• Proceedings of the PSK Conference
• /
• 2003.10b
• /
• pp.213.2-213.2
• /
• 2003

A simple analytical procedure using FT-NIR for the rapid determination of individual ingredients was evaluated. Direct measurements were made by reflection using a reflectance accessory, by transmittance using tablet accessory and turn table. FT-NIR spectral data were transformed to the first derivative. Partial Least Square Regression(PLSR) was applied to quantify near-infrared (NIR) spectra of 2 ingredients. These calibration models were cross-validated (leave-one-out approach). The prediction ability of the models was evaluated on ambroxol tablets and compared with the real values in manufacturing procedure. (omitted)

• Nonlinear Functional Analysis and Applications
• /
• v.29 no.1
• /
• pp.165-177
• /
• 2024

In this paper, we investigate the suitable conditions for the existence results for a class of 𝔍-Hilfer fractional nonlinear Fredholm-Volterra models with new conditions. The findings are based on Banach contraction principle and Schauder's fixed point theorem. Also, the generalized Hyers-Ulam stability and generalized Hyers-Ulam-Rassias stability for solutions of the given problem are provided.

• Journal of Applied Reliability
• /
• v.10 no.3
• /
• pp.183-197
• /
• 2010

Web businesses are one of the most dynamic industries where lots of new business models are emerging while the other obsoleted ones are fading away almost every day. It is, therefore, difficult to establish a classification scheme for ever-changing web businesses. Previous researches on business models focus on classifying web businesses in one dimension which made some web sites difficult to fit into one category. We propose two dimensional classification scheme based on the means and the sources of revenue. The two dimensional classification provides more clear and broad perspectives of the web businesses and ways to identify web sites in combinations of several business models.

• Biomolecules & Therapeutics
• /
• v.5 no.2
• /
• pp.117-124
• /
• 1997

The analgesic effects of DA-5018, a new caosaucin derivative, were evaluated in various experimental pain models. Drugs were administered subcutaneously or topically. When drugs were administered subcutaneously, 1) the $ED_{50}$ of DA-5018, morphine . HCI, capsaicin and acetaminophen were 0.091-2.0, 0.3-4.3, 1.4-26.5 and 45.4-643 mg/kg, respectively in various pain or inflammatory models including acetic acid writhing, formalin, tail flick, Randall-Selitto, hot plate and crouton oil-induced ear edema test, 2) the AD2 values (the dose for doubling of pain threshold of vehicle control) of DA-5018, capsaicin and ketoprpgin were 1.07 $\pm$ 0. 18, 23.47$\pm$4.46 and 2.97$\pm$0.43 mg/kg in Freund's complete adjuvant (FCA)-induced arthritic pain model. And by topical application, 1) neither DA-5018 0.3% cream nor Zostrix-HP (capsaicin 0.075%) were effective in formalin test, 2) although DA-5018 0.3% cream significantly inhibited the croton oil-induced ear edema being better than Zostrix-HP and Kenofen (ketoprofen 3%). 3) In FCA model, DA-5018 0.3% cream reversed the decreased pain threshold of arthritic rat from 136.4 g (day 0) to 289.0 g (day 5) and 250.1 g (day 10), which was similar to Zostrix-HP. These results suggest that DA-5018 administered subcutaneously has a potent and broad analgesic spectrum than nonsteroidal antiinflammatory drugs against acute and chronic pain, and by topical application it exerts comparable analgesic and antiinglammaatory effects to capsaicin cream.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.3
• /
• pp.401-406
• /
• 2021

Recently, mean-teacher models based on convolutional recurrent neural networks are popularly used in audio event detection. The mean-teacher model is an architecture that consists of two parallel CRNNs and it is possible to train them effectively on the weakly-labelled and unlabeled audio data by using the consistency learning metric at the output of the two neural networks. In this study, we tried to improve the performance of the mean-teacher model by using additional derivative features of the log-mel spectrum. In the audio event detection experiments using the training and test data from the Task 4 of the DCASE 2018/2019 Challenges, we could obtain maximally a 8.1% relative decrease in the ER(Error Rate) in the mean-teacher model using proposed derivative features.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.6
• /
• pp.1171-1180
• /
• 2010

It is well known that the asymptotic convergence rates of nonparametric regression estimator gets worse as the dimension of covariates gets larger. One possible way to overcome this problem is reducing the dimension of covariates by using single index models. Two coefficient estimation methods in single index models are introduced. One is semiparametric least square estimation method, which tries to find approximate solution by using iterative computation. The other one is weighted average derivative estimation method, which is non-iterative method. Both of these methods offer the parametric convergence rate to normal distribution. However, practical comparison of these two methods has not been done yet. In this article, we compare these methods by examining the variances of estimators in various models.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1041-1041
• /
• 2001

