• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.1-11
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• 2018

Multivariate process control has become important in various applied fields. For instance, there are many situations in which the simultaneous monitoring of multivariate quality characteristics is necessary for the manufacturing industry. Despite its importance, its practical usage is not as convenient because it is difficult to identify the source of the out-of-control signal in a multivariate control chart. In this paper, we will introduce how to detect the source of the out-of-control by using confidence intervals for new observations, and will discuss the identification and interpretation of the out-of-control variable through simulation studies.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1071-1071
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• 2001

Near-infrared spectroscopy (NIRS) is potentially a powerful and revolutionary technology for environmental analysis. It is supported by a large body of scientific and experiential knowledge. The instrumentation is well-developed, with easy-to-use, highly dependable instruments, but at the same time it is still developing, particularly with the production of more portable and rapid instruments, and more powerful software. NIRS is used globally in numerous industries for commodity analysis. Yet NIRS is largely unknown in the field of environmental chemistry and monitoring, and is not even routinely used in soil analysis, where the research literature on NIRS extends over four decades. Part of the explanation for the poor visibility of NIRS is the fact that NIRS is not routinely taught in Chemistry programs in universities, where most environmental chemists and environmental technicians are trained. This presentation examines the unique capabilities of NIRS, such as rapid, real-time analysis; analysis of whole samples; simultaneous analysis of multiple constituents; cost-effectiveness, and portability, as they match needs for analysis in several environmental areas. Examples of NIRS usage and published and unpublished results will be described for such areas as soil and sediment analysis; water quality monitoring; and nutrient loading in application of manures and sewage sludge (biosolids) to land. Present barriers to the use of NIRS in environmental analysis will be discussed. It is argued that emerging environmental problems and increasing attention to some traditional problems will enhance the application of NIRS in the future.

• Atmosphere
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• v.18 no.3
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• pp.225-235
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• 2008

Sulfur hexafluoride ($SF_6$), man-made compound, has been paid attention as a potent greenhouse gas. After Kyoto Pototcol on Climate Change in 1997, nations established the policy aimed at minimizing release of $SF_6$ to atmosphere. We have developed and operated an automatic analytical system for monitoring atmospheric $SF_6$ using gas chromatography with electron capture detector (GC-ECD) and packed separate-column. Here, we report and discuss 4-month record of atmospheric $SF_6$ concentrations monitored at Seoul National University (SNU) pilot station near the Kwanak Mountain, Seoul. Most of observed $SF_6$ concentrations were excessively high compared with Northern Hemisphere (NH) background trend obtained from National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) monitoring stations. And the observed $SF_6$ showed extremely wide variability ranging from 4.6 pptv to $1.1{\times}10^3$ pptv, which may be affected by local sources placed nearby. Simultaneous wind data with $SF_6$ measurements show that relatively high values of $SF_6$ correspond to weak wind as well as southerly. There are many engineering installations to the south of the station. The regional value of the atmospheric $SF_6$ estimated from the data selection by wind conditions is about 6.8 pptv. This value, which is similar to concentrations of urban areas, is higher than NH background concentration.

• Journal of Haehwa Medicine
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• v.22 no.1
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• pp.129-143
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• 2013

This study was conducted to investigate the residue amount of pesticide on the 41 medicinal herbs in Daejeon area. This study was carried out to monitor the current status of pesticide residues in commercial medicinal herbs for sale of food use in 2012. It was performed using GC/ECD, GC/NPD, HPLC to analyze pesticides residues. Residues of 283 pesticides were analyzed by a simultaneous multiresidue method in 41 medicinal herbs being on sale in Daejeon. The medicinal herbs detected pesticides in 10 of 41 cases, showed a detection rate of 24.39%. The medicinal herbs which exceed the maximum residue limit were five cases as Cnidii Rhizoma, Osterici Radix, Artemisiae Capillaris Herba, Zizyphi Fructus and Alismatis Rhizoma. And pesticide residue of Cnidii Rhizoma and Alismatis Rhizoma exceeds the limit standard presented in only medicine use of KFDA. The residual pesticides which had the high detection rate were Chlopyrifos, Tebuconazole and Endosulfan in the detection of medicinal herbs. For further research, standards of Pesticide Residues in medicinal herbs should be added and more research of pesticide residues in medicinal herbs required. And standards of pesticide residues in medicinal herbs should be applied equally as medicines and food.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.509-521
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• 2008

Two control charts are usually required to monitor both the process mean and variance. In this paper, we introduce control procedures for jointly monitoring the process mean and variance with one control chart, and investigate efficiency of the introduced charts by comparing with the combined two EWMA charts. Our numerical results show that the GLR chart, the Omnibus EWMA chart, and the Interval chart have good ARL properties for simultaneous changes in the process mean and variance.

