• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.302-313
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• 2021

As the domestic consulting industry matured, consultants were required to have insight into customer's business and consulting business. Gaining these insights requires deep understanding of the business domains and high degree of competencies. This study empirically analyzed the data collected through the survey in order to apply the ICMCI competence model to domestic consultants. As a result of the study, it was found that business competency and technical competency had a positive effect on project performance, but values & behavior competency were not statistically significant. On the other hand, it was found that only technical competency, values & behavior competency had a positive effect on social-relational competency. Through this study, it was confirmed that a deep understanding and perception of the consulting business is necessary to grow into a professional consultant, but there is a limit to generalizing the research results because the characteristics of the population cannot be sufficiently reflected with a small sample.

• Journal of Convergence for Information Technology
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• v.11 no.9
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• pp.109-114
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• 2021

Cr(VI)-quinoline compound[(C₉H₇NH)₂Cr₂O₇] was synthesized by the reaction between of quinoline and chromium(VI) trioxide, and structure was FT-IR, elemental analysis. The oxidation ability of benzyl alcohol greatly depends upon the dielectric constant of the used organic solvent, where carbon tetrachloride was worst and N,N'-dimethylformamide was best solvent. Noticeably, in N,N'-dimethylformamide solvent, Cr(VI)-quinoline compound oxidized substituted benzyl alcohols. The Hammett reaction constant(ρ)=-0.69(303K). As a resuit, Cr(VI)-quinoline compound was found as efficicent oxidizing agent that converted benzyl alcohol, allyl alcohol, primary alcohol and secondary alcohols to the corresponding aldehydes or ketones. Cr(VI)-quinoline compound was selective oxidizing agent of benzyl alcohol, allyl alcohol and primary alcohol in the presence of secondary alcohol ones.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.343-352
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• 2021

A convergence study was conducted to develop a smartphone application for self-practice of core nursing skills and evaluate its usefulness for undergraduate nursing students. Mobile Application Rating Scale and seven essay questionnaire were used to for usability evaluation among 22 undergraduate nursing students. The score of the information domain was the highest with 4.19(SD 0.79). The subjective quality domain showed the lowest score of 3.08(SD 0.87). Participants' performance confidence score was 8.23(SD 1.60), and learning satisfaction score was 7.89(SD 0.87). Participants reported that the convenience and repetitive self-learning were the strengths of the app. In addition, design and technical supplementation, and lecturer-feedback would improve effectiveness of the current educational app. Findings of this convergent study would be helpful to promote the application of mobile apps for effective self-learning of core nursing skills in undergraduate nursing education. Future resesarch is needed to examine effectiveness study of mobile app on the performance of core nursing skills.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.95-114
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• 2021

This study is to study the effect of corporate performance compensation system on organizational effectiveness and motivation, and the effect of organizational effectiveness and motivation on corporate performance, targeting employees of automobile maintenance service companies. 430 questionnaires obtained through the survey were used for the study. As a result of testing the research hypothesis, tangible reward had a significant positive (+) effect on job satisfaction, but intangible reward had a positive (+) effect on job satisfaction, but it was not significant. Also, tangible and intangible rewards have a significant positive (+) effect on organizational commitment and motivation. Job satisfaction has a significant positive (+) effect on productivity and service quality. However, organizational commitment had a significant positive (+) effect on productivity, but had a positive (+) effect on service quality, but was not significant. Lastly, motivation has a significant positive (+) effect on productivity and service quality. Through the research results, the relationship structure between the performance compensation system, organizational effectiveness and motivation, and corporate performance was identified, and the application of the performance compensation system to employees in the automobile industry was presented.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.295-302
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• 2021

Surface modification of recycled plastic film-based aggregates is demonstrated to enhance the interaction between aggregates and cement paste. It is shown that the oxygen(O₂) atmospheric pressure plasma(APP) treatment leads to a drastic increase in hydrophilicity. In case of the plasma treatment at 100W of RF power, 15/4sccm of O₂/Ar flow rate and 30sec of discharging time, the water contact angle on the aggregates surface decreased from 104.5° to 44.0°. In addition, the contact angle of surface modified aggregates kept in air increased with time elapse. Improvement of hydrophilicity can be explained by the formation of new hydrophilic oxygen functional groups which is identified as C-OH, C-O-C, C=O, -COOH by X-ray photoelectron spectroscopy(XPS) analysis and Fourier-transform infrared spectroscopy(FT-IR). Therefore, it can be concluded that the plasma treatment process is an effective method to improve adhesion of the recycled plastic film-based aggregates and cement paste.

• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.151-155
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• 2021

The application of environmental DNA in the domestic ecosystem is also accelerating, but the processing and analysis of the produced data is limited, and doubts are raised about the reliability of the analyzed and produced biological taxa identification data, and the sample medium (target sample, water, air, sediment, Gastric contents, feces, etc.) and quantification and improvement of analysis methods are also needed. Therefore, in order to secure the reliability and accuracy of biodiversity research using the environmental DNA of the domestic ecosystem, it is a process of actively using the database accumulated through ecological taxonomy and undergoing verification procedures, and experts verifying the resolution of the data increased by gene sequence analysis. This is absolutely necessary. Environmental DNA research cannot be solved only by applying molecular biology technology, and interdisciplinary research cooperation such as ecology-taxa identification-genetics-informatics is important to secure the reliability of the produced data, and researchers dealing with various media can approach it together. It is an area in desperate need of an information sharing platform that can do this, and the speed of development will proceed rapidly, and the accumulated data is expected to grow as big data within a few years.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.144-150
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• 2021

The purpose of this paper is to review the direction of the slicing security policy, which is a major consideration in the context of standardization in 5G communication network security, to derive security vulnerability diagnosis items, and to present about analyzing and presenting the issues of discussion for 5G communication network virtualization. As for the research method, the direction of virtualization security policy of 5G communication network of ENISA (European Union Agency for Cybersecurity), a European core security research institute, and research contents such as virtualization security policy and vulnerability analysis of 5G communication network from related journals were used for analysis. In the research result of this paper, the security structure in virtualization security of 5G communication network is arranged, and security threats and risk management factors are derived. In addition, vulnerability diagnosis items were derived for each security service in the risk management area. The contribution of this study is to summarize the security threat items in 5G communication network virtualization security that is still being discussed, to be able to gain insights of the direction of European 5G communication network cybersecurity, and to derive vulnerabilities diagnosis items to be considered for virtualization security of 5G communication network. In addition, the results of this study can be used as basic data to develop vulnerability diagnosis items for virtualization security of domestic 5G communication networks. In the future, it is necessary to study the detailed diagnosis process for the vulnerability diagnosis items of 5G communication network virtualization security.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.9
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• pp.359-366
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• 2021

A number of construction companies in Korea invest considerable human and financial resources to construct a system for managing apartment defect data and for categorizing repair tasks. Thus, this study proposes machine learning models to automatically classify defect complaint text-data into one of the sub categories of 'finishing work' (i.e., one of the defect repair tasks). In the proposed models, we employed two word representation methods (Bag-of-words, Term Frequency-Inverse Document Frequency (TF-IDF)) and two machine learning classifiers (Support Vector Machine, Random Forest). In particular, we conducted both binary- and multi- classification tasks to classify 9 sub categories of finishing work: home appliance installation work, paperwork, painting work, plastering work, interior masonry work, plaster finishing work, indoor furniture installation work, kitchen facility installation work, and tiling work. The machine learning classifiers using the TF-IDF representation method and Random Forest classification achieved more than 90% accuracy, precision, recall, and F1 score. We shed light on the possibility of constructing automated defect classification systems based on the proposed machine learning models.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.530-536
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• 2021

Recently, due to the development of deep learning, end-to-end speech recognition, which directly maps graphemes to speech signals, shows good performance. Especially, among the end-to-end models, conformer shows the best performance. However end-to-end models only focuses on the probability of which grapheme will appear at the time. The decoding process uses a greedy search or beam search. This decoding method is easily affected by the final probability output by the model. In addition, the end-to-end models cannot use external pronunciation and language information due to structual problem. Therefore, in this paper conformer with lexicon transducer is proposed. We compare phoneme-based model with lexicon transducer and grapheme-based model with beam search. Test set is consist of words that do not appear in training data. The grapheme-based conformer with beam search shows 3.8 % of CER. The phoneme-based conformer with lexicon transducer shows 3.4 % of CER.