• Fire Science and Engineering
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• v.12 no.2
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• pp.69-75
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• 1998

Overall view of fire science research in Korea is introduced by observing research papers published in the Journal of Korean Institute of Fire Science and Engineering, together with research interests and researchs undergoing at universities and research institutes. The role of Koran Institute of Fire Science and Engineering in promoting fire reseaches in Korea is described. In addition, research projects conducted Korean Institute of Fire Science and Engineering in cooperation with universities and research institutes are introduced.

• Journal of the Korean Regional Science Association
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• v.13 no.2
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• pp.119-141
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• 1997

This study aims to identify the role of science park for technology commercialization and business promotion. After theoretical review about science park and technology commercialization, the instruments for stimulating entrepreneurship and business in science park are described. The experience of Taedok Science Town is examined in terms of main sectors of activities, universities as base for technology transfer and the potential for technology commercialization. In conclusion, the complex model is suggested as the development strategy for business incubation in accordance with the stages of development and active technology commercialization.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.spc1
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• pp.295-306
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• 2004

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.13 no.1
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• pp.183-198
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• 2002

In this paper we discuss what Competitive Intelligence means, why it is growing in importance in the business world and how Library and Information Science Schools in the United States are responding to the opportunities presented by Competitive Intelligence. As a conclusion, we discuss some of the implications of our findings for Library and Information Science education in Korea.

• Journal of Animal Science and Technology
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• v.63 no.1
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• pp.198-198
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• 2021

• Korean Journal of Agricultural Science
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• v.49 no.1
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• pp.173-173
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• 2022

• The Korean Journal of Mycology
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• v.49 no.3
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• pp.425-425
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• 2021

• Korean Journal of Radiology
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• v.23 no.9
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• pp.847-852
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• 2022

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.103-111
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• 2021

Obesity affects individuals of all gender and ages worldwide; consequently, several studies have performed great works to define factors causing it. This study develops an effective method to trace obesity levels based on supervised data mining techniques such as Random Forest and Multi-Layer Perception (MLP), so as to tackle this universal epidemic. Notably, the dataset was from countries like Mexico, Peru, and Colombia in the 14- 61year age group, with varying eating habits and physical conditions. The data includes 2111 instances and 17 attributes labelled using NObesity, which facilitates categorization of data using Overweight Levels l I and II, Insufficient Weight, Normal Weight, as well as Obesity Type I to III. This study found that the highest accuracy was achieved by Random Forest algorithm in comparison to the MLP algorithm, with an overall classification rate of 96.7%.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.19-26
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• 2021

CPU is considered the main and most important resource in the computer system. The CPU scheduling is defined as a procedure that determines which process will enter the CPU to be executed, and another process will be waiting for its turn to be performed. CPU management scheduling algorithms are the major service in the operating systems that fulfill the maximum utilization of the CPU. This article aims to review the studies on the CPU scheduling algorithms towards comparing which is the best algorithm. After we conducted a review of the Round Robin, Shortest Job First, First Come First Served, and Priority algorithms, we found that several researchers have suggested various ways to improve CPU optimization criteria through different algorithms to improve the waiting time, response time, and turnaround time but there is no algorithm is better in all criteria.