• Korean Journal of Environment and Ecology
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• v.22 no.1
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• pp.43-58
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• 2008

For this study, which was conducted in the summer from $2004\sim2007$, 10 small and medium sized streams in Korea were selected(Munsan and Gokreung Stream in the Han River watershed, Mi, Ssanggye and Nam Stream in the Nakdong River watershed, Gapeong and Jojong Stream in the Bukhan River watershed, Cheongmi, Yanghwa and Bokha Stream in the Namhan River watershed), and plant surveys were performed using the belt transect method on the most natural 1km sections of each stream in order to clarify the natural environment condition of the plants in each stream. In the results of the plant survey, the total number of plant species recorded was 296. After selecting 121 species of those surveyed plant in order of frequency, an RDA(Redundancy Analysis) and a Pearson Correlation Analysis were performed to determine the correlation between the selected plant species and environmental factors( such as distance from channel, size of bed material, number of bars, altitude, bed slope, width of channel, and measured data of water quality) of the study sites. There was no significant correlation between the 121 plant species and altitude, bed slope, and number of bars at the research sites, but the correlation of plant species with size of bed material, width of channel, electrical conductivity, and phosphate$(PO_4-P)$ concentration was from very high to moderate. Also, the spectrum of these plant species reflects the actual environmental conditions so the method used in the study seems to be correct, but owing to the range of diversity, the results of the study seem to be difficult to extend to other streams. Nevertheless, it is expected that this data can be used as a basic material for researching plants by stream characteristics or in selecting plant species for streams.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.486-493
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• 2002

In this paper, we proposed the effective multispectral image compression method using CIBP(classified interband bidrectional prediction) and extended SPIHT(set partition in hierarchical trees) in wavelet domain. We determine separately feature bands that have the highest correlation with other bands in the visible range and in the infrared range of wavelengths. Feature bands are coded to remove the spatial redundancy with SPIHT in the wavelet domain. Prediction bands that have high correlation with feature bands are wavelet transformed and they are classified into one of three classes considering reflection characteristics of the baseband. For Prediction bands, CIBP is performed to reduce the spectral redundancy. for the difference bands between prediction bands and the predicted bands, They are ordered to upgrade the compression efficiency of extended SPIHT with the largest error magnitude. The arranged bands are coded to compensate the prediction error with extended SPIHT. Experiments are carried out on the multispectral images. The results show that the proposed method reconstructs higher quality images than images reconstructed by the conventional methods at the same bit rate.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.307-315
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• 2014

A new modified lossless intra-coding method based on a cross residual transform is applied to HEVC(High Efficiency Video Coding). The HEVC standard including a multi-directional spatial prediction method to reduce spatial redundancy encodes the pixels in a PU (Prediction Unit) by using neighboring pixels. In the new modified lossless intra-coding method, the spatial prediction is performed by pixel-based DPCM but is implemented by block-based manner by using cross residual transform on the HEVC standard. The experimental results show that the new lossless intra-coding method reduces the bit rate of approximately 8.4% in comparison with the lossless-intra coding method in the HEVC standard and the proposed method results in slightly better compression ratio than the JPEG2000 lossless coding.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.80-87
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• 2010

The method of function synthesis is essential when we control the systems not known their characteristic, by predicting the function to satisfy a relation between input and output from the given pairs of input-output data. In general the most systems operate non-linearly, it is easy to come about problem is composed with combinations of parameter, constant, condition, and so on. Genetic programming is proposed by one of function synthesis methods. This is a search method of function tree to satisfy a relation between input and output, with appling genetic operation to function tree to convert function into tree structure. In this paper, we indicate problems of a function synthesis method by an existing genetic programming propose four type of new improved method. In other words, there are control of function tree growth, selection of local search method for early convergence, effective elimination of redundancy in function tree, and utilization of problem characteristic of object, for preventing function from complicating when the function tree is searched. In case of this improved method, we confirmed to obtain superior structure to function synthesis method by an existing genetic programming in a short period of time by means of computer simulation for the two-spirals problem.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.495-502
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• 2013

Motion estimation (ME) that limits the performance of image quality and encoding speed has been developed to reduce temporal redundancy in video sequences and plays an important role in digital video compression. But it is computational demanding part of the encoder. Multi-view video is obtained by capturing one three-dimensional scene with many cameras at different positions. ME for Multi-view video requires high computational complexity. To reduce computational complexity and maintain the image quality, a fast motion estimation method is proposed in this paper. The proposed method uses a hierarchical search strategy. This strategy method consists of modified diamond search patten, multi gird diamond search pattern, and raster search pattern. These search patterns place search points symmetrically and evenly that can cover the overall search area not to fall into the local minimum or exploits the characteristics of the distribution of motion vectors to place the search points. Experiment results show that the speedup improvement of the proposed method over TZ search method (JMVC) can be up to 1.2 ~3 times faster while maintaining similar video quality and bit rates.

