• Journal of Digital Convergence
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• v.16 no.10
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• pp.11-26
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• 2018

A strategic technology selection for GHG reduction is crucial to secure mitigation means. Especially, a technology selection for a public sector is encouraged to consider integrated perspectives due to various stakeholders under public goals. However, previous studies have mainly focused on technological and economic factors, moreover, consistent criteria have not been applied. This study develops indicators for the GHG reduction technology selection from the public perspective based on delphi method with 22 experts. The result provides valid indicators of technology selection for GHG reduction considering an aspect of technology, economics, environment, policy, society. Specifically, 16 indicators from 5 categories on commercialized technology, and 18 indicators from 5 categories on new technology. We expect that those indicators are useful for a decision-making tool of technology selection. Moreover, provide the basis for the study of judgement criteria to evaluate GHG reduction technology.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.235-235
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• 2022

Genome selection is a promising tool for plant and animal breeding, which uses genome-wide molecular marker data to capture large and small effect quantitative trait loci and predict the genetic value of selection candidates. Genomic selection has been shown previously to have higher prediction accuracies than conventional marker-assisted selection (MAS) for quantitative traits. In this study, the prediction accuracy of 10 agricultural traits in the wheat core group with 567 points was compared. We used a cross-validation approach to train and validate prediction accuracy to evaluate the effects of training population size and training model.As for the prediction accuracy according to the model, the prediction accuracy of 0.4 or more was evaluated except for the SVN model among the 6 models (GBLUP, LASSO, BayseA, RKHS, SVN, RF) used in most all traits. For traits such as days to heading and days to maturity, the prediction accuracy was very high, over 0.8. As for the prediction accuracy according to the training group, the prediction accuracy increased as the number of training groups increased in all traits. It was confirmed that the prediction accuracy was different in the training population according to the genetic composition regardless of the number. All training models were verified through 5-fold cross-validation. To verify the prediction ability of the training population of the wheat core collection, we compared the actual phenotype and genomic estimated breeding value using 35 breeding population. In fact, out of 10 individuals with the fastest days to heading, 5 individuals were selected through genomic selection, and 6 individuals were selected through genomic selection out of the 10 individuals with the slowest days to heading. Therefore, we confirmed the possibility of selecting individuals according to traits with only the genotype for a shorter period of time through genomic selection.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.596-602
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• 2010

In this study, a fmite element model was developed for analysis of feeding a structure in open loop control The finite element analysis (FEA) can simulate dynamic behavior of the structure of a machine tool rapidly traveling with a screw feeding driving system. The feeding mechanism was implemented with screw element of the FEA tool used in this study. The procedure was developed for the dynamic transient FEA. First, motion parameters such as jerk and velocity were introduced for the structure to be fed in open loop control When its traveling distance was determined, set-points for the distance were generated based on the motion parameters. The set-points were applied to the FE model constructed for the traveling structure. The FEA was executed and evaluated. In this study, the FEA procedure was applied to the column of a machine tool and the dynamic behavior of the column was evaluated. The FEA helps in evaluation of the motion characteristics of a structure. The convergence time of the structure vibration posterior to feeding termination can be estimated and the stiffness of the flexible structure is also evaluated against jerk, and acceleration. It provides the feeding force which is helpful in selection of the feeding motor.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.1038-1043
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• 1997

To adapt the neural network proess for the purpose of determination of optimal utting onditions (optimal cutting speed and feed rate), some selection strategies for the machining factors are necessary, which is considered planning cutting process. In this case, factors that have both nonlinearity and strong relationship must be selected. Although tool grade and chemical properties of workpiece material have strong effect to cutting speed, it's not easy to find a analytic relation between them. In this paper, a mathematical method for determining the optimal amount of cutting (depth of cut, feed rate) is presented by tool goemetry and heat generation during cutting process. And various tool grade and workpiece material groups ase classified based on its chemical properties. Thier chemical composition and hardness are used as input pattern for neural network learnig. The result of learning shows the relationship between tool grade and workpiece material and it is proved that it can be used as a sub-system for automatic process planning system.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.5
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• pp.447-454
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• 2015

