• Journal of Korea Technology Innovation Society
• /
• v.6 no.1
• /
• pp.110-124
• /
• 2003

In this study, we establish technology classification system for twelve material and component(MC) areas to sup-port systematic information services for MCT-20l0 which is supported by Korean government. We propose some design principles for MC technology classification system. The principles are suggested by considering of the characteristics of MC classification, regarding with scope, originality, hierarchy, relationship between technology classification and product classification, duplication and complex structure, use of information system, and life cycle of the classification system.

• Journal of Information Science Theory and Practice
• /
• v.10 no.spc
• /
• pp.39-45
• /
• 2022

For national industrial development in the Fourth Industrial Revolution, it is necessary to provide researchers with appropriate job information. This can be achieved by interconnecting the National Science and Technology Standard Classification System used for management of research activity with the Korean Employment Classification of Occupations used for job information management. In the present study, an automatic linkage model of classification systems is introduced based on a pre-trained language model for interconnecting science and technology information with job information. We propose for the first time an automatic model for linkage of classification systems. Our model effectively maps similar classes between the National Science & Technology Standard Classification System and Korean Employment Classification of Occupations. Moreover, the model increases interconnection performance by considering hierarchical features of classification systems. Experimental results show that precision and recall of the proposed model are about 0.82 and 0.84, respectively.

• International Journal of Knowledge Content Development & Technology
• /
• v.13 no.1
• /
• pp.111-130
• /
• 2023

There are the national science and technology standard classification system used in Korea, the classification according to the standard classification system for educational organization units, and the Korean standard education classification by the National Statistical Office. It is not suitable for calculation or evaluation, and classification is still mixed depending on the purpose of use. Therefore, in this study, the current status of academic standard classification, issues related to the standard classification system such as research foundation associations and research institutes, and issues related to the academic standard classification through the analysis of existing prior research issues, etc. As a result of the research, first, it is necessary to maintain and strengthen the linkage of the academic classification system, such as maintaining the linkage between the relevant departmental classification systems and strengthening the linkage with the relevant classification system, as a result of analysis of major issues in the academic standard classification system, and the systematic improvement cycle of the revision process and management system and settings are required.

• International Journal of Knowledge Content Development & Technology
• /
• v.2 no.1
• /
• pp.51-65
• /
• 2012

While science and technology information service portals and heterogeneous databases produced in Korea and other countries are integrated, methods of connecting the unique classification systems applied to each database have been studied. Results of technologists' research, such as, journal articles, patent specifications, and research reports, are organically related to each other. In this case, if the most basic and meaningful classification systems are not connected, it is difficult to achieve interoperability of the information and thus not easy to implement meaningful science technology information services through information convergence. This study aims to address the aforementioned issue by analyzing mapping systems between classification systems in order to design a structure to connect a variety of classification systems used in the academic information database of the Korea Institute of Science and Technology Information, which provides science and technology information portal service. This study also aims to design a mapping system for the classification systems to be applied to actual science and technology information services and information management systems.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.204-206
• /
• 2003

In order to utilize remote sensed images effectively, a lot of image classification methods are suggested for many years. But, the accuracy of traditional methods based on pixel-based classification is not high in general. In this study, object oriented classification based on image segmentation is used to classify Landsat images. A necessary prerequisite for object oriented image classification is successful image segmentation. Object oriented image classification, which is based on fuzzy logic, allows the integration of a broad spectrum of different object features, such as spectral values , shape and texture. Landsat images are divided into urban, agriculture, forest, grassland, wetland, barren and water in sochon-gun, Chungcheongnam-do using object oriented classification algorithms in this paper. Preliminary results will help to perform an automatic image classification in the future.

• Journal of Korea Technology Innovation Society
• /
• v.6 no.2
• /
• pp.265-277
• /
• 2003

The various technologies of the science and technology field were systematized to manage information, personnel and R&D activities related to S&T effectively. The resulting “National Standard Science and Technology Classification” which were composed of 19 areas, 160 divisions and 1,023 categories could contribute to establish rational S&T policy. “National Standard Science and Technology Classification” is synthetic in national level because they include all areas of S&T activities. 5 criteria, which were inclusiveness, exclusiveness, likeness, scale and universality, were used to exert every effort in including the opinion of all experts and to consider harmony between S&T areas. In addition, “National Standard Science and Technology Classification” was prepared to be interchangeable with various classification which were used in other R&D management institutes under the different ministries.

• Korean Management Science Review
• /
• v.10 no.1
• /
• pp.1-22
• /
• 1993

Systemetic classification of a technology is critical to the development of technology strategy. This paper suggests a new technology classification scheme for computer and communication : a two-level scheme. Technology is first classified by its role and function in the upper level which forms a 2 * 2 matrix. The technology is then further classified into the lower level of 3 classes by associations among technology elements. Thus, a new classification scheme of 2 * 2 * 3 matrix is proposed for the computer and communication technology.

• Journal of the Semiconductor & Display Technology
• /
• v.10 no.2
• /
• pp.1-5
• /
• 2011

In recent years, worldwide production of solar wafers increased rapidly. Therefore, the solar wafer technology in the developed countries already has become an industry, and related industries such as solar wafer manufacturing equipment have developed rapidly. In this paper we propose the color classification method of the polycrystalline solar wafer that needed in manufacturing equipment. The solar wafer produced in the manufacturing process does not have a uniform color. Therefore, the solar wafer panels made with insensitive color uniformity will fall off the aesthetics. Gaussian mixture models (GMM) are among the most statistically mature methods for clustering and we use the Gaussian mixture models for the classification of the polycrystalline solar wafers. In addition, we compare the performance of the color feature vector from various color space for color classification. Experimental results show that the feature vector from YCbCr color space has the most efficient performance and the correct classification rate is 97.4%.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.2
• /
• pp.109-114
• /
• 2021

When we inspect scaffold defect using sight, inspecting performance is decrease and inspecting time is increase. We need for automatically scaffold defect detection method to increase detection accuracy and reduce detection times. In this paper. We produced scaffold defect classification models using densenet, alexnet, vggnet algorithms based on CNN. We photographed scaffold using multi dimension camera. We learned scaffold defect classification model using photographed scaffold images. We evaluated the scaffold defect classification accuracy of each models. As result of evaluation, the defect classification performance using densenet algorithm was at 99.1%. The defect classification performance using VGGnet algorithm was at 98.3%. The defect classification performance using Alexnet algorithm was at 96.8%. We were able to quantitatively compare defect classification performance of three type algorithms based on CNN.

• International Journal of Computer Science & Network Security
• /
• v.21 no.6
• /
• pp.169-180
• /
• 2021

Since machine learning was invented, there have been many different machine learning-based algorithms, from shallow learning to deep learning models, that provide solutions to the classification tasks. But then it poses a problem in choosing a suitable classification algorithm that can improve the classification/detection efficiency for a certain network context. With that comes whether an algorithm provides good performance, why it works in some problems and not in others. In this paper, we present a data-centric analysis to provide a way for selecting a suitable classification algorithm. This data-centric approach is a new viewpoint in exploring relationships between classification performance and facts and figures of data sets.