• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.1
• /
• pp.62-68
• /
• 2012

Steady-State Visually Evoked Potentials (SSVEP) are natural response signal associated with the visual stimuli with specific frequency. By using SSVEP, occipital lobe region is electrically activated as frequency form equivalent to stimuli frequency with bandwidth from 3.5Hz to 75Hz. In this paper, we propose an experimental paradigm for analyzing EEGs based on the properties of SSVEP. At first, an experiment is performed to extract frequency feature of EEGs that is measured from the image-based visual stimuli associated with specific objective with affordance and object-related affordance is measured by using mirror neuron system based on the frequency feature. And then, linear discriminant analysis (LDA) method is applied to perform the online classification of the objective pattern associated with the EEG-based affordance data. By using the SSVEP measurement experiment, we propose a Brain-Computer Interface (BCI) system for recognizing user's inherent intentions. The existing SSVEP application system, such as speller, is able to classify the EEG pattern based on grid image patterns and their variations. However, our proposed SSVEP-based BCI system performs object pattern classification based on the matters with a variety of shapes in input images and has higher generality than existing system.

• Korean Journal of Food Science and Technology
• /
• v.45 no.2
• /
• pp.142-147
• /
• 2013

This study was conducted to evaluate and compare new beer (NB) with market beers, e.g., New castle brown ale (NC), Victoria bitter (VB), and Coopers pale ale (CP) using physicochemical parameters. In addition, pattern recognition analyses were carried out using an electronic nose based on mass spectrometry (MS-E nose) and an electronic tongue (E-tongue) for differentiation of the different types of beer. The measured alcohol content of NB was 4.37%. NB was not significantly different compared with other types of beer with regard to bitterness unit, color, and polyphenol content (p<0.05). On the basis of the flavor pattern determined by the MS-E nose, NB was separated by DF1 (first score from discriminant function analysis), while NC, VB, and CP were located in the same group. The result of the E-tongue showed that the different samples could be clearly discriminated; NB was less sour. It was suggested that the discriminant function analysis (DFA) given by the MS-E nose and E-tongue could be used for evaluations during new product development. Furthermore, because of its simplicity, it might be possible to use the validated method for the evaluation of beer.

• Korean Journal of Adult Nursing
• /
• v.15 no.2
• /
• pp.267-277
• /
• 2003

Purpose: The purpose of this study was to evaluate the applicability of braden scale to assess pressure ulcer risk patients and to identify additional risk factors of pressure sores in an neurologic intensive care unit. Method: The subjects of this study were 66 patients in neurologic intensive care units. Data was prospectively collected from Sep. to Dec., 2002. Data were analyzed by mean, percentage, t-test, chi-square, discriminant analysis using Spss pc+. Result: The results of this study were as follows: 1) There was a significant difference between scoring of braden scale and pressure ulcer development. The subscales that predicted pressure ulcer development using braden scale only were sensory perception, moisture, mobility, friction & shear. By using these subscales, sensitivity was 86.7%, and specificity was 61.1%, and total hit ratio was 72.7%. 2) Additional pressure ulcer risk factors which showed significance for discriminating two group were protein, albumin, gender, level of consciousness, pattern of bowel elimination. By using the combination of these additional risk factors in addition to the braden scale, total hit ratio increased to 84.8%. Conclusion: This data suggest that albumin, protein, gender, level of consciousness, pattern of bowel elimination in addition to the braden scale should be included in the pressure sore assessment tool.

• Journal of Multimedia Information System
• /
• v.7 no.2
• /
• pp.97-106
• /
• 2020

The subjective experience would degrade the current artificial artistic aesthetic analysis. Since Qiong kiln ceramics have a long history and occupy a very important position in ceramic arts, we employed computer-aided technologies to quickly automatically accurately and quantitatively process a large number of Qiong kiln ceramic images and generate the detailed statistical data. Because the color features are simple and significant visual characteristics, the color features of Qiong kiln ceramics are analyzed for the quantitative aesthetics. The Qiong kiln ceramic images are segmented with GrabCut algorithm. Three moments (1st-order, 2nd-order, and 3rd-order) are calculated in two typical color spaces, namely RGB and HSV. The discrimination powers of the color features are analyzed according to various dynasties (Tang Dynasty, Five Dynasties, Song Dynasty) and various utensils (Pot, kettle, bowl), which are helpful to the selection of the discriminant color features among various dynasties and utensils. This paper is helpful to promoting the quantitative aesthetic research of Qiong kiln ceramics and is also conducive to the research on the aesthetics of other ceramics.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.16 no.1
• /
• pp.34-45
• /
• 1996

The signal pattern recognition program which can perform signal acquisition and processing, the extraction and selection of features, the classifier design and the evaluation, is developed and applied to the classification of artificial defects in the weld zone of Austenitic STS304. The neural network classifier is compared with the linear discriminant function classifier and the empirical Bayesian classifier. The signal through a broadband sensor is compared with that through a resonance type sensor. In recognition rate, the neural network classifier is best, and the signal through a broadband sensor is better.