Design and application of hardware-in-the-loop simulation (HILS) for design of CNC-controlled machine tool feed drives is discussed. The CNC machine tool is a complex mechatronics system where the complexity results from the software-based controller composed of a variety of functionalities and advanced control algorithms. Therefore, using a real CNC controller in the control simulation has merits considering the efforts and accuracy of the simulation modeling. In this paper challenges in HILS for a CNC controlled feed drive, such as minimization of time delay and transmission error that are caused by discretization of the feed drive model, is elaborated. Using an experimental HILS setup of a machine tool feed drive applications in controller gain selection and CNC diagnostics are presented.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.4
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• pp.47-53
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• 2007

A bearing is one of core parts in automobile. Rubber seal of the bearing is important to improve performance of bearing, formed by hot-press die of rubber seal for the intricate shape. In this study, formed tools are used to machine die of bearing rubber seal and the machining operation is classified into the several process of high precision. Design of experiments is used to optimize selection of the formed tools for the efficient machining of the hot-press die. The cutting force, tool wear and tool life are determined to characteristics. And, the clearance angle, the rake angle and the length cutting edge are considered as the major factors. Experiments are repeated to use one-way factorial design, and tool life is predicted by regression model.

• Structural Engineering and Mechanics
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• v.73 no.5
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• pp.501-513
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• 2020

In the present work, the optimization of machining parameters to achieve the desired technological parameters such as surface roughness, tool radial vibration and material removal rate have been carried out using response surface methodology (RSM). The hard turning of EN19 alloy steel with coated carbide (GC3015) cutting tools was studied. The main problem faced in manufacturer of hard and high precision components is the selection of optimum combination of cutting parameters for achieving required quality of surface finish with maximum production rate. This problem can be solved by development of mathematical model and execution of experiments by RSM. A face centred central composite design (FCCD), which comes under the RSM approach, with cutting parameters (cutting speed, feed rate and depth of cut) was used for statistical analysis. A second-order regression model were developed to correlate the cutting parameters with surface roughness, tool vibration and material removal rate. Consequently, numerical and graphical optimization were performed to obtain the most appropriate cutting parameters to produce the lowest surface roughness with minimal tool vibration and maximum material removal rate using desirability function approach. Finally, confirmation experiments were performed to verify the pertinence of the developed mathematical models.

• Journal of Korean society of Dental Hygiene
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• v.19 no.1
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• pp.1-17
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• 2019

This study investigates the overall research trends and related factors affecting the turnover of dental hygienists in Korea during the past 10 years (2007-2017) and analyzed the differences in the results of the research according to the main measurement tools. The literature review focused on turnover of dental hygienists in Korea. Inclusion criteria of selected studies were as follows: the domestic and foreign academic journals and theses published for the past 10 years (between 2007-2017). The most commonly used tool for measuring dental hygienist turnover was a tool developed by Lawler. The most used significant general characteristics is age and income, Job satisfaction (57.1%) and organizational commitment (40.0%) were the most frequently used predictors of turnover. The variables used for each turnover measurement tool were different, showing that the study results was different from according to the variables and significance level. Although there have been many studies related to the turnover of dental hygienists, different results have been shown depending on the measurement tools. When conducting research related to dental hygienist turnover, specific and clear presentation of measurement tool selection or development is needed.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.222-228
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• 2003

A tool which can be used for the analysis of a robot soccer game is presented. The tool enables automatic filtering and selection of game sequences which are suitable for the analysis of the game. Fuzzy logic is used since the data gathered by a camera is highly noisy. The data used in the paper was recorded during the game Germany - Slovenia in Hagen, on November 11, 2001. The dynamic parameters of our robots are estimated using the least squares technique. Meandering parameters are estimated and an attempt is made to identify the strategy of the opposing team with the method of introspection.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.83-88
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• 2001

In order to suggest the proper optimal conditions of the CNC milling machining for the Thin-wall surface, some experiments were carried out. The process was applied in the aerospace industry for the machining of light alloys, notably aluminium. In recent year, however, the mold and die industry has begun to use the technology for the production of components, including those manufactured from hardened tool steels. And the end mill is an important tool in the milling process. A typical example for the end mill is the milling of pocket and slot in which a lot of material is removed from the workpiece. Therefore the proper selection of cutting parameter for end milling is one of the important factors affecting the cutting cost. In this paper, we choose the optimal parameters(cutting forces) to cut thin-walled Al part by experiment.