• Clean Technology
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• v.28 no.3
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• pp.203-209
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• 2022

An environmental evaluation was conducted by employing LCA methodology for a mechanical seal manufacturing process that uses recycled silicon recovered from end-of-cycle PV modules. The recycled silicon was purified and reacted with carbon to synthesize β-SiC particles. Then the particles underwent compression molding, calcination and heat treatment to produce a product. Field data were collected and the potential environmental impacts of each stage were calculated using the LCI DB of the Ministry of Environment. The assessment was based on 6 categories, which were abiotic resource depletion, acidification, eutrophication, global warming, ozone depletion and photochemical oxidant creation. The environmental impacts by category were 45 kg CO₂ for global warming and 2.23 kg C₂H₄ for photochemical oxide creation, and the overall environmental impact by photochemical oxide creation, resource depletion and global warming had a high contribution of 98.7% based on weighted analysis. The wet process of fine grinding and mixing the raw silicon and carbon, and SiC granulation were major factors that caused the environmental impacts. These impacts need to be reduced by converting to a dry process and using a system to recover and reuse the solvent emitted to the atmosphere. It was analyzed that the environmental impacts of resource depletion and global warming decreased by 53.9% and 60.7%, respectively, by recycling silicon from end-of-cycle PV modules. Weighted analysis showed that the overall environmental impact decreased by 27%, and the LCA analysis confirmed that recycling waste modules could be a major means of resource saving and realizing carbon neutrality.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.1-9
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• 2022

Today, apartment houses account for a very high proportion of the types of residence. This study analyzed the difference between the bidding construction cost using the long-term repair allowance and using the general repair cost, and analyzed the difference of factors affecting the amount of use of these two items. For this purpose, related data on apartment housing complexes located in seven representative districts of Busan from 2017 to 2021 were collected and analyzed from the apartment housing management information system. As a result of statistical analysis, the type of bidding variable had the greatest negative(-) effect on the bidding construction cost, and the next factor that affected was different between the amount of long-term repair allowance used and general repair cost used. In addition, there was a difference in statistical significance in the type of bidding by construction year for the number of bidding works between the case of using the long-term repair allowance and the case of using the general repair cost. The results of this analysis will help to find ways to reduce bidding construction costs. However, it is expected to find additional meaning by including more detailed variables such as technical ability.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.207-212
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• 2023

Near-infrared (NIR) absorbing dyes have been applied to various applications such as optical filters, biotechnology, energy storage and conversion, coating additive, and traditionally information-storage materials. Because image sensors used in cellphones and digital cameras have sensitivity in the NIR region, the NIR cut-off filter is essential to achieving more clear images. As energy storage and conversion have been important, diverse NIR absorbing materials have been developed to extend the absorption region to the NIR region, and NIR absorbing materials-based research has proceeded to improve device performances. Adding NIR-absorbing dye with a photo-thermal effect to a self-healable coating system has been attractive for future mobility technology, and more effective self-healing properties have been reported. In this report, the chemical structures of representative NIR-absorbing dyes and state of the art research based on NIR-absorbing dyes are introduced.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.575-576
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• 2020

본 논문은 근래에 식용곤충 식품에 대한 수요 및 국민적 관심이 증가하여 관련 산업이 급격히 성장하고 있는 가운데, 건강기능성 효과가 널리 알려진 흰점박이꽃무지 유충의 안정적인 생산량 확보를 위한 스마트 사육사를 제작하고 그 성능을 평가한 결과이다. 사육사는 L6m×W3m×H2.8m 크기로 제작하였으며, 안정적인 사육환경을 위하여 사육실과 공조실을 분리하여 설계하였다. 공시재료는 생후 15일이 경과된 흰점박이꽃 무지 유충 1령이며, 스마트 사육사 내 사육환경은 온도 25±2℃, 습도 65±5%로 제어하였다. 사육조사는 매주 1회, 유충의 체중, 길이, 두께를 측정하였으며, 스마트 사육사의 성능평가를 위해 일반 사육농가(전북 소재)와 비교·분석하였다. 사육 4주 후 조사 결과, 스마트 사육사에서 사육한 유충의 체중과 길이는 각각 평균 1.97g/마리와 3.75cm로, 일반농가의 1.58g/마리와 3.55cm에 비해 비교적 높은 것으로 나타났다. 하지만, 두께의 경우 2주 차까지 일반농가에서 대체로 높은 것으로 나타났으며, 이후 3~4주 차에서는 큰 차이를 보이지 않았다. 따라서 본 연구를 통해 개발한 흰점박이꽃무지 유충 스마트 사육사는 일반농가와 비교해 사육이 비교적 빠르고 생산량을 더 많이 확보할 수 있는 시스템으로 농가소득 증대에 유용할 것으로 판단되며, 장소 및 시간에 상관없이 생육환경 제어가 가능하여 개발된 시제품의 보급 확대가 필요하다.

