• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.313-326
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• 2018

This paper introduces core techniques on ship detection and tracking based on a compact HF radar platform which is necessary to establish a wide-area surveillance network. Currently, most HF radar sites are primarily optimized for observing sea surface radial velocities and bearings. Therefore, many ship detection systems are vulnerable to error sources such as environmental noise and clutter when they are applied to these practical surface current observation purpose systems. In addition, due to Korea's geographical features, only compact HF radars which generates non-uniform antenna response and has no information on target information are applicable. The ship detection and tracking techniques discussed in this paper considers these practical conditions and were evaluated by real data collected from the Yellow Sea, Korea. The proposed method is composed of two parts. In the first part, ship detection, a constant false alarm rate based detector was applied and was enhanced by a PCA subspace decomposition method which reduces noise. To merge multiple detections originated from a single target due to the Doppler effect during long CPIs, a clustering method was applied. Finally, data association framework eliminates false detections by considering ship maneuvering over time. According to evaluation results, it is claimed that the proposed method produces satisfactory results within certain ranges.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.1
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• pp.42-62
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• 2012

This paper suggests a genuine method to estimate the agglomeration effects of Industrial Cluster focusing on the FOODPOLIS (KOREA NATIONAL FOOD CLUSTER). In this study, we will focus on two issues related to the clustering effect. First, Clusters affect productivity, and a cluster allows companies to operate more productively in inputs; accessing technology, human resource, information, services, and needed institutions. Second, we assume that the effects of Industrial Cluster can be estimated from measurement on differency of an added value between large-scale enterprises and smaller ones. To demonstrate effectiveness of this approach, the estimated effect was compared with that from the related study (A Mini-Cluster). Industry Clusters have been considered as critical factors for regional competitiveness and economic revitalization. For this, the government and local government should find a way and strategy to provide useful contents that can attract the participation of firms and to secure strategic positioning and competition strategies.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.173-193
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component-based software development to promote application interaction and integration within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web services repositories not only be well-structured but also provide efficient tools for an environment supporting reusable software components for both service providers and consumers. As the potential of Web services for service-oriented computing is becoming widely recognized, the demand for an integrated framework that facilitates service discovery and publishing is concomitantly growing. In our research, we propose a framework that facilitates Web service discovery and publishing by combining clustering techniques and leveraging the semantics of the XML-based service specification in WSDL files. We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the Web service domain. We have developed a Web service discovery tool based on the proposed approach using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web services repositories. We believe that both service providers and consumers in a service-oriented computing environment can benefit from our Web service discovery approach.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.33-54
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• 2010

The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of public Web service repositories have been proposed, but the Web service taxonomy generation has not been satisfactorily addressed. Unfortunately, most existing Web service taxonomies are either too rudimentary to be useful or too hard to be maintained. In this paper, we propose a Web service taxonomy generation framework that combines an artificial neural network based clustering techniques with descriptive label generating and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service repositories. We report on some preliminary results demonstrating the efficacy of the proposed approach.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.1
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• pp.341-357
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• 2018

Due to the paradigm of open science and advanced digital information technology, data sharing and re-use have been actively conducted and considered data-intensive in a wide variety of disciplines. This study aims to investigate the intellectual structure portrayed by the research products re-using the data sets from ICPSR. For the purpose of this study, a total of 570 research products published in 2017 from the ICPSR site were collected and analyzed in two folds. First, the authors and publications of those research products were analyzed in order to show the trends of research using ICPSR data. Authors tend to be affiliated with university or research institute in the United States. The subject areas of journals are recognized into Social Sciences, Health, and Psychology. In addition, a network with clustering analysis was conducted with using co-word occurrence from the titles of the research products. The results show that there are 12 clusters, mental health, tabocco effect, disorder in school, childhood, and adolescence, sexual risk, child injuries, physical activity, violent behavior, survey, family role, women, problem behavior, gender differences in research areas. The structure portrayed by ICPSR data re-uses demonstrates that substantial number of studies in Medicine have been conducted with a perspective of social sciences.

• Horticultural Science & Technology
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• v.31 no.5
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• pp.580-589
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• 2013

This study was carried out to evaluate the suitability of microsatellite markers for varietal identification and genetic relationship of 170 commercial pepper cultivars. The relationship between marker genotypes and 11 pepper cultivars with different morphological traits was also analyzed. Of the 302 pairs of microsatellite primers screened against 11 pepper cultivars, 24 pairs were highly polymorphic in terms of number of alleles. These markers were applied for the construction of DNA profile data base for 170 commercial pepper cultivars. A total of 164 polymorphic amplified fragments were obtained from 24 microsatellite primers. The average polymorphism information content was 0.673 ranging from 0.324 to 0.824. One hundred and sixty four microsatellite alleles were used to calculate Jaccard's distance coefficients using unweighted pair group method. A clustering group of varieties, based on the results of microsatellite analysis, were categorized into 3 major groups corresponding to morphological traits. The phenogram discriminated all varieties by markers genotypes. These microsatellite markers will be useful as a tool for protection of plant breeders' intellectual property rights through variety identification in distinctness, uniformity and stability test.

