• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.141-145
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• 2009

In this paper, we propose an efficient lossless compression algorithm using spatial and temporal information. The proposed method obtains higher lossless compression of images than other lossless compression techniques. It is divided into two parts, a motion adaptation based predictor part and a residual error coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors. The predictor decides the proper selection of the spatial and temporal prediction values according to each past prediction error. The reduced error is coded by existing context coding method. Experimental results show that the proposed algorithm has better performance than those of existing context modeling methods.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.9
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• pp.1158-1165
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• 1999

조건부 분기 명령어(conditional branch instruction)의 잘못된 분기 예측(branch misprediction)은 프로세서의 성능 향상에 심각한 장애 요인이 되고 있다. 특히 시분할(time-sharing) 시스템과 같이 문맥 교환(context switch)이 발생하는 멀티프로그래밍 환경(multiprogramming environment)에서는 더욱 낮은 분기 예측 정확성(branch prediction accuracy)을 보인다. 본 논문에서는 문맥 교환이 발생하는 멀티프로그래밍 환경에서 높은 분기 예측 정확성을 보이는 중첩 분기 예측표 교환(Overlapped Predictor Table Switch, OPTS) 기법을 소개한다. 분기 예측표(predictor table)를 분할하여 각각의 프로세스(process)에 할당하는 OPTS 기법은 문맥 교환의 영향을 최소화함으로써 높은 분기 예측 정확성을 유지하는 분기 예측 방법이다.Abstract There is wide agreement that one of the most important impediments to the performance of current and future pipelined superscalar processors is the presence of conditional branches in the instruction stream. Accurate branch prediction is required to overcome this performance limitation. Many branch predictors have been proposed to help to alleviate this problem, including the two-level adaptive branch predictor, and more recently, hybrid branch predictor. In a less idealized environment, such as a time-sharing system, code of interest involves context switches. Context switches, even at fairly large intervals, can seriously degrade the performance of many of the most accurate branch prediction schemes. In this study, we measure the effect of context switch on the branch prediction accuracy in various situation and show the feasibility of our new mechanism, OPTS(Overlapped Predictor Table Switch), which save and restore branch history table at every context switch.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.736-739
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• 2009

In this paper, an efficient lossless compression algorithm using motion adaptation is proposed. It is divided into two parts: a motion adaptation based nonlinear predictor part and a residual data coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors using motion adaption. The predictor decides the proper selection of the intra and inter prediction values according to the past prediction error. The reduced error is coded by existing context adaptive coding method. Experimental results show that the proposed algorithm has the higher compression ratio than context modeling methods, such as FELICS, CALIC, and JPEG-LS.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.291-300
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• 2013

In this paper, we propose method-free permutation predictor hypothesis tests in the context of sufficient dimension reduction. Different from an existing method-free bootstrap approach, predictor hypotheses are evaluated based on p-values; therefore, usual statistical practitioners should have a potential preference. Numerical studies validate the developed theories, and real data application is provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3295-3311
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• 2020

With the wide application of hyperspectral images, it becomes more and more important to compress hyperspectral images. Conventional recursive least squares (CRLS) algorithm has great potentiality in lossless compression for hyperspectral images. The prediction accuracy of CRLS is closely related to the correlations between the reference bands and the current band, and the similarity between pixels in prediction context. According to this characteristic, we present an improved CRLS with adaptive band selection and adaptive predictor selection (CRLS-ABS-APS). Firstly, a spectral vector correlation coefficient-based k-means clustering algorithm is employed to generate clustering map. Afterwards, an adaptive band selection strategy based on inter-spectral correlation coefficient is adopted to select the reference bands for each band. Then, an adaptive predictor selection strategy based on clustering map is adopted to select the optimal CRLS predictor for each pixel. In addition, a double snake scan mode is used to further improve the similarity of prediction context, and a recursive average estimation method is used to accelerate the local average calculation. Finally, the prediction residuals are entropy encoded by arithmetic encoder. Experiments on the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) 2006 data set show that the CRLS-ABS-APS achieves average bit rates of 3.28 bpp, 5.55 bpp and 2.39 bpp on the three subsets, respectively. The results indicate that the CRLS-ABS-APS effectively improves the compression effect with lower computation complexity, and outperforms to the current state-of-the-art methods.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1285-1293
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• 2011

We establishes the polynomial convergence of a new class of path-following methods for semidefinite linear complementarity problems (SDLCP) whose search directions belong to the class of directions introduced by Monteiro [9]. Namely, we show that the polynomial iteration-complexity bound of the well known algorithms for linear programming, namely the predictor-corrector algorithm of Mizuno and Ye, carry over to the context of SDLCP.

• Journal of the Korean Home Economics Association
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• v.42 no.11
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• pp.109-122
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• 2004

This study examined the characteristics of children, parents, family, and the extra context related to the parenting stress of employed and unemployed mothers from a broader perspective. The subjects were 323 employed mothers 3nd 300 unemployed mothers of pre-school age children. Parenting stress due to the role of being a parent for both employed and unemployed mothers was correlated with the chid's activity level, husband support, quality of life, available social support, and satisfaction of early childhood program's location. Parenting stress due to child-rearing of both employed and unemployed mothers was correlated with child's birth order, activity level and rhythmicity of child, husband support, quality of life, available social support, and satisfaction of early childhood program. Number of children was the strongest predictor of parenting stress due to the role of being a parent for employed mothers and the child's activity level for unemployed mothers. Besides, the child's activity level was the strongest predictor of parenting stress due to child-rearing for both employed and unemployed mothers.

• Journal of applied mathematics & informatics
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• v.6 no.3
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• pp.685-696
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• 1999

We present local and semilocal convergence results for New-ton's method in a Banach space setting. In particular using Lipschitz-type assumptions on the second Frechet-derivative we find results con-cerning the radius of convergence of Newton's method. Such results are useful in the context of predictor-corrector continuation procedures. Finally we provide numerical examples to show that our results can ap-ply where earlier ones using Lipschitz assumption on the first Frechet-derivative fail.

• Culinary science and hospitality research
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• v.22 no.1
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• pp.87-95
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• 2016

The purpose of current study is to develop and estimate a proposed model that explains the potential relationships among food quality, experiential value, price fairness, image, satisfaction, and behavioral intention in context of water park. In addition, the study will verify how these factors link to each other. Results show that food quality is a significant antecedent of experience value, price fairness, water park image. Also, the experiential value and water park image influence on visitors' satisfaction. Last, the satisfaction is critical predictor of behavioral intention. These findings will contribute to understand the consumers' perception about water park, and how derives the customer satisfaction and behavioral intention. In sum, present study will serve insights for industry marketers and managers in water park segment.

• Culinary science and hospitality research
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• v.20 no.5
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• pp.93-100
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• 2014

This study performed to identify the relationships among experiential value, brand image, satisfaction and customer loyalty in context of full-service restaurant, and to find the moderating effect of gender on the formulated model. SPSS 18.0 and AMOS 18.0 were employed to conduct frequency analysis, reliability analysis, exploratory and confirmatory factor analysis, and multigroup analysis to examine moderating effect. Results confirmed the validity and reliability and found significant relationships among the constructs. First, two factors of experiential value (e.g., aesthetic and economic value) have positive influence on brand image, satisfaction, and brand image was significant predictor of customer satisfaction. Second, satisfaction was significant antecedent of attitudinal loyalty and the attitudinal loyalty has influence on behavioral loyalty. In addition, current study identified moderating effect of gender between playfulness and brand image even though there was on significant relationship between both constructs. These results will be meaningful for developing marketing strategies and successful business especially for full-service restaurants.