• Journal of Digital Convergence
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• v.19 no.12
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• pp.567-575
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• 2021

This study was aimed to identify surgical ward nurses' importance-performance awareness toward early mobilization after abdominal surgery patients. The date were collected from 162 nurses and the importance and performance of early mobilization were analyzed by the IPA method. The collected data were analyzed using the SPSS/WIN 25.0 by implementing descriptive statistics, independent t-test, paired t-test, and ANOVA. Early mobilization was divided into exercise of pulmonary complications and early ambulation. As a result of the study, the areas requiring concentration were 'check risk of aspiration', and areas requiring improvement were 'oral care', 'check lung sound', 'percussion/vibration', 'suction', and 'reinforcement exercise in bed'. Therefore, each item of early mobilization is recommended to reduce the gap between importance and performance in clinical care.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.463-468
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• 2021

Although the IoT is showing explosive growth due to the development of technology and the spread of IoT devices and activation of services, serious security risks and financial damage are occurring due to the activities of various botnets. Therefore, it is important to accurately and quickly detect the activities of these botnets. As security in the IoT environment has characteristics that require operation with minimum processing performance and memory, in this paper, the minimum characteristics for detection are selected, and KNN (K-Nearest Neighbor), Naïve Bayes, Decision Tree, Random A comparative study was conducted on the performance of machine learning algorithms such as Forest to detect botnet activity. Experimental results using the Bot-IoT dataset showed that KNN can detect DDoS, DoS, and Reconnaissance attacks most effectively and efficiently among the applied machine learning algorithms.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.229-239
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• 2021

For this study, we have extensively analyzed the presentation data of the government's financial-related departments and the data of each financial institution and electronic financial institution.. As a result, In Korea's electronic financial environment, real changes such as first) expansion of non-face-to-face finance, second) teleworking in the financial sector, third) abolition of accredited certification, fourth) advanced voice phishing, fifth) openness of the financial industry and diversification of forms, sixth) the'walletless society'. In addition to the above, however, global changes triggered by the Fourth Industrial Revolution spread to the financial security sector, making it difficult to respond to problems such as artificial intelligence/ deep learning/ user analysis/ deepfake technology. As the proportion of electronic finance is increasing socially, it should be studied in the fields of electronic finance and its environment, and crime and criminal investigation.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.471-479
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• 2019

The purpose of this study was to investigate the determinants of preventive behavior intention to the particulate matter. The results based on the survey of 280 university students showed that the perceived susceptibility and barriers to the particulate matter do not have statistically significant effects on the preventive behavior intention. However, perceived severity and benefits, subjective norm, and self-efficacy to the particulate matter had statistically significant positive effects on the preventive behavior intention. The results of this study suggested that communication strategies to increase perceived severity and benefits, subjective norm and self-efficacy should be required to improve the degree of preventive behavior intention to the particulate matter of college students. It is expected to contribute explaining preventive actions against environmental hazards such as air pollution in the future.

• Journal of Digital Convergence
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• v.17 no.7
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• pp.285-292
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• 2019

With the popularization of PC, SNS and IoT, a lot of data is generated and the amount is increasing exponentially. Artificial neural network learning is a topic that attracts attention in many fields in recent years by using huge amounts of data. Artificial neural network learning has shown tremendous potential in speech recognition and image recognition, and is widely applied to a variety of complex areas such as medical diagnosis, artificial intelligence games, and face recognition. The results of artificial neural networks are accurate enough to surpass real human beings. Despite these many advantages, privacy problems still exist in artificial neural network learning. Learning data for artificial neural network learning includes various information including personal sensitive information, so that privacy can be exposed due to malicious attackers. There is a privacy risk that occurs when an attacker interferes with learning and degrades learning or attacks a model that has completed learning. In this paper, we analyze the attack method of the recently proposed neural network model and its privacy protection method.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.71-78
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• 2019

