• Journal of KIISE:Computer Systems and Theory
• /
• v.33 no.3
• /
• pp.157-165
• /
• 2006

The change of external/internal factors of the cell rquires specific biological functions to maintain life. Such functions encourage particular genes to jnteract/regulate each other in multiple ways. Accordingly, we applied a linear decomposition model IFSA, which derives hidden variables, called the 'expression mode' that corresponds to the functions. To interpret gene interaction/regulation, we used a cross-correlation method given an expression mode. Linear decomposition models such as principal component analysis (PCA) and independent component analysis (ICA) were shown to be useful in analyzing high dimensional DNA microarray data, compared to clustering methods. These methods assume that gene expression is controlled by a linear combination of uncorrelated/indepdendent latent variables. However these methods have some difficulty in grouping similar patterns which are slightly time-delayed or asymmetric since only exactly matched Patterns are considered. In order to overcome this, we employ the (IFSA) method of [1] to locate phase- and shut-invariant features. Membership scoring functions play an important role to classify genes since linear decomposition models basically aim at data reduction not but at grouping data. We address a new function essential to the IFSA method. In this paper we stress that IFSA is useful in grouping functionally-related genes in the presence of time-shift and expression phase variance. Ultimately, we propose a new approach to investigate the multiple interaction information of genes.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.41 no.6
• /
• pp.81-89
• /
• 2004

In this paper, we compare face recognition rate by PCA algorithm using distance change and embedded data being input left side and right side image in stereo images. The proposed method detects face region from RGB color space to YCbCr color space. Also, The extracted face image's scale up/down according to distance change and extracts more robust face region. The proposed method through an experiment could establish standard distance (100cm) in distance about 30∼200cm, and get 99.05% (100cm) as an average recognition result by scale change. The definition of super state is specification region in normalized size (92${\times}$112), and the embedded data extracts the inner factor of defined super state, achieved face recognition through PCA algorithm. The orignal images can receive specification data in limited image's size (92${\times}$112) because embedded data to do learning not that do all learning, in image of 92${\times}$112 size averagely 99.05%, shows face recognition rate of test 1 99.05%, test 2 98.93%, test 3 98.54%, test 4 97.85%. Therefore, the proposed method through an experiment showed that if apply distance change rate could get high recognition rate, and the processing speed improved as well as reduce face information.

• Journal of KIISE
• /
• v.42 no.12
• /
• pp.1535-1543
• /
• 2015

The brain-computer interface obtains a user's electroencephalogram as a replacement communication unit for the disabled such that the user is able to control machines by simply thinking instead of using hands or feet. In this paper, we propose a feature extraction method based on a non-selected filter by SBCSP to classify motor imagery EEG. First, we divide frequencies (4~40 Hz) into 4-Hz units and apply CSP to each Unit. Second, we obtain the FLD score vector by combining FLD results. Finally, the FLD score vector is projected onto the optimal plane for classification using PCA. We use BCI Competition III dataset IVa, and Extracted features are used as input for LS-SVM. The classification accuracy of the proposed method was evaluated using $10{\times}10$ fold cross-validation. For subjects 'aa', 'al', 'av', 'aw', and 'ay', results were $85.29{\pm}0.93%$, $95.43{\pm}0.57%$, $72.57{\pm}2.37%$, $91.82{\pm}1.38%$, and $93.50{\pm}0.69%$, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.6
• /
• pp.27-37
• /
• 2008

Applications of 3D data increase with advancement of multimedia technique and contents, and it is necessary to manage and to retrieve for 3D data efficiently. In this paper, we propose a new method using the sliced shape which extracts efficiently a feature description for shape-based retrieval of 3D models. Since the feature descriptor of 3D model should be invariant to translation, rotation and scale for its model, normalization of models requires for 3D model retrieval system. This paper uses principal component analysis(PCA) method in order to normalize all the models. The proposed algorithm finds a direction of each axis by the PCA and creates orthogonal n planes in each axis. These planes are orthogonalized with each axis, and are used to extract sliced shape image. Sliced shape image is the 2D plane created by intersecting at between 3D model and these planes. The proposed feature descriptor is a distribution of Euclidean distances from center point of sliced shape image to its outline. A performed evaluation is used for average of the normalize modified retrieval rank(ANMRR) with a standard evaluation from MPEG-7. In our experimental results, we demonstrate that the proposed method is an efficient 3D model retrieval.

