• KSCI Review
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• v.2 no.1
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• pp.130-139
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• 1995

This paper suggests the method to shorten the search area by using edge detection and subimage partition. For the purpose reduce encoding time, The Domain areas are reduced 1/64 by partitioning original image to subimage, and classified them into edge area and shade area so that detect only the area in the same class. for achieving an encoding with good fidelity, tried to differ the search method as the threshold value of edge which is included in subimage, and compared the compression rate and fidelity when set the size of range block as $4{\times}4$ and $8{\times}8$.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.671-681
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• 2019

This paper examines the applicability of artificial neural network (ANN) and multivariate adaptive regression splines (MARS) to predict the compressive strength of bacteria incorporated geopolymer concrete (GPC). The mix is composed of new bacterial strain, manufactured sand, ground granulated blast furnace slag, silica fume, metakaolin and fly ash. The concentration of sodium hydroxide (NaOH) is maintained at 8 Molar, sodium silicate ($Na_2SiO_3$) to NaOH weight ratio is 2.33 and the alkaline liquid to binder ratio of 0.35 and ambient curing temperature ($28^{\circ}C$) is maintained for all the mixtures. In ANN, back-propagation training technique was employed for updating the weights of each layer based on the error in the network output. Levenberg-Marquardt algorithm was used for feed-forward back-propagation. MARS model was developed by establishing a relationship between a set of predictors and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Six models based on ANN and MARS were developed to predict the compressive strength of bacteria incorporated GPC for 1, 3, 7, 28, 56 and 90 days. About 70% of the total 84 data sets obtained from experiments were used for development of the models and remaining 30% data was utilized for testing. From the study, it is observed that the predicted values from the models are found to be in good agreement with the corresponding experimental values and the developed models are robust and reliable.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2625-2634
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• 2022

Discretization errors are extremely challenging conundrums of discrete ordinates calculations for radiation transport problems with void regions. In previous work, we have presented a multi-collision source method (MCS) to overcome discretization errors, but the efficiency needs to be improved. This paper proposes a goal-oriented algorithm for the MCS method to adaptively determine the partitioning of the geometry and dynamically change the angular quadrature in remaining iterations. The importance factor based on the adjoint transport calculation obtains the response function to get a problem-dependent, goal-oriented spatial decomposition. The difference in the scalar fluxes from one high-order quadrature set to a lower one provides the error estimation as a driving force behind the dynamic quadrature. The goal-oriented algorithm allows optimizing by using ray-tracing technology or high-order quadrature sets in the first few iterations and arranging the integration order of the remaining iterations from high to low. The algorithm has been implemented in the 3D transport code ARES and was tested on the Kobayashi benchmarks. The numerical results show a reduction in computation time on these problems for the same desired level of accuracy as compared to the standard ARES code, and it has clear advantages over the traditional MCS method in solving radiation transport problems with reflective boundary conditions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.37-43
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• 2023

Compressed still image or video bitstreams require protection from channel errors in a wireless channel. Embedded Zerotree Coding(EZW), SPIHT could have provided unprecedented high performance in image compression with low complexity. If bit error is generated by dint of wireless channel transmission problem, the loss of synchronization on between encoder and decoder causes serious performance degradation. But wavelet zerotree coding algorithms are producing variable-length codewords, extremely sensitive to bit errors. The idea is to partition the lifting coefficients. A many partition of lifting transform coefficients distributes channel error from wireless channel to each partition. Therefore synchronization problem that caused quality deterioration in still image and video stream was improved.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.51-53
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• 2021

본 논문에서는 초고해상도를 갖는 복소 홀로그램을 압축하기 위한 전용 코덱에서 SPIHT(set partitioning in hierarchical trees)를 사용할 경우에 발생할 수 있는 문제점을 해결하기 위한 방법을 제안한다. 복소 홀로그램을 위한 코덱의 개발은 크게 전용 압축 방법을 만드는 방법과 HEVC 및 JPEG2000과 같은 앵커 코덱을 이용하고 전후처리 기법을 추가하는 방법으로 구분될 수 있다. 전용 압축 방법을 만드는 경우에, 복소 홀로그램의 공간적인 특성이 매우 독특하기 때문에 이 신호를 해석하기 위한 별도의 변환 도구가 필요하다. 많은 연구들에서 웨이블릿 변환이 여기에 좋은 대안이 될 수 있다는 것을 보여왔다. 웨이블릿 변환을 사용할 경우에 압축을 위해서 EZW, EBCOT 그리고 SPIHT를 사용할 수 있다. EBCOT의 경우에 복잡도가 너무 높고, EZW으 경우에는 성능이 좋지 않다. 따라서 SPIHT는 좋은 대안이 될 수 있을 것이다. 그러나 EZW와 SPIHT 같은 부대역 단위의 제로트리 기반의 알고리즘들은 고해상도의 영상에 대해서 고압축으로 코딩할 경우에 비트스트림 제어 시 온전한 부대역의 정보가 제대로 전송되지 못하는 문제점을 갖는다. 본 논문에서는 웨이블릿 부대역의 분할 방법을 이용하여 이와 같은 문제를 해결하기 위한 시도를 하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.69-74
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• 2023

In this paper we review techniques for building and analyzing wavelets on irregular point sets in one and two dimensions. In particular we focus on subdivision schemes and commutation. Subdivision means the skill that approximates the initial lines or mesh into a tender curve or a curved surface by continuous partitioning operation. The key to generalizing wavelet constructions to non-traditional settings is the use of generalized subdivision. The first generation setting is already connected with subdivision schemes, but they become even more important in the construction of second generation wavelets. Subdivision schemes provide fast algorithms, create a natural multi-resolution structure, and yield the underlying scaling functions and wavelets we seek.

