• 제목/요약/키워드: predictive ability

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Comparative Molecular Similarity Indices Analysis (CoMSIA) of 8-substituted-2-aryl-5-alkylaminoquinolines as Corticotropin-releasing factor-1 Receptor Antagonists

  • Nagarajan, Santhosh Kumar;Madhavan, Thirumurthy
    • Journal of Integrative Natural Science
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    • v.9 no.4
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    • pp.241-248
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    • 2016
  • Corticotropin-releasing factor receptors (CRFRs) activate the hypothalamic-pituitary-adrenal axis, which is an integral part of the fight or flight response to stress. Increase in CRH level is observed in Alzheimer's disease and major depression and hypoglycemia. Here, we report on the relevant physicochemical parameters required for the CRFR inhibitors. Comparative molecular similarity indices analysis (CoMSIA) was performed with the derivatives of 8-substituted-2-aryl-5-alkylaminoquinolinesas CRFR inhibitors. The best predictions were obtained for the best CoMSIA model with a $q^2$ of 0.576 with 6 components and $r^2$ of 0.977. The statistical parameters from the generated CoMSIA models indicated that the data are well fitted and have high predictive ability. CoMSIA contour maps could be useful in the designing of more potent and novel CRFR derivatives.

Leave-one-out Bayesian model averaging for probabilistic ensemble forecasting

  • Kim, Yongdai;Kim, Woosung;Ohn, Ilsang;Kim, Young-Oh
    • Communications for Statistical Applications and Methods
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    • v.24 no.1
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    • pp.67-80
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    • 2017
  • Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

An Implementatin of a Multi-Channel Speech Surveillance System Over Telephone Lines

  • Kim, Sung-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.4E
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    • pp.17-21
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    • 1998
  • This paper presents an implementation of a multi-channel speech surveillance system over telephone lines using TMS320C31 DSP chips. The incoming speech into each telephone line are first compressed simultaneously in real-time by the popular vector-sum excited linear predictive (VSELP) speech coding algorithm at the rate of 8 Kbps. The compressed steech bit streams are then multiplexed with those of other users. The multiplexed speech bit streams are transferred to the system storage equipments with some other required information so that a system operator can later monitor the stored speech data whenever it is necessary. The host program runs under Microsoft Windows95 for an efficient man-machine interface and a future upgrade-ability. We have confirmed that the overall 64-channel system operates satisfactorily in realtime. We also have checked approximately up to 2,880 total hours of recording capability of the system on a playback module and two removable backup drives.

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Quantitative Structure-Activity Relationships and Molecular Docking Studies of P56 LCK Inhibitors

  • Bharatham, Nagakumar;Bharatham, Kavitha;Lee, Keun-Woo
    • Bulletin of the Korean Chemical Society
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    • v.27 no.2
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    • pp.266-272
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    • 2006
  • Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for 67 molecules of 2-amino-benzothiazole-6-anilide derivatives against lymphocyte-specific protein tyrosine kinase (P56 LCK). The molecular field analysis (MFA) and receptor surface analysis (RSA) were employed for QSAR studies and the predictive ability of the model was validated by 15 test set molecules. Structure-based investigations using molecular docking simulation were performed with the crystal structure of P56 LCK. Good correlation between predicted fitness scores versus observed activities was demonstrated. The results suggested that the nature of substitutions at the 2-amino and 6-anilide positions were crucial in enhancing the activity, thereby providing new guidelines for the design of novel P56 LCK inhibitors.

The Study of Adjusting the Cost Matrix in Loss Function Approach for Multiresponse Optimization (다중 반응 변수 문제 해결을 위한 손실 함수 방법에서 비용 행렬의 보정에 관한 연구)

  • Lee Dae-Won;Kim So-Hui;Kim Gwang-Jae;Lee Jae-Uk
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.10a
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    • pp.31-34
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    • 2004
  • For solving multiresponse problems, a variety of loss function approaches have been proposed assuming that a cost matrix is known and fixed. However a cost matrix is also an important factor in loss function approaches, because the optimal solution is very sensitive to the cost matrix. In this paper. we propose a novel method for adjusting the cost matrix by considering the predictive ability of the estimated response models. Simulation results for the generated data set show that the proposed method is competitive with previously reported methods.