• Analytical Science and Technology
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• v.20 no.3
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• pp.183-192
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• 2007

The various environmental regulation directives such as RoHS (restriction of hazardous substances in electrical and electronic products) and WEEE (waste from electrical and electronic equipments) are practically used as the technical barrier in international trade (TBT) of vehicles and electrical and electronic products recently. Regarding such an environmental regulation, Korea Research Institute of Standards Science (KRISS) organized a proficiency testing scheme to establish the reliability of measurement results produced by the relevant research institutes and test laboratories in Korea. Participants were 31 laboratories related to production of the electrical and electronic equipments and mobile vehicles. Two polypropylene samples of pellet type were employed as the proficiency testing materials (PTMs). Cadmium and lead were the analytes chosen among six components regulated in European Union (EU) RoHS directive. The PTMs were sent to the participants by post on September $1^{st}$ 2006, and deadline for results submission were October $10^{th}$ 2006. The results of each laboratory were evaluated in comparison with KRISS reference values using Robustic Z-score and Youden plot methods. The results of the various sample digestion methods were also compared. Most of participants reported good agreement within 10 % range of reference values. However, results from several laboratories showed significant biases from reference values. These laboratories should establish the quality assurance system for improvement of the measurement reliability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.839-848
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• 2006

Korea has become the 5th country to own and operate the high speed railroad in 2004. However, there were many difficulties until Koreans enjoy the first bullet train service with the average hourly speed of 300km. The high speed railroad requires elevated quality standards differently from the traditional railways. In addition to the technical difficulties, the construction project itself was an unpleasant case with huge delays and cost overruns mainly due to the lack of experiences, deficiency of owner$^{\circ}{\O}$s role, and increase of public resistances triggered by environmental concerns. This paper analyzes the reasons for delays on this mega-project. With respect to the characteristics of the whole project level, it is very complicated/linear project, whose total length is around 412 km with the composition of various sections in the route of the railway which have basically different conditions. For that reason, the analysis is performed in both macro and micro level. First, macroscopic analysis is performed to find critical subdivisions in the railway route that induces the significant delay in the opening due date. Then, microscopic analysis is followed to quantify the causes and effects of delays focused on these critical subdivisions in more detailed way. Finally, this paper provides lessons learned from this project to avoid the decisive delays in performing the similar large-scaled projects.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.27-35
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• 2023

In this paper, we propose a process of increasing productivity by applying a deep learning-based defect detection and classification system to the prepreg fiber manufacturing process, which is in high demand in the field of producing composite materials. In order to apply it to toe prepreg manufacturing equipment that requires a solution due to the occurrence of a large amount of defects in various conditions, the optimal environment was first established by selecting cameras and lights necessary for defect detection and classification model production. In addition, data necessary for the production of multiple classification models were collected and labeled according to normal and defective conditions. The multi-classification model is made based on CNN and applies pre-learning models such as VGGNet, MobileNet, ResNet, etc. to compare performance and identify improvement directions with accuracy and loss graphs. Data augmentation and dropout techniques were applied to identify and improve overfitting problems as major problems. In order to evaluate the performance of the model, a performance evaluation was conducted using the confusion matrix as a performance indicator, and the performance of more than 99% was confirmed. In addition, it checks the classification results for images acquired in real time by applying them to the actual process to check whether the discrimination values are accurately derived.

