• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.153-165
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• 2022

This study is about the Novel Engineering(NE) education program : a class model that combines reading and engineering. By including the process of directly designing and programming a virtual reality using CospacesEdu (a VR authoring tool for the NE class), the effects of the educational program on learners' STEAM literacy and Learning immersion are demonstrated. Moreover, the subject of this education is Dokdo in South Korea. As a result, the average of STEAM literacy is increased, and a significant change is confirmed statistically in Convergence. Learning immersion shows significant improvement in Challenges-skills balance. On the other hand, some students experience difficulties due to the long research stages, from reading a book to researching for information to designing VR and rewriting a story with the collected information. In conclusion, this study will help generalise other education using NE, and this developed program will be a reference that would suggest a new way of teaching.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.1-11
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• 2021

As the aging of large domestic SOC facilities accelerates, facility maintenance is also changing from safety evaluation based on the current condition to performance-oriented preventive and preemptive maintenance based on the prediction of the level of future obsolescence. In particular, in the case of bridges, class 1 and 2 bridges are systematically managed along with many studies, but for small and medium-sized class 3 bridges there is no collection and utilization of historical data presenting performance degradation during their service life. Therefore, in this study, 3D model-based demonstration DB system was designed and developed to intuitively check the damage change rate at the damage location by registering the maintenance history by life cycle for each member's exterior damage in the 3D bridge object and to enable API-based comprehensive performance evaluation.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.1-10
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• 2023

The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.245-261
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• 2024

The COVID-19 pandemic has led to the widespread adoption of contactless transactions, resulting in a noticeable increase in the trend towards fully unmanned stores. In such stores, all operational processes are automated, primarily using artificial intelligence (AI) technology. However, this AI technology has several security vulnerabilities, which can be critical in the environment of fully unmanned stores. This paper analyzes the security vulnerabilities that AI-based fully unmanned stores may face, focusing particularly on the object detection model YOLO, demonstrating that Hiding Attacks and Altering Attacks using adversarial patches are possible. It is confirmed that objects with adversarial patches attached may not be recognized by the detection model or may be incorrectly recognized as other objects. Furthermore, the paper analyzes how Data Augmentation techniques can mitigate security threats by providing a defensive effect against adversarial patch attacks. Based on these results, we emphasize the need for proactive research into defensive measures to address the inherent security threats in AI technology used in fully unmanned stores.

• Journal of Practical Engineering Education
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• v.16 no.5_spc
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• pp.619-633
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• 2024

This study analyzes the competency model of the Learning Factory at TU Darmstadt, Germany, aiming to derive implications for developing competency-based curricula in South Korean universities. It proposes an integrated model that combines theoretical knowledge with practical experience, allowing for the transformation of existing knowledge into necessary competencies for task execution. Additionally, it advocates for a learner-centered approach that enhances active engagement in the learning process, empowering students to take charge of their education. By implementing this integrated and learner-centered model, students can develop the transformative competencies required for future societal demands. This approach is expected to act as a catalyst for advancing competency-based education within South Korea's higher education system, ultimately fostering a more effective and responsive educational environment.

• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.268-275
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• 2017

The photosynthetic rates of crops depend on growth environment factors, such as light intensity and temperature, and their photosynthetic efficiencies vary with growth stage. The objective of this study was to compare two different models expressing canopy photosynthetic rates of romaine lettuce (Lactuca sativa L., cv. Asia Heuk romaine) using three variables of light intensity, temperature, and growth stage. The canopy photosynthetic rates of the plants were measured 4, 7, 14, 21, and 28 days after transplanting at closed acrylic chambers ($1.0{\times}0.8{\times}0.5m$) using light-emitting diodes, in which indoor temperature and light intensity were designed to change from 19 to $28^{\circ}C$ and 50 to $500{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. At an initial $CO_2$ concentration of $2,000{\mu}mol{\cdot}mol^{-1}$, the canopy photosynthetic rate began to be calculated with $CO_2$ decrement over time. A simple multiplication model expressed by simply multiplying three single-variable models and a modified rectangular hyperbola model were compared. The modified rectangular hyperbola model additionally included photochemical efficiency, carboxylation conductance, and dark respiration which vary with temperature and growth stage. In validation, $R^2$ value was 0.849 in the simple multiplication model, while it increased to 0.861 in the modified rectangular hyperbola model. It was found that the modified rectangular hyperbola model was more suitable than the simple multiplication model in expressing the canopy photosynthetic rates affected by environmental factors (light Intensity and temperature) and growth factor (growth stage) in plant factory modules.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.99-107
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• 2017

This paper proposes a battery model coefficient correction method for improving the accuracy of existing lithium battery equivalent models. BMS(battery management system) has been researched and developed to minimize shortening of battery life by keeping SOC(state of charge) and state of charge of lithium battery used in various industrial fields such as EV. However, the cell balancing operation based on the battery cell voltage can not follow the SOC change due to the internal resistance and the capacitor. Various battery equivalent models have been studied for estimation of battery SOC according to the internal resistance of the battery and capacitors. However, it is difficult to apply the same to all the batteries, and it tis difficult to estimate the battery state in the transient state. The existing battery electrical equivalent model study simulates charging and discharging dynamic characteristics of one kind of battery with error rate of 5~10% and it is not suitable to apply to actual battery having different electric characteristics. Therefore, this paper proposes a battery model coefficient correction algorithm that is suitable for real battery operating environments with different models and capacities, and can simulate dynamic characteristics with an error rate of less than 5%. To verify proposed battery model coefficient calibration method, a lithium battery of 3.7V rated voltage, 280 mAh, 1600 mAh capacity used, and a two stage RC tank model was used as an electrical equivalent model of a lithium battery. The battery charge/discharge test and model verification were performed using four C-rate of 0.25C, 0.5C, 0.75C, and 1C. The proposed battery model coefficient correction algorithm was applied to two battery models, The error rate of the discharge characteristics and the transient state characteristics is 2.13% at the maximum.

