• Journal of Digital Convergence
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• v.20 no.5
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• pp.423-432
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• 2022

Due to the development of treatments due to COVID-19, the Firm-value of the pharmaceutical industry has increased. However, the development of treatments has been delayed, and the development of overseas markets has become difficult due to COVID-19. Therefore, this study aims to present an efficient management plan for each firm by analyzing the management efficiency of these firms. As for the research method, DEA analysis was conducted for the pharmaceutical industry. Through this method, we propose values of input variables that inefficient companies can benchmark. As a result of the analysis, there was no significant difference in management efficiency before and after COVID-19, but it was confirmed that the management efficiency of certain Firm decreased. Through this study, it is possible to judge a Firm's survival competitiveness and management strategy, and furthermore, a plan to continuously grow and enhance competitiveness was suggested.

• Advances in nano research
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• v.12 no.6
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• pp.549-566
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• 2022

Mining of ore minerals (sfalerite, cinnabar, and chalcopyrite) from the old mine has led in significant environmental effects as contamination of soils and plants and acidification of water. Also, nanoparticles (NP) have obtained global importance because of their widespread usage in daily life, unique properties, and rapid development in the field of nanotechnology. Regarding their usage in various fields, it is suggested that soil is the final environmental sink for NPs. Nanoparticles with excessive reactivity and deliverability may be carried out as amendments to enhance soil quality, mitigate soil contaminations, make certain secure land-software of the traditional change substances and enhance soil erosion control. Meanwhile, there's no record on the usage of Nano superior substances for mine soil reclamation. In this study, five soil specimens have been tested at 4 sites inside the region of mine (<100 m) to study zeolites, and iron sulfide nanoparticles. Also, through using Artificial Neural Network (ANN) and Extreme Learning Machine (ELM), this study has tried to appropriately estimate the mechanical properties of soil under the effect of these Nano particles. Considering the RMSE and R2 values, Zeolite Nano materials could enhance the mine soil fine through increasing the clay-silt fractions, increasing the water holding capacity, removing toxins and improving nutrient levels. Also, adding iron sulfide minerals to the soils would possibly exacerbate the soil acidity problems at a mining site.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.11-18
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• 2022

As the need for software development manpower increases, various educational programs appear and the popularity of bootcamp style education program for software development increases. However, despite the operations and forms of bootcamp education programs are completely different from the existing software development education programs, there is a lack of research in understanding bootcamp as a software education program. Therefore, this study tried to derive the core elements of the education program through a case study on bootcamp software developer education program. After conducting interviews of 7 members who have completed a series of bootcamp software developer education program X, seven characteristics of bootcamp-type software development education program were derived: intensive theory education, sense of growth and achievement, team project-based learning, community characteristics, peer pressure, stress and fatigue due to short-term learning, and contact-free specialty. Based on the derived characteristics, the advantages and improvements of bootcamp-type education were described, and the direction of the bootcamp-type education program for software developer was discussed.

• Computers and Concrete
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• v.29 no.6
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• pp.375-391
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• 2022

This paper examined the impact of the cross-sectional structure on the structural results under different loading conditions of reinforced concrete (RC) members' management limited in Carbon Fiber Reinforced Polymers (CFRP). The mechanical properties of CFRC was investigated, then, totally 32 samples were examined. Test parameters included the cross-sectional shape as square, rectangular and circular with two various aspect rates and loading statues. The loading involved concentrated loading, eccentric loading with a ratio of 0.46 to 0.6 and pure bending. The results of the test revealed that the CFRP increased ductility and load during concentrated processing. A cross sectional shape from 23 to 44 percent was increased in load capacity and from 250 to 350 percent increase in axial deformation in rectangular and circular sections respectively, affecting greatly the accomplishment of load capacity and ductility of the concentrated members. Two Artificial Intelligence Models as Extreme Learning Machine (ELM) and Particle Swarm Optimization (PSO) were used to estimating the tensile and flexural strength of specimen. On the basis of the performance from RMSE and RSQR, C-Shape CFRC was greater tensile and flexural strength than any other FRP composite design. Because of the mechanical anchorage into the matrix, C-shaped CFRCC was noted to have greater fiber-matrix interfacial adhesive strength. However, with the increase of the aspect ratio and fiber volume fraction, the compressive strength of CFRCC was reduced. This possibly was due to the fact that during the blending of each fiber, the volume of air input was increased. In addition, by adding silica fumed to composites, the tensile and flexural strength of CFRCC is greatly improved.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.1-10
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• 2021

This paper aimed to look at the awareness of foreign workers in social platforms by using text mining, one of the big data techniques and draw suggestions for foreign workers. To achieve this purpose, data collection was conducted with search keyword 'Foreign Worker' from Jan. 1, to Dec. 31, 2020, and frequency analysis, TF-IDF analysis, and degree centrality analysis and 100 parent keywords were drawn for comparison. Furthermore, Ucinet6.0 and Netdraw were used to analyze semantic networks, and through CONCOR analysis, data were clustered into the following eight groups: foreigner policy issue, regional community issue, business owner's perspective issue, employment issue, working environment issue, legal issue, immigration issue, and human rights issue. Based on such analyzed results, it identified national awareness of foreign workers and main issues and provided the basic data on policy proposals for foreign workers and related researches.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.479-488
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• 2022

In recent years, with the rapid development of machine learning technology, research utilizing machine learning has been actively conducted in fields such as cognition, reasoning and judgment, and action among various technologies constituting intelligent systems. In order to utilize this machine learning, it is indispensable to collect data for learning. However, the types of data generated vary according to the environment in which the data is generated, and the types and forms of data required are different depending on the learning model to be used for machine learning. Due to this, there is a problem that the existing data collection method cannot be reused in a new environment, and a specialized data collection module must be developed each time. In this paper, we propose a specification-based methology for data collection in artificial intelligence system to solve the above problems, ensure the reusability of the data collection method according to the data collection environment, and automate the implementation of the data collection function.

