• Journal of the Korea Institute of Building Construction
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• v.24 no.4
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• pp.507-515
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• 2024

Recent advancements in Building Information Modeling(BIM) have significantly impacted the construction industry, driving competitiveness and innovation. However, rebar construction, a critical component influencing project quality and cost, has lagged behind in BIM adoption. Traditional methods relying heavily on 2D drawings for rebar detailing have hindered efficiency and introduced potential errors. This paper presents a novel system designed to automate the detailed modeling of rebar, thereby promoting BIM integration within rebar construction and optimizing construction management processes. The system leverages confirmed structural drawings from the post-structural design phase to automatically generate intricate rebar models for columns and beams. To ensure adherence to domestic structural design standards, the system is developed using C# programming language and the Revit API. By automating rebar modeling, this system aims to minimize human error, reduce labor-intensive tasks, and enhance overall rebar construction efficiency through the effective utilization of generated rebar model data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1968-1985
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• 2024

At present, the world is witnessing a rapid change in all the fields of human civilization business interests and goals of all the sectors are changing very fast. Global changes are taking place quickly in all fields - manufacturing, service, agriculture, and external sectors. There are plenty of hurdles in the emerging technologies in agriculture in the modern days. While adopting such technologies as transparency and trust issues among stakeholders, there arises a pressurized necessity on food suppliers because it has to create sustainable systems not only addressing demand-supply disparities but also ensuring food authenticity. Recent studies have attempted to explore the potential of technologies like blockchain and practices for smart and sustainable agriculture. Besides, this well-researched work investigates how a scientific cum technological blockchain architecture addresses supply chain challenges in Precision Agriculture to take up challenges related to transparency traceability, and security. A robust registration phase, efficient authentication mechanisms, and optimized data management strategies are the key components of the proposed architecture. Through secured key exchange mechanisms and encryption techniques, client's identities are verified with inevitable complexity. The confluence of IoT and blockchain technologies that set up modern farms amplify control within supply chain networks. The practical manifestation of the researchers' novel blockchain architecture that has been executed on the Hyperledger network, exposes a clear validation using corroboration of concept. Through exhaustive experimental analyses that encompass, transaction confirmation time and scalability metrics, the proposed architecture not only demonstrates efficiency but also underscores its usability to meet the demands of contemporary Precision Agriculture systems. However, the scholarly paper based upon a comprehensive overview resolves a solution as a fruitful and impactful contribution to blockchain applications in agriculture supply chains.

• Journal of Web Engineering
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• v.12 no.7
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• pp.2159-2173
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• 2020

Various physiological benefits have been linked to Hizikia fusiforme (HF), an edible brown seaweed. Here, fucose-containing sulfated polysaccharides were extracted from celluclast-processed HF (SPHF) and their antitumor efficacy against bladder cancer was evaluated in vitro and in vivo. SPHF possesses high sulfated polysaccharide and fucose contents and free radical scavenging activities compared to those of celluclast-processed HF extracts (CHF). SPHF inhibited bladder cancer EJ cell proliferation via G1-phase cell cycle arrest. This was due to the induction of p21WAF1 expression associated with the downregulation of CDKs and cyclins. Moreover, JNK phosphorylation was identified as an SPHF-mediated signaling molecule. SPHF treatment also hindered the migration and invasion of EJ cells by inhibiting MMP-9 expression, which was attributed to the repression of transcriptional binding to NF-κB, AP-1, and Sp-1 in the MMP-9 promoter region. In an animal study, SPHF treatment suppressed EJ tumor growth in xenograft mice similarly to cisplatin. Furthermore, no toxicity signs were found after weight loss assessment, biochemical tests, and organ tissue immunostaining during oral administration of 20-200 mg/kg SPHF for 20 days. Therefore, our study demonstrates the antitumor efficacy of SPHF in vitro and in vivo, thus highlighting its potential for bladder cancer treatment development.

• Journal of the Korean Ceramic Society
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• v.59
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• pp.338-349
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• 2020

Large scale with high-purity hexagonal aluminum nitride nanoparticles (AlN NPs) was synthesized using DC thermal plasma arc discharge method (TPAD). Argon gas was used as the plasma forming gas, while ammonia (NH₃) gas was used as the reactive gas, which was fed into the reactor at a constant flow rate of 5 LPM. In order to optimize the process for high yield, the experiments were carried out at various plasma input powers, such as 1.5, 3.0, and 4.5 kW. Following the optimization, to examine the influence of using pure nitrogen gas, an experiment was also carried out in the nitrogen ambience. The phase identification and structural determination of the synthesized NPs were carried out using XRD and Raman spectroscopic analyses. While the morphology, particle size, and elemental compositions of the synthesized NPs were observed from SEM, HRTEM, XPS, and EDX analyses. The photoluminescence response was confirmed from the PL spectrum. The PL emission peaks observed around 440 nm (2.8 eV) and 601 nm (2.07 eV), respectively, which correspond to the UV blue and red band emissions of both AlN and Al/AlN NPs. The results show that the synthesized nano-AlN NPs exhibit excellent crystallinity with a high yield of approximately 210 g/h. The current plasma technology can be regarded as a perfect potential process for developing nano-AlN powders with improved efficiency.

