• Title/Summary/Keyword: Model generation

Search Result 5,495, Processing Time 0.035 seconds

Characteristics of Water Level and Velocity Changes due to the Propagation of Bore (단파의 전파에 따른 수위 및 유속변화의 특성에 관한 연구)

  • Lee, Kwang Ho;Kim, Do Sam;Yeh, Harry
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.28 no.5B
    • /
    • pp.575-589
    • /
    • 2008
  • In the present work, we investigate the hydrodynamic behavior of a turbulent bore, such as tsunami bore and tidal bore, generated by the removal of a gate with water impounded on one side. The bore generation system is similar to that used in a general dam-break problem. In order to the numerical simulation of the formation and propagation of a bore, we consider the incompressible flows of two immiscible fluids, liquid and gas, governed by the Navier-Stokes equations. The interface tracking between two fluids is achieved by the volume-of-fluid (VOF) technique and the M-type cubic interpolated propagation (MCIP) scheme is used to solve the Navier-Stokes equations. The MCIP method is a low diffusive and stable scheme and is generally extended the original one-dimensional CIP to higher dimensions, using a fractional step technique. Further, large eddy simulation (LES) closure scheme, a cost-effective approach to turbulence simulation, is used to predict the evolution of quantities associated with turbulence. In order to verify the applicability of the developed numerical model to the bore simulation, laboratory experiments are performed in a wave tank. Comparisons are made between the numerical results by the present model and the experimental data and good agreement is achieved.

A Case Study of New Franchise Brand Launching Through Proactive Market Response: BEERBARKET'S Successful Story of INTO FRANCHISE SYSTEMS (선행적 대응을 통한 프랜차이즈 뉴비즈니스 런칭 사례 : (주)인토외식산업의 맥주바켓 성공사례)

  • Seo, Min-Gyo
    • The Korean Journal of Franchise Management
    • /
    • v.3 no.1
    • /
    • pp.111-129
    • /
    • 2012
  • Domestic franchise industry is a promising business to more than 10% per year growth rate and emerging as core of retail. In addition, due to the socio-cultural phenomena, including the retirement of the baby-boom generation, the growth of the franchise industry for some time expected to continue. But Domestic franchise reveals that limits to ensure for new franchisees because that few industries are concentrated to advance for franchisor and franchisees. Franchisors that within the industry came to a saturated, are for the growth and expansion of business into new industries to deploy as second, third brand. But reality is that the more success rather than failure. Therefore, in this study is a new brand development approach and case study results it focus on the BEERBARKET's successful story of INTO FRANCHISE SYSTEMS, INC. Case analysis results of this study, are reveled that franchise headquarters derived through research methods and research information, environmental survey and analysis should be continuously and objectively. Thus, based on the derived contents, the new brand Biz-Model should be established for recognition from the industry and customers. Ability to respond sensitively to changes in the environment and business activities can be associated with linking franchise headquarters belonging to the saturated competitive environment more is needed. Through proactively respond Franchise New business launching instance that BEERBARKET's successful story of INTO FRANCHISE SYSTEMS, INC. suggests the need to study about how to respond to environmental changes.

A Study on the Establishment of Entropy Source Model Using Quantum Characteristic-Based Chips (양자 특성 기반 칩을 활용한 엔트로피 소스 모델 수립 방법에 관한 연구)

  • Kim, Dae-Hyung;Kim, Jubin;Ji, Dong-Hwa
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2021.10a
    • /
    • pp.140-142
    • /
    • 2021
  • Mobile communication technology after 5th generation requires high speed, hyper-connection, and low latency communication. In order to meet technical requirements for secure hyper-connectivity, low-spec IoT devices that are considered the end of IoT services must also be able to provide the same level of security as high-spec servers. For the purpose of performing these security functions, it is required for cryptographic keys to have the necessary degree of stability in cryptographic algorithms. Cryptographic keys are usually generated from cryptographic random number generators. At this time, good noise sources are needed to generate random numbers, and hardware random number generators such as TRNG are used because it is difficult for the low-spec device environment to obtain sufficient noise sources. In this paper we used the chip which is based on quantum characteristics where the decay of radioactive isotopes is unpredictable, and we presented a variety of methods (TRNG) obtaining an entropy source in the form of binary-bit series. In addition, we conducted the NIST SP 800-90B test for the entropy of output values generated by each TRNG to compare the amount of entropy with each method.

