• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.561-575
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• 2023

The information security industry has seen a wide variety of growth over the past few decades. In particular, various solutions have been proposed in terms of technology, management, and institutional aspects. Nevertheless, it should be notedthat security accidents continue to occur every year. This proves that there are limitations to various business changes in the digital era as existing security is being promoted with technology-oriented and prevention-oriented policies. Thus, people-centric security (PCS) has recently become a hot topic in order to escape the limitations of traditional securityapproaches. Through the concept of information security violations, PCS strategic principles, and expert interviews, this studyaims to present a fundamental security incident response plan by classifying human-caused vulnerabilities into 5 categories and classifying them into 21 detailed components.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.101-107
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• 2018

Recently, Korea's defense industry has advanced highly, and defense R&D budget is gradually increasing in defense budget. However, without objective analysis of defense industry technology, effective defense R&D activities are limited and defense budgets can be used inefficiently. Therefore, in addition to analyzing the defense industry technology quantitatively reflecting the opinions of the experts, this paper aims to analyze the defense industry technology objectively by quantitative methods, and to make efficient use of the defense budget. In addition, we propose a patent analysis method to grasp the characteristics of the defense industry technology and the vacant technology objectively and systematically by applying the big data analysis method, which is one of the keywords of the 4th industrial revolution, to the defense industry technology. The proposed method is applied to the technology of the firepower industry among several defense industrial technologies and the case analysis is conducted. In the process, the patents of 10 domestic companies related to firepower were collected through the Kipris in the defense industry companies' classification of the Korea Defense Industry Association(KDIA), and the data matrix was preprocessed to utilize IPC codes among them. And then, we Implemented association rule mining which can grasp the relation between each item in data mining technique using R program. The results of this study are suggested through interpretation of support, confidence lift index which were resulted from suggested approach. Therefore, this paper suggests that it can help the efficient use of massive national defense budget and enhance the competitiveness of defense industry technology.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.33-48
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• 2024

This study aims to establish the scope and statistics of the K-address information industry in Korea, estimating its size and prospects and estimates the economic effects through K-address information industry based on Input-Output analysis. Considering the characteristics and sectoral structure of the K-address information industry, the study delineates the scope and specific sectors, constructing sectoral statistics linked to the KSIC and the Bank of Korea's industrial classification. The study estimates the sectoral industry size, taking into account potential markets. Furthermore, it analyzes the economic impact of each sector within the K-address information industry. To figure out the economic effects, the study conducts Input-Output analysis by setting the K-address information industry as an exogenous sector in the input-output table. The results indicate that the overall size of the K-address information industry is estimated to grow from 406.1 billion KRW in 2021 to 3.65 trillion KRW in 2030. The economic effects of the K-address information industry vary by sector, emphasizing the importance of synergies and integration with related sectors, particularly those with significant inducement effects in high value-added manufacturing and service sectors. Furthermore, the industry's sensitivity to economic fluctuations is evident through the input-output analysis of inter-industry chain effects.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.3
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• pp.287-298
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• 2013

Objectives: Workers who use chemicals are exposed to safety accidents and occupational diseases. Employers are required to provide workers with Material Safety Data Sheets (MSDSs) in order to prevent accidents and diseases related to chemicals. Thus, it is very important to offer reliable MSDSs. In this paper, we assessed the reliability of MSDSs for chemicals including formaldehyde. Methods: To evaluate MSDS reliability, we collected 14 MSDSs and bulk samples from the chemical industry. MSDS reliability was evaluated by the completeness of details. In order to evaluate the adequacy of the formaldehyde contents in a mixture, bulk samples were collected and analyzed by HPLC. The result of Globally Harmonized System (GHS) classification was confirmed by identifying physical chemical properties, toxicology information and ecological information. Results: The result of the evaluation of 14 MSDSs showed 76.29% average reliability on each item, especially 53.9% average appropriate rate on hazard risk classification. No chemicals failed to match between the content (%) in MSDSs and the result of analysis. Conclusions: To elevate MSDSs reliability, the certified education of MSDS drafters and reorganization of the MSDS circulation system is required.

• Fashion & Textile Research Journal
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• v.21 no.6
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• pp.697-707
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• 2019

This review paper deals with materials, classification, and a current article investigation on smart textile sensors for wearable vital signs monitoring (WVSM). Smart textile sensors can lose electrical conductivity during vital signs monitoring when applying them to clothing. Because they should have to endure severe conditions (bending, folding, and distortion) when wearing. Imparting electrical conductivity for application is a critical consideration when manufacturing smart textile sensors. Smart textile sensors fabricate by utilizing electro-conductive materials such as metals, allotrope of carbon, and intrinsically conductive polymers (ICPs). It classifies as performance level, fabric structure, intrinsic/extrinsic modification, and sensing mechanism. The classification of smart textile sensors by sensing mechanism includes pressure/force sensors, strain sensors, electrodes, optical sensors, biosensors, and temperature/humidity sensors. In the previous study, pressure/force sensors perform well despite the small capacitance changes of 1-2 pF. Strain sensors work reliably at 1 ㏀/cm or lower. Electrodes require an electrical resistance of less than 10 Ω/cm. Optical sensors using plastic optical fibers (POF) coupled with light sources need light in-coupling efficiency values that are over 40%. Biosensors can quantify by wicking rate and/or colorimetry as the reactivity between the bioreceptor and transducer. Temperature/humidity sensors require actuating triggers that show the flap opening of shape memory polymer or with a color-changing time of thermochromic pigment lower than 17 seconds.

