• Journal of Ginseng Research
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• v.40 no.4
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• pp.395-399
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• 2016

Background: Korean ginseng (Panax ginseng) is one of the most important medicinal plants in the Orient. Among nine cultivars of P. ginseng, Chunpoong commands a much greater market value and has been planted widely in Korea. Chunpoong has superior quality "Chunsam" ($1^{st}$ grade ginseng) when made into red ginseng. Methods: A rapid and reliable method for discriminating the Chunpoong cultivar was developed by exploiting a single nucleotide polymorphism (SNP) in the auxin repressed protein gene of nine Korean ginseng cultivars using specific primers. Results: An SNP was detected between Chunpoong and other cultivars, and modified allele-specific primers were designed from this SNP site to specifically identify the Chunpoong cultivar and P. quinquefolius via multiplex polymerase chain reaction (PCR). Conclusion: These results suggest that great impact to prevent authentication of precise Chunpoong and other cultivars using the auxin repressed protein gene. We therefore present an effective method for the authentication of the Chunpoong cultivar of P. ginseng and P. quinquefolius.

• International Journal of Internet, Broadcasting and Communication
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• v.5 no.2
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• pp.1-4
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• 2013

With the recent development of the ubiquitous computing technology, there are increasing interest and research in technologies such as sensors and RFID related to information recognition and location positioning in various ubiquitous fields. Especially, RTLS (Real-Time Locating Services) dealing with spatio-temporal data is emerging as a promising technology. For these reasons, the ISO/IEC published RTLS standard specification for compatibility and interoperability in RTLS. Therefore, in this paper, we designed and implemented Spatio-temporal Query Processing Systems for efficiently managing and searching the incoming Spatio-temporal data stream of moving objects. Spatio-temporal Query Processing Systems's spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. Web Server uses the SOAP(Simple Object Access Protocol) message between client and server for interoperability and translates client's SOAP message into CQL(Continuous Query Language) of the spatio-temporal middleware.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.8
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• pp.707-716
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• 2013

Tire noise is divided into two parts. One is pattern noise the other one is road noise. Pattern noise primarily occurs in over 500 Hz frequency but road noise occurs mainly in low frequency. It is important to develop a technology to predict the pattern noise at the design stage. Prediction technology of pattern noise has been developed by using image processing. Shape of tire pattern is computed by using imaging signal processing. Its results are different with the measured one. Therefore, the prediction of actual measured pattern noise is valuable. In the signal processing theory is applied to calculate the impulse response for the measurement environment. This impulse response used for the prediction of pattern noise by convolving this impulse response by the results of image processing of tire pattern.

• Smart Structures and Systems
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• v.17 no.6
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.44 no.3
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• pp.308-317
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• 2011

A MBES (multibeam echo sounder) survey around Yokji Island, Korea, was conducted to find an effective method for removing error data. Two post-processing software programs, PDS2000 (RESON) and HIPS (CARIS), were used to remove the error data using an interactive editing method and the CUBE algorithm filter. The post-processing with the PDS2000 and HIPS programs, using the interactive editing method, took 120 and 168 hours, respectively, and there was little difference in the seafloor images. The processing time of the PDS2000 and HIPS programs using the CUBE algorithm filter was 36 and 60 hours, respectively. Nevertheless, there was little difference in the seafloor images because of differences in the factor parameters in each of the post-processing programs. Therefore, post-processing using CUBE filtering can save time in data processing and provide consistent results, excluding the subjective decisions of the operator. This method is more effective than other methods for rejecting erroneous multibeam echo sounder data.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.355-366
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• 2002

The web is one of the most plentiful sources of images. The web has an immediate need for image processing technology in Java. This paper provides a practical introduction to statistical image processing using Java on the web. The paper describes how images are represented in Java and deals with four image processing operations based on basic statistical methods: point processing, spatial filtering, edge detection and image segmentation.

• Applied Biological Chemistry
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• v.36 no.5
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• pp.339-345
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• 1993

To utilize effectively sardine as a material of pickled products, we investigated on processing of vinegar pickled sardine. The moisture, the crude ash and histamine contents showed a little change during vinegar pickling of salted sardine. The pH and viable cell counts decreased during vinegar pickling of salted sardine. The pickled sardine processed with vinegar seasoning solution mixed antioxidants was retarded in lipid oxidation during processing. The principal taste compounds of vinegar pickled sardine were organic acid (acetic acid), IMP and free amino acids such as histidine, lysine, glutamic acid and arginine. The vinegar pickled sardine was higher in the contents of limiting amino acids of cereal such as lysine, and 20 : 4 and polyunsaturated fatty acid such as 20 : 5 and 22 : 6 than those of other processed foods.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.5
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• pp.101-111
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• 2015

Establishment of appropriate data in certain formats is essential for agricultural water cycle analysis, which involves complex interactions and uncertainties such as climate change, social & economic change, and watershed environmental change. The main objective of this study was to develop web-based Data processing and Model linkage Techniques for Agricultural Water-Resource analysis (AWR-DMT). The developed techniques consisted of database development, data processing technique, and model linkage technique. The watershed of this study was the upper Cheongmi stream and Geunsam-Ri. The database was constructed using MS SQL with data code, watershed characteristics, reservoir information, weather station information, meteorological data, processed data, hydrological data, and paddy field information. The AWR-DMT was developed using Python. Processing technique generated probable rainfall data using non-stationary frequency analysis and evapotranspiration data. Model linkage technique built input data for agricultural watershed models, such as the TANK and Agricultural Watershed Supply (AWS). This study might be considered to contribute to the development of intelligent watercycle analysis by developing data processing and model linkage techniques for agricultural water-resource analysis.

• Korean Chemical Engineering Research
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• v.56 no.3
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• pp.343-348
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• 2018

Each of the two polycarbonates (PC) of different molecular weights was blended with acrylonitrile-butadiene-styrene (ABS) under high-shear rate processing to afford PC/ABS. Sizes of ABS dispersed phases and mechanical properties of PC/ABS blends were investigated and high-shear rate processing of PC/ABS was carried out by changing screw speed and processing time. Prepared specimens were examined by scanning electron microscope (SEM) to observe morphology changes. Sizes of ABS dispersed phases in PC/ABS blends were observed to decrease gradually as screw speeds increased. Tensile strengths and elongations of specimens were investigated by universal testing method (UTM) to study the influence of molecular weight of PC exerting on PC/ABS blends. As a result, PC1/ABS blends (PC1: higher molecular weight PC) exhibited more strengthened properties than PC2/ABS (PC2: lower molecular weight PC). The tensile strength of PC1/ABS showed an increasing tendency when the screw speed increased, and the elongation did not show a significant decrease, but increased slightly with increasing shear time at a constant screw speed of 1000 rpm.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.989-998
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• 2013

We cannot analyze big data, which attracts recent attentions in industry and academy, by batch processing algorithms developed in data mining because big data, by definition, cannot be uploaded and processed in the memory of a single system. So an imminent issue is to develop various leaning algorithms so that they can be applied to big data. In this paper, we review various algorithms for support vector machines in the literature. Particularly, we introduce online type and parallel processing algorithms that are expected to be useful in big data classifications and compare the strengths, the weaknesses and the performances of those algorithms through simulations for linear classification.