• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.708-708
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• 2002

Recent developments in sensor technologies have provided remotely sensed data with very high spatial resolution. In order to fully utilize the potential of high resolution images, new image classification strategies are necessary. Unfortunately, the high resolution images increase the spectral within-field variability, and the classification accuracy of traditional methods based on pixel-based classification algorithms such as Maximum-Likelihood method may be decreased (Schiewe 2001). Recent development in Object Oriented Classification based on image segmentation algorithms can be used for the classification of forest patches on rugged terrain of Korea. The objectives of this paper are as follows. First, to compare the pros and cons of image classification methods based on pixel-based and object oriented classification algorithm for the forest patch classification. Landsat ETM＋ data and IKONOS data will be used for the classification. Second, to investigate ways to increase classification accuracy of forest patches. Supplemental data such as DTM and Forest Type Map of 1:25,000 scale are used for topographic correction and image segmentation. Third, to propose the best classification strategy for forest patch classification in terms of accuracy and data requirement. The research site for this paper is Namhansansung Provincial Park located at the eastern suburb of Seoul Metropolitan City for its diverse forest patch types and data availability. Both Landsat ETM＋ and IKONOS data are used for the classification. Preliminary results can be summarized as follows. First, topographic correction of reflectance is essential for the classification of forest patches on rugged terrain. Second, object oriented classification of IKONOS data enables higher classification accuracy compared to Landsat ETM＋ and pixel-based classification. Third, multi-stage segmentation is very useful to investigate landscape ecological aspect of forest communities of Korea.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.139-146
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• 2024

Surface-enhanced Raman scattering (SERS) enables the detection of various types of π-conjugated biological and chemical molecules owing to its exceptional sensitivity in obtaining unique spectra, offering nondestructive classification capabilities for target analytes. Herein, we demonstrate an innovative strategy that provides significant machine learning (ML)-enabled predictive SERS platforms through surface-engineered graphene via complementary hybridization with Au nanoparticles (NPs). The hybridized Au NPs/graphene SERS platforms showed exceptional sensitivity (10^-7 M) due to the collaborative strong correlation between the localized electromagnetic effect and the enhanced chemical bonding reactivity. The chemical and physical properties of the demonstrated SERS platform were systematically investigated using microscopy and spectroscopic analysis. Furthermore, an innovative strategy employing ML is proposed to predict various analytes based on a featured Raman spectral database. Using a customized data-preprocessing algorithm, the feature data for ML were extracted from the Raman peak characteristic information, such as intensity, position, and width, from the SERS spectrum data. Additionally, sophisticated evaluations of various types of ML classification models were conducted using k-fold cross-validation (k = 5), showing 99% prediction accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.149-150
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• 2008

Generally, the propeller shaft rate (PSR) estimation algorithm for the classification of the sonar target has the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family from the frequency spectrum, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.555-567
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• 2014

Biometric performance improvement is a challenging task. In this paper, a hierarchical strategy fusion based on multimodal biometric system is presented. This strategy relies on a combination of several biometric traits using a multi-level biometric fusion hierarchy. The multi-level biometric fusion includes a pre-classification fusion with optimal feature selection and a post-classification fusion that is based on the similarity of the maximum of matching scores. The proposed solution enhances biometric recognition performances based on suitable feature selection and reduction, such as principal component analysis (PCA) and linear discriminant analysis (LDA), as much as not all of the feature vectors components support the performance improvement degree.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.498-512
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• 2023

The traditional newspaper industry faces the opportunities and challenges of industry transformation and integration with new media. Consequently, the catalogs of newspapers and magazines are also updated. In this study, necessary information on catalogs was obtained and used to analyze the overall development trend of the newspaper industry. A word frequency analysis was then performed on the introduction and product categories of the catalogs, and the content and types of newspapers and magazines were examined. Furthermore, related factors such as price, number of pages, publishing frequency, and best-selling status were analyzed; the correlation among factors affecting best-selling status was also explored. Subsequently, each element and a combination of elements were used to generate a dataset, build three classification models, and analyze the accuracy of predictions of whether newspapers sold well under other circumstances. The experimental results showed that price is the most critical factor affecting the best-selling status of newspapers and magazines. Publishing frequency and the number of pages were also found to be significant indicators that impact people's subscription choices. Finally, a competitive strategy regarding content, price, quality, and positioning was developed.

