• Atmosphere
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• v.23 no.2
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• pp.237-243
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• 2013

A set of scripts for GrADS (Grid Analysis and Display System) and R was implemented to produce agricultural climate information using the future climate scenarios based on the Representative Concentration Pathways. The GrADS script was used to calculate agricultural climate indices including growing degree days and cooling degree days. The script generated agricultural climate maps of these indices, which are compatible with common Geographic Information System (GIS) applications. To perform a statistical analysis using the agricultural climate maps, a script for R, which is open source statistical software, was used. Because a large number of spatial climate data were produced, parallel processing packages such as SNOW, doSNOW, and foreach were used to perform a simple statistical analysis in the R script. The parallel script of R had speedup on workstations with multi-CPU cores.

• Applied Microscopy
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• v.45 no.2
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• pp.101-105
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• 2015

Numerous digital image analysis techniques have been developed with regard to transmission electron microscopy (TEM) with the help of programming. DigitalMicrograph (DM, Gatan Inc., USA), which is installed on most TEMs as operational software, includes a script language to develop customized software for image analysis. Based on the DM script language, this work provides a script source listing for quantitative strain measurements based on a geometric phase analysis.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.243-251
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• 2018

The gridded simulation of crop growth, which would be useful for shareholders and policy makers, often requires specialized computation tasks for preparation of weather input data and operation of a given crop model. Here we developed an automated system to allow for crop growth simulation over a region using the DSSAT (Decision Support System for Agrotechnology Transfer) model. The system consists of modules implemented using R and shell script languages. One of the modules has a functionality to create weather input files in a plain text format for each cell. Another module written in R script was developed for GIS data processing and parallel computing. The other module that launches the crop model automatically was implemented using the shell script language. As a case study, the automated system was used to determine the maximum soybean yield for a given set of management options in Illinois state in the US. The AgMERRA dataset, which is reanalysis data for agricultural models, was used to prepare weather input files during 1981 - 2005. It took 7.38 hours to create 1,859 weather input files for one year of soybean growth simulation in Illinois using a single CPU core. In contrast, the processing time decreased considerably, e.g., 35 minutes, when 16 CPU cores were used. The automated system created a map of the maturity group and the planting date that resulted in the maximum yield in a raster data format. Our results indicated that the automated system for the DSSAT model would help spatial assessments of crop yield at a regional scale.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.108-110
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• 2006

계량기의 시장이 독점 시장에서 자유 시장으로 천이 되면서 시장은 계량기의 상호운용능력과 계량기의 지능, 관리능력 그리고 보안등의 부가적인 기능들을 요구 하게 되었다. 이러한 시장의 요구에 맞추어 DLMS 프로토콜을 표준으로 하고 COSEM 오브젝트 모델링 기법을 사용하는 계량기 표준인 IEC 62056이 제정되었다. 본 논문에서는 IEC 62056에서 정의한 프로토콜 및 서비스에 적합한 DLMS/COSEM 계량기의 S/W 아키텍처 및 그 설계 방법을 제안한다. 계량기 S/W는 크게 MCS와 MOM으로 구성되며, MCS는 계량기의 모델링 스크립트로 COSEM 오브젝트와 계량기의 구체적인 기능을 명시하고, MOM은 MCS를 읽어 계량기를 구동 시키는 모듈로 MCS에서 선언된 기능 및 동작을 해석하여 계량기를 전기, 가스, 수도 등의 기능을 갖는 계량기로 동작시키는 역할을 한다.

• Computational Structural Engineering
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• v.20 no.2 s.76
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• pp.44-54
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• 2007

• Journal of Powder Materials
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• v.24 no.4
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• pp.285-291
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• 2017

We propose a custom analysis technique for the dark field (DF) image based on transmission electron microscopy (TEM). The custom analysis technique is developed based on the $DigitalMicrograph^{(R)}$ (DM) script language embedded in the Gatan digital microscopy software, which is used as the operational software for most TEM instruments. The developed software automatically scans an electron beam across a TEM sample and records a series of electron diffraction patterns. The recorded electron diffraction patterns provide DF and ADF images based on digital image processing. An experimental electron diffraction pattern is recorded from a IrMn polycrystal consisting of fine nanograins in order to test the proposed software. We demonstrate that the developed image processing technique well resolves nanograins of ~ 5 nm in diameter.

• Genomics & Informatics
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• v.16 no.4
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• pp.37.1-37.3
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• 2018

Gene-gene interaction is a key factor for explaining missing heritability. Many methods have been proposed to identify gene-gene interactions. Multifactor dimensionality reduction (MDR) is a well-known method for the detection of gene-gene interactions by reduction from genotypes of single-nucleotide polymorphism combinations to a binary variable with a value of high risk or low risk. This method has been widely expanded to own a specific objective. Among those expansions, fuzzy-MDR uses the fuzzy set theory for the membership of high risk or low risk and increases the detection rates of gene-gene interactions. Fuzzy-MDR is expanded by a maximum likelihood estimator as a new membership function in empirical fuzzy MDR (EFMDR). However, EFMDR is relatively slow, because it is implemented by R script language. Therefore, in this study, we implemented EFMDR using RCPP ($c^{{+}{+}}$ package) for faster executions. Our implementation for faster EFMDR, called EMMDR-Fast, is about 800 times faster than EFMDR written by R script only.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.45 no.3
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• pp.277-285
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• 2019

In this study, effective cosmetic raw material weighing and bulk manufacturing management system were constructed by using bar code or quick response code (QR code) and database. Raw material labels and weighing labels for bulk manufacturing were published in web environment using the information entered in the database using ScriptX, a print component of Medi&Co. By checking the weighing and manufacturing process by using scanner, tablet and PC, it was possible to remarkably improve the product error caused by erroneous amount or misapplication which is the most cause of error in the production of cosmetic bulk. In conclusion, applying a database that utilizes bar code and QR code to cosmetics manufacturing can reduce the various problems in the process, thereby improving quality control and productivity of cosmetics.

• Journal of Korea Foundry Society
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• v.18 no.5
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• pp.431-438
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• 1998

Microstructure of A356 aluminum alloys cast in the permanent mold was investigated by optical microscope and image analyzer, with particular respect to the shape and size distribution of iron intermetallics known as ${\beta}-phase$ ($Al_5FeSi$). Morphologies of the ${\beta}-phase$ was found to change gradually with the Be:Fe ratio like these. In Be-free alloys, ${\beta}-phase$ with needlelike morphology was well developed, but script phase was appeared when the Be:Fe ratio is above 0.2:1. With the Be:Fe ratios of 0.4:1-1:1, script phase as well as Be-rich phase was also observed. In case of higher Be addition, above 1:1, Be-rich phase was observed on all regions of the specimens, and increasing of the Be:Fe ratios gradually make the Be-rich phase coarse. It was also observed that the ${\beta}-phase$ with needlelike morphology was coarsened with increase of the Fe content in Be-free alloys. However, in Be-added alloys, length and number of these ${\beta}-phases$ were considerably decreased with the increased Be:Fe ratio. Beryllium addition improved tensile properties and impact toughness of the A356 aluminium alloy, due to the formation of a script phase or a Be-rich phase instead of a needlelike ${\beta}-phase$. The DSC tests indicated that the presence of Be could increase the amount of Mg which is available for $Mg_2Si$ precipitate hardening, and enhance the precipitation kinetics by lowering the ternary eutectic temperature.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.33-40
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• 2020

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman's framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.