• Geomechanics and Engineering
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• v.22 no.1
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• pp.81-95
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• 2020

Measurement of the unconfined compressive strength (UCS) of the rock is critical to assess the quality of the rock mass ahead of a tunnel face. In this study, extensive field studies have been conducted along 3,885 m of the new Nagasaki tunnel in Japan. To predict UCS, a hybrid model of artificial neural network (ANN) based on genetic algorithm (GA) optimization was developed. A total of 1350 datasets, including six parameters of the Measurement-While- Drilling data and the UCS were considered as input and output parameters respectively. The multiple linear regression (MLR) and the ANN were employed to develop contrast models. The results reveal that the developed GA-ANN hybrid model can predict UCS with higher performance than the ANN and MLR models. This study is of great significance for accurately and effectively evaluating the quality of rock masses in tunnel engineering.

• Journal of Biosystems Engineering
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• v.29 no.4
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• pp.323-328
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• 2004

A surface plasmon resonance (SPR) sensing system, which belonged to a family of thin film refractometry-based sensors, was fabricated to measure the alcohol contents in alcoholic beverages. In this study, a SPR owe was obtained by a photodiode array with 128 pixels and transformed into a refractive index which was calculated by means of the first moment of values below a baseline of 0.85. When the sensing system was applied to Soju, Cheonju, Igwaduju and Tacju highly linear relationships between the refractive index by SPR and the contents of alcohol were obtained. That is, the coefficients of determination in their linear models were 0.992, 0.933, 0.918 and 0.954, respectively. Meanwhile, the effect of sample preparations on the accuracy of measurement was analyzed. As for Soju and Tacju, the best calibration equations were obtained when no sample preparation was applied. The best calibration models for measurement of Cheonju and Igwaduju were obtained through the samples filtered by $C_{18}$ disks.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1043-1053
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• 2004

The performance of a component can significantly influence the overall performance of the system being developed in the component based software development. Existing performance measurement tools for components are often built specific to the component model or middleware. One disadvantage of this approach is that when the system is moved to a new platform during the life-cycle of the system, the measurement tools also need to be adapted. A similar problem is observed when components built for different platforms are integrated with a new integration technology like Web Services. This paper presents a new model for measuring component performances, which is independent of particular component models or middleware. This method presents a interoperability for each performance data by model transformation process from middleware independent performance measuring models to middleware dependent performance measuring models. Our model allows objective performance data to be obtained that can be used to compare performances of components based on different component models or middleware platforms.

• Smart Media Journal
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• v.13 no.2
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• pp.44-51
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• 2024

The construction of a stress measurement detaset plays a curcial role in various modern applications. In particular, for the efficient training of artificial intelligence models for stress measurement, it is essential to compare various biases and construct a quality-controlled dataset. In this paper, we propose the construction of a stress measurement dataset with quality management through the comparison of various biases. To achieve this, we introduce strss definitions and measurement tools, the process of building an artificial intelligence stress dataset, strategies to overcome biases for quality improvement, and considerations for stress data collection. Specifically, to manage dataset quality, we discuss various biases such as selection bias, measurement bias, causal bias, confirmation bias, and artificial intelligence bias that may arise during stress data collection. Through this paper, we aim to systematically understand considerations for stress data collection and various biases that may occur during the construction of a stress dataset, contributing to the construction of a dataset with guaranteed quality by overcoming these biases.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.557-563
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• 2009

The research develops measurement processes for estimating and evaluating the gauge R&R(Reproducibility & Repeatability) using ANOVA(Analysis of Variance) of experimental design tools. The ten-step processes developed include experimental goal setting, the selection of characteristics(factors, levels), data model, ANOVA, EMS(Expected Mean Square), estimation of gauge precisions, and evaluation indexes. The three-factor combined measurement models are presented to show the processes developed in this paper.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.68-73
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• 2009