• Journal of Oriental Neuropsychiatry
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• v.22 no.2
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• pp.107-128
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• 2011

Objectives : This experiment was designed to investigate the efficacy of DDTCMT hot water extract & ultra-fine powder on Alzheimer's Disease Model. Methods : The effects of the DDTCMT hot water extract on expression of IL-$1{\beta}$, IL-6, TNF-${\alpha}$, COX-2, NOS-II, IL-10, IL-1 receptor antagonist mRNA and production of IL-$1{\beta}$, IL-6, TNF-${\alpha}$ in BV2 microglial cell line treated by lipopolysacchaide(LPS) were investigated. Expression of NO, ROS in BV2 microglial cell line treated by LPS and AChE activity in PC-12 cell treated by NGF were investigated. anti-AChE was observed through Western blot analysis. The effects of the DDTCMT hot water extract & ultra-fine powder on the behavior of the memory deficit mice induced by scopolamine were investigated. Results : 1. The DDTCMT hot water extract significantly decreased the production of mIL-6, mNOS-II, mTNF-${\alpha}$, and increased the production of mIL-10, mIL-1 receptor antagonist. 2. The DDTCMT hot water extract significantly suppressed the production of IL-$1{\beta}$, IL-6, TNF-${\alpha}$ in BV2 microglial cell line treated by LPS. 3. The DDTCMT hot water extract significantly suppressed the NO and ROS production in BV2 microglial cell line treated by LPS. 4. The DDTCMT hot water extract groups showed inhibition of AChE activity in NGF treated PC-12 cell line. 5. The DDTCMT hot water extract suppressed anti-AChE expression in NGF treated PC-12 cell line was observed by Western blot analysis. 6. The DDTCMT hot water extract & ultra-fine powder groups showed significantly inhibitory effect on the scopolamine -induced impairment of memory in the experiment of Morris water maze. Conclusions : These results suggest that the DDTCMT hot water extract & ultra-fine powder may be effective for the prevention and treatment of Alzheimer's disease.

• Journal of Oriental Neuropsychiatry
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• v.18 no.2
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• pp.101-132
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• 2007

Objective : This research investigates the effect of the NogYongDaeBoTang,(NYDBT) on Alzheimer's disease. Method : The effects of the NYDBT extract on (1) $IL-1{\beta}$, IL-6, and $TNF-{\alpha}$ mRNA of PC-12 cells treated with LPS; (2) acetylcholinesterase(AChE), amyloid precursor proteins(APP), and glial fibrillary acidic protein(GFAP) mRNA the AChE activity and the APP production of PC-12 cell treated with CT-105; (3) the behavior; (4) expression of $IL-1{\beta}$, $TNF-{\alpha}$, MDA, $IL-1{\beta}$ mRNA, and $TNF-{\alpha}$ mRNA; (5) the infarction area of the hippocampus, and brain tissue injury in Alzheimer‘s diseased mice induced with ${\beta}A$ were investigated. Results : 1. The NYDBT extract suppressed the expression of $IL-1{\beta}$, IL-6 and $TNF-{\alpha}$ mRNA in BV2 microglia cell line treated with LPS. 2. The NYDBT extract suppressed the expression of $IL-1{\beta}$, IL-6, and $TNF-{\alpha}$ protein production in BV2 microglia cell line treated with LPS. 3. For the NYDBT extract group a significant inhibitory effect on the memory deficit was shown for the mice with Alzheimer's disease induced by $A{\beta}$ in the Morris water maze experiment, which measured stop-through latency, and distance movement-through latency. 4. The NYDBT extract suppressed the over-expression of $IL-1{\beta}$ protein, $TNF-{\alpha}$ protein, MDA, and CD68/CD11b, in the mice with Alzheimer's disease induced by $A{\beta}$. 5. The NYDBT extract reduced the infarction area of hippocampus, and controlled the injury of brain tissue in the mice with Alzheimer's disease induced by $A{\beta}$. 6. The NYDBT extract reduced the Tau protein, GFAP protein, and presenilin1/2 protein (immunohistochemistry) of hippocampus in the mice with Alzheimer's disease induced by $A{\beta}$. Conclusions : These results suggest that the NYDBT extract may be effective for the prevention and treatment of Alzheimer's disease.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.289-292
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• 2008

기존의 웹 수집 로봇에서 처리하지 못하는 자바스크립트 함수 링크를 처리하기 위하여 인터넷 익스플로러의 "Active Script Engine"을 사용하였다. 또한 자바스크립트 함수 링크를 처리 하였을 경우 웹 수집 로봇의 수집량을 측정하기 위하여 웹 수집 로봇을 개발하였다. 웹 수집 로봇을 개발하기 위해서 구글봇과 네이봇 등 웹 수집 로봇의 구조를 파악하여, 수집 로봇에 활용되는 구성요소를 구현하고 분산처리형태의 웹 수집 로봇을 설계하여 개발했다. 또한 개발된 웹 로봇에 제안된 자바스크립트 처리 모델을 추가하여 성능 평가를 하였다. 성능평가 방법은 자바스크립트를 사용하는 웹사이트의 게시판을 대상으로 하여 웹 수집량을 비교 분석하는 것이다. 웹사이트 게시물 1000개인 경우, 일반 웹 로봇의 경우에는 1페이지밖에 수집하지 못하였고, 제안된 웹 로봇의 경우 1000개 이상의 웹 페이지를 수집하는 결과를 얻었다.