This study aims to identify good borrowers within the context of P2P lending. P2P lending is a growing platform that allows individuals to lend and borrow money from each other. Inherent in any loans is credit risk of borrowers and needs to be considered before any lending. Specifically in the context of P2P lending, traditional models fall short and thus this study aimed to rectify this as well as explore the problem of class imbalances seen within credit risk data sets. This study implemented an over-sampling technique known as Synthetic Minority Over-sampling Technique (SMOTE). To test our approach, we implemented five benchmarking classifiers such as support vector machines, logistic regression, k-nearest neighbor, random forest, and deep neural network. The data sample used was retrieved from the publicly available LendingClub dataset. The proposed SMOTE revealed significantly improved results in comparison with the benchmarking classifiers. These results should help actors engaged within P2P lending to make better informed decisions when selecting potential borrowers eliminating the higher risks present in P2P lending.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.123-135
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• 2018

The objective of this paper is to investigate the issues related to the supply chain management in plant engineering industry, and propose the framework to improve the project efficiency. The preliminary case study shows that EPC's fragmented nature, lack of coordination and information sharing, and lack of proper risk and change management contribute to project delay and cost overrun. To examine the level of informatization and information sharing in supply chain, survey responses from the suppliers and subcontractors have been collected. The statistical results show that information sharing, early involvement in design process and awareness in SCM have influenced the level of collaboration, but supplier assessment and informatization have no impact on the collaboration. A conceptual model is proposed in order to facilitate the integration of design, procurement and construction functions. Implications from the study are also provided.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.191-204
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• 2019

This study empirically confirmed whether individual characteristics and social capital have distinctive influence on entrepreneurship and entrepreneurship, and whether entrepreneurship consulting has a moderating effect in the context of high interest in entrepreneurship with 223 data. All of the personal characteristics, network, trust, and consulting experience had a significant influence on the entrepreneurial intention, while the external control and reciprocity norms had a significant influence on the entrepreneurial anxiety. The experience of consulting revealed that it has a moderating effect of weakening influence of risk-taking tendency and network on the entrepreneurial will and strengthening the influence of external control on the entrepreneurial anxiety. This research has significance in terms of distinguishing effects of entrepreneurial intention and anxiety and the moderating effect of consulting. In future research, it is expected that verification of entrepreneurial anxiety should be done.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.523-531
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• 2018

This study was conducted to investigate the relation between working conditions and occupational injuries among Korean employees. This study was based on the 4th Korean Working Conditions Survey(KWCS) and a total of 36,292 data were analyzed. Multivariate logistic regression was used to investigate the relation of working conditions and occupational injuries after controlling for individual variables. After control of personal factors, perception of the threat to health or safety(OR=3.77, 95% CI=2.934-4.844), 49-59 working hours(OR=1.63, 95% CI=1.023-2.601), 60 hours or more per week(OR=2.66, 95% CI=1.683-4.197), and manual occupation type(OR=1.76, 95% CI=1.218-2.536) were associated with occupational injuries. Our results indicate that working conditions influence occupational injuries, and the focus should be on prevention and management strategies for occupational injuries to vulnerable workers.

• Journal of IKEEE
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• v.22 no.4
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• pp.953-958
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• 2018

In this study, a portable detection system was developed that can detect harmful gas and signals simultaneously in an enclosed space of industrial sites and underground facilities. The developed system is a sensor module for gas detection, a patch type 1 channel small ECG sensor, a module for three-axial acceleration detection sensor, and a system for statistics. In order to verify the performance of the system modules, the digital resolution, signal frequency, output voltage, and ultra-small modules were evaluated. As a result of the performance of the developed system, the digital resolution was 300 (rps) and the signal amplification gain was 500 dB or more, and the ECG module was manufactured with $50mm{\times}10mm{\times}10mm$ to increase patch utilization. It is believed that the product of this research will be valuable if it is used as an IoT-based management system for real-time monitoring of industrial workers.