• Journal of Engineering Education Research
• /
• v.17 no.4
• /
• pp.43-47
• /
• 2014

The rapid development of science & technology and the globalization of society have accelerated the fractionation and specialization of academic disciplines. Accordingly, Korean colleges and universities are continually dropping antiquated courses to make room for new courses that better meet societal demands. With emphasis placed on providing students with a broader range of choices in terms of course selection, compulsory courses have given way to elective courses. On average, 4 year institutions of higher learning in Korea currently offer somewhere in the neighborhood of 1,000 different courses yearly. The classification of an ever growing list of courses offered and the practical use of such data would not be possible without the aid of computers. For example, if we were able to show the pre/post requisite relationship among various courses as well as the commonalities in substance among courses, such data generated regarding the interrelationship of different courses would undoubtedly greatly benefit the students, as well as the professors, during course registration. Furthermore, the GT system's relatively simple approach to course classification and coding will obviate the need for the development of a more complicated keyword based search engine, and hopefully contribute to the standardization of the course coding scheme in the future..Therefore, as a sample case project, this study will use GT to classify and code all courses offered at the College of Engineering of K University, thereby developing a system that will facilitate the scanning of relevant courses.

• Proceedings of the Korea Contents Association Conference
• /
• 2014.06a
• /
• pp.291-292
• /
• 2014

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1999.11a
• /
• pp.494-497
• /
• 1999

Neural networks are shown to be effective in being able to distinguish incomplete penetration-like weld defects by directly analyzing the plasma which is generated on each impingement of the laser on the materials. The performance is similar to that of existing methods based on extracted feature parameters. In each case around 93% of the defects in a database derived from 100 artificially produced defects of known types can be placed into one of two classes: incomplete penetration and bubbling. Especially we present simulator for weld defects classification and data analysis. The present method based on classification using plasma is faster, and the speed is sufficient to allow on-line classification during data collection.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1998.10a
• /
• pp.166-170
• /
• 1998

Classification and Coding(C&C) systems as a core of design information management have been accomplished by many studies in terms of design and manufacturing attribute based on Group Technology. Those are very difficult to apply in make-to-order(MTO) manufacturing because the environment of MTO has various characteristics of product, many licensors, engineering change, insufficiency of integrated management system for codes and so on. This paper presents a suitable C&C system to MTO manufacturing which consider management level and drawing.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.1383-1387
• /
• 2009

As information technologies in construction field get developed, various studies and projects are in progress for improvement of construction industry. Meanwhile, web-basis online system for building materials is tending upward. However, most of the informations about classification system for building materials and specifications are not systematic yet. Most field staffs have some troubles in making full use of the material information, repeating inefficient works from constructional design to the maintenance of it. This study designed auto-categorization system classified by materials, multi-search engines, auto-converting/creating electronic catalog as well as RFID search support to provide standardized building materials information.

• The Journal of the Korea Contents Association
• /
• v.9 no.1
• /
• pp.131-138
• /
• 2009

This paper is about adult certification on Mobile RFID Service Environments coming through the combination of RFID(Radio Frequency IDentification) technology, as the core technology of ubiquitous environments, and mobile telecommunication technology. To overcome the shortcoming of simple adult certification on current internet, we suggest a framework for content-based classification and propose an adult certification system using it. At first, we explain conventional methods for adult certification, and show a criteria of content-based classification for preventing an exposure of adult contents from minors. Additionally, we describe data structure and system for the proposed adult certification on mobile RFID environment, and finish it with concluding remarks.

• Journal of Biosystems Engineering
• /
• v.38 no.4
• /
• pp.264-269
• /
• 2013

Purpose: This study was carried out to develop a classification index and grade levels to rate agricultural heaters for energy efficiency classification. Methods: The classification index was developed mainly by taking simplicity of calculation and easy access to relevant data into consideration. The grade levels were developed on the basis of a 5-grade classification system in which graded heaters are to be normally distributed over the grades. The value of each grade level were determined in terms of the classification index values calculated using the published performance data of agricultural heaters tested at the FACT in Korea over the past 12 years. Results: The thermal efficiency of agricultural heaters based on the enthalpy method was proposed as a reasonable classification index. The grade levels were proposed in equation form for three types of agricultural heaters: fossil fuel heaters, wood pellet heaters and wood pellet boilers. A reasonable energy efficiency classification of agricultural heaters could be performed using the proposed classification index and grade levels. Conclusions: It is expected that energy saving programs will be extended to agricultural machines in the near future. The classification index and grade levels to rate agricultural heaters for energy efficiency classification were developed and proposed for such near future to come.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.464-465
• /
• 2018

Bass and Bluegill, which are representative ecosystem disturbance species, are reported to be the most important factor in the reduction of domestic native fish populations in Korea. Therefore, it is necessary to develop system and field application technology for the extermination of these foreign species. Recently, the CNN(Convolutional Neural Network), one of the deep learning systems for the recognition, classification, and learning, has shown excellent performance. However, CNN data used for object recognition and classification were mainly applied to recognition and classification of other objects with distinct characteristics. This study proposes a system that applies CNN to the classification of fish species with similar characteristics.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.13 no.5
• /
• pp.894-902
• /
• 2010

This paper presents a vision-based robust off-road terrain classification method against environmental variation. As a supervised classification algorithm, we applied a neural network classifier using wavelet features extracted from wavelet transform of an image. In order to get over an effect of overall image feature variation, we adopted environment sensors and gathered the training parameters database according to environmental conditions. The robust terrain classification algorithm against environmental variation was implemented by choosing an optimal parameter using environmental information. The proposed algorithm was embedded on a processor board under the VxWorks real-time operating system. The processor board is containing four 1GHz 7448 PowerPC CPUs. In order to implement an optimal software architecture on which a distributed parallel processing is possible, we measured and analyzed the data delivery time between the CPUs. And the performance of the present algorithm was verified, comparing classification results using the real off-road images acquired under various environmental conditions in conformity with applied classifiers and features. Experiments show the robustness of the classification results on any environmental condition.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.33 no.2
• /
• pp.73-79
• /
• 2020

Building Information Modeling (BIM) tools have not only increased the use of technology in the design process, but also increased the need for more information standard systems. The object classification system consists of 327 types of construction results obtained from 25 kinds of facilities, 174 types of parts, and 207 types of construction parts. In the previous study, the property classification system was developed into 4 major classifications, 13 middle classifications, 58 small classifications (category), and 333 attribution information of roads and rivers. It is extremely difficult to input the property information according to such extensive object classification. In addition, the development of external applications such as Revit plug-ins has created a need to automate specific and repetitive tasks. Therefore, following the BIM property classification system, an attribute input program was implemented for the system to enhance the productivity and convenience of the BIM users.