• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.179-189
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• 2023

Hybrid sufficient dimension reduction (SDR) methods to a weighted mean of kernel matrices of two different SDR methods by Ye and Weiss (2003) require heavy computation and time consumption due to bootstrapping. To avoid this, Park et al. (2022) recently develop the so-called cross-distance selection (CDS) algorithm. In this paper, two variations of the original CDS algorithm are proposed depending on how well and equally the covk-SAVE is treated in the selection procedure. In one variation, which is called the larger CDS algorithm, the covk-SAVE is equally and fairly utilized with the other two candiates of SIR-SAVE and covk-DR. But, for the final selection, a random selection should be necessary. On the other hand, SIR-SAVE and covk-DR are utilized with completely ruling covk-SAVE out, which is called the smaller CDS algorithm. Numerical studies confirm that the original CDS algorithm is better than or compete quite well to the two proposed variations. A real data example is presented to compare and interpret the decisions by the three CDS algorithms in practice.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.2
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• pp.221-224
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• 2012

This paper presents the strength safety of a hybrid alarm valve by a finite element analysis. The stress and strain of a conventional hybrid alarm valve are calculated for the given maximum test pressure of 2MPa. Especially, the FEM computed maximum stress of a conventional hybrid valve is only 18.6% of yield strength, 370MPa. This means that the conventional valve is designed with a thick thickness of a valve structure. But, new hybrid alarm valve model, which is developed by optimized design method in this study, shows more low level of 43% in maximum stress and strain compared with that of a conventional hybrid valve. These results may recommend the reduction of a weight and a dimension for an optimized hybrid alarm valve.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.61-68
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• 2012

Recommender Systems have gained much popularity among researchers and is applied in a number of applications. The exponential growth of users and products poses some key challenges for recommender systems. Recommender Systems mostly suffer from scalability and accuracy. The accuracy of Recommender system is somehow inversely proportional to its scalability. In this paper we proposed a Context Aware Hybrid Recommender System using matrix reduction for Hybrid model and clustering technique for predication of item features. In our approach we used user item-feature rating, User Demographic information and context information i.e. specific time and day to improve scalability and accuracy. Our Algorithm produce better results because we reduce the dimension of items features matrix by using different reduction techniques and use user demographic information, construct context aware hybrid user model, cluster the similar user offline, find the nearest neighbors, predict the item features and recommend the Top N- items.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.30 no.2
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• pp.201-205
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• 2004

In these several years, as many people have been attracted by the functional cosmetics, there are a lot of study to enhance the stability of active ingredients for light, heat, oxygen, etc. in the academic and industrial field. Especially, catechin is well known as strong anti-oxidant, anti-inflammatory and reducing agent for oxidative stress but it is very unstable for light, heat, oxygen. etc. In this study, the stability and skin penetration of catechin are improved by 3-dimensional method. As I-dimension, porous silica is prepared using sol-gel method, and then catechin is adsorbed in pores of silica. As 2-dimension, solid lipid nanoparticles (SLN) are obtained using non-phospholipid vesicles. Finally 3-dimension is completion through lamellar phase self-organization that combines SLN catechin with skin lipid matrix. We used laser light scattering system, cyro-SEM, chromameter, HPLC and image analyzer to analyze our 3-dimentional systems. According to chromameter date, the color stability of 3-dimensional catechin is enhanced by 5-10 times compared with general liposome systems. We also confirmed through HPLC analysis that 3-dimensional catechin is more long lasting. The effect of skin penetration and wrinkle reduction are improved, too.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.877-878
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• 2008

We suggest a feature reduction method to classify mouse function data sets, which integrate several biological data sets represented as high dimensional vectors. To increase classification accuracy and decrease computational overhead, it is important to reduce the dimension of features. To do this, we employed Hybrid Huberized Support Vector Machine with kernels used for a kernel logistic regression method. When compared to support vector machine, this a pproach shows the better accuracy with useful features for each mouse function.

