• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.4
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• pp.363-373
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• 2019

Waste characterisation associated with nuclear site decommissioning relies on radiochemical analysis of a diverse range of sample types, requiring extensive validation of analytical techniques using matrix-matched materials. The absence of relevant reference materials has hindered robust method development and validation. The paper discusses how method validation in support of nuclear waste characterisation can be achieved without using reference materials. The key stages in an analytical procedure are evaluated and a multi-stage approach is proposed with the ultimate aim of determining an operational envelope for an analytical procedure.

• Journal of Astronomy and Space Sciences
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• v.28 no.1
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• pp.63-70
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• 2011

The needs for satellite formation flying are gradually increasing to perform the advanced space missions in remote sensing and observation of the space or Earth. Formation flying in low Earth orbit can perform the scientific missions that cannot be realized with a single spacecraft. One of the various techniques of satellite formation flying is the determination of the precise baselines between the satellites within the formation, which has to be in company with the precision validation. In this paper, the baseline of Gravity Recovery and Climate Experiment (GRACE) A and B was determined with the real global positioning system (GPS) measurements of GRACE satellites. And baseline precision was validated with the batch and sequential processing methods using K/Ka-band ranging system (KBR) biased range measurements. Because the proposed sequential method validate the baseline precision, removing the KBR bias with the epoch difference instead of its estimation, the validating data (KBR biased range) are independent of the data validated (GPS-baseline) and this method can be applied to the real-time precision validation. The result of sequential precision validation was 1.5~3.0 mm which is similar to the batch precision validation.

• Journal of Pharmaceutical Investigation
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• v.37 no.3
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• pp.187-192
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• 2007

A reversed phase HPLC analysis of atorvastatin (AS) standard solution was performed using diclofenac (DF) as internal standard. Column oven temperature, flow rate and the composition of the mobile phase were varied in order to determine a practical system setup using a C18 column and UV detector. Two C18 columns of different length were compared regarding their influence on the AS peak shape. Based on these preliminary experiments a validation study was performed utilizing a C18 column at $62^{\circ}C$ with a mobile phase consisting of sodium phosphate buffer (0.05 M, pH 4.0), methanol and acetonitrile (40:50:10, v/v/v). The detection limit for AS was $0.1{\mu}g/ml$ and inter- and intra-day calibration curves were linear over a concentration range of $0.2-50{\mu}g/ml$. Accuracy and precision were satisfactory in the AS concentration range of $0.5-50{\mu}g/ml$.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4518-4526
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• 2023

NECP-SARAX is a neutronics analysis code system for advanced reactor developed by Nuclear Engineering Computational Physics Laboratory of Xi'an Jiaotong University. In past few years, improvements have been implemented in TULIP code which is the cross-section generation module of NECP-SARAX, including the treatment of resonance interface, considering the self-shielding effect in non-resonance energy range, hyperfine group method and nuclear library with thermal scattering law. Previous studies show that NECP-SARAX has high performance in both fast and thermal spectrum system analysis. The accuracy of TULIP code in fast and thermal spectrum system analysis is demonstrated preliminarily. However, a systematic verification and validation is still necessary. In order to validate the applicability of TULIP code for full energy range, 147 fast spectrum critical experiment benchmarks and 170 thermal spectrum critical experiment benchmarks were selected from ICSBEP and used for analysis. The keff bias between TULIP code and reference value is less than 300 pcm for all fast spectrum benchmarks. And that bias keeps within 200 pcm for thermal spectrum benchmarks with neutron-moderating materials such as polyethylene, beryllium oxide, etc. The numerical results indicate that TULIP code has good performance for the analysis of fast and thermal spectrum system.

• Journal of KIISE:Databases
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• v.32 no.6
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• pp.628-640
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• 2005

The XML is well accepted in several different Web application areas. As soon as many users and applications work concurrently on the same collection of XML documents, isolating accesses and modifications of different transactions becomes an important issue. When an XML document correctly corresponds to the rules laid out in a DTD or XML schema, it is also said to be valid. The valid XML document's validity should be guaranteed after the document is updated. The validation method mentioned above, however, results in lower degree of concurrency. For getting higher degree of concurrency and minimizing the range of the XML document validity, a new validation method based on a specific locking method is required. In this paper we propose the sequence group validation method for minimizing the range of the XML document validity. We also propose the boundary locking method for isolating accesses and modifications of different transactions while supporting the valid XML document's validity. Finally, the results of some experiments show the validation and locking methods increase the degree of transaction concurrency.

