• Near Infrared Analysis
• /
• v.1 no.2
• /
• pp.1-8
• /
• 2000

Using the net analyte signal, hybrid linear analysis was proposed to predict chemical concentration. In this paper, we select a sample from training set and apply orthogonal signal correction to obtain an improved pseudo unit spectrum for hybrid least analysis. using the mean spectrum of a calibration training set, we first show the calibration by hybrid least analysis is effective to the prediction of not only chemical concentrations but also physical property variables. Then, a pseudo unit spectrum from a training set is also tested with and without orthogonal signal correction. We use two data sets, one including five chemical concentrations and the other including ten physical property variables, to compare the performance of partial least squares and modified hybrid least analysis calibration methods. The results show that the hybrid least analysis with a selected training spectrum instead of well-measured pure spectrum still gives good performances, which is a little better than partial least squares.

• Korean Journal of Food Science and Technology
• /
• v.51 no.3
• /
• pp.227-236
• /
• 2019

Antioxidant activity in water and ethanol extracts of dried Lycium chinense fruit, as a result of the total phenolic and tannin content, was measured using a number of chemical and biochemical assays for radical scavenging and inhibition of lipid peroxidation, with the analysis being extended by applying a bootstrapping statistical method. Previous statistical analyses mostly provided linear correlation and regression analyses between antioxidant activity and increasing concentrations of phenolics and tannins in a concentration-dependent mode. The present study showed that multiple component or multivariate analysis by applying multiple regression analysis or regression planes proved more informative than linear regression analysis of the relationship between the concentration of individual components and antioxidant activity. In this paper, we represented the multivariate analysis of antioxidant activities of both phenolic and tannin contents combined in the water and ethanol extracts, which revealed the hidden observations that were not evident from linear statistical analysis.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2009.03a
• /
• pp.1043-1052
• /
• 2009

To derive easily the coefficient of permeability from several other soil properties, the estimation model of coefficient of permeability was proposed using linear regression analysis. The coefficient of permeability is one of the major factors to evaluate the soil characteristics. The study area is located in Kangwon-do Pyeongchang-gun Jinbu-Myeon. Soil samples of 45 spots were taken from the study area and various soil tests were carried out in laboratory. After selecting the soil factor influenced by the coefficient of permeability through the correlation analysis, the estimation model of coefficient of permeability was developed using the linear regression analysis between the selected soil factor and the coefficient of permeability from permeability test. Also, the estimation model of coefficient of permeability was compared with the results from permeability test and empirical equation, and the suitability of proposed model was proved. As the result of correlation analysis between various soil factors and the coefficient of permeability using SPSS(statistical package for the social sciences), the largest influence factor of coefficient of permeability were the effective grain size, porosity and dry unit weight. The coefficient of permeability calculated from the proposed model was similar to that resulted from permeability test. Therefore, the proposed model can be used in case of estimating the coefficient of permeability at the same soil condition like study area.

• Sleep Medicine and Psychophysiology
• /
• v.15 no.1
• /
• pp.5-11
• /
• 2008

Sleep is an essential process maintaining the life cycle of the human. In parallel with physiological, cognitive, subjective, and behavioral changes that take place during the sleep, there are remarkable changes in the electroencephalogram (EEG) that reflect the underlying electro-physiological activity of the brain. However, analyzing EEG and relating the results to clinical observations is often very hard due to the complexity and a huge data amount. In this article, I introduce several linear and non-linear tools, developed to analyze a huge time series data in many scientific researches, and apply them to EEG to characterize various sleep states. In particular, the spectral analysis, detrended fluctuation analysis (DFA), and synchrony analysis are administered to EEG recorded during nocturnal polysomnography (NPSG) processes and daytime multiple sleep latency tests (MSLT). I report that 1) sleep stages could be differentiated by the spectral analysis and the DFA ; 2) the gradual transition from Wake to Sleep during the sleep onset could be illustrated by the spectral analysis and the DFA ; 3) electrophysiological properties of narcolepsy could be characterized by the DFA ; 4) hypnic jerks (sleep starts) could be quantified by the synchrony analysis.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2009.09a
• /
• pp.1065-1078
• /
• 2009

The shear strength has been managed as an important factor in soil mechanics. The shear strength estimation model was developed to evaluate the shear strength using only a few soil properties by the linear regression analysis model which is one of the statistical methods. The shear strength is divided into two part; one is the internal friction angle ($\Phi$) and the other is the cohesion (c). Therefore, some valid soil factors among the results of soil tests are selected through the correlation analysis using SPSS and then the model are formulated by the linear regression analysis based on the relationship between factors. Also, the developed model is compared with the result of direct shear test to prove the rationality of model. As the results of analysis about relationship between soil properties and shear strength, the internal friction angle is highly influenced by the void ratio and the dry unit weight and the cohesion is mainly influenced by the void ratio, the dry unit weight and the plastic index. Meanwhile, the shear strength estimated by the developed model is similar with that of the direct shear test. Therefore, the developed model may be used to estimate the shear strength of soils in the same condition of study area.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.5
• /
• pp.139-148
• /
• 2002

Motion errors of linear motion guideway are analyzed theoretically in this paper. For the analysis, an new algorithm predicting motion errors of bearing and guideway is proposed using the Hertz's elastic deformation theory. Accuracy averaging effect can be calculated quantitatively by analyzing relationship between motion errors of guideway and spatial frequency of rail form error. Influences of design parameters on the motion errors including the number of balls, preload, ball diameter, bearing length and the number of bearings are analyzed. As it is difficult to measure the rail form error, experimental results are compared with results analyzed by the equivalent analysis method which evaluate the motion errors of guideway using the measured errors of bearing. From the experimental results, it is confirmed that the proposed analysis method it effective lo analyze the motion errors of linear motion bearing and guideway.

