• YAKHAK HOEJI
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• v.35 no.1
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• pp.1-6
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• 1991

Fast Hartley transform(FHT) was used for the identification of derivative UV spectra of pharmaceuticals, with the advantages of relatively shorter computing time of FHT and more precise results. The arccosine value of dot product of two vectors of normalized FHT coefficients calculated from two compared derivative spectra was a reasonable parameter for the spectral identification. Using this parameter, the similar patterns of derivative spectra of 13 penicillins can be differenciated from each other. The concentration difference and the minor contamination did not interfere the results of identification procedures. All these procedures of identification were accomplished successfully by the computer program, [SPECMAN PLUS] version 1.30, which was developed for this article.

• YAKHAK HOEJI
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• v.28 no.3
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• pp.185-190
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• 1984

Protothalipine colorless needle crystal, mp $195-6^{\circ}$, $C_{21}H_{25}NO_{5}$) and jatrorrhizine chloride (Base A, orange needle crystal, mp $198^{\circ}$) are identified by chemical, spectral analysis, and comparison with authentic sample. Base B (reddish crystal, mp $192-4^{\circ}$) might be a artifact substance, which was changed from the jatrorrhizine chloride. Base C (yellowish needle crystal, mp $228~230^{\circ}$) and Base D (reddish needle crystal, mp $211~213^{\circ}$) were assumed to be thalifendine chloride, desoxythalidastine chloride by phytochemical and spectral analysis respectively.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3112-3112
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• 2001

Near-Infrared Spectroscopy (NIRS) was investigated aiming at the identification of falsified drugs. The identification is based on comparison of the NIR spectrum of a sample with a typical spectra of an authentic drug using multivariate modelling and classification algorithms (PCA/SIMCA). Two spectrophotometers (Brimrose - Luminar 2000 and 2030), based on acoustic-optical filter (AOTF) technology, sharing the same controlling computer, software (Brimrose - Snap 2.03) and the data acquisition electronics, were employed. The Luminar 2000 scans the range 850 1800 nm and was employed for transmitance/absorbance measurements of liquids with a transflectance optical bundle probe with total optical path of 5 mm and a circular area of 0.5 $\textrm{cm}^2$. Model 2030 scans the rage 1100 2400 nm and was employed for reflectance measurement of solids drugs. 300 spectra, acquired in about 20 s, were averaged for each sample. Chemometric treatment of the spectral data, modelling and classification were performed by using the Unscrambler 7.5 software (CAMO Norway). This package provides the Principal Component Analysis (PCA) and SIMCA algorithms, used for modelling and classification, respectively. Initially, NIRS was evaluated for spectrum acquisition of various drugs, selected in order to accomplish the diversity of physico-chemical characteristics found among commercial products. Parameters which could affect the spectra of a given drug (especially if presented as solid tablets) were investigated and the results showed that the first derivative can minimize spectral changes associated with tablet geometry, physical differences in their faces and position in relation to the probe beam. The effect of ambient humidity and temperature were also investigated. The first factor needs to be controlled for model construction because the ambient humidity can cause spectral alterations that should cause the wrong classification of a real drug if the factor is not considered by the model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.1074-1083
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• 2011

Noise of digital camera has been noticeable to its users. Particularly, noise of a barrel assembly module in zoom in/zoom out operation is recorded while taking a video. Reduction of barrel noise becomes crucial but there are not many studies on noise of digital camera due to its short history of use. In this study, experiment-based analyses are implemented to identify sources of noise and vibration because of complexity and compactness of the barrel system. Output noise is acquired in various operation conditions using synchronization for spectral analysis. Noise sources of a barrel assembly in zoom operating are first identified by the comparison with gear frequency analysis and then correlation analysis between noise and vibration is applied to confirm the generation path of noise. Analysis on noise transfer characteristic of zoom module is also carried out in order to identify the most contributing components. One of possible countermeasures of noise in zoom operating is investigated by an experimental approach.

• Speech Sciences
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• v.10 no.2
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• pp.249-258
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• 2003

This study attempted to examine a speaker identification method using difference sum and correlation coefficient determined from a pair of intensity level matrices of band-pass-filtered numeric sounds produced by ten female speakers of similar age and height. Subjects recorded three digit numbers at a quiet room at a sampling rate of 22 kHz on a personal computer. Collected data were band-pass-filtered at five different band ranges. Then, matrices of five intensity levels at 100 proportional time points were obtained. Pearson correlation coefficients and the sum of absolute intensity differences between a pair of given matrices were determined within and across the speakers. Results showed that very high correlation coefficient and small difference sum generally occurred within each speaker but some individual variation was also observed. Thus, the matrix pair with a higher coefficient and a smaller difference sum was averaged to form each individual's model. Comparison among the speakers yielded generally low coefficients and large differences, which suggests successful speaker identification, but among them there were a few cases with very high coefficients and small differences. Future studies will focus on finer band ranges and additional spectral parameters at some peak points of the intensity contour at a low frequency band.