• Journal of the Korean Society of School Health
• /
• v.7 no.1
• /
• pp.29-36
• /
• 1994

The purpose of this study was to explain the performance pattern of health education and related factors in elementary school. The data were collected from school nurses who have been working elementary school. Sample of 77 were analyzed by percent distribution, ${\chi}^2$-test, discriminant analysis. The performance rates of health education was 74%, Only 19% of total carried out health education of 6 hours per week. Important variables that was showed significant association with health education level were as follows: Perception of importance about health education among personal characteristics of school nurses and size of school c1ass, cooperation level of school administrator, operation method of school health clinic, the difficulty of school health clinic among school organization characteristics. The canonical correlation between the health education (yes or no) and important independent variables was 0.52. Among them, operation method of school health clinic. perceiveness of health education, size of school class represented the significant contribution (canonical coefficient: 0.66, 0.54, 0.52) to school health education. These findings suggest that structure and management variables of school organization are more important than personal variables of school nurses related to activation of school health education. Therefore, it is expected that the quantity and quality improvement of school health education be able to accomplish through the systematic support of school organization and government demension.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.11
• /
• pp.1022-1028
• /
• 2013

It is well knowns that based on the CSP (Common Spatial Pattern) algorithm, the linear projection of an EEG (Electroencephalography) signal can be made to spaces that optimize the discriminant between two patterns. Sharing disadvantages from linear time invariant systems, CSP suffers from the non-stationary nature of EEGs causing the performance of the classification in a BCI (Brain-Computer Interface) system to drop significantly when comparing the training data and test data. The author has suggested a simple idea based on the parallel model of CSP filters to improve the performance of BCI systems. The model was tested with a simple CSP algorithm (without any elaborate regularizing methods) and a perceptron learning algorithm as a classifier to determine the improvement of the system. The simulation showed that the parallel model could improve classification performance by over 10% compared to conventional CSP methods.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.4
• /
• pp.692-700
• /
• 2017

In this paper, we propose the structural design of Interval Type-2 FCM based RBFNN. Proposed model consists of three modules such as condition, conclusion and inference parts. In the condition part, Interval Type-2 FCM clustering which is extended from FCM clustering is used. In the conclusion part, the parameter coefficients of the consequence part are estimated through LSE(Least Square Estimation) and WLSE(Weighted Least Square Estimation). In the inference part, final model outputs are acquired by fuzzy inference method from linear combination of both polynomial and activation level obtained through Interval Type-2 FCM and acquired activation level through Interval Type-2 FCM. Additionally, The several parameters for the proposed model are identified by using differential evolution. Final model outputs obtained through benchmark data are shown and also compared with other already studied models' performance. The proposed algorithm is performed by using Iris and Vehicle data for pattern classification. For the validation of regression problem modeling performance, modeling experiments are carried out by using MPG and Boston Housing data.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.7 no.2
• /
• pp.200-205
• /
• 2006

Abstract This paper presents a personal identification method based on BMME and LDA for images acquired at anterior and posterior occlusion expression of teeth. The method consists of teeth region extraction, BMME, and pattern recognition forthe images acquired at the anterior and posterior occlusion state of teeth. Two occlusions can provide consistent teeth appearance in images and BMME can reduce matching error in pattern recognition. Using teeth images can be beneficial in recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, the algorithm was successful in teeth recognition for personal identification for 20 people, which encouraged our method to be able to contribute to multi-modal authentication systems.

• Journal of Ecology and Environment
• /
• v.44 no.3
• /
• pp.185-195
• /
• 2020

Background: The flathead grey mullet Mugil cephalus has the widest distribution among mugilid species. Recent studies based on mitochondrial DNA sequences showed that the species comprises at least 14 different groups, three of which occur in the northwest Pacific. We analyzed the otolith microchemistry of M. cephalus at several locations in Korea to improve understanding of migration pattern and population origin. Results: We collected 123 sagittal otoliths from seven locations and determined their concentrations of eight elements (⁷Li, ²⁴Mg, ⁵⁵Mn, ⁵⁷Fe, ⁶⁰Ni, ⁶³Cu, ⁸⁸Sr, and ¹³⁸Ba) using laser ablation inductively coupled plasma mass spectrometry. Mean otolith elemental ratios differed significantly among the locations. The Sr:Ca, Fe:Ca, and Ba:Ca ratios were significantly higher than others, and useful chemical signatures for investigating the habitat use of M. cephalus populations. We identified five diverse and complicated migration patterns using the otolith data that we collected: estuarine resident (type I), freshwater migrant (type II), estuarine migrant (type III), seawater resident (type IV), and seawater migrant (type V). A canonical discriminant analysis plot revealed separation of two groups (type II in the Yellow Sea vs. other types in remaining locations). Two locations on Jeju Island, despite their close proximity, had fish with quite different migration patterns, corroborating previous molecular studies that distinguished two groups of fishes. Conclusion: We successfully showed that the migration patterns of the Korean mullet varied by location. Only fish from the western sector of Jeju had a unique migration pattern, which is likely confined population in this area. Among the eight otolith elements measured, the Sr:Ca ratio was found to be the best indicator of migration pattern and population origin.