• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1242-1242
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• 2001

The use of fibre optic probes for NIR quality control in the industry is becoming very important, as it provides a powerful tool to reduce sample analysis time and it facilitates the implementation of on-line analyses. However, most of the applications of fibre optics and probes have been done on suspensions, clear liquids and films, chemical and pharmaceutical products and also on fruits and animal products. Traditional applications of near infrared spectroscopy in agriculture have been developed in reflectance mode and calibration transfer could be an interesting way to reduce efforts. Classical methods for calibration transfer between different instruments involve the use of sealed reference cups, but, as fibre optic analysis does not use cups, it is necessary to develop new methods for calibration transfer without standards (Blank et al., 1996). In this paper, we have studied how the most used mathematical pretreatments (three methods of Multiplicative Scatter Correction, Standard Normal Variate, Detrending and derivatives) and their combinations applied to calibration development can contribute to reduce spectral differences between instruments. Calibration equations were obtained for three sets of cereals (barley, wheat and maize) scanned in reflectance mode and then they were validated with samples analysed in reflectance and interactance-reflectance mode (fibre optic). Preliminary results show how some combination of pretreatments reduce the differences in the predicted values, measured as standard error of differences, facilitating the use of calibrations obtained in reflectance for samples analysed by interactance-reflectance. However, the application of pretreatments is not enough to satisfy the control limits for calibration transfer suggested by Shenk et al. (1992), and it should be necessary to combine them with a specific algorithm for instruments standardization.

• The Journal of Korean Society for Radiation Therapy
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• v.8 no.1
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• pp.29-35
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• 1996

We are often faced with the clinical situations that is inevitably extended SSD for electron beam therapy due to anatomical restriction or applicator structure. But there are some difficulties in accurately predicting output and properties. In electron beam treatment , unlike photon beam the decrease in output for extended SSD does not follow inverse-square law accurately because of a loss of side scatter equilibrium, which is particularly significant for small cone size and low energies. The purpose of our study is to analyze the output in changing with the energy, cone size, air gap beyond the standard SSD and to compare inverse-square law factor derived from calculated effective SSD, mominal SSD with measured output factor. In addition, we have analyzed the change of PDD for several cones with different SSDs which range from 100cm to 120cm with 5cm step and with different energies(6MeV, 9MeV, 12MeV, 16MeV, 20MeV). In accordance with our study, an extended SSD produces a significant change in beam output, negligible change in depth dose which range from 100cm to 120cm SSDs. In order to deliver the more accurate dose to the neoplastic tissue, first of all we recommend inverse-square law using the table of effective SSDs with cone sizes and energies respectively or simply to create a table of extended SSD air gap correction factor. The second we need to have an insight into some change of dose distribution including PPD, penumbra caused by extended SSD for electron beam therapy.

• Journal of Korean Academy of Nursing Administration
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• v.17 no.2
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• pp.168-179
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• 2011

Purpose: The purpose of this study was to identify level of recognition of the importance, satisfaction and contribution of APNs' role by physicians, nurses, and advanced practice nurses. Method: Perceived importance and satisfaction were measured with a 23-item questionnaire on APN role with 5 subcategories. APNs' contribution was investigated using a 13-item outcome questionnaire developed by the researchers. Between August 15 and October 31, 2009, the researchers collected data from 68 physicians, 265 nurses, and 23 APNs all working in a single tertiary hospital. Data were analyzed using descriptive statistics, Kruskal-Wallis Test with Bonferroni's Correction and scatter plot. Result: The importance (3.24~3.39, 4 point scale), satisfaction (3.02~3.13, 4 point scale), and contribution of APNs' role (3.39~4.12, 5 point scale) were well recognized by the health care professionals. All the three health care professional groups rated APNs' contribution high in medical service management, continuity of care, patient accessibility, improvement in patient satisfaction, and patient and family education. 'Importance-Satisfaction Analysis' showed that patient data management by APNs needed greater effort. Conclusions: The findings show that the importance, satisfaction, contribution of APNs' role are recognized, and indicate a need for further development of APNs' role through efforts to overcome the gaps identified through this research.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.5
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• pp.401-406
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• 2001