• Nuclear Engineering and Technology
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• v.44 no.7
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• pp.781-790
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• 2012

The HyperGam program was developed for the analysis of complex HPGe ${\gamma}$-ray spectra. The previous version of HyperGam was mainly limited to the analysis of ${\gamma}$-ray peaks and the manual logging of the result. In this study, it is specifically developed into a tool for the isotopic analysis of spectra. The newly developed features include nuclide identification and activity determination. An algorithm for nuclide identification was developed to identify the peaks in the spectrum by considering the yield, efficiency, energy and peak area for the ${\gamma}$-ray lines emitted from the radionuclide. The detailed performance of nuclide identification and activity determination was accessed using the IAEA 2002 set of test spectra. By analyzing the test spectra, the numbers of radionuclides identified truly (true hit), falsely (false hit) or missed (misses) were counted and compared with the results from the IAEA 2002 tests. The determined activities of the radionuclides were also compared for four test spectra of several samples. The result of the performance test is promising in comparison with those of the well-known software packages for ${\gamma}$-ray spectrum analysis.

• YAKHAK HOEJI
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• v.38 no.4
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• pp.366-371
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• 1994

To improve the identification power of TLC/HPTLC the in situ reflectance spectra obtained directly from plates with commercial scanner are used. The spectrum normalization should be carried out prior to comparing and searching the spectra from library for the identification of compounds. Because the reflectance does not obey the Lambert-Beer's law, there arise some problems in normalization. These problems could be solved to some extent by normalizing the spectra with regression methods. The spectra are manipulated with the regression function of a curve obtained from the correlation plot. When the parabola was used as the manipulating function, the spectra were identified with the accuracy of 97% and this result was better than that of conventionally used the point and area normalization method.

• Journal of the Korean Wood Science and Technology
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• v.48 no.4
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• pp.503-512
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• 2020

Using Na₂CO₃ versus NaCl as chemical activator, we compared the quality of activated carbon produced from oil palm fronds as raw material. These activators were selected for comparison because both are readily available and are environmentally friendly. In the manufacturing, we used Indonesian National Standard (SNI 06-3730-1995) parameters. For the quality comparison, we determined activated-carbon yield, moisture, ash, volatiles, and fixed-carbon contents; and adsorption capacity of iodine. The best characteristics, assessed by morphological surface analysis and Fourier transform infrared (FTIR) spectral analysis, were observed in the carbon activated by Na₂CO₃ at an activator concentration of 10% and carbonization temperature of 400 ℃. The results were as follows: activated-carbon yield, 84%; water content, 8.80%; ash content, 2.20%; volatiles content, 14.80%; fixed-carbon content, 68.60%; and adsorption capacity of iodine, 888.51 mg/g. Identification using the FTIR spectrophotometer showed the presence of the functional groups O-H, C=O, C=C, C-C, and C-H in the Na₂CO₃-activated carbon.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.675-696
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• 2023

Terpenoids, also referred to as terpenes, are a large family of naturally occurring chemical compounds present in the essential oils extracted from medicinal plants. In this study, a nondestructive methodology was created by combining ATR-FT-IR (attenuated total reflectance-Fourier transform infrared), and Raman spectroscopy for the terpenoids assessment in medicinal plants essential oils from ten different geographical locations. Partial least squares regression (PLSR) and support vector regression (SVR) were used as machine learning methodologies. However, a deep learning based model called as one-dimensional convolutional neural network (1D CNN) were also developed for models comparison. With a correlation coefficient (R²) of 0.999 and a lowest RMSEP (root mean squared error of prediction) of 0.006% for the prediction datasets, the SVR model created for FT-IR spectral data outperformed both the PLSR and 1 D CNN models. On the other hand, for the classification of essential oils derived from plants collected from various geographical regions, the created SVM (support vector machine) classification model for Raman spectroscopic data obtained an overall classification accuracy of 0.997% which was superior than the FT-IR (0.986%) data. Based on the results we propose that FT-IR spectroscopy, when coupled with the SVR model, has a significant potential for the non-destructive identification of terpenoids in essential oils compared with destructive chemical analysis methods.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.5 no.1
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• pp.65-72
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• 1993

An experiment has been carried out to identify flow patterns in a horizontal condensing flow with R-113. Characteristics of flow patterns were determined based upon a statistical analysis of differential pressure fluctuations at an orifice. The probability density function and power spectral density function of instantaneous pressure drop curves for various flow conditions were obtained. In comparison to the results of air-water flows, the flow patterns in a condensing flow such as annular, wavy, slug and plug could be identified. The experimental data determined by this technique were compared with the flow pattern maps suggested by other investigators. The result indicates that the statistical characteristics of differential pressure fluctuations at an orifice may be a useful tool for identifying flow patterns both in condensing flows and in adiabatic two-phase flows.