• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.369-375
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• 2021

In this study, heterogeneous ZnO/CNTF composites were developed to improve the NO₂-sensing response, facilitated by the self-heating property. Highly conductive and mechanically stable CNTFs were prepared by a wet-spinning process assisted by the liquid crystal (LC) behavior of CNTs. Metal-organic frameworks (MOFs) of ZIF-8 were precipitated on the surface of the CNTF (ZIF-8/CNTF) via one-pot synthesis in solution. The subsequent calcination process resulted in the formation of the ZnO/CNTF composites. The calcination temperatures were controlled at 400, 500, and 600 ℃ in an N₂ atmosphere to confirm the evolution of the microstructures and NO₂-sensing properties. Gas sensor characterization was performed at 100 ℃ by applying a DC voltage to induce Joule heating through the CNTF. The results revealed that the ZnO/CNTF composite after calcination at 500 ℃ (ZnO/CNTF-500) exhibited an improved response (R_air/R_gas = 1.086) toward 20 ppm NO₂ as compared to the pristine CNTF (R_air/R_gas = 1.063). Selective NO₂-sensing properties were demonstrated with negligible responses toward interfering gas species such as H₂S, NH₃, CO, and toluene. Our approach for the synthesis of MOF-driven ZnO/CNTF composites can provide a new strategy for the fabrication of wearable gas sensors integrated with textile materials.

• Korean Journal of Materials Research
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• v.32 no.11
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• pp.508-514
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• 2022

Piezoelectric composite films which are enabled by inorganic piezoelectric nanomaterials-embedded polymer, have attracted enormous attention as a sustainable power source for low powered electronics, because of their ease of fabrication and flexible nature. However, the absorption of applied stress by the soft polymeric matrices is a major issue that must be solved to expand the fields of piezoelectric composite applications. Herein, a flexible and porous piezoelectric composite (piezoelectric sponge) comprised of BaTiO₃ nanoparticles and polydimethylsiloxane was developed using template method to enhance the energy conversion efficiency by minimizing the stress that vanishes into the polymer matrix. In the porous structure, effective stress transfer can occur between the piezoelectric active materials in compression mode due to direct contact between the ceramic particles embedded in the pore-polymer interface. The piezoelectric sponge with 30 wt% of BaTiO₃ particles generated an open-circuit voltage of ~12 V and a short-circuit current of ~150 nA. A finite element method-based simulation was conducted to theoretically back up that the piezoelectric output performance was effectively improved by introducing the sponge structure. Furthermore, to demonstrate the feasibility of pressure detecting applications using the BaTiO₃ particles-embedded piezoelectric sponge, the composite was arranged in a 3 × 3 array and integrated into a single pressure sensor. The fabricated sensor array successfully detected the shape of the applied pressure. This work can provide a cost-effective, biocompatible, and structural strategy for realizing piezoelectric composite-based energy harvesters and self-powered sensors with improved energy conversion efficiency.

• Journal of Ginseng Research
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• v.46 no.2
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• pp.248-254
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• 2022

Background: Zinc homeostasis is essential for human health and is regulated by several zinc transporters including ZIP and ZnT. ZIP4 is expressed in the small intestine and is important for zinc absorption from the diet. We investigated in the present study the effects of Panax ginseng (P. ginseng) extract on modulating Zip4 expression and cellular zinc levels in mouse Hepa cells. Methods: Hepa cells were transfected with a luciferase reporter plasmid that contains metal-responsive elements, incubated with P. ginseng extract, and luciferase activity was measured. Using ⁶⁵ZnCl₂, zinc uptake in P. ginseng-treated cells was measured. The expression of Zip4 mRNA and protein in Hepa cells was also investigated. Finally, using a luciferase reporter assay system, the effects of several ginsenosides were monitored. Results: The luciferase activity in cells incubated with P. ginseng extract was significantly higher than that of control cells cultured in normal medium. Hepa cells treated with P. ginseng extract exhibited higher zinc uptake. P. ginseng extract induced Zip4 mRNA expression, which resulted in an enhancement of Zip4 protein expression. Furthermore, some ginsenosides, such as ginsenoside Rc and Re, enhanced luciferase activity driven by intracellular zinc levels. Conclusion: P. ginseng extract induced Zip4 expression at the mRNA and protein level and resulted in higher zinc uptake in Hepa cells. Some ginsenosides facilitated zinc influx. On the basis of these results, we suggest a novel effect of P. ginseng on Zip4-mediated zinc influx, which may provide a new strategy for preventing zinc deficiency.

• Journal of The Korean Association of Information Education
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• v.26 no.1
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• pp.75-84
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• 2022

Currently, education is being conducted through face-to-face classes and instructional design using blended learning, an integrated online and offline model that utilizes online characteristics. As the paradigm of education has changed from face-to-face classes to non-face-to-face classes since COVID-19, teaching methods to respond to changes are required in the educational field. In this paper, as a instructional design model using online, we proposed a instructional design model that conducts online classes in non-real time and then conducts online face-to-face classes using virtual classrooms in real time. In addition, a teaching strategy that can apply the online face-to-face teaching design model using the proposed virtual class room to software classes was presented. The proposed instructional design model will be able to prepare for a paradigm shift in education with a teaching design that can accommodate the characteristics of face-to-face education online.