The applicability of non-destructive near infrared reflectance spectroscopic (NIRS) method was tested to determine the protein and oil contents of intact soybean [Glycine max (L.) Merr.] seeds. A total of 198 soybean calibration samples and 101 validation samples were used for NIRS equation development and validation, respectively. In the developed non-destructive NIRS equation for analysis of protein and oil contents, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing, and 1 point second smoothing) and 2, 1, 20, 10 math treatment conditions with Standard Normal Variate and Detrend (SNVD) scatter correction method and entire spectrum (400-2500 nm) by using Modified Partial Least Squares (MPLS) regression, respectively. Validation of these non-destructive NIRS equations showed very low bias (protein: 0.060%, oil: -0.017%) and standard error of prediction (SEP, protein: 0.568 %, oil : 0.451 %) as well as high coefficient of determination ($R^2$, protein: 0.927, oil: 0.906). Therefore, these non-destructive NIRS equations can be applicable and reliable for determination of protein and oil content of intact soybean seeds, and non-destructive NIRS method could be used as a mass screening technique for selection of high protein and oil soybean in breeding programs.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.123-130
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• 2007

The aim of this study was to propose a fusion and registration method with heterogeneous small animal acquisition system in small animal in-vivo study. After an intravenous injection of $^{18}F$-FDG through tail vain and 60 min delay for uptake, mouse was placed on an acryl plate with fiducial markers that were made for fusion between small animal PET (microPET R4, Concorde Microsystems, Knoxville TN) and Discovery LS CT images. The acquired emission list-mode data was sorted to temporally framed sinograms and reconstructed using FORE rebining and 2D-OSEM algorithms without correction of attenuation and scatter. After PET imaging, CT images were acquired by mean of a clinical PET/CT with high-resolution mode. The microPET and CT images were fusion and co-registered using the fiducial markers and segmented lung region in both data sets to perform a point-based rigid co-registration. This method improves the quantitative accuracy and interpretation of the tracer.

• Journal of the Korean Society of Radiology
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• v.9 no.3
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• pp.139-145
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• 2015

When examining a patient using SPECT, gamma rays emitted from the body decrease or scatter. And when they reach the detector they spread in accordance with physical characteristics and geometric shapes of the scanner, quantitative analysis was difficult. For exact quantitative analysis of gamma rays emitted from the body, so that they must be considered to correction about PVE(partial volume effect). In this paper, sinogram filter was implemented to solve comprehensive PVE of SPECT. According to the results in which implemented filter was applied, partial volume effect caused by SPECT was removed. To compare proposed method and conventional method, PSNR(Peak Signal to Noise Ratio) was executed. As a result, proposed method was indicated as 7dB, conventional method was indicated as 14db respectively. dB(decibel) level of the proposed methods is lower, since the MSE(mean square error) becomes greater because scattered ray was removed, PSNR value is low. Therefore, by applying the proposed method for removing the PVE of SPECT imaging method, the image quality is improved.

• Korean Chemical Engineering Research
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• v.45 no.6
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• pp.596-603
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• 2007

Rapid or on-line coal analysis is of great interest in coal industry as it would allow efficient plant operation. Multivariate analysis has been applied to near-infrared(NIR) spectra coal for investigating the relationship between coal properties(%) (moisture, ash, volatile matter, fixed carbon, carbon, hydrogen, nitrogen, oxygen, sulfur), heating value(kcal/kg) and corresponding near-infrared spectral data. The quantitative analysis was carried out by applying PLS(partial least squares regression) to determine a methodology able to establish a relationship between coal properties and NIR spectral data being applied mathematical pre-treatments for minimizing the physical features of the samples. As a results of the analysis, this technique is able to classify the species of coals and to predict the all coal properties except ash, nitrogen and sulfur. The efficient operation of coal fired power plant is expected owing to real time on-line coal analysis of moisture and heating value.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.633-644
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• 2020

