• Environmental Engineering Research
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• v.14 no.4
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• pp.200-210
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• 2009

The modern era of water quality modeling in the United States began in the 1960s. Pushed by advances in computer technology as well as environmental sciences, water quality modeling evolved through five broad periods: (1) initial model development with mainframe computers (1960s - mid 1970s), (2) model refinement and generalization with minicomputers (mid 1970s - mid 1980s), (3) model standardization and support with microcomputers (mid 1980s - mid 1990s), (4) better model access and performance with faster desktop computers running Windows and local area networks linked to the Internet (mid 1990s - early 2000s), and (5) model integration and widespread use of the Internet (early 2000s - present). Improved computer technology continues to drive improvements in water quality models, including more detailed environmental analysis (spatially and temporally), better user interfaces and GIS software, more accessibility to environmental data from on-line repositories, and more robust modeling frameworks linking hydrodynamics, water quality, watershed and atmospheric models. Driven by regulatory needs and advancing technology, water quality modeling will continue to improve to better address more complicated water bodies and pollutant types, and more complicated management questions. This manuscript describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions.

• Journal of the Korean Society of Systems Engineering
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• v.7 no.1
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• pp.31-41
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• 2011

The purpose of this paper is to provide an abstracted meta-model for executing Capabilities Portfolio Management (CPM) effectively based on DoDAF2.0. The purpose of developing an architecture is for beneficial use of it. A good set of architectural artifacts facilitates the manipulation and use of them in meeting its usage objectives well. Systems engineering methodologies evolve to accommodate or to deal with enterprise or SoS/FoS level problems. And DoD's Capabilities Portfolio Management (CPM) is a good example which demonstrates enterprise or SoS level problems. However, the complexity of the architecture framework makes it difficult to develop and use the architecture models and their associated artifacts. DoDAF states that it was established to guide the development of architectures and to satisfy the demands of a structured, repeatable method for evaluating alternatives which add value to decisions and management practices. One of the objectives of DoDAF2.0 is to define concepts and models usable in CPM which is one of DoD's six core processes. However, DoDAF and various guidelines state requirements for CPM rather than how to. This paper provides methodology for CPM which includes process and tailored meta-models based on DoDAF Meta Model (DM2).

• Journal of Microbiology and Biotechnology
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• v.25 no.10
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• pp.1583-1588
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• 2015

The large intestine is a home for trillions of microbiota, which confer many benefits on the host, including production of vitamins, absorption of nutrients, pathogen displacement, and development of the immune system. For several decades, germ-free animals have been used to study the interaction between the host and its microbiota. This minireview describes the technical aspects for establishing and maintaining germ-free animals and highlights the advantages and disadvantages for germ-free animals as experimental models.

• Korean Management Science Review
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• v.19 no.2
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• pp.91-124
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• 2002

The use of network planning models and tools is essential for effective KII (Korea Information Infrastructure) planning and analysis in that it will significantly reduce the risk and uncertainty embeded in the development and the provision of future broadband services. The purpose of this study is to develop a theoretical framework and a computer tool for modeling the various aspects of the KII topology and architecture and evaluating the techno-economic feasibility of the KII implementation strategy.

• Journal of Korean Society of Rural Planning
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• v.20 no.1
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• pp.91-104
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• 2014

Self-sufficiency rate of food in South Korea is almost at the lowest level among OECD countries, and the decrease tend of farmland is expected to be continued. In this situation, Korea experienced a rapid change in the international price of grain due to changes in amount of grain production and food weaponization. It also started to reinforce the appropriateness of maintenance of farmland above certain standard. As one of policy means for this situation, this study selected "the use of idle farmland" as a subject, and started to consider the way to suggest the policy projects using idle farmland. The result of this study is summarized as follows. Firstly, this study defined the meaning of idle farmland, and set up the scope of idle farmland needed to this study. Secondly, this study analyzed the domestic major policy projects with prevention function of idle farmland as well as the policy projects related to idle farmland. It also investigated "recycling measures of idle farmland" that is recently promoted in Japan, and deducted the direction for developing a new model. Lastly, It suggested 9 policy project models that are finally able to use idle farmland. Suggested models are designed to access from various directions. This study suggested contents, entity, target and characteristics of projects in order to set up proper directions in promoting policy projects using idle farmland.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.163-172
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• 2004