  • PDF

Stress analysis of high-temperature superconducting wire under electrical/magnetic/bending loads

  • Dongjin Seo;Yunjo Jung;Hong-Gun Kim;Hyung-Seop Shin;Young-Soon Kim
    • Progress in Superconductivity and Cryogenics
    • /
    • v.25 no.4
    • /
    • pp.19-23
    • /
    • 2023
  • The Second-generation high-temperature superconducting (HTS) Rare-Earth Barium Copper Oxide (REBCO) wire is a composite laminate having a multi-layer structure (8 or more layers). HTS wires will undergo multiple loads including the bending-tension loads during winding, high current density, and high magnetic fields. In particular, the wires are subjected to bending stress and magnetic field stress because HTS wires are wound around a circular bobbin when making a high-field magnetic. Each of the different laminated wires inevitably exhibits damage and fracture behavior of wire due to stress deformation, mismatches in thermal, physical, electrical, and magnetic properties. Therefore, when manufacturing high-field magnets and other applications, it is necessary to calculate the stress-strain experienced by high-temperature superconducting wire to present stable operating conditions in the product's use environment. In this study, the finite element model (FEM) was used to simulate the strain-stress characteristics of the HTS wire under high current density and magnetic field, and bending loads. In addition, the result of obtaining the neutral axis of the wire and the simulation result was compared with the theoretical calculation value and reviewed. As a result of the simulation using COMSOL Multiphysics, when a current of 100 A was applied to the wire, the current value showed the difference of 10-9. The stress received by the wire was 501.9 MPa, which showed a theoretically calculated value of 500 MPa and difference of 0.38% between simulation and theoretical method. In addition, the displacement resulted is 30.0012 ㎛, which is very similar to the theoretically calculated value of 30 ㎛. Later, the amount of bending stress by the circular mandrel was received for each layer and the difference with the theoretically obtained the neutral axis result was compared and reviewed. This result will be used as basic data for manufacturing high-field magnets because it can be expanded and analyzed even in the case of wire with magnetic flux pinning.

Analysis of Inquiry Unit of Science 10 in Terms of Nature of Science (과학의 본성의 측면에서 10학년 과학의 탐구 단원 분석)

  • Cho, Jung-Il
    • Journal of The Korean Association For Science Education
    • /
    • v.28 no.6
    • /
    • pp.685-695
    • /
    • 2008
  • An analysis on the Inquiry unit of Science 10 textbooks was conducted in terms of nature of science (NOS). The subject of the analysis was instructional objectives, activities and sentences in the unit of ten Science 10 textbooks. Contents of the instructional objectives could be grouped into nature of science, nature of scientists, scientific methods, and Science-Technology-Society. The concrete nature of scientific knowledge (SK) and constructing scientific theory or model, however, were not found in the objectives. The total number of activities in the Inquiry unit was 38. Seventeen out of them were presented without any supplemental or introductory materials, and 21 activities were provided with information followed by questions, discussions or investigations. For the most activities, any clear statements about NOS elements and desired/informed views of NOS were not made. The sentences of the Inquiry units were mixed up with constructivist and inductive views on NOS. The definition of science tended to be described based on the inductive view. And the generation of SK tended to be described as discovering regularities in natural phenomena rather than constructing theories. For science teachers who want to teach NOS effectively, stating clear learning objectives and elements of NOS and presenting reading materials with relevant views on nature of science were necessary.

Uncertainty Calculation Algorithm for the Estimation of the Radiochronometry of Nuclear Material (핵물질 연대측정을 위한 불확도 추정 알고리즘 연구)

  • JaeChan Park;TaeHoon Jeon;JungHo Song;MinSu Ju;JinYoung Chung;KiNam Kwon;WooChul Choi;JaeHak Cheong
    • Journal of Radiation Industry
    • /
    • v.17 no.4
    • /
    • pp.345-357
    • /
    • 2023
  • Nuclear forensics has been understood as a mendatory component in the international society for nuclear material control and non-proliferation verification. Radiochronometry of nuclear activities for nuclear forensics are decay series characteristics of nuclear materials and the Bateman equation to estimate when nuclear materials were purified and produced. Radiochronometry values have uncertainty of measurement due to the uncertainty factors in the estimation process. These uncertainties should be calculated using appropriate evaluation methods that are representative of the accuracy and reliability. The IAEA, US, and EU have been researched on radiochronometry and uncertainty of measurement, although the uncertainty calculation method using the Bateman equation is limited by the underestimation of the decay constant and the impossibility of estimating the age of more than one generation, so it is necessary to conduct uncertainty calculation research using computer simulation such as Monte Carlo method. This highlights the need for research using computational simulations, such as the Monte Carlo method, to overcome these limitations. In this study, we have analyzed mathematical models and the LHS (Latin Hypercube Sampling) methods to enhance the reliability of radiochronometry which is to develop an uncertainty algorithm for nuclear material radiochronometry using Bateman Equation. We analyzed the LHS method, which can obtain effective statistical results with a small number of samples, and applied it to algorithms that are Monte Carlo methods for uncertainty calculation by computer simulation. This was implemented through the MATLAB computational software. The uncertainty calculation model using mathematical models demonstrated characteristics based on the relationship between sensitivity coefficients and radiative equilibrium. Computational simulation random sampling showed characteristics dependent on random sampling methods, sampling iteration counts, and the probability distribution of uncertainty factors. For validation, we compared models from various international organizations, mathematical models, and the Monte Carlo method. The developed algorithm was found to perform calculations at an equivalent level of accuracy compared to overseas institutions and mathematical model-based methods. To enhance usability, future research and comparisons·validations need to incorporate more complex decay chains and non-homogeneous conditions. The results of this study can serve as foundational technology in the nuclear forensics field, providing tools for the identification of signature nuclides and aiding in the research, development, comparison, and validation of related technologies.

