• Management & Information Systems Review
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• v.36 no.5
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• pp.85-98
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• 2017

The purpose of this study is to exploratory examine the structural relationships among meaningfulness of work, personality(Big 5 character-types) and job stress. To conduct such examination, the author (i) designated meaningfulness of work, personality(Big 5 character-types) and job stress as variables and (ii) designed a research model by conducting preceding studies on the variables. To examine the research model the author collected the survey data from the residents in Kyoungsangbuk-do, 332 copies of questionnaire. Collected data were analyzed using SPSS and AMOS programs. The analysis results are as follows. Especially, (1) the meaningfulness of work had a positive effect on agreeableness, conscientiousness, and extraversion. (2) the meaningfulness of work had a negative effect on neuroticism. (3) the meaningfulness of work had no effect on openness to experience. (4) the neuroticism factor had a positive effect on psychological job stress and physical job stress. (5) the openness to experience had a negative effect on psychological job stress and physical job stress. (6) the meaningfulness of work had no effect on psychological job stress and physical job stress. The implications and limitation which this study are as follows. First, this study has discovered that there was statistically significant relationship between the meaningfulness of work and Big 5 character-types. Second, Big 5 character-types(neuroticism, openness to experience) had statistically effect on psychological job stress and physical job stress. This study have limitation in that was conducted based on cross-sectional design of research. Because, the mechanism of job stress is a dynamic process.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.245-256
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• 2021

The Fourth Industrial Revolution brought the quantitative value of data across the industry and entered the era of 'Big Data'. This is due to both the rapid development of information & communication technology and the diversity & complexity of customer purchasing tendencies. An enterprise's core competence in the Big Data Era is to analyze and utilize the data to make strategic decisions for enterprise. However, most of traditional studies on Big Data have focused on technical issues and future potential values. In addition, these studies lacked interest in managing the quality and utilization levels of internal & external customer Big Data held by the entity. To overcome these shortages, this study attempted to derive influential factors by recognizing the quality management information systems and quality management of the internal & external Big Data. First of all, we conducted a survey of 204 executives & employees to determine whether Big Data quality management, Big Data utilization, and level management have a significant impact on corporate work efficiency & corporate management performance. For the study for this purpose, hypotheses were established, and their verifications were carried out. As a result of these studies, we found that the reasons that significantly affect corporate management performance are support from the management class, individual innovation, changes in the management environment, Big Data quality utilization metrics, and Big Data governance system.

• Journal of the Health Care and Life Science
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• v.10 no.1
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• pp.1-14
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• 2022

This study is a study on the possibility of using big data-related education programs in health and medical administration-related departments using health and medical big data. This paper intends to examine the health and medical big data from five perspectives. 1st, in addition to the aforementioned 'Health and Medical Big Data Open System', I would like to examine the characteristics and application technologies of public big data disclosed by 'Korea Welfare Panel', 'Public Big Data', 'Seoul City Big Data', 'Statistical Office Big Data', etc. 2nd, it is intended to examine the appropriateness of whether the applicable health and medical big data can be used as living data in regular subjects of health and medical administration and health information related departments of junior colleges. 3rd, we want to select the most appropriate tool for classroom lectures using existing statistical processing packages and programming languages. Fourth, finally, by using verified health and medical big data and appropriate tools, we want to test the possibility of expressing graphs, etc. in class and the steps from writing a report. 4th, I would like to describe the relative advantages of R language that can satisfy portability, installability, cost effectiveness, compatibility, and big data processing potential.

• Journal of the Korea Safety Management & Science
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• v.21 no.4
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• pp.17-23
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• 2019

The applications of information and communication technology (ICT) into real industrial fields are getting great attentions in recent years. More and more industrial practitioners and scientific researchers are conducting studies and trying to adopt the technologies into diverse industrial fields. The purpose of this study is to review the technologies such as big data and smart sensors and to provide application cases in order to facilitate grafting the 4th industrial revolutionary technologies onto the safety and health systems. Based on the comprehensive reviews on literature, reports, and industrial cases, we found that big data technology has been used in industries for investigating work related disease. In addition, digital image technology and drone have been applied to establish safety system in construction industry. Lastly, some companies have tried to apply the technologies to build their own safety and health system.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.184-195
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• 2004

Current companies 집중 on how to operate and select projects to achieve the best result. 6sigma projects are chosen in the best suitable concept, which are solved by the 6Sigma experts according to the priority. And every project has to be launched not the view of individual management factors but the total factors, Big Y. Therefore, a process needs to be treated to connect the vital few factors in various processes to improve the yield, which is the main performance criteria in a manufacturing industry This report is to make the total optimization through the Vital-Few mapping between quality characteristics and process factors in a manufacturing line. Accordingly, it means to secure lower variance by making the CTP(Critical To Process) optimization and finally to improve the yield.