In the software development project applying object-oriented development methodology, the research on the UCP(Use Case Point) as a method to estimate development effort is being carried on. The existing research proposes the linear model calculating the development effort that multiplies an invariant on AUCP(Adjusted Use Case Point) which applied technical and environmental factors. However, the statistical model that estimates the development effort using AUCP and UUCP(Unadjusted Use Case Point) is not being studied. The irrelevant relationship of the linear regression model, whose development period is increasing tremendously as the software size increases, is confirmed. Moreover, during the UCP calculating process, there can be errors in FP by applying the TCF(Technical Complexity Factor) and EF(Environmental Factor). This paper presents a non-linear regression model, that does not consider the TCF and EF, and that estimate the development effort from UUCP directly by utilizing the exponential function. An exponential function is selected among the linear, logarithm, polynomial, power, and exponential model via statistical evaluations of the models mentioned above.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.151-158
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• 2002

Automotive engineers involved in a new car project use various CAD systems that are chosen based on work requirements. For example, engineers in Hyundai Motors are using Pro/Designer and Alias fur the style design, but they use CATIA to design parts and assemblies, ANSYS for FEM analysis, and Pro/Engineer to design engines. Because they use different CAD systems, they have difficulties in collaborative design. Data, which contains errors, is transferred between CAD systems. It is difficult to find out such errors in a large CAD model. An evaluation method for CAD models has been developed in this study. This diagnosis tool analyses a STEP or an IGES file generated from a CAD system, and produces a quantitative error report. The tool has been tested with actual data sets. This paper proposes an algorithm that produces mathematical error values of entities of IGES models that have geometrical data, and entities of STEP models that have topological data, and inspects every part off model. To develop this system, we have used the OpenCASCADE kernel, which is an open source kernel developed by Matra Datavision of France.

• Journal of The Korean Association of Information Education
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• v.7 no.3
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• pp.331-339
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• 2003

This study is the content about the development of ICT(Information and Communication Technology) teaching-learning model to support the korean language learning. Firstly, we proposed 3 types on developing models for ICT teaching-learning in korean language learning, we developed 4 ICT teaching-learning models based on analysing the curriculum of korean language course and studying the preceding works. Moreover we offered the strategies for applying ICT teaching-learning models with korean language learning. The developed 4 ICT teaching-learning models in this study are expected that ICT will use to design ICT teaching-learning model in another courses and teachers take advantage of the 4 models in korean lesson effectively.

• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.54-67
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• 2021

This paper presents the ISRI (Information Systems Research Indicators) Web tool, publicly and freely available at isri.sciencesphere.org. Targeting Information Systems (IS) researchers, it compiles and organizes IS adoption and use theories/models, constructs, and indicators (measuring variables) available in the scientific literature. Aiming to support the IS theory development process, the purpose of ISRI is to gather and systematize information on research indicators to help researchers and practitioners' work. The tool currently covers eleven theories/models: DeLone and McLean's IS Success Model (D&M ISS); Diffusion of Innovations Theory (DOI); Motivational Model (MM); Social Cognitive Theory (SCT); Task-Technology Fit (TTF); Technology Acceptance Model (TAM); Technology-Organization-Environment Framework (TOE); Theory of Planned Behavior (TPB); Decomposed Theory of Planned Behavior (DTPB); Theory of Reasoned Action (TRA); and Unified Theory of Acceptance and Use of Technology (UTAUT). It also includes currently over 400 constructs, nearly 2,500 indicators, and about 60 application contexts related to the models. For the creation of the tool's database, nearly 580 references were used.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.29-34
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• 2023

The flow from developing a machine learning model to deploying it in a production environment suffers challenges. Efficient and reliable deployment is critical for realizing the true value of machine learning models. Bridging this gap between development and publication has become a pivotal concern in the machine learning community. FastAPI, a modern and fast web framework for building APIs with Python, has gained substantial popularity for its speed, ease of use, and asynchronous capabilities. This paper focused on leveraging FastAPI for deploying machine learning models, addressing the potentials associated with integration, scalability, and performance in a production setting. In this work, we explored the seamless integration of machine learning models into FastAPI applications, enabling real-time predictions and showing a possibility of scaling up for a more diverse range of use cases. We discussed the intricacies of integrating popular machine learning frameworks with FastAPI, ensuring smooth interactions between data processing, model inference, and API responses. This study focused on elucidating the integration of machine learning models into production environments using FastAPI, exploring its capabilities, features, and best practices. We delved into the potential of FastAPI in providing a robust and efficient solution for deploying machine learning systems, handling real-time predictions, managing input/output data, and ensuring optimal performance and reliability.