CINEMAPIC : Generative AI-based movie concept photo booth system (시네마픽 : 생성형 AI기반 영화 컨셉 포토부스 시스템)

  • Seokhyun Jeong;Seungkyu Leem;Jungjin Lee
    • Journal of the Korea Computer Graphics Society
    • /
    • v.30 no.3
    • /
    • pp.149-158
    • /
    • 2024
  • Photo booths have traditionally provided a fun and easy way to capture and print photos to cherish memories. These booths allow individuals to capture their desired poses and props, sharing memories with friends and family. To enable diverse expressions, generative AI-powered photo booths have emerged. However, existing AI photo booths face challenges such as difficulty in taking group photos, inability to accurately reflect user's poses, and the challenge of applying different concepts to individual subjects. To tackle these issues, we present CINEMAPIC, a photo booth system that allows users to freely choose poses, positions, and concepts for their photos. The system workflow includes three main steps: pre-processing, generation, and post-processing to apply individualized concepts. To produce high-quality group photos, the system generates a transparent image for each character and enhances the backdrop-composited image through a small number of denoising steps. The workflow is accelerated by applying an optimized diffusion model and GPU parallelization. The system was implemented as a prototype, and its effectiveness was validated through a user study and a large-scale pilot operation involving approximately 400 users. The results showed a significant preference for the proposed system over existing methods, confirming its potential for real-world photo booth applications. The proposed CINEMAPIC photo booth is expected to lead the way in a more creative and differentiated market, with potential for widespread application in various fields.

Temperature Prediction and Control of Cement Preheater Using Alternative Fuels (대체연료를 사용하는 시멘트 예열실 온도 예측 제어)

  • Baasan-Ochir Baljinnyam;Yerim Lee;Boseon Yoo;Jaesik Choi
    • Resources Recycling
    • /
    • v.33 no.4
    • /
    • pp.3-14
    • /
    • 2024
  • The preheating and calcination processes in cement manufacturing, which are crucial for producing the cement intermediate product clinker, require a substantial quantity of fossil fuels to generate high-temperature thermal energy. However, owing to the ever-increasing severity of environmental pollution, considerable efforts are being made to reduce carbon emissions from fossil fuels in the cement industry. Several preliminary studies have focused on increasing the usage of alternative fuels like refuse-derived fuel (RDF). Alternative fuels offer several advantages, such as reduced carbon emissions, mitigated generation of nitrogen oxides, and incineration in preheaters and kilns instead of landfilling. However, owing to the diverse compositions of alternative fuels, estimating their calorific value is challenging. This makes it difficult to regulate the preheater stability, thereby limiting the usage of alternative fuels. Therefore, in this study, a model based on deep neural networks is developed to accurately predict the preheater temperature and propose optimal fuel input quantities using explainable artificial intelligence. Utilizing the proposed model in actual preheating process sites resulted in a 5% reduction in fossil fuel usage, 5%p increase in the substitution rate with alternative fuels, and 35% reduction in preheater temperature fluctuations.

Enhancing Leadership Skills of Construction Students Through Conversational AI-Based Virtual Platform