• Wind and Structures
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• v.38 no.1
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• pp.1-13
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• 2024

In order to effectively simulate nonstationary stochastic turbulent wind fields, four separation hybrid (SEP-H) models are proposed in the present study. Based on the assumption that the lateral turbulence component at one single-point is uncorrelated with the longitudinal and vertical turbulence components, the fluctuating wind is separated into 2nV-1D and nV1D nonstationary stochastic vector processes. The first process can be expressed as double proper orthogonal decomposition (DPOD) or proper orthogonal decomposition and spectral representation method (POD-SRM), and the second process can be expressed as POD or SRM. On this basis, four SEP-H models of nonstationary stochastic turbulent wind fields are developed. In addition, the orthogonal random variables in the SEP-H models are presented as random orthogonal functions of elementary random variables. Meanwhile, the number theoretical method (NTM) is conveniently adopted to select representative points set of the elementary random variables. The POD-FFT (Fast Fourier transform) technique is introduced in frequency to give full play to the computational efficiency of the SEP-H models. Finally, taking a long-span bridge as the engineering background, the SEP-H models are compared with the dimension-reduction DPOD (DR-DPOD) model to verify the effectiveness and superiority of the proposed models.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.30-35
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• 2008

As demands for being economical, precise drilling process is on the increase. Therefore, the objective of this study is to develop a step cutter that can be controllable through micro dimension and can be changed from separate manufacturing processes of drilling and boring into an integrated one. In order to attain this object the step cutter is designed with a 3D geometric modeling and the design could be modified easily by using parametric modeling methodology. Also, collision is not occurred during manufacturing process because of cutting simulation. The step cutter is assembled by parts made up of 5-axis machining and sintering. Validation tests are accomplished. They show that developed cutter has characteristics such as reduction of machining time as well as the good surface roughness of the machined hole. Indeed, reliability could be obtained from a durability test.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1143-1152
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• 2009

A canonical correlation analysis(CCA)-based method is proposed for prediction of future climate change which combines information from ensembles of atmosphere-ocean general circulation models(AOGCMs) and observed climate values. This paper focuses on predictions of future climate on a regional scale which are of potential economic values. The proposed method is obtained by coupling the classical CCA with empirical orthogonal functions(EOF) for dimension reduction. Furthermore, we generate a distribution of climate responses, so that extreme events as well as a general feature such as long tails and unimodality can be revealed through the distribution. Results from real data examples demonstrate the promising empirical properties of the proposed approaches.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.10
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• pp.865-871
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• 2014

Paradigm shift to 3-D chip stacking in electronic packaging has induced a lot of integration challenges due to the reduction in wafer thickness and pitch size. This study presents a hybrid bonding technology by self-alignment effect in order to improve the flip chip bonding accuracy with ultra-thin wafer. Optimization of Cu pillar bump formation and evaluation of various factors on self-alignment effect was performed. As a result, highly-improved bonding accuracy of thin wafer with a $50{\mu}m$ of thickness was achieved without solder bridging or bump misalignment by applying reflow process after thermo-compression bonding process. Reflow process caused the inherently-misaligned micro-bump to be aligned due to the interface tension between Si die and solder bump. Control of solder bump volume with respect to the chip dimension was the critical factor for self-alignment effect. This study indicated that bump design for 3D packaging could be tuned for the improvement of micro-bonding quality.

• Journal of the Korean Magnetics Society
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• v.26 no.3
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• pp.81-85
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• 2016

This paper introduces a performance integration method to predict variation characteristic of a performance function of electromagnetic machines or devices due to manufacturing tolerances. A normalized performance function space and a hybrid mean value technique are adapted to effectively predict mean and variance, which can identify probabilistic distribution of the performance function. To verify the effectiveness and accuracy of the proposed method, a mathematical problem and a loudspeaker model are tested, and numerical results are compared with those of existing methods such as Monte Carlo simulation and univariate dimension reduction method.