• Journal of Ginseng Research
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• v.6 no.1
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• pp.56-66
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• 1982

The effects of various dehiscent application such as dehiscent materials (big chaffs, vermiculite etc.), growth regulators and agricultural chemicals (plant protector.) on stimulation of dehiscence and shortening of dehiscent period were investigated Results obtained were as follows : 1. The moisture content of endosperm and seed coat at 10 day after dehiscent application amounts between 40% and 50%. 2. Endosperm diameter was increased with time of stratification, and the embryo growth showed in linear function, 3. Non-dehiscent seed showed also normally development of embryo, and the property of dehiscence dependent from physico-chemical nature of ginseng seed coat. 4. The best dehiscent materials were big chaffs and followed vermiculite, sand and sand with big chaffs. 5. The effect of dehiscence of ginseng seed showed higher activity in fungi than in bacteria in general. 6. Agricultural chemicals ( plant Protector) reduced the dehiscent rate of ginseng seed 7. The best timing of dehiscent treatment was between August 1 and August 10 but the smaller amount of dehiscent rate after August 10 dehiscent appllication indicated that big chaffs and growth regulator treatment may be controlled shortening of dehiscent period of ginseng seed.

• The Korean Journal of Physiology
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• v.19 no.2
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• pp.215-225
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• 1985

흰쥐의 태아에서 ACTH의 분비양상을 알아보기 위하여, 태아의 제태일수에 따라 혈장 및 뇌하수체 전엽에서 여러 분자형태의 ACTH를 방사면역측정법으로 측정하였다. 태아의 혈장 ACTH농도는 제태 19일에서 가장 높았으며 그후 계속 감소하여 출생후 1주에서 가장 낮은 값을 보였다. 출생 1주후부터 ACTH농도는 다시 증가하기 시작하여 출생후 21일에서는 거의 성체의 값에 도달하였다. 측정된 ACTH는 chromatogram상에서 항상 3가지 peak가 나타났다. 즉 'big'형 ('big' ACTH, $MW\approx44,000$), 'intermediate'형 ('intermediate' ACTH, $MW\approx13,000$)및 'little'형 ('little' ACTH, $MW\approx4,500$)으로 구분되었다. 임신말기 (제태기간 17일에서 21일 사이)에서 태아 혈장의 ACTH는 'little'형의 비율이 증가한 반면 'big'형의 비율은 감소하였다. 그러나 뇌하수체 전엽에서 분비된 ACTH는 3가지 형이 같은 비율이었다. 뇌하수체 전엽에서 분리한 'big'형의 ACTH를 시침관내에서 trypsin을 처리한 결과 'intermediate'형과 little'형이 출현하였다. 이 결과로 미루어 태아 흰쥐의 뇌하수체에서 분비된 ACTH가 순환도증 다른 형으로 전환될 수 있음이 시사된다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.197-198
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• 2019

In this study, the study was conducted to derive the utility of the safety management system applying block chain technology and big data technology to improve the problems of construction sites where concealment and operation of safety accidents occur. If block chain technology and big data technology are applied to construction safety management, transparent data can be collected, and based on the collected data, it is possible to predict accidents that can occur at the construction site and establish countermeasures. It can also be an opportunity to strengthen the safety awareness of construction workers and managers, and can clearly identify the responsibility in the event of a safety accident. This study suggests that the application of the 4th Industrial Revolution technology could be a great opportunity to innovate the construction industry which is less than other industries.

• Asia pacific journal of information systems
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• v.34 no.1
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• pp.226-247
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• 2024

Most studies on recommender systems to evaluate recommendation performances focus on offline evaluation methods utilizing past customer transaction records. However, evaluating recommendation performance through real-world stimulation becomes challenging. Moreover, such methods cannot evaluate the duration of the recommendation effect. This study measures the personalized recommendation (stimulus) effect when the product recommendation to customers leads to actual purchases and evaluates the duration of the stimulus personalized recommendation effect leading to purchases. The results revealed a 4.58% improvement in recommendation performance in the online environment compared with that in the offline environment. Furthermore, there is little difference in recommendation performance in offline experiments by period, whereas the recommendation performance declines with time in online experiments.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.251-258
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• 2016

Big data processing is a broad term for processing data sets so large or complex that traditional data processing applications are inadequate. Widespread use of smart devices results in a huge impact on the way we process data. Many organizations are contemplating how to incorporate or integrate those devices into their enterprise data systems. We have proposed a way to process big data by way of integrating Raspberry Pi into a Hadoop cluster as a computational grid. We have then shown the efficiency through several experiments and the ease of scaling of the proposed system.