• Journal of Venture Innovation
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• v.4 no.1
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• pp.39-50
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• 2021

This was empirical research aimed at determining the effects of emotional labor, Resilience and service environment, on the performance of Long-term Care Hospital Employee. The participants were 180 employees working in long-term care hospitals in Gyeonggi-do. The collected data were analyzed using the SPSS statics19.0 program. The study were analyzed by frequency analysis and descriptive statistics, ANOVA, Scheffe? test, Pearson correlation coefficients, and stepwise regression. As a result of the study, age, marriage status, career, and position affected performance among the general characteristics.tion coefficients, and stepwise regression. As a result of the study, the average performance was 91.25 (±12.46) points, emotional labor was 41.25 (±4.21) points, Resilience was 52.89 (±6.37), and the service environment was 78.93(±15.3) points. The performance showed a positive correlation with emotional labor(r=.326, p<.001) service environment (r=.384, p=.005) and Resilience (r=.417, p<.001) of Long-term Care Hospital Employee. Service environment was the biggest factor affecting performance, and the second was resilience. The explanatory power of this regression model was 48.2% and was statistically significant (F=58.249, p<.001).

• Membrane Journal
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• v.34 no.2
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• pp.154-162
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• 2024

Anion exchange membranes (AEMs) are essential components in water electrolysis systems, serving to physically separate the generated hydrogen and oxygen gases while enabling the selective transport of hydroxide ions between electrodes. Key characteristics sought in AEMs include high ion conductivity and robust chemical and mechanical stability in alkaline. In this study, quaternized Poly(terphenyl piperidinium)/cellulose nanocrystals (qPTP/CNC) mixed matrix membrane was fabricated. The polymer matrix, PTP, was synthesized via super-acid polymerization, known for its excellent ion conductivity and alkaline durability. The qPTP/CNC membrane showed a dense and uniform morphology without significant voids or large aggregates at the polymer-nanoparticle interface. The qPTP/CNC membrane containing 2 wt% CNC demonstrated a high ion exchange capacity of 1.90 mmol/g, coupled with low water uptake (9.09%) and swelling ratio (5.56%). Additionally, the qPTP/CNC membrane showed significantly lower resistance and superior alkaline stability (384 hours at 50℃ in 1 M KOH) compared to the commercial FAA-3-50 membrane. These results highlight the potential of hydrophilic additive CNC in enhancing ion conductivity and alkaline durability of ion exchange membranes.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.267-278
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• 2024

This study was a descriptive research study targeting medical students to determine the impact of self-directed learning ability, self-regulated learning, and communication ability on self-efficacy in performing medical treatment. This study randomly selected medical students from Region J, located in Province G, as the approximate population, and a total of 125 copies were finally analyzed. Descriptive statistics were analyzed using t-test, ANOVA, correlation, and multiple regression analysis using IBM SPSS/25. Self-efficacy in performing medical treatment was related to self-directed learning ability (r=.61, p<.001), self-regulated learning (r=.50, p<.001), and communication ability (r=.33, p<.001). There was a positive correlation with all of them. As a result of analyzing the variables that affect the subject's self-efficacy in performing medical treatment using hierarchical multiple regression, self-directed learning ability was found to be the factor that best predicts self-efficacy in performing medical treatment, followed by self-regulated learning and communication ability. The total explanatory power was 46.6%. Acquiring specialized knowledge and becoming a doctor after graduation through clinical practice and acquiring the basic clinical practice skills necessary to successfully perform one's duties are important tasks that medical students must accomplish. Therefore, in order to improve medical students' self-efficacy in performing medical treatment, the importance of improving health care, major satisfaction, and life satisfaction must be recognized and managed. In addition, efforts to develop programs and improve systematic systems that can improve self-directed learning, self-regulated learning, and communication skills should also be supported.