• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.136-140
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• 2004

A power-plant simulation tool has been developed for training the plant operators and testing a plant control system. The simulation tool is composed of a graphic editor, a component model builder and a system simulation solver. Such new programing techniques as object-oriented modeling and GUI(Graphical User Interface) are employed in developing the simulation tool. The graphic editor is based on the OpenGL library for effective implementation of GUI while the component model builder is based on object-oriented programming for efficient generalization of component models. The developed tool has been verified through the simulation of a real power plant.

• Food Science of Animal Resources
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• v.35 no.5
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• pp.630-637
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• 2015

In the dairy industry, natural plant-based powders are widely used to develop flavor and functionality. However, most of these ingredients are water-insoluble; therefore, emulsification is essential. In this study, the efficacy of high pressure homogenization (HPH) on natural plant (chocolate or vanilla)-based model emulsions was investigated. The particle size, electrical conductivity, Brix, pH, and color were analyzed after HPH. HPH significantly decreased the particle size of chocolate-based emulsions as a function of elevated pressures (20-100 MPa). HPH decreased the mean particle size of chocolate-based emulsions from 29.01 μm to 5.12 μm, and that of vanilla-based emulsions from 4.18 μm to 2.44 μm. Electrical conductivity increased as a function of the elevated pressures after HPH, for both chocolate- and vanilla-based model emulsions. HPH at 100 MPa increased the electrical conductivity of chocolate-based model emulsions from 0.570 S/m to 0.680 S/m, and that of vanilla-based model emulsions from 0.573 S/m to 0.601 S/m. Increased electrical conductivity would be attributed to colloidal phase modification and dispersion of oil globules. Brix of both chocolate- and vanilla-based model emulsions gradually increased as a function of the HPH pressure. Thus, HPH increased the solubility of plant-based powders by decreasing the particle size. This study demonstrated the potential use of HPH for enhancing the emulsification process and stability of the natural plant powders for applications with dairy products.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2002.11a
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• pp.95.2-96
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• 2002

• Journal of Microbiology and Biotechnology
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• v.34 no.5
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• pp.1003-1016
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• 2024

This study explores the potential of plant-based decellularization in regenerative medicine, a pivotal development in tissue engineering focusing on scaffold development, modification, and vascularization. Plant decellularization involves removing cellular components from plant structures, offering an eco-friendly and cost-effective alternative to traditional scaffold materials. The use of plant-derived polymers is critical, presenting both benefits and challenges, notably in mechanical properties. Integration of plant vascular networks represents a significant bioengineering breakthrough, aligning with natural design principles. The paper provides an in-depth analysis of development protocols, scaffold fabrication considerations, and illustrative case studies showcasing plant-based decellularization applications. This technique is transformative, offering sustainable scaffold design solutions with readily available plant materials capable of forming perfusable structures. Ongoing research aims to refine protocols, assess long-term implications, and adapt the process for clinical use, indicating a path toward widespread adoption. Plant-based decellularization holds promise for regenerative medicine, bridging biological sciences with engineering through eco-friendly approaches. Future perspectives include protocol optimization, understanding long-term impacts, clinical scalability, addressing mechanical limitations, fostering collaboration, exploring new research areas, and enhancing education. Collectively, these efforts envision a regenerative future where nature and scientific innovation converge to create sustainable solutions, offering hope for generations to come.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.3
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• pp.102-106
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• 2010

Recently process industries from oil and gas procedures and mining companies to manufactures of chemicals, foods, and beverages has been exploring the USN (Ubiquitous Sensor Networks) technology to improve safety of production processes. However, to apply the USN technology in the large-scale plant industry, reliability and security issues are not fully addressed yet, and the absence of the industrial sensor networking standard causes a compatibility problem with legacy equipment and systems. Although this situation, process industry such as energy plants are looking for the secure wireless plant solution to provide detailed, accurate safety monitoring from previously hard-reach, unaccordable area. In this paper, SPSF (Smart Plant Safety Framework based on Reliable-Secure USN) is suggested to fulfill the requirements of high-risk industrial environments for highly secure, reliable data collection and plant monitoring that is resistant to interference. The SPSF consists of three main layers: 1) Smart Safety Sensing Layer, 2) Smart Safety Network Layers, 3) Plant Network System Layer.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1570-1575
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• 2009

The purpose of this research is to propose the conceptual model of Scenario-based Project Planning Expert System which has not been used in domestic LNG plant industry. This research examines data on the plant project planning expert system of domestic and oversea, analyzes the components of project planning expert systems and benchmark excellent cases. The conceptual model of LNG plant project planning expert system is established through the procedure as has been noted above. The results of this research are as follows: First, this research draws out such components of LNG plant project planning expert system as feasibility, cost control, contract management and risk management. Second, this research proposes the conceptual model of LNG plant project planning expert system which core module is consist of feasibility evaluation, life cycle cost evaluation and decision making. Finally, each module of LNG plant project planning expert system would be integrated into the Scenario-based Project Planning Expert System.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.381-384
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• 2008

This paper presents an operational technique to maximize profit of a cogeneration power plant. To minimize errors in a loss and gain analysis of a cogeneration power plant, the energy sale profit in the cost-based-pool electric power trade market, the heat sale profit, and the supplementary fund profit for electric power industry are taken into consideration. The objective is to optimize the heat-electric power ratio to maximize profit of a cogeneration power plant. Furthermore, the constrained bidding technique to optimize heat-electric power ratiocan be obtained. Profits from of a cogeneration power plant are composed of three categories, such as the energy sale profit in the cost-based-pool electric power trade market, the heat sale profit, and the supplementary fund profit for electric power industry. Profits of a cogeneration power plant are varied enormously by the operation modes. The profits are mainly determined by the amount of constrained heat generation in each trading time. And the three profit categories arecoupled tightly via the heat-electric power ratio. The result of this case study can be used as a reference to a cogeneration power plant under the power trading system considered in this case.

• Research in Plant Disease
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• v.30 no.1
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• pp.99-102
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• 2024

Integrated pest management is essential for controlling plant diseases that reduce crop yields. Rapid diagnosis is crucial for effective management in the event of an outbreak to identify the cause and minimize damage. Diagnosis methods range from indirect visual observation, which can be subjective and inaccurate, to machine learning and deep learning predictions that may suffer from biased data. Direct molecular-based methods, while accurate, are complex and time-consuming. However, the development of large multimodal models, like GPT-4, combines image recognition with natural language processing for more accurate diagnostic information. This study introduces GPT-4-based system for diagnosing plant diseases utilizing a detailed knowledge base with 1,420 host plants, 2,462 pathogens, and 37,467 pesticide instances from the official plant disease and pesticide registries of Korea. The AI plant doctor offers interactive advice on diagnosis, control methods, and pesticide use for diseases in Korea and is accessible at https://pdoc.scnu.ac.kr/.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2003.10a
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• pp.27-27
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• 2003

• Proceedings of the Korean Society of Crop Science Conference
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• 2020.06a
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• pp.158-158
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• 2020