• Journal of Ecology and Environment
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• v.46 no.3
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• pp.172-182
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• 2022

Background: The coronavirus problem is an ecological problem stemming from a sudden change in the relationship between parasites and hosts. Ecologists judge organisms that are established out of their original territory as exotic species. Unlike in their original habitat, these exotic species become very aggressive in their newly settled habitat. Coronavirus infection damage was bigger in Europe or the United States than that in the country of its origin, China, and its neighboring countries. Therefore, coronavirus infection damage resembles the damage due to the invasive species. Results: Exotic species are found in places with similar environmental conditions to those of their origin when introduced to other ecological regions. However, there are few ecological ill effects in their place of origin, while the damage is usually severe in the ecological regions in which it is introduced. According to historical records, exotic infectious diseases, such as European smallpox and measles, also showed a similar trend and caused great damage in newly established places. Therefore, it is expected that measures to manage exotic species could be used for the prevention of exotic infectious diseases such as the coronavirus. Conclusions: Prevention comes first in the management of exotic species, and in order to come up with preventive measures, it is important to collect information on the characteristics of related organisms and their preferred environment. In this respect, ecosystem management measures such as exotic species management measures could be used as a reference to prevent and suppress the spread. To put these measures into practice, it is urgently required to establish an international integrated information network for collecting and exchanging information between regions and countries. Furthermore, a systematic ecosystem-management strategy in which natural and human environments could continue sustainable lives in their respective locations may serve as a countermeasure to prevent infectious diseases.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.445-454
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• 2022

The purpose of this study was to investigate the mediating effect of academic self-efficacy in the relationship between self-management competency and employment preparation behavior of senior nursing students. The data were analyzed using SPSS 26.0 program, frequency analysis, t-test, ANOVA, Pearson's correlation, and multiple regression. As a result of the study, self-management competency was positively correlated with academic self-efficacy, employment preparation behavior, and academic self-efficacy with employment preparation behavior. Academic self-efficacy showed a partial mediating effect between self-management competency and employment preparation behavior. The higher the level of self-management competency and academic self-efficacy, the higher the level of employment preparation behavior, and the explanatory power (R²) was 34%. Therefore, it suggests that it is important to develop self-management competency and to prepare an integrated strategy that can induce a sense of academic self-efficacy in order to promote the employment preparation behavior of nursing students.

• International Journal of Computer Science & Network Security
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• v.23 no.2
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• pp.173-182
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• 2023

The UAE government has set its sights on creating a smart, electronic-based government system that utilizes AI. The country's collaboration with India aims to bring substantial returns through AI innovation, with a target of over $20 billion in the coming years. To achieve this goal, the UAE launched its AI strategy in 2017, focused on improving performance in key sectors and becoming a leader in AI investment. To ensure public safety as the role of AI in government grows, the country is working on developing integrated cyber security solutions for SCADA systems. A questionnaire-based study was conducted, using the AI IQ Threat Scale to measure the variables in the research model. The sample consisted of 200 individuals from the UAE government, private sector, and academia, and data was collected through online surveys and analyzed using descriptive statistics and structural equation modeling. The results indicate that the AI IQ Threat Scale was effective in measuring the four main attacks and defense applications of AI. Additionally, the study reveals that AI governance and cyber defense have a positive impact on the resilience of AI systems. This study makes a valuable contribution to the UAE government's efforts to remain at the forefront of AI and technology exploitation. The results emphasize the need for appropriate evaluation models to ensure a resilient economy and improved public safety in the face of automation. The findings can inform future AI governance and cyber defense strategies for the UAE and other countries.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.285-295
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• 2022

The trapping efficacy of five commercially available sex pheromones manufactured in Korea, the Netherlands, North America, China, and Costa Rica was evaluated to determine the population dynamics of Spodoptera frugiperda and Mythimna loreyi and their relationships with the weather parameters of maize fields in Miryang, Gyeongnam Province, Korea in 2019. The results show that the sex pheromone manufactured in Costa Rica were more efficient at capturing S. frugiperda and M. loreyi than those manufactured in other countries. The lowest number of S. frugiperda moths were captured using sex pheromones manufactured in the Netherlands. We noted that more than four population peaks of both the moth species and weather parameters influenced the moth population dynamics in Miryang. A positive relationship was observed between the population of S. frugiperda and weather parameters, such as mean temperature, rainfall, and relative humidity, for sex pheromones manufactured in Korea. Furthermore, a positive relationship was recorded between the population of M. loreyi and wind speed for the sex pheromone manufactured in Korea. The results of this study suggest that the sex pheromones manufactured in Costa Rica are the best solution for the efficient capture of S. frugiperda and M. loreyi under typical weather conditions in the southern parts of Korea. In addition, the outcomes of this study are discussed in terms of population dynamics and integrated pest management for S. frugiperda and M. loreyi as alternatives to chemical management by maize producers. Further studies related to the continuous improvement in the capture efficiency of both moth species using sex pheromones are now needed.