• Proceedings of the Technology Innovation Conference
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• 1997.12a
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• pp.197-228
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• 1997

This study aims to evaluate and identify the Patterns of the technological competitiveness of the Korean industry. Such statistics as R&D expenditure and R&D manpower as input indexes, US patent registrations and export sales as output indexes were used. it was turned out that such industrial types as specialized-suppliers industries, scale-intensive industries and science-intensive industries showed relatively strong technical competitiveness. However, resource-intensive industries and labor-intensive industries which had maintained a competitive advantage in the 1970s and the 1980s appeared to be gradually losing their technological competitiveness. These results are by and large in accordance with the trends of export performance. This study conducted the canonical discriminant analysis in order to test the correctness of the patterns displayed in the technological competitiveness of the Korean industry. The result of the analysis showed that the five patterns of technical strength of the Korean industries are significantly independent each other for four respective variables which are used to distinguish industries. This implies that the ex ante industrial classification into five typers was correct in terms of the ex post statistics, and that the patterns of technological competitiveness discovered in this study are also statistically correct.

• ETRI Journal
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• v.18 no.3
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• pp.161-170
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• 1996

We show that the electrically coupled Hindmarsh-Rose neuronal model exhibits various patterns of phase locking at fixed parameter value. Through the analysis of the effective coupling, the system is shown to be stabilized in one of these patterns according to the initial conditions. This corresponds to the parameter-tuning independent mode-switching mechanism that changes the electrical output of neuronal systems. It is also presented how the stable fixed points of the effective coupling which characterize the phase locking patterns depend on the external current.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.898-902
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• 2003

In this paper we proposes a new technique for identification of breast cancer by classification of proteome pattern generated from 2-D polyacrylamide gel electrophoresis (2-D PAGE) and development of cancer diagnosis system : HABIT. Proteome patterns reflect the underlying pathological state of a human organ and it is believed that the anomalies or diseases of human organs are identified by the analysis or classification of the patterns. Proteome patterns consist of quantitative information of the spots such as their size, position, and density in the proteome image produced from 2-D PAGE, for the Image mining of proteome pattern, SVM(support vector machine) and GA(genetic algorithm) are used to generate a decision model for the identification of breast cancer The decision model was then used to classify an independent set of test proteome patterns into the affecter and unaffecter classes. The proposed technique was tested by actual clinical test samples and showed a good performance of a hit ratio of 90%.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.188-195
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• 1999

The fMRI signals are composed of many various signals. It is very difficult to find the accurate parameter for the model of fMRI signal containing only neural activity, though we may estimating the signal patterns by the modeling of several signal components. Besides the nose by the physiologic motion, the motion of object and noise of MR instruments make it more difficult to analyze signals of fMRI. Therefore, it is not easy to select an accurate reference data that can accurately reflect neural activity, and the method of an analysis of various signal patterns containing the information of neural activity is an issue of the post-processing methods for fMRI. In the present study, fMRI data was analyzed with the Independent Component Analysis(ICA) method that doesn't need a priori-knowledge or reference data. ICA can be more effective over the analytic method using cross-correlation analysis and can separate the signal patterns of the signals with delayed response or motion related components. The Principal component Analysis (PCA) threshold, wavelet spatial filtering and analysis of a part of whole images can be used for the reduction of the freedom of data before ICA analysis, and these preceding analyses may be useful for a more effective analysis. As a result, ICA method will be effective for the degree of freedom of the data.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.93-104
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• 2009

Modular implementation of a feature is a first step toward feature-oriented product line engineering, which develops and then utilizes core assets to configure products in terms of features. Aspect-oriented programming provides effective mechanisms for improving the modularity of feature implementations. However, as features in general are not independent of each other, changes in the implementation of one feature may cause changes to or side effects in the implementation of other features. Moreover, since the time at which a feature is incorporated into products, called feature binding time, may be various from compile time through load time to run time, a feature may have to be implemented differently depending on when the feature is bound into a product. To make each feature implementation module as independent as possible, this paper proposes aspectual implementation patterns that can effectively separate feature dependencies as well as feature binding time from feature implementation modules. These patterns enable flexible composition of feature implementation modules without affecting other modules according to feature selection. The approaches are demonstrated and evaluated based on a product line of scientific calculator applications.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.6
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• pp.61-67
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• 2004

We propose a new algorithm to generate additional training patterns using the brain-style information processing algorithm, that is, supervised and unsupervised learning models. This will be useful in the case that we do not have enough number of training patterns because of limitation such as time consuming, economic problem, and so on. We adopt the independent component analysis as an unsupervised model for generating exempalr patterns and multilayer perceptions as supervised models for verifying usefulness of the generated patterns. After statistical analysis of the proposed pattern generation algorithm, we verify successful operations of our algorithm through simulation of handwritten digit recognition with various numbers of training patterns.

