelet. Among the low-frequency bands, only the 6th coefficient(D6) are selected as the input feature. After that, the fuzzy-ART network for classification of the PVC is learned by using input feature which comprises of binary data converted by applying threshold to D6. The MIT/BIH database including the PVC is used for the evaluation. The designed fuzzy-ART network showed the PVC classification ratio of 96.52%.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.163-168
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• 2011

In this paper, we proposed non-linear gamma curve algorithm for gamma correction. The previous non-linear gamma curve algorithm is generated by the least square polynomial using the Gauss-Jordan inverse matrix. However, the previous algorithm has some weak points. When calculating coefficients using inverse matrix of higher degree, occurred truncation errors. Also, only if input sample points are existed regular interval on 10-bit scale, the least square polynomial is accurately works. To compensate weak-points, we calculated accurate coefficients of polynomial using eigenvalue and orthogonal value of mat11x from singular value decomposition (SVD) and QR decomposition of vandemond matrix. Also, we used input data part segmentation, then we performed polynomial curve fitting and merged curve fitting results. When compared the previous method and proposed method using the mean square error (MSE) and the standard deviation (STD), the proposed segmented polynomial curve fitting is highly accuracy that MSE under the least significant bit (LSB) error range is approximately $10^{-9}$ and STD is about $10^{-5}$.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.569-578
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• 2020

By estimating conditional quantile functions of the response, quantile regression (QR) can provide comprehensive information of the relationship between the response and the predictors. In addition, kernel quantile regression (KQR) estimates a nonlinear conditional quantile function in reproducing kernel Hilbert spaces generated by a positive definite kernel function. However, it is infeasible to use the KQR in analysing a massive data due to the limitations of computer primary memory. We propose a divide and conquer based KQR (DC-KQR) method to overcome such a limitation. The proposed DC-KQR divides the entire data into a few subsets, then applies the KQR onto each subsets and derives a final estimator by aggregating all results from subsets. Simulation studies are presented to demonstrate the satisfactory performance of the proposed method.