• International journal of advanced smart convergence
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• v.9 no.4
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• pp.8-15
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• 2020

This study was conducted in order to determine the effect of intraoperative hemoglobin changes on intraoperative neuromonitoring (IONM). This was a retrospective study that included 339 participants who underwent cerebrovascular surgery. We compared anesthetic agents, intraoperative hemoglobin, hematocrit, blood transfusion, and blood loss. We examined motor evoked potential and sensory evoked potential to patients. There were significant differences in hemoglobin changes, bleeding levels, transfusion, anesthesia time, and postoperative mobility disorders. Moreover, compared with patients who received transfusions, those who did not receive transfusion had a lower average hemoglobin level, as well as a higher bleeding amount, and a need of higher anesthesia time and anesthetic dose. Also, we found vasospasm occurred while surgery can bring adverse results after operation. This study showed that an intraoperative decrease in hemoglobin levels affects the function of cerebral perfusion, which could result in abnormal nerve monitoring results. However, as this study could not find a relation of anesthetics to IONM, there is a need for further research regarding the association between anesthetics and hemoglobin changes and IONM.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.65-71
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• 2015

The role of information systems and business strategies of companies have attempted a variety of changes in the information technology environment that is displayed various. The advent of big data and knowledge-based analysis began to have great significance in the field of strategic planning for information systems specially constructed. The organization factors that affect the strategic planning of information systems through the application and practical Many researchers, technology, environmental have been introduced specifically. Input factors that affect the planning of information systems of these. In this study, it found the elements of the communication mechanism that exists between information and factors, the process of when developing a plan for information systems, and to study its relevance and convergence.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.253-259
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• 2018

The Korea Convergence Society. Recently, as the 4th industrial revolution is rising, there are many changes in various field of industries. Among these industries, autonomous vehicles based on artificial intelligence, big data and internet of things is one of the most promising industry. Autonomous vehicle stray from classical car domain of manufacturers and suppliers, IT/Electronics suppliers and communication companies are widen their business area to autonomous vehicle technology. In this paper, we analysis the state of art of autonomous vehicle technology and development direction of industries/research institute. Finally, we discuss the social/economic effects of autonomous vehicle.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.4
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• pp.503-509
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• 2021

Objectives: The utility of the system was analyzed by applying the smart safety technology system to the aging pipe rehabilitation facility construction classified as a confined space. Methods: Smart safety management system was applied to a site where the aging pipe rehabilitation work was in progress. The working environment was measured for 25 days, and the toxic gas saturation was analyzed according to the working time and working place. Results: Based on the measured results, two characteristic environmental changes in the confined space were confirmed. First, when working inside an aging pipe, the tendency of carbon dioxide saturation increases with working time and the number of workers. Second, oxygen decreases when working in a space away from the entrance. Conclusions: Various applications of smart safety technology have been confirmed based on the measured data, and this is expected to be useful for environmental characteristic analysis and safety management when applied to a confined space composed with various conditions in the future.

• Journal of applied mathematics & informatics
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• v.39 no.3_4
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• pp.419-435
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• 2021

This paper deals with numerical treatment of singularly perturbed differential equations involving small delays. The highest order derivative in the equation is multiplied by a perturbation parameter 𝜀 taking arbitrary values in the interval (0, 1]. For small 𝜀, the problem involves a boundary layer of width O(𝜀), where the solution changes by a finite value, while its derivative grows unboundedly as 𝜀 tends to zero. The considered problem contains delay on the convection and reaction terms. The terms with the delays are approximated using Taylor series approximations resulting to asymptotically equivalent singularly perturbed BVPs. Inducing exponential fitting factor for the term containing the singular perturbation parameter and using central finite difference for the derivative terms, numerical scheme is developed. The stability and uniform convergence of difference schemes are studied. Using a priori estimates we show the convergence of the scheme in maximum norm. The scheme converges with second order of convergence for the case 𝜀 = O(N^-1) and for the case 𝜀 ≪ N^-1, the scheme converge uniformly with first order of convergence, where N is number of mesh intervals in the domain discretization. We compare the accuracy of the developed scheme with the results in the literature. It is found that the proposed scheme gives accurate result than the one in the literatures.

• Fourth Industrial Review
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• v.2 no.1
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• pp.19-32
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• 2022

Purpose - As new technologies that have led the 4th industrial revolution spread after the COVID-19 pandemic, the business crisis of existing financial institutions and the threat of employee jobs are growing, especially in the financial sector. The purpose of this study is to propose a human-technology convergence curriculum for creating high value-added in financial institutions and upskilling financial manpower. Research design, data, and methodology - In this study, a curriculum was designed to strengthen job competency for Private Bankers, high-quality employees of a bank dealing with high-net-worth owners. The focus of the design is that learners acquire skills to use robo-advisors as a tool and supplement artificial intelligence ethics. Result - The curriculum is organized into a total of 16 classes, and the main contents are changes in the financial environment and financial consumers, the core technology of robo-advisors and AI ethics, and establishment and evaluation of hyper-personalized asset management strategies using robo-advisors. To achieve the educational goal, two evaluations are performed to derive individual tasks and team project results. Conclusion - Human-centered upskilling convergence education will contribute to improving employee value and expanding corporate high value-added business areas by utilizing new technologies as tools. It is expected that the development and application of convergence curriculum in various fields will continue to be advanced in the future.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.353-360
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• 2023