• BMB Reports
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• v.57 no.7
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• pp.324-329
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• 2024

The aim of the present study is to provide a rational background for silencing the V-set and transmembrane domain containing 2 like (VSTM2L) in consort with recognising soluble VSTM2L against cholangiocarcinoma. A therapeutic target against cholangiocarcinoma was selected using iterative patient partitioning (IPP) calculation, and it was verified by in vitro and in silico analyses. VSTM2L was selected as a potential therapeutic target against cholangiocarcinoma. Silencing the VSTM2L expression significantly attenuated the viability and survival of cholangiocarcinoma cells through blockade of the intracellular signalling pathway. In silico analysis showed that VSTM2L affected the positive regulation of cell growth in cholangiocarcinoma. Liptak's z value revealed that the expression of VSTM2L worsened the prognosis of cholangiocarcinoma patients. In addition, soluble VSTM2L was significantly detected in the whole blood of cholangiocarcinoma patients compared with that of healthy donors. Our report reveals that VSTM2L might be the potential therapeutic target and a soluble prognostic biomarker against cholangiocarcinoma.

• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1045-1055
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• 2007

Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.

• Horticultural Science & Technology
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• v.29 no.4
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• pp.306-310
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• 2011

This study examined the changes in the distribution of nitrogenous compounds in various parts of 3- and 4-year-old persimmon (Diospyros kaki cv. Fuyu) with fruits (fruited) and without fruits (defruited). The effect of the changes was then related to the storage and their reutilization for new growth in the following year. From June 15 to November 1, the partitioning of amino acids among perennial parts of fruited trees was inconsistent, whereas that of defruited trees was characterized by a significant increase. Compared with the fruited trees, amino acids accumulated in the perennial parts of defruited trees were 1.66 g and 3.48 g more in 3- and 4-year-old trees, respectively. Of the total proteins increased during this period, the proportions distributed to the perennial parts of the tree were less than 50% for fruited trees, but they were more than 90% for defruited trees. Roots were the strongest sink for proteins; percent proteins in the roots amounted to 94 in defruited 3-year-old trees and 76 in 4-year-old trees. Compared with the proteins accumulated in perennial parts of fruited trees, those of defruited trees were 1.64 g more in 3-year-old and 2.58 g more in 4-year-old trees. During this period, the nitrogenous compounds decreased by 0.50-0.56 g in the leaves of fruited trees, while they increased by 0.66-0.78 g in their fruits. During the new growth from April 10 to June 10 of the following year, amino acids decreased both in the fruited and defruited trees. Proteins, especially in the root, decreased in the trees that had been previously defruited. More amino acids and proteins were found in the newly grown parts of the defruited trees. Compared with the fruited trees, the defruited trees accumulated nitrogenous compounds more in roots than in the other parts of the perennial parts. The reserve nitrogenous compounds contributed to the new shoot growth and fruit set in the following year.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1558-1565
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• 2020

Objective: The objective of this study was to characterize the number of loci affecting growth traits and the distribution of single nucleotide polymorphism (SNP) effects on growth traits, and to understand the genetic architecture for growth traits in Hanwoo (Korean cattle) using genome-wide association study (GWAS), genomic partitioning, and hierarchical Bayesian mixture models. Methods: GWAS: A single-marker regression-based mixed model was used to test the association between SNPs and causal variants. A genotype relationship matrix was fitted as a random effect in this linear mixed model to correct the genetic structure of a sire family. Genomic restricted maximum likelihood and BayesR: A priori information included setting the fixed additive genetic variance to a pre-specified value; the first mixture component was set to zero, the second to 0.0001×σ²_g, the third 0.001×σ²_g, and the fourth to 0.01×σ²_g. BayesR fixed a priori information was not more than 1% of the genetic variance for each of the SNPs affecting the mixed distribution. Results: The GWAS revealed common genomic regions of 2 Mb on bovine chromosome 14 (BTA14) and 3 had a moderate effect that may contain causal variants for body weight at 6, 12, 18, and 24 months. This genomic region explained approximately 10% of the variance against total additive genetic variance and body weight heritability at 12, 18, and 24 months. BayesR identified the exact genomic region containing causal SNPs on BTA14, 3, and 22. However, the genetic variance explained by each chromosome or SNP was estimated to be very small compared to the total additive genetic variance. Causal SNPs for growth trait on BTA14 explained only 0.04% to 0.5% of the genetic variance Conclusion: Segregating mutations have a moderate effect on BTA14, 3, and 19; many other loci with small effects on growth traits at different ages were also identified.