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Interrelation of Retention Factor of Amino-Acids by QSPR and Linear Regression

  • Lee, Seung-Ki;Polyakova, Yulia;Row, Kyung-Ho
    • Bulletin of the Korean Chemical Society
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    • v.24 no.12
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    • pp.1757-1762
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    • 2003
  • The interrelation between retention factors of several L-amino acids and their physico-chemical and structural properties can be determined in chromatographic research. In this paper we describe a predictor for retention factors with various properties of the L-amino acids. Eighteen L-amino acids are included in this study, and retention factors are measured experimentally by RP-HPLC. Binding energy ($E_b$), hydrophobicity (log P), molecular refractivity (MR), polarizability (${\alpha}$), total energy ($E_t$), water solubility (log S), connectivity index (${\chi}$) of different orders and Wiener index (w) are theoretically calculated. Relationships between these properties and retention factors are established, and their predictive and interpretive ability are evaluated. The equation of the relationship between retention factors and various descriptors of L-amino acids is suggested as linear and multiple linear form, and the correlation coefficients estimated are relatively higher than 0.90.

Implementation of Fuzzy Self-Organizing Networks Algorithm and Its Application to Nonlinear Systems (퍼지 자기구성 네트워크 알고리즘의 구현 및 비선형 시스템으로의 응용)

  • Park, Byoung-Jun;Kim, Dong-Won;Lee, Dae-Keun;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.3001-3003
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    • 2000
  • In this paper. we propose Fuzzy Self-Organizing Networks (FSON) using both Polynomial Neural Networks(PNN) and Fuzzy Neural Networks(FNN) for model identification of complex and nonlinear systems. The proposed FSON is generated from the mutually combined structure of both FNN and PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get the better output performance with superb predictive ability. In order to evaluate the performance of proposed models. we use the nonlinear data sets. The results show that the proposed FSON can produce the model with higher accuracy and more robustness than previous any other method.

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Understanding the Mapping Principle of One Syllable One Character as a Predictor of Word Reading Development in Chinese

  • Lin, Dan;Shiu, Ling-Po;Liu, Yingyi
    • Child Studies in Asia-Pacific Contexts
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    • v.6 no.2
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    • pp.73-85
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    • 2016
  • Speech-print mapping awareness is defined as the awareness of the principles underpinning how speech sound is matched to print symbols. Chinese is unique in that it follows the one syllable one character mapping principle. The present study examined the predictive power of speech-print mapping awareness in young children's word reading. Seventy-four Hong Kong children from the first and second kindergarten years were tested with phonological awareness, visual skills, syllable-level mapping awareness, and Chinese reading ability at Time 1. Chinese reading abilities were tested again 1 year later. It was found that syllable-level mapping awareness predicted Chinese word reading abilities 12 months later. Further, it seemed that the link of syllable mapping to Chinese reading is particularly significant for beginning readers. The findings suggest that understanding the language-specific speech-print mapping principle is critical for reading acquisition at the early stage of reading development.

Foreign Exchange Rate Uncertainty in Korea

  • Lee, Seojin
    • East Asian Economic Review
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    • v.24 no.2
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    • pp.165-184
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    • 2020
  • Applying Ismailov and Rossi (2018), I newly construct the Korea FX uncertainty based on the density distribution of historical forecast errors. This uncertainty index properly captures the rare but significant events in the Korean currency market and provides information distinct from other uncertainty measures in recent studies. I show that 1) FX uncertainty arising from unexpected depreciation has a stronger impact on Korea-U.S. exchange rates and that 2) macro variables, such as capital flows or interest rate differentials, have predictive ability regarding Korea FX uncertainty for short horizons. These findings enable us to predict the events of sudden currency crashes and understand the Korea-U.S. exchange rate dynamics.

Particle tracking acceleration via signed distance fields in direct-accelerated geometry Monte Carlo

  • Shriwise, Patrick C.;Davis, Andrew;Jacobson, Lucas J.;Wilson, Paul P.H.
    • Nuclear Engineering and Technology
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    • v.49 no.6
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    • pp.1189-1198
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    • 2017
  • Computer-aided design (CAD)-based Monte Carlo radiation transport is of value to the nuclear engineering community for its ability to conduct transport on high-fidelity models of nuclear systems, but it is more computationally expensive than native geometry representations. This work describes the adaptation of a rendering data structure, the signed distance field, as a geometric query tool for accelerating CAD-based transport in the direct-accelerated geometry Monte Carlo toolkit. Demonstrations of its effectiveness are shown for several problems. The beginnings of a predictive model for the data structure's utilization based on various problem parameters is also introduced.