• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.12-23
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• 2003

The expansion of internet and the development of communication technology have brought about an explosive increasement of data. Further progress has led to the increasing demand for efficient and effective data analysis tools. According to this demand, data mining techniques have been developed to find out knowledge from a huge amounts of raw data. This paper suggests a generalization based classification method which explores rules from real world data appearing repeatedly. Also, it analyzed the relation between weather data and forest fire, and efficiently predicted through it as a prediction model by applying the suggested generalization based classification method to forest fire data. Additionally, the proposed method can be utilized variously in the important field of real life like the analysis and prediction on natural disaster occurring repeatedly, the prediction of energy demand and so forth.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.75-81
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• 2012

Road identification is the important task for extracting a road region from the high-resolution satellite images, when the road candidates is extracted by the pre-processing tasks using a binarization, noise removal, and color processing. Therefore, we propose a noble approach for identifying a road using the orientation-selective spatial filters, which is motivated by a computational model of neuron cells found in the primary visual cortex. In our approach, after the neuron cell typed spatial filters is applied to the isolated connected-labeling road candidate regions, proposed method identifies the region of perceiving the strong orientation feature with the real road region. To evaluate the effectiveness of the proposed method, the accuracy&error ratio in the confusion matrix was measured from road candidates including road and non-road class. As a result, the proposed method shows the more than 92% accuracy.

• Journal of Practical Engineering Education
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• v.8 no.1
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• pp.57-62
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• 2016

The purpose of this study is to provide the basic data and to construct education system by analizing the case of Japan on the lifelong vocational competency development utilizing the university. Japan has grown by the world leading technology and talented people. In a globalized world, In order to achieve economic growth, It is necessary to connect the Human resource development to the overall growth of the economy. After the law on policy implementation system for the Lifelong Learning Promotion is enacted. University of japan, the newly defined the philosophy of lifelong learning in the Fundamental Law of Education. Then, University of japan has induced people to actively participate in the lifelong vocational competency development. In this paper, we refer to the Shizuoka University in Japan and learning support program and we studied the method for the activation of improvement and field placement of the training capacity of field training using the case of Japan on the lifelong vocational competency development utilizing the university.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.5
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• pp.74-83
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• 2004

The carrier phase measurements from GPS and GLONASS have different characteristics and therefore, have to be processed with different methods to provide precise positions or attitudes. In this contribution, at first, a measurement model is derived which can be used to not only GLONASS only applications but also both GPS and GLONASS applications. And then an error analysis of the proposed method performed using the derived model to derive analytic relationships between GDOP, PDOP and RGDOP. Finally, an integer ambiguity resolution method which was used in GPS is expanded to GPS and GLONASS. The proposed results can be directly applied to the design and analysis of GLONASS receiver and application programs. Furthermore, it is expected that the suggested method can also be effectively applied to combine the characteristically different measurements from the future satellite navigation systems such as GPS modernization, Galileo and QZSS.

• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.512-521
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• 1999

SGML, defined as the ISO 8879, is a meta-language to define a document type, used as basic format for electronic documents. Since an SGML document is composed of a document type definition and a document instance conforms to the definition, it is necessary for SGML document authoring tools to compose and validate document type and document instance. In present, formal models and procedures for SGML documents are not defined, it's not easy to construct such tools. We propose a model of SGML authoring tool consists of SGML parser, document type definition editor, SGML document editor and style editor. We also introduce and implement formal procedure for each component. For user convenience, we adopted icon based visual programming method, and solved the HANGUL problems. The SGML authoring tool is implemented I Windows NT system using java and C++ programming language.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.786-792
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• 2012

A microarray is a collection of thousands of DNAs or RNAs arranged on a substrate, and it enables one to navigate large amounts of gene expression. However, a researcher uses his designed experimental methods to focus on particular phenotypes from the available mass of data. In this paper, we used MicroRNAs(miRNAs) and Protein-Protein Interation(PPI) databases to enhance and expand meanings in microarray data. Further, the expanded data are linked with the Online Mendelian Inheritance in Man(OMIM), and International Statistical Classification of Diseases and Related Health Problems, $10^{th}$ Revision(ICD-10), in order to extract common genetic relationships between diseases. This approach, we expect, should provide new biological views.

• Journal of Korean Society of Archives and Records Management
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• v.18 no.4
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• pp.149-182
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• 2018

In the era of digital transformation, new technologies have begun to be applied in the field of records management, away from the traditional view that emphasized the existing institutional and administrative aspects. Therefore, this study analyzed the service status of archives, libraries, and museums applied with advanced intelligent technology and identified the differences. Then, we proposed how to apply intelligent archival information services based on the analysis results. The reason for including libraries and museums in the research is that they are covered by a single category as an information service provider. To achieve our study aims, we conducted literature and case studies. Based on the results of the case study, we proposed the application strategies of intelligent archival information services. The results of this study are expected to help develop intelligent archival service models that are suitable for the changed electronic records environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.1-9
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• 2018

In the fourth industrial revolution, which has become an issue now, we have been able to receive instant analysis results faster than the existing slow speed through various Big Data technologies, and to conduct real-time monitoring on mobile and web. First, various irregular sensor Data is generated using IoT device, Raspberry Pi. Sensor Data is collected in real time, and the collected data is distributed and stored using several nodes. Then, the stored Sensor Data is processed and refined. Visualize and output the analysis result after analysis. By using these methods, we can train the human resources required for Big Data and mobile related fields using IoT, and process data efficiently and quickly. We also provide information that can confirm the reliability of research results through real time monitoring.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.619-630
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• 2019

Dyslipidemia is a representative chronic disease affecting Koreans that requires continuous management. It is also a known risk factor for cardiovascular disease such as hypertension and diabetes. However, it is difficult to diagnose vascular disease without a medical examination. This study identifies risk factors for the recognition and prevention of dyslipidemia. By integrating them, we construct a statistical instrumental nomogram that can predict the incidence rate while visualizing. Data were from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. First, a chi-squared test identified twelve risk factors of dyslipidemia. We used a naïve Bayesian classifier model to construct a nomogram for the dyslipidemia. The constructed nomogram was verified using a receiver operating characteristics curve and calibration plot. Finally, we compared the logistic nomogram previously presented with the Bayesian nomogram proposed in this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1670-1675
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• 2021

The adoption of smart construction technology in the construction industry is progressing rapidly. By utilizing smart construction technologies such as BIM (Building Information Modeling), drones, artificial intelligence, big data, and Internet of Things technology, it has the effect of lowering the accident rate at the construction site and shortening the construction period. In order to introduce a digital twin platform for construction site management, real-time construction site management is possible in real time by constructing the same virtual space. The digital twin virtual space construction method collects and processes data from the entire construction cycle and visualizes it using a 3D model file. In this paper, we introduce a modeling automation technique that constructs an efficient digital twin space by automatically generating 3D modeling that composes a digital twin space based on 3D spatial data.