Rice paper is an element of Vietnamese cuisine that can be used to wrap vegetables and meat. Rice and starch are the main ingredients of rice paper and their mixing ratio is important for quality control. In a commercial factory, assessment of food safety and quantitative supply is a challenging issue. A rapid and non-destructive monitoring system is therefore necessary in commercial production systems to ensure the food safety of rice and starch flour for the rice paper wrap. In this study, fluorescence hyperspectral imaging technology was applied to classify grain flours. Using the 3D hyper cube of fluorescence hyperspectral imaging (fHSI, 420 - 730 nm), spectral and spatial data and chemometric methods were applied to detect and classify flours. Eight flours (rice: 4, starch: 4) were prepared and hyperspectral images were acquired in a 5 (L) × 5 (W) × 1.5 (H) cm container. Linear discriminant analysis (LDA), partial least square discriminant analysis (PLSDA), support vector machine (SVM), classification and regression tree (CART), and random forest (RF) with a few preprocessing methods (multivariate scatter correction [MSC], 1^st and 2^nd derivative and moving average) were applied to classify grain flours and the accuracy was compared using a confusion matrix (accuracy and kappa coefficient). LDA with moving average showed the highest accuracy at A = 0.9362 (K = 0.9270). 1D convolutional neural network (CNN) demonstrated a classification result of A = 0.94 and showed improved classification results between mimyeon flour (MF)1 and MF2 of 0.72 and 0.87, respectively. In this study, the potential of non-destructive detection and classification of grain flours using fHSI technology and machine learning methods was demonstrated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.181-184
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• 2006

Knowledge of the ionospheric peak parameter foF2 (the critical frequency of F2 layer) is one of key essential factors for predicting ionospheric characteristics and delay correction of satellite positioning. However, the foF2 was almost estimated using an empirical model of International Reference Ionosphere (IRI) or other expensive observing techniques, such as ionosondes and scatter radar. In this paper, the ionospheric peak parameter foF2 is the first observed by ground-based GPS with all weather, low-cost and near real time properties. Compared with the IRI-2001 and independent ionosondes at or near the GPS receiver stations, the foF2 obtained from ground-based GPS is in better agreement, but closer to the ionosonde. However, during nighttime, the IRI model overestimated the GPS observed values during winter and equinox months.Furthermore, seasonal variation trend of the foF2 in 2003 is studied using foF2 monthly median hourly data measured over South Korea. It has shown that the systematic diurnal changes of foF2 are apparent in each season and the higher values of foF2 are observed during the equinoxes (semiannual anomaly) as well as in mid-daytime of each season.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.559-570
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• 2017

A partial least squares regression (PLSR) model was developed to map the internal soluble solids content (SSC) of apples using a ground-based hyperspectral scanner that could simultaneously acquire outdoor data and capture images of large quantities of apples. We evaluated the applicability of various preprocessing techniques to construct an optimal prediction model and calculated the optimal band through a variable importance in projection (VIP)score. From the 515 bands of hyperspectral images extracted at wavelengths of 360-1019 nm, 70 reflectance spectra of apples were extracted, and the SSC ($^{\circ}Brix$) was measured using a digital photometer. The optimal prediction model wasselected considering the root-mean-square error of cross-validation (RMSECV), root-mean-square error of prediction (RMSEP) and coefficient of determination of prediction $r_p^2$. As a result, multiplicative scatter correction (MSC)-based preprocessing methods were better than others. For example, when a combination of MSC and standard normal variate (SNV) was used, RMSECV and RMSEP were the lowest at 0.8551 and 0.8561 and $r_c^2$ and $r_p^2$ were the highest at 0.8533 and 0.6546; wavelength ranges of 360-380, 546-690, 760, 915, 931-939, 942, 953, 971, 978, 981, 988, and 992-1019 nm were most influential for SSC determination. The PLSR model with the spectral value of the corresponding region confirmed that the RMSEP decreased to 0.6841 and $r_p^2$ increased to 0.7795 as compared to the values of the entire wavelength band. In this study, we confirmed the feasibility of using a hyperspectral scanner image obtained from outdoors for the SSC measurement of apples. These results indicate that the application of field data and sensors could possibly expand in the future.