• Proceedings of the Korean Society of Marine Engineers Conference
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• 2011.06a
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• pp.79-79
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• 2011

The oceans are an untapped resource, capable of making a major contribution to our future energy needs. In the search for a non polluting renewable energy source, there is a push to find an economical way to harness energy from the ocean. Tidal stream is one of ocean energy form that is being investigated as potential source for power generation. Tidal current turbines are therefore designed as conversion machinery to generate power from tidal currents. A study on energy extraction from tidal currents is presented in this paper.

• International Journal of Contents
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• v.8 no.1
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• pp.30-38
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• 2012

Text extraction and binarization are the important pre-processing steps for text recognition. The performance of text binarization strongly related to the accuracy of recognition stage. In our proposed method, the first stage based on line detection and shape feature analysis applied to locate the position of a business card and detect the shape from the complex environment. In the second stage, several local regions contained the possible text components are separated based on the projection histogram. In each local region, the pixels grouped into several connected components based on the connected component labeling and projection histogram. Then, classify each connect component into text region and reject the non-text region based on the feature information analysis such as size of connected component and stroke width estimation.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.447-459
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• 2020

After reading a document, people construct a concept about the information they consumed and merge multiple words to set up keywords that represent the material. With that in mind, this study suggests a smarter and more efficient keyword extraction method wherein scholarly journals are used as the basis for the establishment of production rules based on a concept information of words appearing in a document in a way in which author-provided keywords are functional although they do not appear in the body of the document. This study presents a new way to determine the importance of each keyword, excluding non-relevant keywords. To identify the validity of extracted keywords, titles and abstracts of journals about natural language and auditory language were collected for analysis. The comparison of author-provided keywords with the keyword results of the developed system showed that the developed system was highly useful, with an accuracy rate as good as up to 96%.

• Preventive Nutrition and Food Science
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• v.6 no.2
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• pp.133-135
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• 2001

The edible part of cucurbita moschata Duch, which is commonly used as a Korean traditional medicine as well as a popular food source, was studied to isolate anti-complementary substance. Extracts of Cucurbita moschata Duch showed significant anti-complementary activities on the classical pathway of the complement system. Especially, the ripe Cucurbita moschata Duch had more activity than that of the complement system. Especially, the ripe Cucurbita moschata Duch had more activity than that of the green one in terms of the overall anti-complementary activity. Among the extracts of various organic solvents of the ripe Cucurbita moschata Duch, chloroform and ethyl-acetate extracts, which are non-polar solvent extracts, showed the strongest activities. These results suggest that the major difference in the solvent extraction for the anti-complementary substances depends on the change in the chemical composition such as the fatty acid with the degree of ripening.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.31-38
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• 2011

Skin color is a very important information for an automatic face recognition. In this paper, we proposed a skin region extraction method using the MLP(Multi-Layer Perceptron) and skin color model. We use the adaptive lighting compensation technique for improved performance of skin region extraction. Also, using an preprocessing filter, normally large areas of easily distinct non-skin pixels, are eliminated from further processing. Experimental results show that the proposed method has better performance than the conventional methods, and reduces processing time by 31~49% on average.

• The korean journal of orthodontics
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• v.50 no.1
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• pp.52-62
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• 2020

This case report presents the orthodontic treatment of a 25-year-old patient with skeletal Class II and severe maxillary arch crowding, moderate mandibular arch crowding, anterior crossbite, and a missing lower incisor. He was treated with molar distalization using a modified C-palatal plate and temporary anchorage devices to create sufficient space for retraction. The total treatment duration was 21 months. After treatment, his occlusion and smile esthetics showed significant improvement. The modified C-palatal plate represents a treatment modality that enhances the prospects of non-extraction treatment and reduces the need for extraction.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.231-240
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• 2001

Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1999.05a
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• pp.169-172
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• 1999

Recently, the wavelet transform has been a new and powerful tool for signal processing. It is more suitable specially for the feature extraction and detection of non-stationary signals than traditional methods such as, the Fourier Transform(FT), the Fast Fourier Transform(FFT) and the Least Square Method etc. because of the characteristic of the multi-scale analysis and time-frequency domain localization. The wavelet transform has been developed for the analysis of PD pulse signal to raise in the progress of insulation degradation. In this paper, the wavelet transform was applied to one foundational method for feature extraction. For the obtain experimental data, a computer-aided partial discharge measurement system with a single acoustic sensor was used. If we are applying to the neural network method the accumulated data through the extracted feature, it is expected that we can detect the PD pulse signal in the insulation materials on the on-line.

• ETRI Journal
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• v.33 no.4
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• pp.547-557
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• 2011

This study presents an approach for extracting boundaries of various buildings, which have concave boundaries, inner yards, non-right-angled corners, and nonlinear edges. The approach comprises four steps: building point segmentation, boundary tracing, boundary grouping, and regularization. In the second and third steps, conventional algorithms are improved for more accurate boundary extraction, and in the final step, a new algorithm is presented to extract nonlinear edges. The unique characteristics of airborne light detection and ranging (LIDAR) data are considered in some steps. The performance and practicality of the presented algorithm were evaluated for buildings of various shapes, and the average omission and commission error of building polygon areas were 0.038 and 0.033, respectively.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.225-226
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• 2005

In this Study, we have acquired 5-simulation Fault types Signals of high voltage Motor stator winding using epoxy/mica coupler. In order to know stator winding fault type using fault signals, we have performed feature extraction to apply wavelet transform technique. we have obtained skewness and kurtosis as statistical parameters of fault signal pattern from non deterioration state winding. We have know that 5 fault signals types have done an exponential function pattern shape but individually fault a class widely was different each other a signal waveform of pattern.