• Archives of Metallurgy and Materials
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• v.63 no.3
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• pp.1433-1437
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• 2018

Neodymium-Iron-Boron (Nd-Fe-B) magnets are considered to have the highest energy density, and their applications include electric motors, generators, hard disc drives, and MRI. It is well known that a fiber structure with a high aspect ratio and the large specific surface area has the potential to overcome the limitations, such as inhomogeneous structures and the difficulty in alignment of easy axis, associated with such magnets obtained by conventional methods. In this work, a suitable heat-treatment procedure based on single-step and multistep treatments to synthesize sound electrospun Nd-Fe-B-O nanofibers of Φ572 nm was investigated. The single-step heat-treated (directly heat-treated at 800℃ for 2 h in air) samples disintegrated along with the residual organic compounds, whereas the multistep heat-treated (sequential three-step heat-treated including three steps;: dehydration (250℃ for 30 min in an inert atmosphere), debinding (650℃ for 30 min in air), and calcination (800℃ for 1 h in air)) fibers maintained sound fibrous morphology without any organic impurities. They could maintain such fibrous morphologies during the dehydration and debinding steps because of the relatively low internal pressures of water vapor and polymer, respectively. In addition, the NdFeO3 alloying phase was dominant in the multistep heat-treated fibers due to the removal of barriers to mass transfer in the interparticles.

• Journal of Environmental Science International
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• v.33 no.9
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• pp.645-665
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• 2024

For volatile organic compounds (VOCs) emanating from workplaces within the Noksan national industrial complex, the emission characteristics of pollutants were identified through zone-based measurements using vehicles equipped with selective ion flow tube mass spectrometry(SIFT-MS). The average concentration of total VOCs was higher in zones 2, 4, and 5 than in zones 1, 3, and 6, and was 2.1 to 4.2 times higher than background concentrations. The average concentrations of pollutants investigated were (from highest to lowest) methyl ethyl ketone, formaldehyde, methanol, and n-hexane. However, the pollutants that should be prioritized for reduction to decrease ozone generation were (from highest to lowest) methyl ethyl ketone, n-hexane, for maldehyde, and ethylbenzene+xylene. Benzene, a substance governed by atmospheric environmental standards, exhibited a frequency distribution exceeding the stipulated limits, and concentrations exceeding 100 ppb were identified for methyl ethyl ketone, methanol, toluene, and n-hexane. In certain class 4 and 5 workplace facilities, VOC emissions and emission prevention installations were inadequately managed, necessitating the formulation of management measures for small enterprises. Also, workplaces that emit large amounts of VOCs need to upgrade to VOC-prevention installations with higher processing efficiencies. To efficiently monitor VOCs in a wide range of areas, such as the Noksan national industrial complex, it is considered appropriate to monitor workplaces that emit high concentrations of VOCs using mobile SIFT-MS in real time rather than relying on fixed monitoring methods. A specialized method targeting approximately 10 VOCs is necessary to quickly track emission sources.Furthermore, it is essential to phase in a system for the intensive management of suspected workplaces based on accumulated data from SIFT-MS in areas where high VOC concentrations are measured and to establish a cooperative system for sharing data between relevant institutions.

• Herbal Formula Science
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• v.32 no.3
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• pp.223-233
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• 2024

