• Korean Journal of Geomatics
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• v.1 no.1
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• pp.85-93
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• 2001

Geospatial database, which is the basis for Geo-Spatial Information Systems, is produced by conventional mapping methods. Recently, with increased demand for digital forms of the geospatial database, studies are carried out to automate its production. The automated mapping system is composed of the image acquisition subsystem, positioning subsystem, point referencing subsystem and the visualization subsystem. The image acquisition subsystem is the most important part of the overall production line because it is the starting point and will affect all subsequent processes. This paper presents a software analysis and design of the image acquisition subsystem. The design was carried out using the Unified Modeling Language which is a modeling method used extensively in the software engineering field.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.60-62
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• 2015

The BIM-based architectural design can be the optimal method to improve all sectors of construction industry and reduce environmental impact through digital technologies. The goals and effects of BIM needs in LH to be newly planned based on the experience of public sectors, which will ultimately contribute to maximization of effectiveness. Referring the excellent case in the UK, the current BIM standards according to maturity level 2 handle the contents related to modeling, collaborative data production, data management and assure BIM data have to be used from building construction to operation and maintenance of buildings. Therefore the strategy for the utilization of BIM for construction projects in LH consisted of three steps; first, the minimization of defects via BIM: second, strengthening the competitiveness of construction and asset management: third, upgrading the system of building production and maintenance control. After this trial, LH can accumulate know-how for building construction to be more costeffective and competitive.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• Proceedings of the Korean Society of Organic Agriculture Conference
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• 2001.10a
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• pp.192-206
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• 2001

A major challenge in the transition from conventional to organic production in a grain intensive region such as the Com Belt legion of the U.S.A. is how to profitably select and manage a crop relation. The opportunity cast of forgoing grain production for forage and green manure crops is significant. Many organic researchers and writers emphasize the need to bring an animal enterprise into the farming system for diversification and enhanced labor utilization. Livestock also add value to grain and forage crops to offset decreased grain production and can recapture nutrients used in crop production that can be recycled through manure. In grain intensive regions, organic farmers should consider swine production as a natural fit for the farming system. Swine are very efficient and adaptable animals that can add value to both grain and forage crops. While somewhat lacking, there is a reasonable body of literature on organic and sustainable swine production. However, there is relatively little specific information available to organic farmers to assist in the initial decision to enter organic swine production and to evaluate marketing alternatives. The primary focus of this paper is to give some background on organic animal production(emphasis on swine) in the Central United States and outline production and marketing decisions and considerations, relative to market trends, demographics and standards(U.S.). At the farm level, decisions must be made regarding resources, such as land, labor, financial and social capital, all relative to opportunities, all in the context of the standards and market forces beyond the farm. At the personal level the farmer must also make decisions about convictions regarding organic or environmentally friendly agriculture, willingness to change, impacts on lifestyle and family, and the transition to organic methods within the planning horizon of the farmer and the family business.

• Journal of Microbiology and Biotechnology
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• v.19 no.9
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• pp.972-981
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• 2009

In this paper, a fed-batch cultivation process in recombinant Escherichia coli BL21(DE3) bacteria, for the production of human soluble catechol-O-methyltransferase (hSCOMT), is presented. For the first time, a straightforward model is applied in a recombinant hSCOMT expression system and distinguishes an initial cell growth phase from a protein production phase upon induction. Specifically, the kinetic model predicts biomass, substrate, and product concentrations in the culture over time and was identified from a series of fed-batch experiments designed by testing several feed profiles. The main advantage of this model is that its parameters can be identified more reliably from distinct fed-batch strategies, such as glycerol pulses and exponential followed by constant substrate additions. Interestingly, with the limited amount of data available, the proposed model accomplishes satisfactorily the experimental results obtained for the three state variables, and no exhaustive process knowledge is required. The comparison of the measurement data obtained in a validation experiment with the model predictions showed the great extrapolation capability of the model presented, which could provide new complementary information for the COMT production system.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.194-200
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• 2020

Cities in Indonesia include diverse scattered industrial centers comprising industries that can sustain the existing economic pace. For industrial data collection, the city government still relies on census that consumes extensive time and money. The public are unfamiliar with industries owing to their lack of industry information; therefore, the market share is not optimal. In addition, the opportunity to procure investors for business development is limited. A Geographic Information System (GIS) is a computer system that can record, store, write, analyze, and display geographical data. Using the Rapid Application Development (RAD) method, GIS was developed on a website platform to provide information on industry profiles, types of production, investment values, industry maps, and industrial locations in each village and sub-district to a wider community. The RAD method was chosen compared to the waterfall method because it could accelerate website development process.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.711-719
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• 2021

EBS has been producing numerous educational contents with traditional virtual studio production systems since the early 2000s and applied AR video production system in October 2020, twenty-years after. Although the basic concept of synthesizing graphic elements and actual image in real time by tracking camera movement and lens information is similar to the previous one but the newly applied AR video production system contains some of advanced technologies that are improved over the previous ones. Marker tracking technology that enables camera movement free and position tracking has been applied that can track the location stably, and the operating software has been applied with Unreal Engine, one of the representative graphic engines used in computer game production, therefore the system's rendering burden has been reduced, enabling high-quality and real-time graphic effects. This system is installed on a crane camera that is mainly used in a crane shot at the live broadcasting studio and applied for live broadcasting programs for children and some of the videos such as program introductions and quiz events that used to be expressed in 2D graphics were converted to 3D AR videos which has been enhanced. This paper covers the effect of introduction and application of the AR video production system on EBS content production and the future development direction and possibility.

• Korean Journal of Geomatics
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• v.3 no.2
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• pp.107-114
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• 2004

The National Geographic Information Institute (NGII) in korea, through the National Geographic Information System (NGIS) Program, has prepared to generate and disseminate digital elevation data for Korea. This is a pilot research to propose a policy for production, maintenance, and supply of Korea Digital Elevation Data(KDED). Customer demands for accuracy and resolution of DEM was surveyed through a questionnaire. In order to investigate the quality, the technical efficiency and the production cost, a tentative DEM in a small test site was generated based on digital topographic maps (original paper map scale 1:5,000), analytical plotter, and LIDAR. The Accuracy standard for KDED was derived based on source data generation methods. As a result of this research, a uniformly spaced grid model was recommended for KDED. Its preferable grid space is 5m in urban areas and its vicinity, and 10m in field and mountainous area. LIDAR has been valuated as a proper KDED generation method fulfilling customers' demands for the accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.329-331
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• 2018

In this paper, we propose a monitoring system that starts with the supply of raw materials for threading, is processed into a lathe machine, and checks for defects of the product are automatically performed by the robot with Smart Factory technology through assembly and disassembly. Completion check according to the production instruction quantity and production instruction is made by checking the production status according to whether or not the raw material is worn by the displacement sensor, and checking the pitch and the contour of the processed female and male to determine OK and NG. The robotic system acts as a relay for loading and unloading of raw materials, pallet transfer, and overall process, and it acts as an intermediary for organically driving. The location information of the threaded products is collected by using the non-contact wireless tag and the energy saving system Production efficiency and utilization rate were checked. The environmental sensor collects the air-conditioning environment data (temperature, humidity), measures the temperature and humidity accurately, and checks the quality of product processing. It monitors and monitors the driving hazard level environment (overheating, humidity) of the product. Controls for CNC and robot module PLC as a heterogeneous system.