• Journal of Korean Society of Water and Wastewater
• /
• v.37 no.6
• /
• pp.425-435
• /
• 2023

Organoleptic parameters such as color, odor, and flavor influence consumer perception of drinking water quality. This study aims to evaluate the taste of the selected bottled and tap water samples using an electronic tongue (E-tongue) instead of a sensory test. Bottled and tap water's mineral components are related to the overall preference for water taste. Contrary to the sensory test, the potentiometric E-tongue method presented in this study distinguishes taste by measuring the mineral components in water, and the data obtained can be statistically analyzed. Eleven bottled water products from various brands and one tap water from I city in Korea were evaluated. The E-tongue data were statistically analyzed using multivariate statistical tools such as hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the E-tongue method can clearly distinguish taste discrimination in drinking water differing in water quality based on the ion-related water quality parameters. The water quality parameters that affect taste discrimination were found to be total dissolved solids (TDS), sodium (Na+), calcium (Ca²⁺), magnesium (Mg²⁺), sulfate (SO₄^2-), chloride (Cl^-), potassium (K⁺) and pH. The distance calculation of HCA was used to quantify the differences between 12 different types of drinking water. The proposed E-tongue method is a practical tool to quantitatively evaluate the differences between samples in water quality items related to the ionic components. It can be helpful in quality control of drinking water.

• Journal of Korean Society of Forest Science
• /
• v.89 no.5
• /
• pp.666-676
• /
• 2000

For the study of morphological variation of Q. variabilis natural population in Korea, 19 populations were selected through the country in considering latitude, longitude, and geographical characters. Thirty trees were randomly selected from each population and 60 mature leaves were sampled from each tree. Four characters (leaf blade length, maximum blade width, petiole length, and vein number) were measured, and their ratios (the ratio of blade length to maximum blade width, the ratio of blade length to petiole length, the ratio of petiole length to vein number, upper 1/3 blade width to maximum blade width, and upper 1/3 blade width to lower 1/3 blade width) were calculated. 1. Analysis of variance for all leaf characters were significantly different among populations and among individuals within population. Contributions of variance among individuals within population in all the characters were higher than those among populations. Therefore, selection of plus trees may be preferable to desirable populations for breeding program of Q. variabilis. 2. Among principal component analysis for leaf characters, primary 2 principal components appeared to be major variables for leaf form of Q. variabilis because of the loading contribution of 80.5%. The first contribution component was petiole length/vein number and petiole length ; the second one was upper 1/3 blade width/maximum blade width, upper blade width/lower 1/3 blade width and vein number, respectively. 3. Latitude was positively correlated with blade length/maximum blade width and blade length/petiole length, but negatively correlated with petiole length/vein number, upper 1/3 blade width/maximum blade width, upper 1/3 blade width/lower 1/3 blade width, petiole length, and vein number. But, for longitude and altitude the former two traits and the later five traits exhibited the negative and positive correlation, respectively. 4. Cluster analysis using complete linkage method for leaf characters showed two groups to Euclidean distance 1.6. They were group I of population 1. 4, 5, and 13 and group II of population 2, 3, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, and 19. However, group II was divided again to Euclidean distance 1.3, that is a group including population 3, 7, 10, 14, 15, and 17(group II-1) and the other group comprising population 2, 6, 8, 9, 11, 12, 16, 18, and 19(group II-2). This cluster could be mainly observed due to difference among population in aspect (group I : NE, group II-1 : SE, and group II-2 : SW).

