• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.345-353
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• 2023

This study aimed to investigate the differences in the commercial powder products of the Yeongdong illite based on sales specifications, specifically examining the mineralogical composition, particle size, and chemical composition according to mesh size. The goal was to understand the characteristics of illite powder products and utilize them as a mineralogical database for exploring various applications. Commercial illite powder samples obtained from two mines were subjected to various experiments, including X-ray diffraction (XRD) analysis, laser diffraction particle size analysis, and scanning electron microscopy analysis, X-ray fluorescence analysis. The XRD analysis revealed that the illite powder products from the two mines mainly consisted of illite/muscovite, quartz, and feldspar, indicating similar constituent minerals matching with those of ores for each mine. Laser diffraction particle size analysis indicated the difference in particle size distribution depending on the product specifications, with particle size uniformity tending to increase with increasing mesh sizes. Scanning electron microscopy analysis showed variations in particle shape and size based on specifications. The size of illite particles did not vary significantly with product specifications, with noticeable changes observed mainly in the particle sizes of quartz and feldspar. Furthermore, although there were some differences in chemical composition among the samples from different mines, no significant variations were observed according to specifications. Based on these results, when considering the application of commercial illite powder, it is essential to carefully select it with the consideration of its specifications to account for characteristic variations. The findings of this study present support the great potential of various application fields of commercial illite powder, contributing to industrial utilization and the development of new technologies.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.935-940
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• 2023

Digital-twin technology is emerging as an innovative solution for all industries, including manufacturing and production lines. Therefore, this paper optimizes all the energy used in a biomass plant based on unused resources. We will then implement a digital-twin prototype for biomass plants and evaluate its performance in order to improve the efficiency of plant operations. The proposed digital-twin prototype applies a standard communication platform between the framework and the gateway and is implemented to enable real-time collaboration. and, define the message sequence between the client server and the gateway. Therefore, an interface is implemented to enable communication with the host server. In order to verify the performance of the proposed prototype, we set up a virtual environment to collect data from the server and perform a data collection evaluation. As a result, it was confirmed that the proposed framework can contribute to energy optimization and improvement of operational efficiency when applied to biomass plants.

• Information Systems Review
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• v.24 no.4
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• pp.77-96
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• 2022

Live commerce has recently received substantial attention due to the spread of the non-face-to-face consumption culture driven by the COVID-19 pandemic. Live commerce has a higher purchase conversion rate than other forms of commerce. Accordingly, the likelihood of impulse buying in a live commerce environment is expected to be high. However, there is a shortage of research on consumer impulse buying in the live commerce environment. This study designs a scenario-based experiment using the integrated model of consumption impulse formation and enactment. Through this method, this study validates the influence of the characteristics of live commerce (i.e., vicarious experience and real-time interaction) on consumers' likelihood of impulse buying and further examines the moderating role of a live commerce host feature (i.e., professionalism) in these relationships. The results of this study confirm that both vicarious experience and real-time interaction have a positive effect on consumers' likelihood of impulse buying and that professionalism strengthens the impact of vicarious experience on the likelihood of impulse buying. This study's scenario-based experimental design is meaningful because it analyzes the likelihood of impulse buying in the context of live commerce shopping. Additionally, it provides live commerce service and platform providers with practical insights into how to maximize profits and operate services more efficiently.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.345-354
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• 2024

In this paper, we propose a triple band WLAN antenna for Wi-Fi 6E band with DGS. The proposed antenna has the characteristics required frequency band and bandwidth by considering the interconnection of two strip lines and three areas on the ground place. The total substrate size is 31 mm (W) × 50 mm (L), thickness (h) 1.6 mm, and the dielectric constant is 4.4, which is made of 22 mm (W₆ + W₄ + W₅) × 43mm (L₁ + L₂ + L₃ + L₅) antenna size on the FR-4 substrate. From the fabrication and measurement results, bandwidths of 340 MHz (1.465 to 1.805 GHz) for 900 MHz band, 480 MHz (2.155 to 2.635 GHz) for 2.4 GHz band and 1950 MHz (4.975 to 6.925 GHz) for 5.0/6.0 GHz band were obtained on the basis of -10 dB. Also, gain and radiation pattern characteristics are measured and shown in the frequency triple band as required.