This paper explores notable shifts in the restaurant startup market following the lifting of social distancing measures. Key trends identified include an escalated interest in startups, a heightened focus on the quality and diversity of food, a relative decline in the importance of delivery services, and a growing interest in specific industry sectors. The study's data collection spanned three years, from April 2021 to May 2023, encompassing the period before and after social distancing. Data were sourced from a range of online platforms, including blogs, news sites, cafes, web documents, and intellectual forums, provided by Naver, Daum, and Google. From this collected data, the top 50 words were identified through a refinement process. The analysis was structured around the social distancing application period, comparing data from April 2021 to April 2022 with data from May 2022 to May 2023. These observed trend changes provide founders with valuable insights to seize new market opportunities and formulate effective startup strategies. In summary, We offer crucial insights for founders, enabling them to comprehend the evolving dynamics in food service startups and to adapt their strategies to the current market environment.

• Journal of Fashion Business
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• v.22 no.5
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• pp.64-82
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• 2018

As sustainability of fashion brands is becoming more important in the prolonged depression, the fashion market is also seeking ways to create new value through convergence with various fields. In the fashion market, convergence marketing is engaged with diverse technologies combined with advanced technologies and strategies. This study established the conceptual characteristics of convergence and divergence from a market perspective. Convergence can be summarized as Borderless, Compounding, Diversification, Recombination and Affiliation. The conceptual characteristics of the divergence can be summarized as de-fusion, individualization, differentiation, specialization, and segmentation. The characteristics of convergence revealed through the case of fashion market include the expandability of the new category, the expandability of the consumer, the brand experience, and the expandability of time and space. Divergence is the differentiation of brand value, target customer, and product nature. Through this study, we could understand the differentiation of the fashion market and the direction of the marketing strategy by looking at the characteristic of the convergence marketing - oriented research that has the contrary conceptual characteristics from the extended viewpoint. Based on this, it is possible to see the changes and patterns of brand marketing strategies and techniques in recent fashion market. In the future, it is expected that the systematic study of the marketing strategy of the domestic fashion brand based on the convergence and change characteristics of the fashion market proposed in this study will continue.

• Journal of Korean Society for Atmospheric Environment
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• v.30 no.2
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• pp.188-200
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• 2014

The IPCC 5th Assessment Report (Climate Change 2013: The Physical Science Basis) was accepted at the 36th Session of the IPCC on 26 September 2013 in Stockholm, Sweden. It consists of the full scientific and technical assessment undertaken by Working Group I. This comprehensive assessment of the physical aspects of climate change puts a focus on those elements that are relevant to understand past, document current, and project future of climate change. The assessment builds on the IPCC Fourth Assessment Report and the recent Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation. The assessment covers the current knowledge of various processes within, and interactions among, climate system components, which determine the sensitivity and response of the system to changes in forcing, and they quantify the link between the changes in atmospheric constituents, and hence radiative forcing, and the consequent detection and attribution of climate change. Projections of changes in all climate system components are based on model simulations forced by a new set of scenarios. The report also provides a comprehensive assessment of past and future sea level change in a dedicated chapter. The primary purpose of this Technical Summary is to provide the link between the complete assessment of the multiple lines of independent evidence presented in the main report and the highly condensed summary prepared as Policy makers Summary. The Technical Summary thus serves as a starting point for those readers who seek the full information on more specific topics covered by this assessment. Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased. Total radiative forcing is positive, and has led to an uptake of energy by the climate system. The largest contribution to total radiative forcing is caused by the increase in the atmospheric concentration of $CO_2$ since 1750. Human influence on the climate system is clear. This is evident from the increasing greenhouse gas concentrations in the atmosphere, positive radiative forcing, observed warming, and understanding of the climate system. Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions. The in-depth review for past, present and future of climate change is carried out on the basis of the IPCC 5th Assessment Report.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.11-19
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• 2021

A software system is required to change during its life cycle due to various requirements such as adding functionalities, fixing bugs, and adjusting to new computing environments. Such program code modification should be considered as carefully as a new system development becase unexpected software errors could be introduced. In addition, when reusing open source programs, we can expect higher quality software if code changes of the open source program are predicted in advance. This paper proposes a Convolutional Neural Network (CNN)-based deep learning model to predict source code changes. In this paper, the prediction of code changes is considered as a kind of a binary classification problem in deep learning and labeled datasets are used for supervised learning. Java projects and code change logs are collected from GitHub for training and testing datasets. Software metrics are computed from the collected Java source code and they are used as input data for the proposed model to detect code changes. The performance of the proposed model has been measured by using evaluation metrics such as precision, recall, F1-score, and accuracy. The experimental results show the proposed CNN model has achieved 95% in terms of F1-Score and outperformed the multilayer percept-based DNN model whose F1-Score is 92%.