• Journal of Biomedical Engineering Research
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• v.40 no.2
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• pp.48-54
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• 2019

This paper proposed a method of validation data augmentation for improving the grading accuracy of diabetic macular edema (DME) using deep learning. The data augmentation technique is basically applied in order to secure diversity of data by transforming one image to several images through random translation, rotation, scaling and reflection in preparation of input data of the deep neural network (DNN). In this paper, we apply this technique in the validation process of the trained DNN, and improve the grading accuracy by combining the classification results of the augmented images. To verify the effectiveness, 1,200 retinal images of Messidor dataset was divided into training and validation data at the ratio 7:3. By applying random augmentation to 359 validation data, $1.61{\pm}0.55%$ accuracy improvement was achieved in the case of six times augmentation (N=6). This simple method has shown that the accuracy can be improved in the N range from 2 to 6 with the correlation coefficient of 0.5667. Therefore, it is expected to help improve the diagnostic accuracy of DME with the grading information provided by the proposed DNN.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1230-1244
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• 2022

This paper proposes an algorithm for signal validation using unsupervised methods in emergency situations at nuclear power plants (NPPs) when signals are rapidly changing. The algorithm aims to determine the stuck failures of signals in real time based on a variational auto-encoder (VAE), which employs unsupervised learning, and long short-term memory (LSTM). The application of unsupervised learning enables the algorithm to detect a wide range of stuck failures, even those that are not trained. First, this paper discusses the potential failure modes of signals in NPPs and reviews previous studies conducted on signal validation. Then, an algorithm for detecting signal failures is proposed by applying LSTM and VAE. To overcome the typical problems of unsupervised learning processes, such as trainability and performance issues, several optimizations are carried out to select the inputs, determine the hyper-parameters of the network, and establish the thresholds to identify signal failures. Finally, the proposed algorithm is validated and demonstrated using a compact nuclear simulator.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1511-1511
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• 2001

Energy content, expressed as calories per gram, is an important part of the evaluation and marketing of foods in developed countries. Currently accepted methods of measurement of energy by U.S. food labeling legislation include measurement of gross calories by bomb calorimetry with an adjustment for undigested protein and by calculation using specific factors for the energy values of protein, carbohydrate less the amount of insoluble dietary fiber, and total fat. The ability of NIRS to predict the energy value of diverse, processed and unprocessed cereal food products was investigated. NIR spectra of cereal products were obtained with an NIR Systems monochromator and the wavelength range used for analysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPGI, range 4.05-5.49 cal/g). Energy value was adjusted for undigested protein (CPG2, range 3.99-5.38 cal/g) and undigested protein and insoluble dietary fiber (CPG3, range 2.42-5.35 cal/g). Using a multivariate analysis software package (ISI International, Inc.) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPGI using modified partial least squares regression (n=127) was 0.060 cal/g and 0.95, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 cal/g, 0.98, -0.027 cal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 cal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.

• Journal of Radiation Protection and Research
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• v.31 no.1
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• pp.9-15
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• 2006

A long-range atmospheric dispersion model named LADAS has been developed to understand the characteristics of the transport and diffusion of radioactive materials released into atmosphere. The developed numerical model for validation was compared with the results of the ETEX which is the long-range field tracer experiment. As a comparative study, the calculated concentration distributions agreed well in the case of the usage of the mixing heights calculated by the Richardson number than the usage of the constant mixing heights in LADAS model. Also, the calculated concentrations agreed with the time series of the measured ones at some sampling points.

• Korean Journal of Veterinary Service
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• v.45 no.3
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• pp.237-242
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• 2022

The simultaneous analysis of mycotoxins using LC-MS/MS, a food official analysis method, was applied with compound feed for pets with high consumer preferences. In this study, the linearity of all calibration curves showed good linearity of 0.99 or more. and both the accuracy (recovery rate) and precision (repeatability) criteria of the concentration range for each mycotoxin in the National Agricultural Products Quality Management Service's Validation and Verification Guidelines were met. And as a result of analyzing FAPAS QCM in the same way, it was assesed that the z-scores of Aflatoxin B₁, Ochratoxin A, Zearalenone, and Fumonisin B₁, were within ±2 range. This study showed that the application of the food official analysis method to compound feed for pets is suitable.