Removal of variability in spectra data before the application of chemometric modeling will generally result in simpler (and presumably more robust) models. Particularly for sparsely sampled data, such as typically encountered in diode array instruments, the use of Savitzky-Golay (S-G) derivatives offers an effective method to remove effects of shifting baselines and sloping or curving apparent baselines often observed with scattering samples. The application of these convolution functions is equivalent to fitting a selected polynomial to a number of points in the spectrum, usually 5 to 25 points. The value of the polynomial evaluated at its mid-point, or its derivative, is taken as the (smoothed) spectrum or its derivative at the mid-point of the wavelength window. The process is continued for successive windows along the spectrum. The original paper, published in 1964 [1] presented these convolution functions as integers to be used as multipliers for the spectral values at equal intervals in the window, with a normalization integer to divide the sum of the products, to determine the result for each point. Steinier et al. [2] published corrections to errors in the original presentation [1], and a vector formulation for obtaining the coefficients. The actual selection of the degree of polynomial and number of points in the window determines whether closely situated bands and shoulders are resolved in the derivatives. Furthermore, the actual noise reduction in the derivatives may be estimated from the square root of the sums of the coefficients, divided by the NORM value. A simple technique to evaluate the actual convolution factors employed in the calculation by the software will be presented. It has been found that some software packages do not properly account for the sampling interval of the spectral data (Equation Ⅶ in [1]). While this is not a problem in the construction and implementation of chemometric models, it may be noticed in comparing models at differing spectral resolutions. Also, the effects on parameters of PLS models of choosing various polynomials and numbers of points in the window will be presented.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.8
• /
• pp.718-722
• /
• 2015

This paper proposes a fractional-order PID (Proportional-Integral-Derivative) control used electromagnetic strip stabilization controller in a continuous galvanizing line. Compared to a conventional PID controller, a fractional-order PID controller has integration-fractional-order and derivation-fractional-order as additional control parameters. Thanks to increased control parameters, more precise controller adjustment is available. In addition, accurate transfer function of a real system generally has a fractional-order form. Therefore, it is more adequate to use a fractional-order PID controller than a conventional PID controller for a real world system. Finite element models of a $1200{\times}2000{\times}0.8mm$ strip, which were extracted using a commercial software ANSYS were used as simulation plants, and Gaussian mixture models were used to find optimized control parameters that can reduce the strip vibrations to the lowest amplitude. Simulation results show that a fractional-order PID controller significantly reduces strip vibration and transient response time than a conventional PID controller.

• The Korean Journal of Applied Statistics
• /
• v.6 no.2
• /
• pp.393-399
• /
• 1993

When we compute the maximum likelihood estimators of the parameters for the logistic regression models, which are useful in studying the relationship between the binary response variable and the explanatory variable, the standard error calculations are usually based on the second derivative of log-likelihood function. On the other hand, an estimator of the Fisher information motivated from the fact that the expectation of the cross-product of the first derivative of the log-likelihood function gives the Fisher information is expected to have similar asymptotic properties. These estimators of Fisher information are closely related with the iterative algorithm to get the maximum likelihood estimator. The average numbers of iterations to achieve the maximum likelihood estimator are compared to find out which method is more efficient, and the estimators of the variance from each method are compared as estimators of the asymptotic variance.

• Journal of the Korean Wood Science and Technology
• /
• v.47 no.1
• /
• pp.101-109
• /
• 2019

This paper examines the classification of five coniferous species, including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa), using near-infrared (NIR) spectra. Fifty lumber samples were collected for each species. After air-drying the lumber, the NIR spectra (wavelength = 780-2500 nm) were acquired on the wide face of the lumber samples. Soft independent modeling of class analogy (SIMCA) was performed to classify the five species using their NIR spectra. Three types of spectra (raw, standard normal variated, and Savitzky-Golay $2^{nd}$ derivative) were used to compare the classification reliability of the SIMCA models. The SIMCA model based on Savitzky-Golay $2^{nd}$ derivatives preprocessing was determined as the best classification model in this study. The accuracy, minimum precision, and minimum recall of the best model (PCA models using Savitzky-Golay $2^{nd}$ derivative preprocessed spectra) were evaluated as 73.00%, 98.54% (Korean pine), and 67.50% (Korean pine), respectively.