• Smart Structures and Systems
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• v.14 no.1
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• pp.55-70
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• 2014

The paper presents a multi-objective optimization strategy for a multi-type sensor placement for Structural Health Monitoring (SHM) of long span bridges. The problem is formulated for simultaneous placement of strain sensors and accelerometers (heterogeneous network) based on application demands for SHM system. Modal Identification (MI) and Accurate Mode Shape Expansion (AMSE) were chosen as the application demands for SHM. The optimization problem is solved through the use of integer Genetic Algorithm (GA) to maximize a common metric to ensure adequate MI and AMSE. The performance of the joint optimization problem solved by GA is compared with other established methods for homogenous sensor placement. The results indicate that the use of a multi-type sensor system can improve the quality of SHM. It has also been demonstrated that use of GA improves the overall quality of the sensor placement compared to other methods for optimization of sensor placement.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.201-207
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• 2007

In some manufacturing industries, there are many situation in which the simultaneous monitoring or control of two or more related quality characteristics is necessary. However, monitoring these two or more related quality characteristics independently can be very misleading. When several characteristics of manufactured component are to be monitored simultaneously, multivariate $x^2$ or $T^2$ control chart can be used. In this paper, establishing a early warning system(EWS) using multivariate control charts to analyze early out-of-control signals in melting process with many quality characteristics was presented. This module which we developed to control several characteristics improved efficiency and effectiveness of process control in the melting process.

• Food Science of Animal Resources
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• v.41 no.5
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• pp.816-825
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• 2021

This study aims to validate a fast method of simultaneous analysis of 365 LCamenable and 142 GC-amenable pesticides in hen eggs by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS), respectively, operating in multiple reaction monitoring (MRM) acquisition modes. The sample preparation was based on quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction. Key method performance parameters investigated were specificity, linearity, limit of quantification (LOQ), accuracy, precision and measurement uncertainty. The method was validated at two spiking levels (10 and 50 ㎍/kg), and good recoveries (70%-120%) and relative standard deviations (RSDs) (≤20) were achieved for 92.9% of LC-amenable and 86.6% of GC-amenable pesticide residues. The LOQs were ≤10 ㎍/kg for 94.2% of LC-amenable and 92.3% of GC-amenable pesticides. The validated method was further applied to 100 egg samples from caged hens, and none of the pesticides was quantified.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.441-447
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• 2022

This study describes a novel method for detecting and measuring partial discharge (PD) on an electrical facility such as an insulated power cable or switchgear using fiber optic sensing technology, and a distributed acoustic sensing (DAS) system. This method has distinct advantages over traditional PD sensing techniques based on an electrical method, including immunity to electromagnetic interference (EMI), long range detection, simultaneous detection for multiple points, and exact location. In this study, we present a DAS system for PD detection with performance evaluation and experimental results in a simulated environment. The results show that the system can be applied to PD detection.

• Composites Research
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• v.16 no.3
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• pp.58-67
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• 2003

To perform the realtime strain and fracture monitoring of the smart composite structures, two optical fiber sensor systems are proposed. The two types of the coherent sources were used for fracture signal detection - EDFA with FBG and EDFA with Fabry-Perot filter. These sources were coupled to EFPI sensors imbedded in composite specimens. To understand the characteristics of matrix crack signals, at first, we performed tensile tests using surface attached PZT sensors by changing the thickness and width of the specimens. This paper describes the implementation of time-frequency analysis such as short time Fourier transform (STFT) and wavelet transform (WT) for the quantitative evaluation of fracture signals. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes. And, from the test of tensile load monitoring using optical fiber sensor systems, measured strain agreed with the value of electric strain gage and the fracture detection system could detect the moment of damage with high sensitivity to recognize the onset of micro-crack fracture signal.