• Fashion & Textile Research Journal
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• v.24 no.4
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• pp.460-470
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• 2022

Customized cosmetics are emerging as a consumer product that companies should pay attention to in the beauty industry due to the combination of market trends and institutional introduction of customized cosmetics. In this study, six offline service brands and online service brands currently in Korea were selected to understand the current status of domestic customized cosmetics online and offline services and to derive detailed characteristics, and the cases of each brand were analyzed. The results are as follows. First, customized cosmetics services could be classified online and offline. Second, customized cosmetics brands could be divided into general brand types and brand extension types. Third, skin data measurements could be classified into genetic analysis, big data-based surveys, and device measurements. Fourth, customized cosmetics manufacturing could be classified into a device manufacturing system, a consultant manufacturing system, and an individual production process system. Fifth, customized cosmetics distribution and delivery could be classified into same-day sales, general delivery, and regular delivery. The results of this study are meaningful in that they have identified and analyzed the current status of personalized cosmetics on-line and offline systems in recent trends, and it was confirmed that creative attempts in the domestic customized cosmetics market continue to change. It is hoped that this study will provide information and ideas to the beauty industry and related experts in the future and be used as basic data for customized cosmetics marketing

• Journal of Korean Academy of Nursing
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• v.52 no.4
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• pp.391-406
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• 2022

Purpose: The purpose of this study was to provide foundational knowledge on nursing tasks performed on patients with COVID-19 in a nationally-designated inpatient treatment unit. Methods: This study employs both quantitative and qualitative approaches. The quantitative method investigated the content and frequency of nursing tasks for 460 patients (age ≥ 18 y, 57.4% men) from January 20, 2020, to September 30, 2021, by analyzing hospital information system records. Qualitative data were collected via focus group interviews. The study involved interviews with three focus groups comprising 18 nurses overall to assess their experiences and perspectives on nursing care during the pandemic from February 3, 2022, to February 15, 2022. The data were examined with thematic analysis. Results: Overall, 49 different areas of nursing tasks (n = 130,687) were identified based on the Korean Patient Classification System for nurses during the study period. Among the performed tasks, monitoring of oxygen saturation and measuring of vital signs were considered high-priority. From the focus group interview, three main themes and eleven sub-themes were generated. The three main themes are "Experiencing eventfulness in isolated settings," "All-around player," and "Reflections for solutions." Conclusion: During the COVID-19 pandemic, it is imperative to ensure adequate staffing levels, compensation, and educational support for nurses. The study further propose improving guidelines for emerging infectious diseases and patient classification systems to improve the overall quality of patient care.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1212-1223
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• 2022

Skin lesions are common diseases that range from skin rashes to skin cancer, which can lead to death. Note that early diagnosis of skin diseases can be important because early diagnosis of skin diseases considerably can reduce the course of treatment and the harmful effect of the disease. Recently, the development of computer-aided diagnosis (CAD) systems based on artificial intelligence has been actively made for the early diagnosis of skin diseases. In a typical CAD system, the accurate classification of skin lesion types is of great importance for improving the diagnosis performance. Motivated by this, we propose a novel deep ensemble classification with multi-scale attention networks. The proposed deep ensemble networks are jointly trained using a single loss function in an end-to-end manner. In addition, the proposed deep ensemble network is equipped with a multi-scale attention mechanism and segmentation information of the original skin input image, which improves the classification performance. To demonstrate our method, the publicly available human skin disease dataset (HAM 10000) and the private animal skin lesion dataset were used for the evaluation. Experiment results showed that the proposed methods can achieve 97.8% and 81% accuracy on each HAM10000 and animal skin lesion dataset. This research work would be useful for developing a more reliable CAD system which helps doctors early diagnose skin diseases.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.185-194
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• 2023

The 4-axis strain-gauge, which is widely applied to military weapon systems, is operated in poor temperature and vibration conditions, tolerance may increase and malfunctions may occur. To improve this, this paper proposes a signal-processing software technique for the tolerance of the 4-axis strain gauge applied to a military weapon system. First, the tolerance of the strain-gauge and the signal processing circuit according to the ambient temperature were evaluated and analyzed. Second, a software technique for processing the dead zone and offset area that can improve the tolerance of the strain-gauge is proposed. The experimental results applying the software technique confirmed that it operated normally in the temperature test and operation test. Therefore, the proposed software technique is valid and can be used as useful information to improve tolerance due to ambient temperature and vibration when designing a system using a strain-gauge.