• Journal of Korean Society of Rural Planning
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• v.18 no.4
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• pp.117-127
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• 2012

The demand of rural tourism industry has increased among the urbanites in South Korea, in due to the increase of leisure activity and the emergence of ageing society. Rural amenity resources are gaining various interests, in the value creation and promotion of tourism. In this study, the propensities of city dwellers were separated by life-style classification, and each affinity to the rural amenity resources was examined in accordance with the separation. A questionnaire survey of urbanites in the southern area of Gyeonggi-do, the most populous province in South Korea, was conducted to analyze the preference of city dwellers about rural amenity resource and life-style of themselves. For statistical verification, $IBM^{(R)}$ $SPSS^{(R)}$ Statistics 20 software was used for frequency, reliability, factor and multiple regression analysis of this research. The results of the statistical analyses found a noticeable characteristic in life-style classification. The affinities of urbanites can be classified into four congregations of life-style factors in this statistical model. Each congregation of the factors was named as 'Self-development-oriented', 'Leisure-oriented', 'Achievement-oriented', and 'Culture-oriented' life-style, to represent the characteristics for convenience' sake. Among these styles, only 'Self-development-oriented' and 'Achievement-oriented' showed the positive correlation with rural amenity resources in the multiple regression analysis. In addition, the rural amenity resources were also analyzed in accordance with the life-styles classification of urbanites. City dwellers showed the highest interest to the 'natural resource management facility resource' in natural resources, the 'traditional heritage resource' in cultural resources, and the 'community resource' in social resources. Meanwhile, they showed less interest to 'agricultural and scenery resources' in natural resources, 'specialty production resource' in cultural resources, and 'cooperative farming' in social resources. These characteristics can be constructed as meaning that the urbanites who concern self-development and achievement of their lives have high interest in rural amenity resources, and the main interest of them is not 'return-to-the-farm'(歸農) but 'return-to-the-home'(歸村).

• Fashion & Textile Research Journal
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• v.20 no.1
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• pp.75-82
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• 2018

This study was attempted to clarify differences in sizes and shapes of foot between 20's and 60-70's women and analyzed the characteristics of elderly women's foot shapes as compared with those of young. The 2D data were 101 elderly and 101 young women in Seoul and Gyeonggi-do. The results are as follows: Firstly, the foot length of the elderly was shorter than that of the young, the foot breadth and the heel width were widened, but the toes breadth became smaller and the deformity of the toe 1 and the first metatarsal part appeared. Secondly, in the Foot Index, there was a significant difference in age group, the young is more than the elderly in the narrow type, standard type, the elderly women showed more than three times the young in the wide type. Thirdly, in the factor analysis for the foot type classification, 'foot length' factors in both age groups were large. Next, young group were influenced by 'toes breadth', lateral ball breadth' factors, elderly group was influenced by the 'lateral ball breadth', 'medial ball breadth' factors. Lastly, in the cluster analysis of the elderly group, the types of sole were classified as W-Type(20.8%, wide foot and toes, large heel), H-type(20.8%, small toes breadth, heel), D-type(31.7%, long length and wide lateral ball) and A-Type(26.7%, which is found only in the elderly, small length and large toes angle). As a result, it is necessary to design the shoes that match the characteristics of the soles of the elderly women.

• Tunnel and Underground Space
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• v.13 no.6
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• pp.421-433
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• 2003

Demand for limestone production from both the underground and opencast mines in Korea is gradually increasing. Increase in productivity with safe mining operations is the emphasis laid on the mining industry. KIGAM has undertaken a detailed investigation to apply RMR and Q classification system for the design of underground limestone mining operations. The field investigations were confined to the underground mines of Daesung Mining Development Co. Ltd. and Pyunghae Mines of Korean Airport Service. Modification to the standard RMR and Q for limestone mines in Korea along with the correlation between these two systems are discussed while attempts were also made to calculate the width of a safe unsupported span.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.248-261
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• 1997

Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress in the research on this methodology, it has not been widely used in many practical ultrasonic inspections of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments based on their ultrasonic signals using various tools in artificial intelligence such as neural networks. This software shows the excellent performance in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks. This performance demonstrates the high possibility of this software as a practical tool for ultrasonic flaw classification in weldments.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.49-63
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• 2020

The accurate prediction of box office in the early stage is crucial for film industry to make better managerial decision. With aims to improve the prediction performance, the purpose of this paper is to evaluate the use of machine learning methods. We tested both classification and regression based methods including k-NN, SVM and Random Forest. We first evaluate input variables, which show that reputation-related information generated during the first two-week period after release is significant. Prediction test results show that regression based methods provides lower prediction error, and Random Forest particularly outperforms other machine learning methods. Regression based method has better prediction power when films have small box office earnings. On the other hand, classification based method works better for predicting large box office earnings.