• Physical Therapy Korea
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• v.5 no.2
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• pp.23-38
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• 1998

The objective of this study was to identify the effects of pelvic tilting exercise on gait patterns of hemiplegic patients. The subjects of this study were 31 hemiplegic in- and out-patients of the Rehabilitation Hospital, Yonsei University Medical Center, from September 24, 1997 through November 5, 1997. Pre- and post-treatment change in gait patterns were measured using a ink foot-print. The data were analyzed by the paired t-test, one-way ANOVA, and independent t-test. The findings were as follows: The difference in gait patterns between pre- and post-treatment was statistically significant, with an increase in gait velocity to 7.98 cm/sec post-treatment; an increase in cadence to 7.29 steps/min; a narrowing of the base of support to 1.33 cm; an increase in step length of 3.92 cm on the less affected side and 3.73 cm on the more affected side; an increase in stride length of 5.82 cm on the less affected side and 5.92 cm on the more affected side(statistically not significant in foot angle). In relation to sex, age, cause of stroke, and laterality of paralysis, the difference in gait patterns between pre- and post-treatment was not statistically significant. Where there was no significant difference of the effects of pelvic exercise regarding the degree of spasticity, the presence of a decrease in proprioception, and the duration of treatment. In conclusion, hemiplegic pelvic tilting exercise was found to have transmitting positive effect in improving gait patterns.

• Proceedings of the CALSEC Conference
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• 2004.02a
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• pp.15-20
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• 2004

Positivism ▣Quantitative research ▣Descriptive, predictive, explanatory ▣Quest for university laws ▣Concerned with the empirical testability of theories (·Causal models (if it's not about cause-and-effect, it's not Science)) ▣Assumptions：(·Existence of a priori fixed relationship within phenomena ·Regular patterns of causation ·Independent from human mind(objective, factual)(omitted)

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.4
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• pp.127-142
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• 2020

This study compared the domestic and international commercial design patterns and domestic consumer preferences for wetsuit designs to develop a user-centered wetsuit design. An analysis of the domestic and international design elements for 1,802 wetsuits sold online over the past three years showed that the most frequent shapes, dominant colors, and patterns were the same, as consumers tended to buy full suits that were black or had geometric patterns. Dominant colors and assort/accent colors were different from the survey results. Men's wetsuits used fewer colors and patterns than women's suits. Domestic wetsuits used fewer patterns than those sold abroad; in addition, colors were applied differently. A consumer preference survey conducted on 213 male and female consumers in their 20s and their 50s in Korea indicated that 53.5% of respondents were the most affected by the shape when choosing a wetsuit design. The preferred color scheme was two colors, with a vivid tone used as an accent color. The factor analysis results on wetsuit design preference uncovered the six factors: individuality, display, function, acceptance, imitation, and comparison. An independent sample t-test also showed that men perceive individuality, imitations, and comparison factors higher than women.

• Journal of the Korean Home Economics Association
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• v.35 no.1
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• pp.415-428
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• 1997

In the present study we examined clothing expenditure patterns and related variables in Korea. In addition we analyzed the differences of clothing expenditure patterns between overall overspenders and non-overspenders. We use the Family Income and Expenditure Study published by the National Statistical Office of Korea. Double logarithm functional forms were used to adjust the normality of sample distribution and multiple regression analyses and t-test were utilized as a statistical tools. The present study was divided into four folders. First the income elasticity of clothing expenditures was examined by different groups such as age job and education levels of households as percentage change of clothing expenditures to a percentage change of income. Second to analyze the effects of demogtraphic and socio-economic variables on clothing expenditure we utlized the standardized coefficients in the separate regression equation by demographic and socio-economic variables. Third using spending to income ratio we investigated the differnces of the clothing expenditure patterns between overall overspenders and non-overspenders. Fourth the effects of independent variables by ovespenders and non-overspenders werediscussed.