• Selected Papers of The Society of Naval Architects of Korea
• /
• v.2 no.1
• /
• pp.79-105
• /
• 1994

A ship in waves is suffered from the various wave loads that comes from its motion throughout its life. Because these loads are dynamic, the analysis of a ship structure must be considered as the dynamic problem precisely. In the rationally-based design, the dynamic structural analysis is carried out using dynamic wave loads provided from the results of the ship motion calculation as a rigid body. This method is based on the linear theory assumed low wave height and small amplitude of motion. But at the rough sea condition, high wave height, compared with ship's depth, induce the large ship motion, so the ship section configuration under waterline is rapidly changed at each time. This results in a non-linear problem. Considering above situation in this paper, a strength analysis method is introduced for the hull girder among waves considering non-linear hydrodynamic forces. This paper evaluates the overall or primary level of the ship structural dynamic loading and dynamic response provided from the non-linear wave forces, and bottom flare impact forces by momentum slamming theory. For numerical calculation a ship is idealized as a hollow thin-walled box beam using thin walled beam theory and the finite element method is used. This method applied to a 40,000 ton double hull tanker and attention is paid to the influence of the response of the ship's speed, wave length and wave height compared with the linear strip theory.

• Journal of Environmental Science International
• /
• v.22 no.8
• /
• pp.953-963
• /
• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. Forecasting of seasonal inflow to Andong dam is performed and assessed using statistical methods based on hydrometeorological data. Predictors which is used to forecast seasonal inflow to Andong dam are selected from southern oscillation index, sea surface temperature, and 500 hPa geopotential height data in northern hemisphere. Predictors are selected by the following procedure. Primary predictors sets are obtained, and then final predictors are determined from the sets. The primary predictor sets for each season are identified using cross correlation and mutual information. The final predictors are identified using partial cross correlation and partial mutual information. In each season, there are three selected predictors. The values are determined using bootstrapping technique considering a specific significance level for predictor selection. Seasonal inflow forecasting is performed by multiple linear regression analysis using the selected predictors for each season, and the results of forecast using cross validation are assessed. Multiple linear regression analysis is performed using SAS. The results of multiple linear regression analysis are assessed by mean squared error and mean absolute error. And contingency table is established and assessed by Heidke skill score. The assessment reveals that the forecasts by multiple linear regression analysis are better than the reference forecasts.

• Fibers and Polymers
• /
• v.7 no.2
• /
• pp.203-212
• /
• 2006

The purpose of this study was to examine the effects of the structural properties of plain knit fabrics on the subjective perception of textures, sensibilities, and preference among consumers. This study, then, aimed to provide useful information with respect to planning and designing knitted fabrics by predicting the subjective characteristics analyzed according to their structural properties. For this purpose, we employed statistical analysis tools, such as factor and regression analysis and an adaptive-network-based fuzzy inference system(ANFIS), thereby combining the merits of fuzzy and neural networks and presupposing a non-linear relationship. Through factor analysis, we also categorized the subjective textures into 'roughness', 'softness', 'bulkiness' and 'stretch-ability' with R2=70.32%: and categorized the sensibilities into 'Stable/Neat', 'Natural/Comfortable' and 'Feminine/Elegant' with R2=68.12%. We analyzed subjective textures, sensibilities, and preference with ANFIS, assuming non-linear relationships; consequently, we were able to generate three or four fuzzy rules using wool/rayon fiber content and loop length as input data. The textures of roughness and softness exhibited a linear relationship, but other subjective characteristics demonstrated a non-linear input-output relationship. Compared with linear regression analysis, the ANFIS exhibited had higher predictive power with respect to predicting subjective characteristics.

• Journal of Korean Association for Spatial Structures
• /
• v.24 no.1
• /
• pp.73-80
• /
• 2024

Non-uniform reinforced concrete brace facade systems are newly considered to improve seismic performance of reinforced concrete frame buildings under lateral load. For normal and high strength concrete of 30MPa, 80MPa, and 120MPa, the cross-sections of reinforced concrete brace facade systems were designed as different size with same amount of reinforcements. The strengthened frame systems were analyzed by a non-linear two-dimensional finite element technique which was considering material non-linearities of concrete and reinforcing bars under monotonic and cyclic loadings. From the study of non-linear analysis of the systems, therefore, it was provided that the proposed braced facade systems were reliable to improve laterally load-carrying capacity and minimize damages of concrete members through comparisons of load-displacement curves, crack patterns, and stress distributions of reinforcing bars predicted by current non-linear finite element analysis of frame specimens.