• Journal of KIISE:Databases
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• v.34 no.1
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• pp.18-34
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• 2007

In order to provide various business analysis methods, OLAP(On-Line Analytical Processing) systems represent their data with multidimensional structures. These multidimensional data are often delivered to users in the horizontal format of tables whose columns are corresponding to values of dimension attributes. Since the horizontal tables nay have a large number of columns, they cannot be stored directly in relational database systems. Furthermore, the tables are likely to have many null values (i.e., sparse tables). In order to manage the horizontal tables efficiently, we can store them as the vertical format of tables which has dimension attribute names as their columns thus transforms the columns of horizontal tables into rows. In this way, every queries for horizontal tables have to be transformed into those for vertical tables. This paper proposed a technique for transforming horizontal table queries into vertical table ones by utilizing not only traditional relational algebraic operators but also the PIVOT operator which recent DBMS versions are providing. For achieving this goal, we designed a relational algebraic expression equivalent to the PIVOT operator and we formally proved their equivalence. Then, we developed a transformation technique for horizontal table queries using the PIVOT operator. We also performed experiments to analyze the performance of the proposed method. From the experimental results, we revealed that the proposed method has better performance than existing methods.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1284-1289
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• 2014

In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.986-994
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• 2016

In this paper, a digital closed-circuit television (CCTV) transmission system called the extended reach high definition serial digital interface (ER-SDI) is proposed to increase the transmission distance while preserving the quality using digital modulation. The current standard of HD-serial digital interface (HD-SDI) has the maximum transmission distance of 200 m. Recently, one system which transforms the digital signal to an analog signal and modulates color signal to extend the transmission distance is proposed. Another system which uses IP network is also proposed. However, the former system has a disadvantage of video quality and the latter system has high latency. The proposed ER-SDI is designed to extend the transmission distance of 518 m by adopting multilevel constellations and a channel code for a data rate of 1.485 Gbps. The maximum transmission distance of the proposed system is calculated using the specification of HD-SDI and the experiment result under coaxial cable environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.106-113
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• 2003

The modified discrete cosine transform (MDCT) and inverse MDCT (IMDCT) are employed in subband/transform coding schemes as the analysis/synthesis filter bank based on time domain aliasing cancellation (TDAC). And the MDCT and IMDCT are the most computational intensive operations in layer III of the MPEG audio coding standard. In this paper, we propose a new efficient algorithm for the MDCT/IMDCT computation in various audio coding systems. It is based on the MDCT/IMDCT computation algorithm using the discrete cosine transforms (DCTs), and It employs two discrete cosine transform of type II (DCT-II) to compute the MDCT/IMDCT In addition, it takes advantage of ability in calculating the MDCT/IMDCT computation, where the length of a data block Is divisible by 4. The Proposed algorithm in this paper requires less calculation complexity than the existing method does. Also, it can be implemented by the parallel structure, therefore its structure is particularly suitable for VLSI realization

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2403-2408
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• 2015

For image data the discrete cosine transform (DCT) has comparable energy compaction capability to Karhunen-Loeve transform (KLT) which is optimal. Hence DCT has been widely accepted in various image and video compression standard such as JPEG, MPEG-2, and MPEG-4. Recently some approximate DCT's have been reported, which can be computed much faster than the original DCT because their coefficients are either zero or the power of 2. Although the level of energy compaction is slightly degraded, the approximate DCT's can be utilized in real time implementation of image or visual compression applications. In this paper, an approximate 8-point DCT which contains 17 non-zero power-of-2 coefficients and high energy compaction capability comparable to DCT is proposed. Transform coding experiments with several images show that the proposed transform outperforms the published works.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8B
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• pp.787-795
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• 2002

This paper presents the architecture and the implementation of a 2K/4K/8K-point complex Fast Fourier Transform(FFT) processor for Orthogonal Frequency-Division Multiplexing (OFDM) system. The architecture is based on the Cooley-Tukey algorithm for decomposing the long DFT into short length multi-dimensional DFTs. The transposition memory, shuffle memory, and memory mergence method are used for the efficient manipulation of data for multi-dimensional transforms. Booth algorithm and the COordinate Rotation DIgital Computer(CORDIC) processor are employed for the twiddle factor multiplications in each dimension. Also, for the CORDIC processor, a new twiddle factor generation method is proposed to obviate the ROM required for storing the twiddle factors. The overall 2K/4K/8K-FFT processor requires 600,000 gates, and it is implemented in 1.8 V, 0.18 ${\mu}m$ CMOS. The processor can perform 8K-point FFT in every 273 ${\mu}s$, 2K-point every 68.26 ${\mu}s$ at 30MHz, and the SNR is over 48dB, which are enough performances for the OFDM in DVB-T.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.13-20
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• 2016

In this paper, we propose an object recognition system that can effectively find out its category, its instance name, and several attributes from the color and depth images of an object with hierarchical feature learning. In the preprocessing stage, our system transforms the depth images of the object into the surface normal vectors, which can represent the shape information of the object more precisely. In the feature learning stage, it extracts a set of patch features and image features from a pair of the color image and the surface normal vector through two-layered learning. And then the system trains a set of independent classification models with a set of labeled feature vectors and the SVM learning algorithm. Through experiments with UW RGB-D Object Dataset, we verify the performance of the proposed object recognition system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.388-396
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• 2009

This paper proposes a new fire-smoke detection method by using extracted features from camera images and pattern recognition technique. First, moving regions are detected by analyzing the frame difference between two consecutive images and generate candidate smoke regions by applying smoke color model. A smoke region generally has a few characteristics such as similar color, simple texture and upward motion. From these characteristics, we extract brightness, wavelet high frequency and motion vector as features. Also probability density functions of three features are generated using training data. Probabilistic models of smoke region are then applied to observation nodes of our proposed Dynamic Bayesian Networks (DBN) for considering time continuity. The proposed algorithm was successfully applied to various fire-smoke tasks not only forest smokes but also real-world smokes and showed better detection performance than previous method.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.307-318
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• 2008

One of the primary issues confronting XML message brokers is the difficulty associated with processing a large set of continuous XPath queries over incoming XML seams. This paper proposes a novel system designed to present an effective solution to this problem. The proposed system transforms multiple XPath queries before their run-time into a new region-based data structure, called an XP-table, by sharing their common constraints. An XP-table is matched with a stream relation (SR) transformed from a target XML stream by a SAX parser. This arrangement is intended to minimize the runtime workload of continuous query processing. Also, system performance is estimated and verified through a variety of experiments, including comparisons with previous approaches such as YFilter and LazyDFA. The proposed system is practically linear- scalable and stable for evaluating a set of XPath queries in a continuous and timely fashion.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.1-7
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• 2006

This paper proposes a new method that reduces the complexity of the combined system, which consists of the selective mapping(SLM) and the partial transmit sequence(PTS) in the Orthogonal Frequency Division Multiplexing(OFDM). In order to reduce the Peak-to-Average Power Ratio(PAPR), many techniques have been developed such as SLM and PTS. and their combined systems. However the method that simply combines PTS and SLM to improve the effectiveness of a system increases the complexity of calculation. The scheme employed in this research suggests a system that combines PTS and SLM reducing the complexity via the N($N=2^n$)-point inverse fast Fourier transforms(IFFT), which uses the decimation in time domain not only to improve PAPR but also to reduce the amount of calculation. The proposed method reduces the complexity by multiplying a phase sequence and a subblock index to the data sequences in the middle of IFFT, which yields an optimal sequence with minimal PAPR. The superiority of the proposed method is demonstrated by simulation results and analysis.