• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.53-59
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• 2006

Dynamic neural networks have been applied to diverse fields requiring temporal signal processing such as system identification and signal prediction. This paper proposes the gamma neural network(GAM), which uses gamma memory kernel in the hidden layer of feedforward multilayered network, to improve dynamics of networks and then describes nonlinear adaptive prediction using the proposed network as an adaptive filter. The proposed network is evaluated in nonlinear signal prediction and compared with feedforword(FNN) and recurrent neural networks(RNN) for the relative comparison of prediction performance. Simulation results show that the GAM network performs better with respect to the convergence speed and prediction accuracy, indicating that it can be a more effective prediction model than conventional multilayered networks in nonlinear prediction for nonstationary signals.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.95-102
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• 2017

Gamma generalized linear models have received less attention than Poisson and binomial generalized linear models. Therefore, many old-established statistical techniques are still used in gamma generalized linear models. In particular, existing literature and textbooks still use approximate estimates for the dispersion parameter. In this paper we study the efficiency of various dispersion parameter estimators in gamma generalized linear models and perform numerical simulations. Numerical studies show that the maximum likelihood estimator and Cox-Reid adjusted maximum likelihood estimator are recommended and that approximate estimates should be avoided in practice.

• Journal of Radiation Industry
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• v.5 no.4
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• pp.353-357
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• 2011

Degradation of p-nitrophenol has been carried out using only gamma irradiation or gamma irradiation with $H_2O_2$ or $Na_2S_2O_8$. Effects of different operating parameters such as initial concentration ($50mg\;l^{-1}$, $100mg\;l^{-1}$, $200mg\;l^{-1}$, $300mg\;l^{-1}$, $400mg\;l^{-1}$, $500mg\;l^{-1}$ and $600mg\;l^{-1}$) on the extent of degradation has been investigated. At 5 kGy, $50mg\;l^{-1}$ p-nitrophenol was completely degraded, and the radiolytic degradation of p-nitrophenol was described by the pseudo-first-order kinetic model. The combination of gamma irradiation with $H_2O_2$ or $Na_2S_2O_8$ leads to an enhanced effect, which remarkably increased the degradation efficiency of p-nitrophenol and TOC removal. However, at high $H_2O_2$ concentration, the efficacy of p-nitrophenol degradation is reduced because ${\cdot}OH$ radicals are scavenged by $H_2O_2$ and $Na_2S_2O_8$.

• Bulletin of the Korean Chemical Society
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• v.8 no.5
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• pp.398-403
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• 1987

A general theory of polymer adsorption at a semi-permeable oil-water interface of the biphasic solution is presented. The configurational factor of the solution in the presence of the semi-open boundary at the interface is evaluated by the quasicrystalline lattice model. The present theory gives the feature of the bulk concentration equilibria between oil-water subsystems and the surface excesses of ${\Gamma}^{\alpha}$ and ${\Gamma}^\{beta}$ of the polymer segments as a function of the degree of polymerization $\gamma$, the Flory-Huggins parameter in $\beta$-phase $x_{\rho}^{{\beta}_{\rho}}$, the differential adsorption energy parameter in $\beta$-phase $x_{\sigma}^{{\beta}_{\rho}}$, the differential interaction energy parameter ${\Delta}x_{\rho}$ and the bulk concentration of the polymer in ${\beta}-phase ${\varphi}_2^{{\beta(*)}_2}$. From our numerical results, the characteristics of ${\Gamma}^{\alpha}$ are shown to be significantly different from those of ${\Gamma}^{\beta}$ in the case of high polymers, and this would be the most apparent feature of the adsorption behavior of the polymer at a semi-permeable oil-water interface, which is sensitively dependent on ${\Delta}x_{\rho}$ and r.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.337-343
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• 2021

In this work, self-absorption correction factor related to the variation of the composition and the density of soil samples were evaluated using the p-type HPGe detector. The validated MCNP5 simulation model of this detector was used to evaluate its Full Energy Peak Efficiency (FEPE) under the variation of the composition and the density of the analysed samples. The results indicates that FEPE calculation of low gamma ray is affected by the composition and the density of soil samples. The self-absorption correction factors for different gamma-ray energies which was fitted as a function of FEPEs via density and energy and fitting parameters as polynomial function for the logarithm neper of gamma ray energy help to calculate quickly the detection efficiency of detector. Factor Analysis for the influence of the element composition in analysed samples on the FEPE indicates the FEPE distribution changes from non-metal to metal groups when the gamma ray energy increases from 92 keV to 238 keV. At energies above 238 keV, the FEPE primarily depends only on the metal elements and is significantly affected by aluminium and silicon composition in soil samples.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4057-4065
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• 2023