One of the traditional optical methods to monitor a tool is a CCD sensor-based vision system which captures an aspect of the tool in real time. In the case using the CCD sensor, specific lens-modules are necessary to monitor the tool with higher resolution than its pixel size, and a microprocessor is required to attain desired data from captured images. Thus theses additional devices make the entire measurement system complex. Another method is to use a pair of an optical source and a detector per measuring axis. Since the method is based on the intensity modulation, the structure of the measurement system is simper than the CCD sensor-based vision system. However, in the case measuring the three dimensional position of the tool, it is difficult to apply to micro machine-tools because there may not be space to integrate three pairs of an optical source and a detector. In this paper, in order to develop a tool-origin measurement system which is employed in micro machine-tools, the improved method to measure a tool origin in x, y and z axes is introduced. The method is based on the intensity modulation and employs one pair of an optical source radiating divergent beams and a quadrant photodiode to detect a three dimensional position of the tool. This paper presents the measurement models of the proposed tool-origin sensor. The models were verified experimentally The verification results show that the proposed method is possible and the induced models are available for design.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.518-523
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• 2008

In this study, we analyzed applicability of object database, designed the concept model based on object-oriented idea for measurement data management, and applied the design model to object database. The concept model composes three sub models Infrastructure managing information model, Infrastructure measurement data model, and Measurement unit model. The process to expand measurement data of new type was executed easily without changing database schema in object database. The process to expand measurement data of new type was executed easily without changing database schema in object database. Therefore, applicability of new technology to infrastructures for building a safety management network of road bridges could be increased with object database system.

• Journal of Environmental Impact Assessment
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• v.14 no.6
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• pp.427-441
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• 2005

In order to choose proper dispersion model and emission factors suitable in Korea in evaluating the effect of pollutants emitted by the vehicles in highway on nearby area, various road dispersion models and vehicle emission factors were reviewed. With theoretical inter-comparisons of the exiting models for line source, CALINE 3 and CALINE 4 models which were suggested by US EPA were selected as the road dispersion models for further evaluation with the measurement. The emission factors suggested by Korean Ministry of Environment was turned out to be appropriate since the classification of vehicle kinds was simple and easy to apply in Korea. The comparisons of predicted concentrations by CALINE 3 and 4 models with the measurements in flat, fill and bridge road types showed that CO and PM-10 were in good agreements with experiments and the differences between CALINE 3 and 4 models are negligible. The model concentrations of $NO_2$ by CALINE 4 were also in good agreement with the measurement but those by CALINE 3 were over-predicted. The discrepancies in CALINE 3 model were due to rapid decay reaction of $NO_2$ near the highway, which was not included in CALINE 3 model. For the road type with one & two side cutting grounds, the similar patterns as the flat & fill road type for CO, PM10, & $NO_2$ were observed but the number of data for comparison in these cases were not enough to draw the conclusion. These results lead to the conclusion that CALINE4 model is proper in road environmental impact assessment near the highway in flat, fill and bridge road types.

• Journal of the Korea Fashion and Costume Design Association
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• v.20 no.4
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• pp.31-40
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• 2018

The purpose of this study is to identify the body type characteristics of fashion models by comparing body dimensions and body types of fashion models with ordinary women in their 20s in Korea. To that end, the study selected 71 people, with 28 being female university students in the Seoul area and 43 professional fashion models. One hundred and fifty-seven ordinary woman were selected who ranged from 20 to 29 years old, and 588 women from the 7th Size Korea fit for research purposes. Body measurement items were selected for the direct measurement data for Size Korea, which included 20 items of body size and 10 items of calculation needed for clothing production. The results of the study were as follows. According to the analysis of fashion models and ordinary woman in their 20s, their body size showed significant differences in 25 out of 30 items. The five items that do not show significant differences are bust point-bust point, waist back length, front interscye length, hip circumference-bust circumference, and neck point to bust point to waistline-waist front length. If you integrate the results, the fashion model is much taller than the ordinary woman, has a longer lower body, and has an 8.05 head figure. Also, the fashion model found itself to be the ideal type that ordinary women prefer because of the slimmer waist and bent shape, which is more than that measured in normal women.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.55-63
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• 1999

Past studies on economic control charts for controlling process means assumed that the measures of a quality characteristic do not have measurement error. In practice, however, this assumption is frequently violated. In this paper, the economic design models of three control charts(Xbar control chart, Xbar control chart with warning limits, and CUSUM control chart) for controlling process means are developed on the assumption that the measures can have measurement error. The effects of measurement error on the process control cost and design parameters of three economic control charts are examined. According to the experiments done in this study, when measurement error exists, the economic CUSUM control chart has lower process control cost in comparison with two other control charts. When measurement error becomes larger, both the sample size and the sampling interval increase while the control limits decrease.