• Journal of Families and Better Life
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• v.25 no.3 s.87
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• pp.25-44
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• 2007

The purpose of this study was to classify the financial strategies and investigate major determinants of the financial performance in elderly households. This study used the data of 4,577households with all ages and 1,255 elderly households were from the Korean Labor and Income Panel Study(2000, 2003). The data were analyzed by various statistical methods such as frequency, mean-test, Duncan's multiple range test, k-mean cluster analysis and regression. The major findings were as follows: First, the classified household financial strategy types were Residual(44.3%), Financial Assets(24.0%), Informal Institutional(19.7%), Diversified Portfolio(7.6%), Real Estate(4.5%). Second, the criteria of classification of the financial strategies were relative, not absolute. Third, elderly households that employed a financial assets had the greatest financial performance (62,320,000 won net gain). Households with all ages that employed a diversified portfolio strategy had the greatest financial performance (98,360,000 won net gain). Forth, the determinants of the financial performance were significantly different according to the types of financial strategy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.84-88
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• 2011

In this paper, a new competition strategy for learning vector quantization is proposed. The simple competitive strategy used for learning vector quantization moves the winning prototype which is the closest to the newly given data pattern. We propose a new learning strategy based on k-nearest neighbor prototypes as the winning prototypes. The selection of several prototypes as the winning prototypes guarantees that the updating process occurs more frequently. The design is illustrated with the aid of numeric examples that provide a detailed insight into the performance of the proposed learning strategy.

• International Journal of Costume and Fashion
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• v.5 no.1
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• pp.75-89
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• 2005

The purpose of this study is to empirically ascertain how the fitness between marketing strategy each firm chooses and environment facing each firm affects the performance of firms measured by the growth rate of market share and the growth rate of profit/sales ratio. In doing so, firms are divided into three groups. With regard to the marketing strategy, firms are classified into three groups based on marketing strategy type; prospector, analyzer, and defender. The main result of this study are as follows: First, responding firms are classified into prospector, analyzer, and defender following Miles & Snow's marketing strategy types. This classification is made using a self typing method and further confirmed by a factor analysis using a number of variables relating marketing objectives and marketing mix. Second, the results show that there are significant differences across marketing strategies in the performance measures of the growth rate of market share and profit/sales ratio. It seems, however, that there is no straight forward relationship between the marketing strategy and the performance measures. This strongly implies that the type of marketing strategy to be adopted by each firm should depend on the environment facing each firm. Third, the result indicates that the growth rate of market share tends to depend only on the marketing strategy type regardless of sufficiency and variation of environment, but profit/sales ratio tends to depend on the fitness between marketing strategy type and environment. It implies that a firm should adopt different marketing strategies for different environment characteristics, in order to enhance the efficiency of resources used reflected in the profit/sales ratio.

• Journal of the Korean Society of Physical Medicine
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• v.12 no.4
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• pp.19-28
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• 2017

PURPOSE: The purpose of this study was to describe the Proprioceptive Neuromuscular Facilitation (PNF) Intervention strategy applied International Classification of Functioning, Disability and Health (ICF) Tool about strength, range of motion, scapular stability, pain and function of shoulder for patients with adhesive capsulitis. METHODS: The data was collected by patient with adhesive capsulitis. The patient was a 50-year-old male diagnosed with right shoulder with adhesive capsulitis. We applied the PNF Intervention strategy applied ICF Tool to patient with adhesive capsulitis. PNF interventions were consisting of such as combination of isotonic and stabilizing reversal technique and various positions. PNF interventions were applied, such as those aiming at decreasing pain and disability and increasing range of motion and function for the four weeks. Parameters of result were collected for strength, range of motion, scapular stability, pain and function of shoulder using the hand held dynamometer, goniometer, lateral scapula slide test, and shoulder pain and disability index, respectively. RESULTS: Clinical benefits were observed the patient with adhesive capsulitis for strength, range of motion, scapular stability, pain, and function of shoulder. The patient with adhesive capsulitis improved strength, range of motion, scapular stability, pain, and function of shoulder. CONCLUSION: Patient reported improved strength, range of motion, scapular stability, pain, and function of shoulder after intervention.

• Journal of Fashion Business
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• v.12 no.4
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• pp.46-55
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• 2008

The purpose of this study is to provide the effective internet marketing communication strategy as marketing tools by analyzing the web sites of young casual fashion brands. We've selected 19 young casual fashion brands in 3 department stores and made the classification standard - advertising, promotion, public relation(PR), customer management - and analysed the young casual fashion brands according to 4 classification standard on the web sites. As a result of study, it is found that 19 young casual brands' web sites put an emphasis on activity of customer management and promotion in general. However, they did not conduct the PR and advertising actively compared with other parts. Especially, the promotion strategy occupies more parts than any other parts through the variety of membership card's services. Also they are sending e-mails or providing 1:1(FAQ/Q&A) board to the members as a customer management to be able to help to communicate with customer through the web site.