• Journal of the Korean Geographical Society
• /
• v.31 no.1
• /
• pp.19-37
• /
• 1996

This paper aims at examining the regional difference of changes in the business organization of retailing in the Seoul metropolitan areas, as an attempt to understand regional structure of retailing within metropolitan areas showing the trend of suburbanization. On the national level, retail sales have concentrated on the large metropolitan areas, especially on the Seoul metropolitan area, with the concentration of population and income. Within metropolitan areas, the suburbanization of retailing has made the larger structure of retail and multi-store retail appeared. In order to confirm such phenomenon, this paper is to analyze and to compare the industrial composition of retailing using industry data of 1979 and 1991. And this paper is to analyze the regional changes in the characteristics of business organization of retailing, with the index including the percentages of establishments with less than under four employees, juridical establishments, employees of ordinary times, and the annual sales per establishment of detailing. The characteristics of business organization of retailing in analyzed by principal components analysis, and the types with component in each district (city, county, ward) is analyzed by cluster analysis(Ward method). The data of 1979 were obtained from the statistics in the Census of Wholesale and Retail Trade published by the National Bureau of Statistics of Economic Planning Board, and that of 1991 were obtained from the statistics in the Report on Establishment Census (Vol.3 Wholesale and Retail Trade) published by the National Statistics Office. The following are resultant findings. 1. In Seoul metropolitan area, changes in the industrial composition of retailing with annual sales from, 1979 to 1991 show very higher composition rates of 'general merchandise stores' and 'retailing of personal transport equipment and gasoline service stations', but comparatively lower composition rates of 'retailing of food, beverages and tobacco', 'retailing of textiles, clothing, footwear and apparel accessaries', 'general retail trade, n.e.c.',and 'retailing of household fuel'. 2. The characteristics of business organization of retailing in Seoul metropolitan area presents the prevailence of small, personal business organization and especially larger employees of ordinary times. 3. Business components of retailing by principal components analysis in Seoul metropolitan area are follows: 1 All retaining industries are larger business scale. 2. Larger business take the 'retailing of taxtiles, clothing, footwear and apparel accessories', 'retailing of furniture, home furnishing and equipment', and 'retailing of jewellery and watches' is main characteristic legal organization and employees of ordinary times. 4. Types changes in business organization of retailing in Seoul metropolitan area represent legal organization and employees of ordinary times taking the 'retailing of textiles, clothing, footwear and apparel accessories', 'retailing of furniture, home furnishing and equipment',and 'retailing of jewellery and equipment', and 'retailing of jewellery and watches', and legal organization taking 'general retail trade, n.e.c.' in 1979. All retailing industries are changed into larger business scale, in 1991. These phenomena of business changes appeared southeastern regions in Kyunggi-do(province). And larger business scale taking the 'retailing of textiles, clothing, footwear and apparel accessories', 'retailing of jewellery and watches', and 'general retail trade, n.e.c.; are appeared in the legal organization in 1979. 'Retailing of personal transport equipment and gasoline service stations' are appeared in employees of ordinary times in 1991. These phenomena of business changes in appeared in eastern and northern regions in Kyunggi-do. 5. Changes in the business organization of retailing in Seoul metropolitan area is appeared in legal organization and employees of ordinary times for some industries in 1979, larger business scale of retailing and employees of ordinary times in 'retailing of personal transport equipment and gasoline service stations' are the characteristics in 1991.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_1
• /
• pp.1041-1053
• /
• 2018