Objectives : Natural products containing bioactive compounds with high antioxidant activity are potentially important sources that can contribute to the improvement of various diseases. Therefore, the aim of this study was to investigate phenolic compounds of Cinnamomum cassia (C. cassia) ethanolic extract (CCEE). And then we evaluated the antioxidant effect. Methods : We used liquid chromatography with tandem mass spectrometry (LC-MS/MS) to identify the compounds in CCEE. LC-MS/MS was performed in positive ion mode using Shimadzu, Nexera HPLC system and IDA TOF mass system. Solvent A was distilled water and solvent B was acetonitrile as mobile phase. The analysis was performed at a flow rate of 0.5 ml/min, column temperature of 35 ℃ and wavelength of 284 nm. The antioxidant effect of CCEE was analyzed using DPPH (2,2-diphenyl-2-picrylhydrazyl free radical) and ABTS (2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid)). In addition, total phenolics and total flavonoids contents were measured to determine antioxidant effects. Results : Analysis using LC-MS/MS identified four compounds: Coumarin, Trans-cinnamaldehyde, Trans-cinnamic acid, and 2-Methoxycinnamaldehyde. Free radicals decreased in a concentration-dependent manner starting from 10 ㎍/ml of CCEE, and decreased to a level similar to Ascorbic acid (AA) from a concentration of 60 ㎍/ml onwards. Conclusions : Based on the findings, CCEE exhibits strong antioxidant activity as evidenced by the presence of Coumarin, Trans-cinnamaldehyde, Trans-cinnamic acid, and 2-Methoxycinnamaldehyde. Consequently, this study suggests that CCEE can serve as an important source of natural antioxidants and can be efficiently used in the management of oxidative stress diseases.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.127-136
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• 2024

Flooding presents a significant threat to infrastructure, and climate change is exacerbating these risks. High-speed rail (HSR) infrastructure, designed based on historical data, may struggle to cope with future extreme flood events. Infrastructure stakeholders require forecasting capabilities to predict the intensity and frequency of future floods so they can develop adaptive strategies to mitigate flood risks and impacts. Floods can cause significant damage to HSR infrastructure networks, disrupting their operations. Traditional network theory-based frameworks are insufficient for analyzing the three-dimensional effects of floods on HSR networks. To address this issue, this study proposes a comprehensive approach to assess flood risk and vulnerability under future climate scenarios for HSR networks. The method consists of three components. (i) Generate flood inundation data by utilizing global climate models, Shared Socioeconomic Pathways(SSPs), and the CaMa-Flood model. (ii) Fit extreme flood depths to the Gumbel distribution to generate flood inundation scenarios. (iii) Overlay flood scenarios on the HSR network and quantitatively assess network vulnerability based on topology network. When applied to the HSR system in mainland China, the results indicate that flood severity does not necessarily increase under higher SSPs, but may worsen over time. The minimum flood return period that causes HSR disruptions is decreasing, with Hubei Province showing a significant increase in HSR segment failure probability. Discontinuous phase transitions in HSR network topology metrics suggest potential nationwide collapses under future infrequent floods. These findings can inform preventive measures for the HSR sector and flood-resistant standards for HSR infrastructure. The method used in this study can be extended to analyze the vulnerability of other transportation systems to natural disasters, serving as a quantitative tool for improving resilience in a changing climate.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1220-1229
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• 2024

In the construction industry, professionals are required to have advanced problem-solving skills to adeptly handle the dynamic challenges inherent to project execution. These skills are crucial, as they enable professionals to effectively navigate the complexities and unpredictability of construction projects, ensuring timely and cost-effective completion. This paper explores an innovative approach to enhance the problem-solving skills of construction students through the integration of conversational AI-based serious games into their educational curriculum. The objective of this research was acquired by following three phases: hazard interaction, problem identification, and AI-guided text-based communication. This approach creates an engaging learning environment, simulating real-world construction challenges and problems, focusing on the excavation phase of a construction project as a case study for students to interact with and communicate with the Conversational AI agent through text-based prompts. In the future, the proposed study can be used to evaluate how AI agents can help enhance problem-solving skills by promoting emotional engagement among participants. This research sheds light on the potential of integrating conversational AI in education, providing valuable insights for educators designing construction management training programs by underscoring the importance of engagement in real-world problem-solving scenarios.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.927-947
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• 2024

Due to the global low birth rate and aging population, there is a growing interest in utilizing robot technology as a solution to address labor shortages. Specifically, mobile robots, which are growing rapidly, have become intelligent enough to recognize their environment and avoid obstacles to carry out tasks. However, the integration of IT technology into these robots has led to an increase in potential security vulnerabilities, and security research has been conducted to prepare countermeasures. However, research to examine the security threats of mobile robots in general is insufficient. To enhance the overall security of robot systems, it is imperative to systematically identify security threats starting from the design phase. In this paper, we identify security threats within the mobile robot delivery service environment using a structured approach that involves Data Flow Diagram and STRIDE threat modeling. Additionally, we visualize vulnerabilities and attack techniques through Attack Tree based on the Attack Library, and a Check List has finally been created to derive security requirements. We have been conducted this study with the hope that the results derived from this study will be utilized in establishing guidelines and policies related to robot security and contribute to the establishment of a safe robot foundation.