Haijie Pan, Lirong Zheng^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 493-512, 2022, DOI:10.32604/cmes.2022.019069

Abstract The machine learning model converges slowly and has unstable training since large variance by random using a sample estimate gradient in SGD. To this end, we propose a noise reduction method for Stochastic Variance Reduction gradient (SVRG), called N-SVRG, which uses small batches samples instead of all samples for the average gradient calculation, while performing an incremental update of the average gradient. In each round of iteration, a small batch of samples is randomly selected for the average gradient calculation, while the average gradient is updated by rounding of the past model gradients during internal iterations. By suitably reducing the… More >

Meng Da¹, Huiqin Wang^1,*, Ke Wang¹, Zhan Wang²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 513-527, 2022, DOI:10.32604/cmes.2022.019040

Abstract The properties of the same pigments in murals are affected by different concentrations and particle diameters, which cause the shape of the spectral reflectance data curve to vary, thus influencing the outcome of matching calculations. This paper proposes a spectral matching classification method of multi-state similar pigments based on feature differences. Fast principal component analysis (FPCA) was used to calculate the eigenvalue variance of pigment spectral reflectance, then applied to the original reflectance values for parameter characterization. We first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify the spectral curve. Secondly, the… More >

Ibrahim El rube'^*, Sameer Alsharif

Computer Systems Science and Engineering, Vol.42, No.1, pp. 407-421, 2022, DOI:10.32604/csse.2022.022400

Abstract This article presents a method for the description of key points using simple statistics for regions controlled by neighboring key points to remedy the gap in existing descriptors. Usually, the existent descriptors such as speeded up robust features (SURF), Kaze, binary robust invariant scalable keypoints (BRISK), features from accelerated segment test (FAST), and oriented FAST and rotated BRIEF (ORB) can competently detect, describe, and match images in the presence of some artifacts such as blur, compression, and illumination. However, the performance and reliability of these descriptors decrease for some imaging variations such as point of view, zoom (scale), and rotation.… More >

Shufang Song^1,*, Ruyang He¹, Zhaoyin Shi¹, Weiya Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 65-85, 2021, DOI:10.32604/cmes.2021.015378

Abstract The variable importance measure (VIM) can be implemented to rank or select important variables, which can effectively reduce the variable dimension and shorten the computational time. Random forest (RF) is an ensemble learning method by constructing multiple decision trees. In order to improve the prediction accuracy of random forest, advanced random forest is presented by using Kriging models as the models of leaf nodes in all the decision trees. Referring to the Mean Decrease Accuracy (MDA) index based on Out-of-Bag (OOB) data, the single variable, group variables and correlated variables importance measures are proposed to establish a complete VIM system… More >

Narjes Benameur^1,*, Mazin Abed Mohammed², Ramzi Mahmoudi^3,4, Younes Arous⁵, Begonya Garcia-Zapirain⁶, Karrar Hameed Abdulkareem⁷, Mohamed Hedi Bedoui³

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1233-1252, 2021, DOI:10.32604/cmc.2021.016860

Abstract Left ventricular (LV) dysfunction is mainly assessed by global contractile indices such as ejection fraction and LV Volumes in cardiac MRI. While these indices give information about the presence or not of LV alteration, they are not able to identify the location and the size of such alteration. The aim of this study is to compare the performance of three parametric imaging techniques used in cardiac MRI for the regional quantification of cardiac dysfunction. The proposed approaches were evaluated on 20 patients with myocardial infarction and 20 subjects with normal function. Three parametric images approaches: covariance analysis, parametric images based… More >

Usman Shahzad^1,2,*, Ishfaq Ahmad¹, Ibrahim Mufrah Almanjahie^3,4, Nadia H.Al –Noor⁵

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3411-3430, 2021, DOI:10.32604/cmc.2021.017046

Abstract Variance is one of the most vital measures of dispersion widely employed in practical aspects. A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the presence of extreme values, and thus its results cannot be relied on. Finding momentum from Koyuncu’s recent work, the present paper focuses first on proposing two classes of variance estimators based on linear moments (L-moments), and then employing them with auxiliary data under double stratified sampling to introduce a new class of calibration variance estimators using important properties of L-moments (L-location, L-cv, L-variance). Three populations are… More >

Kuipeng Li^1,2, Hua Han¹, Yunhui Xie¹, Xiaomei Sun^1,*

Phyton-International Journal of Experimental Botany, Vol.90, No.2, pp. 583-593, 2021, DOI:10.32604/phyton.2021.013912

Abstract Optimization of in vitro adventitious root induction contributes to the development of a large-scale production system of hybrid clone seedlings of larch (Larix spp.). We used orthogonal testing to investigate the factors that affect the rooting of hybrid larch shoots–activated carbon, vitamin B1, sucrose, glycine, glutamic acid (Glu), cysteine, pH, and induction time in the dark and indole-3-butyric acid (IBA). Variance analysis showed that the effects of sucrose concentration on rooting rate, survival rate, and average root number, pH on the average number of roots; and Glu on survival rate were all significant (p < 0.05) when compared to the… More >

Usman Shahzad^1,2,*, Ishfaq Ahmad¹, Ibrahim Mufrah Almanjahie^3,4, Nadia H. Al Noor⁵, Muhammad Hanif²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3013-3028, 2021, DOI:10.32604/cmc.2021.014101

Abstract Variance is one of the most important measures of descriptive statistics and commonly used for statistical analysis. The traditional second-order central moment based variance estimation is a widely utilized methodology. However, traditional variance estimator is highly affected in the presence of extreme values. So this paper initially, proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics (L-location, L-scale, L-CV) and auxiliary information. It is demonstrated that the proposed L-Moments based calibration variance estimators are more efficient than… More >

S. Abdel-Khalek^1,2,*, E. M. Khalil^1,3, Beida Alsubei¹, A. Al-Barakaty⁴, S. M. Abo Dahab⁵

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2445-2456, 2021, DOI:10.32604/cmc.2021.013830

Abstract In this paper, we analyzed squeezing in the information entropy, quantum state fidelity, and qubit-qubit entanglement in a time-dependent system. The proposed model consists of two qubits that interact with a two-mode electromagnetic field under the dissipation effect. An analytical solution is calculated by considering the constants for the equations of motion. The effect of the general form of the time-dependent for qubit-field coupling and the dissipation term on the temporal behavior of the qubit-qubit entanglement, quantum state fidelity, entropy, and variance squeezing are examined. It is shown that the intervals of entanglement caused more squeezing for the case of… More >

Wenting Qiao^1,2, Xiaoguang Wu^1,*, Wen Sun³, Qiande Wu^4,*

Structural Durability & Health Monitoring, Vol.14, No.4, pp. 355-374, 2020, DOI:10.32604/sdhm.2020.011479

Abstract To solve the problem that the digital image recognition accuracy of concrete structure cracks is not high under the condition of uneven illumination and complex surface color of concrete structure, this paper has proposed a block segmentation method of maximum entropy threshold based on the digital image data obtained by the ACTIS automatic detection system. The steps in this research are as follows: 1. The crack digital images of concrete specimens with typical features were collected by using the Actis system of KURABO Co., Ltd., of Japan in the concrete beam bending test. 2. The images are segmented into blocks… More >