Organic scintillators are widely used for neutron/gamma detection. Pulse shape discrimination algorithms have been commonly used to discriminate the detected radiations. These algorithms have several limits, in particular with plastic scintillator which has lower discrimination ability, compared to liquid scintillator. Recently, machine learning (ML) models have been explored to enhance discrimination performance. Nevertheless, obtaining an accurate ML model or evaluating any discrimination approach requires a reference neutron dataset. The preparation of this is challenging because neutron sources are also gamma-ray emitters. Therefore, this paper proposes a pipeline to prepare clean labeled neutron/gamma datasets acquired by an organic scintillator. The method is mainly based on a Time of Flight setup and Tail-to-Total integral ratio (TTT_ratio) discrimination algorithm. In the presented case, EJ276 plastic scintillator and ²⁵²Cf source were used to implement the acquisition chain. The results showed that this process can identify and remove mislabeled samples in the entire ToF spectrum, including those that contribute to peak values. Furthermore, the process cleans ToF dataset from pile-up events, which can significantly impact experimental results and the conclusions extracted from them.

• Journal of Korean Academy of Nursing
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• v.41 no.4
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• pp.481-490
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• 2011

Purpose: The purpose of this study was to identify from the International Classification of Functioning model, factors influencing quality of life in elderly persons and to describe the concrete pathway of influence and the power of each variable. Methods: The sample included 334 elders who lived in 5 districts of D Metropolitan City. A structured questionnaire was used and the collected data were analyzed for fitness, using the AMOS 18.0 program. Results: This model was concise and extensive in predicting the quality of life of elders. The research verified the factors influencing quality of life for elders as direct factors such as activity of daily living (ADL) (${\beta}$=.13, t=2.47), leisure activity (${\beta}$=.55, t=5.04), social disengagement (${\beta}$=-.25, t=-2.25), and depression (${\beta}$=-.62, t=-10.86). Indirect factors including economic status (${\gamma}$=.17, p=.009), type of residence (${\gamma}$=.19, p=.004), ADL (${\gamma}$=.12, p=.027) were important factors in predicting quality of life for elders. These variables explained 75.6% of variance in the prediction model. Conclusion: The findings indicate a need for the nursing scientific community to develop intervention programs considering these variables to improve the quality of life for elders.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.10
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• pp.4329-4333
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• 2015

Background: To investigate the change of frequency and immuno-inhibitory function of myeloid-derived suppressor cells (MDSCs) after treatment of cisplatin (DDP) in A375 human melanoma model. Materials and Methods: BALB/c nude mice were inoculated with A375 cells to establish the human melanoma model and randomly divided into control group given normal saline (NS) and experimental group treated with DDP (5 mg/kg). The percentages of MDSCs in the tumor tissue and peripheral blood after DDP treatment were detected by flow cytometry. The proliferation and interferon-${\gamma}$ (IFN-${\gamma}$) secretion of T cells co-cultured with MDSCs were analyzed through carboxyfluorescein succinimidyl ester (CFSE) labeling assay and enzyme-linked immunospot (ELISPOT) assay, respectively. Results: In A375 human melanoma model, DDP treatment could significantly decrease the percentage of MDSCs in the tumor tissue, but exerted no effect on the level of MDSCs in peripheral blood. Moreover, DDP treatment could attenuate the immuno-inhibitory function of MDSCs. T cells co-cultured with DDP-treated MDSCs could dramatically elevate the proliferation and production of INF-${\gamma}$. Conclusions: DDP can decrease the frequency and attenuate immuno-inhibitory function of MDSCs in A375 melanoma model, suggesting a potential strategy to augment the efficacy of combined immunotherapy.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.95.1-95.1
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• 2012

Halo coronal mass ejections (HCMEs) are major cause of geomagnetic storms and their three dimensional structures are important for space weather. In this study, we compare three cone models: an elliptical cone model, an ice-cream cone model, and an asymmetric cone model. These models allow us to determine the three dimensional parameters of HCMEs such as radial speed, angular width, and the angle (${\gamma}$) between sky plane and cone axis. We compare these parameters obtained from three models using 62 well-observed HCMEs from 2001 to 2002. Then we obtain the root mean square error (RMS error) between maximum measured projection speeds and their calculated projection speeds from the cone models. As a result, we find that the radial speeds obtained from the models are well correlated with one another (R > 0.84). The correlation coefficients between angular widths are less than 0.53 and those between ${\gamma}$ values are less than 0.47, which are much smaller than expected. The reason may be due to different assumptions and methods. The RMS errors of the elliptical cone model, the ice-cream cone model, and the asymmetric cone model are 213 km/s, 254 km/s, and 267 km/s, respectively. Finally, we discuss their strengths and weaknesses in terms of space weather application.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.63-71
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• 1990

The hydrodynamic model parameters for the submicron GaAs simulation are calculated using the Monte Carlo method. $\Gamma$, L-, and X-valleys are included in the conduction band of GaAs, and polar optic phonon, acoustic phonon, equivalent intervalley, non-equivalent intervalley, ionized impurity, and piezoelectric scattering are taken into account. The velocity-electric field strength curve obtained in this paper is in good agreement with experimental one. We present the results in tabular form so that other participants can make use of them to simulate the submicron GaAs devices by the hydrodynamic model.