• Structural Engineering and Mechanics
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• v.74 no.6
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• pp.821-832
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• 2020

The fundamental period is an important parameter for seismic design and seismic risk assessment of building structures. In this paper, a simplified theoretical method to predict the fundamental period of masonry infilled reinforced concrete (RC) frame is developed based on the basic theory of engineering mechanics. The different configurations of the RC frame as well as masonry walls were taken into account in the developed method. The fundamental period of the infilled structure is calculated according to the integration of the lateral stiffness of the RC frame and masonry walls along the height. A correction coefficient is considered to control the error for the period estimation, and it is determined according to the multiple linear regression analysis. The corrected formula is verified by shaking table tests on two masonry infilled RC frame models, and the errors between the estimated and test period are 2.3% and 23.2%. Finally, a probability-based method is proposed for the corrected formula, and it allows the structural engineers to select an appropriate fundamental period with a certain safety redundancy. The proposed method can be quickly and flexibly used for prediction, and it can be hand-calculated and easily understood. Thus it would be a good choice in determining the fundamental period of RC frames infilled with masonry wall structures in engineering practice instead of the existing methods.

• The Journal of the Acoustical Society of Korea
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• v.14 no.5
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• pp.89-93
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• 1995

To reduce the redundancy within samples that resulted from uniform sampling method, nonuniform sampling or nonredundant-sample coding methods can be considered. However, it is well known that when conventional nonuniform sampling methods are applied directly to speech signal, the required amount of data is comparable to or mure than that by uniform sampling method like PCM. To overcome this problem, a new nonuniform sampling method is proposed, in which nonuniform sampling is applied to the low-pass filtered speech signal and higher band is compensated by 8 colored Gaussian random noise with various noise levels. By this method, speech signal waveform can be encoded by 1.8 times larger compression ratio than the conventional nonuniform sampling method.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.7
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• pp.30-36
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• 2011

Three-dimensional (3D) memories using through-silicon vias (TSVs) as vertical bus across memory layers are implemented by many semiconductor companies. 3D memories are composed of known-good-dies (KGDs). If additional faults are arisen during bonding, they should be repaired. In order to enhance the yield of 3D memories with inter-die redundancies, a die-matching method is needed to effectively stack memory dies in a 3D memory. In this paper, a new die-matching method is proposed for 3D memory yield enhancement with inter-die redundancies considering additional faults arisen during bonding. Three boundary-limited conditions are used in the proposed die-matching method; they set bounds to the search spaces for selecting memory dies to manufacture a 3D memory. Simulation results show that the proposed die-matching method can greatly enhance the 3D memory yield.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.869-882
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• 2004

This paper proposes an effective method to create logically consistent and structured requirement model by applying consistency control approach of the formal method to the use-case modeling. This method integrates the multi-perspective scattered requirement segments that may overlap and conflict each other into a structured requirement model. The model structure can be analyzed based on context goal and concerned area overlap analysis. The model consistency can be achieved by using specification overlap-based consistency checking method as an integration vehicle. An experimental application to case study shows that the Proposed method can successfully identify requirement overlaps and inconsistency. It can also transfer multi-viewpoint requirement segments into a consistently integrated use-case model to clarify software behaviors and functionality This method helps users to enhance capability to identify specification inconsistency in the use-case modeling at the early stage of software engineering development. The proposed approach can also facilitate communication between users and developers to ensure customer satisfaction.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.537-552
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• 2019

Purpose: The development of information technology makes it easy to utilize high-dimensional categorical data. In this regard, the purpose of this study is to propose a novel method to select the proper categorical variables in high-dimensional categorical data. Methods: The proposed feature selection method consists of three steps: (1) The first step defines the goodness-to-pick measure. In this paper, a categorical variable is relevant if it has relationships among other variables. According to the above definition of relevant variables, the goodness-to-pick measure calculates the normalized conditional entropy with other variables. (2) The second step finds the relevant feature subset from the original variables set. This step decides whether a variable is relevant or not. (3) The third step eliminates redundancy variables from the relevant feature subset. Results: Our experimental results showed that the proposed feature selection method generally yielded better classification performance than without feature selection in high-dimensional categorical data, especially as the number of irrelevant categorical variables increase. Besides, as the number of irrelevant categorical variables that have imbalanced categorical values is increasing, the difference in accuracy between the proposed method and the existing methods being compared increases. Conclusion: According to experimental results, we confirmed that the proposed method makes it possible to consistently produce high classification accuracy rates in high-dimensional categorical data. Therefore, the proposed method is promising to be used effectively in high-dimensional situation.