• Journal of Biomedical Engineering Research
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• v.40 no.3
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• pp.105-115
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• 2019

Brain tumor surgery may be difficult, but it is also incredibly important. The technological improvements for traditional brain tumor surgeries have always been a focus to improve the precision of surgery and release the potential of the technology in this important area of the body. The need for precision during brain tumor surgery has led to an increase in Robotic-assisted surgeries (RAS). One of the challenges to the widespread acceptance of RAS in the neurosurgery is to recognize invisible tumor accurately. Therefore, it is important to detect brain tumor size and location because surgeon tries to remove as much tumor as possible. In this paper, we proposed brain tumor detection procedures for MRI (Magnetic Resonance Imaging) system. A method of automatic brain tumor detection is needed to accurately target the location of the lesion during brain tumor surgery and to report the location and size of the lesion. In the qualitative assessment, the proposed method showed better results than those obtained with other brain tumor detection methods. Comparisons among all assessment criteria indicated that the proposed method was significantly superior to the threshold method with respect to all assessment criteria. The proposed method was effective for detecting brain tumor.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.59-67
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• 2019

Most of the prior researches in brand extension evaluation have utilized purchase intention as a n effective variable to assess the effectiveness of brand extensions. In contrast, the author proposes that trial intention is to better predict consumers' behavioral response in the newly launched brand extension markets where relate to high risk and uncertainty. Furthermore, the study explores the effects of attitude toward parent brand and consumers' characteristics (perceived similarity and consumption experience) on trial intention of brand extensions. In order to achieve the purpose of the study, the data collection was conducted for actual consumers who had experience using parent brand products. This study employed experiment and questionnaire survey and collected data of 186 was analyzed using clustering analysis and regression analysis. The main results are as follows. First, attitude toward parent brand has a positive effect on trial intention of the extensions. Second, perceived similarity and consumption experience of parent brand have moderating effects on the relation of attitude toward parent brand and trial intention of brand extensions. The results provide that both industry and academic researchers with a guide to process trial intention of brand extension from a comprehensive perspective.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.357-369
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• 2018

The Korean common bean (Phaseolus vulgaris L.) has been receiving increased attention as a functional food. The objective of this study was to reveal the phytochemicals genetic variation and antioxidant activity of 209 Korean common bean landraces. Antioxidant activity was evaluated with the DPPH (2,2-diphenyl-1-picryl-hydrazyl-hydrate), ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid), ferric reducing antioxidant power (FRAP), and superoxide dismutase (SOD) assay. Antioxidant activities among common bean accessions showed wide variation. Four flavonoids (kaempferol, myricetin, quercetin, and naringenin) of the 209 Korean common bean landraces were measured using HPLC. Among them, kaempferol had the highest phytochemicals compared to the other three flavonoids. Using the relative antioxidant capacity index (RACI), it was found out that the IT104587 had the highest antioxidant activity. Meanwhile, in clustering analysis, the Korean common bean landraces were classified into three clusters. Among them, cluster II contained 64 landraces with higher antioxidant activities and phytochemicals than the other clusters, except DPPH. The results could provide information on the valuable Korean common bean landraces for the development of new common bean varieties.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.33-40
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• 2021

Currently, the shipping and port industries are implementing strategies to improve port processing capabilities through the expansion and efficient operation of port logistics resources to survive fierce competition with rapidly changing trends. The calculation of the port's processing capacity is determined by the loading and unloading equipment installed at the dock, and the port's processing capacity can be improved through various methods, such as additional deployment of logistics resources or efficient operation of resources in use. However, it is difficult to expect an improvement effect in a short period of time because the additional deployment of logistics resources is clearly limited in time is clear. Therefore, it is a feasible way to find an efficient operation method for resources being used to improve processing capacity. Domestic ports are also actively promoting informatization and digitalization with the development of the 4th industrial revolution technology. However, the calculation of the number of Y/T (Yard Tractor) assignments in the current unloading process depends on expert experience, and related previous studies also focus on the allocations of Y/T or Calculation of the total number of Y/T required. Therefore, this study analyzed the factors affecting the number of Y/T allocations using the loading and unloading information of incoming ships, and based on this, cluster analysis, regression analysis, and deep neural network(DNN) model were used.