  • Rahat HUSSAIN;Akeem PEDRO;Mehrtash SOLTANI;Si Van Tien TRAN;Syed Farhan Alam ZAIDI;Chansik PARK;Doyeop LEE
    • International conference on construction engineering and project management
    • /
    • 2024.07a
    • /
    • pp.1326-1327
    • /
    • 2024
  • The construction industry is renowned for its dynamic and intricate characteristics, which demand proficient leadership skills for successful project management. However, the existing training platforms within this sector often overlook the significance of soft skills in leadership development. These platforms primarily focus on safety, work processes, and technical modules, leaving a noticeable gap in preparing future leaders, especially students in the construction domain, for the complex challenges they will encounter in their professional careers. It is crucial to recognize that effective leadership in construction projects requires not only technical expertise but also the ability to communicate effectively, collaborate with diverse stakeholders, and navigate complex relationships. These soft skills are critical for managing teams, resolving conflicts, and driving successful project outcomes. In addition, the construction sector has been slow in adopting and harnessing the potential of advanced emerging technologies such as virtual reality, artificial intelligence, to enhance the soft skills of future leaders. Therefore, there is a need for a platform where students can practice complex situations and conversations in a safe and repeatable training environment. To address these challenges, this study proposes a pioneering approach by integrating conversational AI techniques using large language models (LLMs) within virtual worlds. Although LLMs like ChatGPT possess extensive knowledge across various domains, their responses may lack relevance in specific contexts. Prompt engineering techniques are utilized to ensure more accurate and effective responses, tailored to the specific requirements of the targeted users. This involves designing and refining the input prompts given to the language model to guide its response generation. By carefully crafting the prompts and providing context-specific instructions, the model can generate responses that are more relevant and aligned with the desired outcomes of the training program. The proposed system offers interactive engagement to students by simulating diverse construction site roles through conversational AI based agents. Students can face realistic challenges that test and enhance their soft skills in a practical context. They can engage in conversations with AI-based avatars representing different construction site roles, such as machine operators, laborers, and site managers. These avatars are equipped with AI capabilities to respond dynamically to user interactions, allowing students to practice their communication and negotiation skills in realistic scenarios. Additionally, the introduction of AI instructors can provide guidance, feedback, and coaching tailored to the individual needs of each student, enhancing the effectiveness of the training program. The AI instructors can provide immediate feedback and guidance, helping students improve their decision-making and problem-solving abilities. The proposed immersive learning environment is expected to significantly enhance leadership competencies of students, such as communication, decision-making and conflict resolution in the practical context. This study highlights the benefits of utilizing conversational AI in educational settings to prepare construction students for real-world leadership roles. By providing hands-on, practical experience in dealing with site-specific challenges, students can develop the necessary skills and confidence to excel in their future roles.

Altered Expression of Peroxiredoxin and Thioredoxin in Septic Animal Model (패혈증 동물 모델에서 Peroxiredoxin 및 Thioredoxin의 발현 변화)

  • Kim, Hyung-Jung;Chae, Ho-Zoon;Ahn, Chul-Min;Kim, Sung-Kyu;Lee, Won-Young
    • Tuberculosis and Respiratory Diseases
    • /
    • v.47 no.4
    • /
    • pp.451-459
    • /
    • 1999
  • Background : In sepsis, excessive generation of reactive oxygen species plays key roles in the pathogenesis of acute lung injury. The serum antioxidants such as catalase and MnSOD are elevated in sepsis and considered as predictors of acute respiratory distress syndrome(ARDS) and prognostic factors of sepsis. Peroxiredoxin(Prx) has recently been known as an unique and major intracellular antioxidant. In this study, we evaluated the expression of Prx I and Prx II in mouse monocyte-macrophage cells(RAW 267.7) after treatment of oxidative stress and endotoxin and measured the amount of Prx I, Prx II and thioredoxin(Trx) in peritoneal and bronchoalveolar lavage fluid of septic animal model. Methods : Using immunoblot analysis with specific antibodies against Prx I, Prx II and Trx, we evaluated the distribution of Prx I and Prx II in human neutrophil, alveolar macrophage and red blood cell. We evaluated the expression of Prx I and Prx II in mouse monocyte-macrophage cells after treatment of $5\;{\mu}M$ menadione and $1\;{\mu}g/ml$ lipopolysaccharide(LPS) and measured the amount of Prx I, Prx II and Trx in peritoneal lavage fluid of intraperitoneal septic animals(septic animal model induced with intraperitoneal 6 mg/Kg LPS injection) and those in bronchoalveolar lavage fluid of intraperitoneal septic animals and intravenous septic animals(septic animal model induced with intravenous 5 mg/Kg LPS injection) and compared with the severity of lung inflammation. Results : The distribution of Prx I and Prx II were so different among human neutrophil, alveolar macrophage and red blood cell. The expression of Prx I in mouse monocyte-macrophage cells was increased after treatment of $5\;{\mu}M$ menadione and $1\;{\mu}g/ml$ lipopolysaccharide but that of Prx II was not increased. The amount of Prx I, Prx II and Trx were increased in peritoneal lavage fluid of intraperitoneal septic animals but were not increased in bronchoalveolar lavage fluid of intraperitoneal and intravenous septic animals regardless of the severity of lung inflammation. Conclusion : As intracellular antioxidant, the expression of Prx I is increased in mouse monocyte-macrophage cells after treatment of oxidative stress and endotoxin. The amount of Prx I, Prx II and Trx are increased in local inflammatory site but not increased in injured lung of septic animal model.

  • PDF