In this study, a real-time storage level and capacity monitoring and forecasting system for Yongdam Dam watershed was developed using high resolution satellite image. The drought indices such as Standardized Precipitation Index (SPI) from satellite data were used for storage level monitoring in case of drought. Moreover, to predict storage volume we used a statistical method based on Principle Component Analysis (PCA) of Singular Spectrum Analysis (SSA). According to this study, correlation coefficient between storage level and SPI (3) was highly calculated with CC=0.78, and the monitoring and predictability of storage level was diagnosed using the drought index calculated from satellite data. As a result of analysis of principal component analysis by SSA, correlation between SPI (3) and each Reconstructed Components (RCs) data were highly correlated with CC=0.87 to 0.99. And also, the correlations of RC data with Normalized Water Surface Level (N-W.S.L.) were confirmed that has highly correlated with CC=0.83 to 0.97. In terms of high resolution satellite image we developed a water detection algorithm by applying an exponential method to monitor the change of storage level by using Multi-Spectral Instrument (MSI) sensor of Sentinel-2 satellite. The materials of satellite image for water surface area detection in Yongdam dam watershed was considered from 2016 to 2018, respectively. Based on this, we proposed the possibility of real-time drought monitoring system using high resolution water surface area detection by Sentinel-2 satellite image. The results of this study can be applied to estimate of the reservoir volume calculated from various satellite observations, which can be used for monitoring and estimating hydrological droughts in an unmeasured area.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1527-1527
• /
• 2001

Glucose, fructose and sucrose being the main sugars that can be found in natural fruit juice. Many instrumental methods, such as GC, LC, electrochemical or spectrometric methods provide information about both the total content of sugars and the specific concentration of each carbohydrate[1]. The simplicity of sample handling and measurement in the near IR(NIR) wavelength region, which allows the use of long pathlength, optical glass cells and optical fibers, makes NIR a good alternative for sugar determination [2]. In the present study, six varieties of persian grapes were harvested at intervals through august to october and analysed for sugars by NIR. The results were processed by principal component regression (PCR) and partial least squares (PLS) analysis. Sample juice was prepared by squeezing through gauze from crashed grape. This solution was treated by zinc ferrocyanide prior to analysis in order to eliminate colored compounds and all optically active nonsugar substances. For glucose and fructose the most characteristic wavelengths were 1456nm corresponding to the first harmonic O-H stretching and the second at 2062nm corresponding to O-H stretching and deformation; secondary characteristic combination bands were also seen at 2265 nm (O-H and C-C stretching) and at 2240 nm (C-H and C-C stretching). However these spectra were taken over a wavelength range from 1100-2500nm at room temperature of 25-$30^{\circ}C$. To test the accuracy of the described procedure, samples of six varieties of grape were analysed by the proposed NIR and a standard method[2]. Good agreement were found between these two sets of the results. To perform the recovery studies , samples of grape juices previously analysed by the proposed method, were spiked with known amounts of each individual sugars and then analysed again. Relative standard deviations varied from 1.4 to 1.8% for six independent measurements of individual and total sugar concentration. In the analysis of real and synthetic samples, precise and accurate results were obtained , providing accuracy errors lower than 1.9% in all cases. Average recoveries of ${97}{\pm}{4%}$ for total sugar and between ${95}{\pm}{5%}$ and ${99}{\pm}{2%}$ for sing1e sugars demonstrate the applicability of the methodology developed to the direct analysis of grape Juice.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.4
• /
• pp.392-400
• /
• 2001

This paper proposes an illuminant estimation algorithm that estimates the spectral power distribution of an incident light source from a single image. The proposed illumination recovery procedure has two phases. First, the surface spectral reflectances are recovered in the maximum achromatic region (MAR) which is the most achromatic and highly bright region of an image after removing partially the effect of illumination using a modified gray world algorithm. Here, the surface reflectances of MAR are estimated using the principal component analysis method along with a set of given 1269 Munsell samples. Second, the Population of reflected lights is determined with 1269 Munsell samples and a set of illuminations then the spectral distribution of re(looted lights of MAR is selected from the spectral database. That is, color differences are compared between the reflected lights of the MAR and the spectral database, which is the set of reflected lights built by the given set of Munsell samples and illuminants. Then the closest colors from the spectral database are selected. Finally, the illuminant of an image can be calculated dividing the average spectral distributions of reflected lights of MAR by the average surface reflectances of the MAR. In order to evaluate the proposed algorithm, experiments with artificial scenes, which are exposed to chromatic illuminants, were performed and the spectral distribution of estimated illumination and color difference are compared with results of the conventional method.