• Journal of Life Science
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• v.34 no.4
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• pp.215-226
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• 2024

Aralia continentalis is widely distributed in Far East Asian countries such as Korea, China, and Japan. A. continentalis has traditionally been used as an herbal remedy for various conditions, including analgesia, headache, inflammation, lameness, lumbago, rheumatism, and dental diseases in Korea. Previously, epi-continentalic acid, continentalic acid, and kaurenoic acid as major active biological compounds belonging to the diterpenoid class were identified. To synthesize diterpenoid derivatives with enhanced bioavailability, Fusarium fujikuroi was employed to biotransform diterpenoids due to its known antibacterial activity. This yielded two derivatives of kaurenoic acid, namely 16α-hydroxyent-kauran-2-on-19-oic acid and 2β, 16α-dihydroxy-ent-kauran-19-oic acid, with their chemical structures elucidated via NMR analysis. These derivatives exhibited increased polarity compared to kaur- enoic acid, as evidenced by their retention time on preparative HPLC using the ODS-A column and structural modifications. Evaluation of their antidiabetic activity targeting PTP1B, a negative regulator of the insulin signaling pathway, revealed inhibitory activities of 30.8% and 27.6%, respectively, at a concentration of 4 ㎍/ml. Additionally, both derivatives demonstrated low cytotoxicity, with an IC50 value 18 times higher than kaurenoic acid. Therefore, the augmented water solubility and reduced toxicity of 16α-hydroxy-ent-kauran-2-on-19-oic acid and 2β, 16α-dihydroxy-ent-kauran-19-oic acid, resulting from biotransformation by F. fujikuroi, render them promising candidates for industrial applications.

• Membrane Journal
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• v.34 no.2
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• pp.87-95
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• 2024

Recent studies explore a wide array of desalination and water treatment methods, encompassing membrane processes such as reverse osmosis (RO), nanofiltration (NF), and electrodialysis (ED) to advanced capacitive deionization (CDI) and its membrane variant (MCDI). Comparative analyses reveal ED's cost-effectiveness in low-salinity scenarios, while hybrid systems (NF-MCDI, RO-NF-MCDI) show improved salt removal and energy efficiency. Novel ion separation methods (NF-CDI, NF-FCDI) offer enhanced efficacy and energy savings. These studies also highlight the efficiency of these methods in treating complex wastewater specific to various industries. Environmental impact assessments emphasize the need for sustainability in system selection. Additionally, the integration of microfabricated sensors into membranes allows real-time monitoring, advancing technology development. These studies underscore the variety and promise of emerging desalination and water treatment technologies. They provide valuable insights for enhancing efficiency, minimizing energy usage, tackling industry-specific issues, and innovating to surpass conventional method limitations. The future of sustainable water treatment appears bright, with continual advancements focused on improving efficiency, minimizing environmental impact, and ensuring adaptability across diverse applications.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.147-155
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• 2024

Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.

• Journal of Powder Materials
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• v.31 no.2
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• pp.169-179
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• 2024

Colloidal quantum dot (QDs) have emerged as a crucial building block for LEDs due to their size-tunable emission wavelength, narrow spectral line width, and high quantum efficiency. Tremendous efforts have been dedicated to improving the performance of quantum dot light-emitting diodes (QLEDs) in the past decade, primarily focusing on optimization of device architectures and synthetic procedures for high quality QDs. However, despite these efforts, the commercialization of QLEDs has yet to be realized due to the absence of suitable large-scale patterning technologies for high-resolution devices., This review will focus on the development trends associated with transfer printing, photolithography, and inkjet printing, and aims to provide a brief overview of the fabricated QLED devices. The advancement of various quantum dot patterning methods will lead to the development of not only QLED devices but also solar cells, quantum communication, and quantum computers.

• Smart Media Journal
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• v.13 no.4
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• pp.114-123
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• 2024

This paper proposes AR stone tower content, an experiential content based on wearable augmented reality (AR). Although wearable augmented reality is gaining attention, the acceptance of the technology is still focused on specialized applications such as industrial sites. On the other hand, the proposed AR stone tower content is based on the material of 'stone tower' so that general users can relate to it and easily participate in it, and it is organized to utilize space in a moving environment and find and stack stones based on natural hand gestures. The proposed AR stone tower content was implemented in the HoloLens 2 environment and evaluated by general users through a pilot exhibition in a small art museum. The evaluation results showed that the overall satisfaction with the content averaged 3.85, and the content appropriateness for the stone tower material was very high at 4.15. In particular, users were highly satisfied with content comprehension and sound, but somewhat less satisfied with object recognition, body adaptation, and object control. The above user evaluations confirm the resonance and positive response to the material, but also highlight the difficulties of the average user in experiencing and interacting with the wearable AR environment.

• Smart Media Journal
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• v.13 no.4
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• pp.33-48
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• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.