Ruiguo Yu^1,2, Zhiqiang Liu^1,2, Jianrong Wang^1,3, Mankun Zhao^1,2, Jie Gao^1,3, Mei Yu^1,3,*

Computer Systems Science and Engineering, Vol.33, No.4, pp. 267-274, 2018, DOI:10.32604/csse.2018.33.267

Abstract The spatio-temporal feature with historical wind power information and spatial information can effectively improve the accuracy of wind power prediction, but the role of the spatio-temporal feature has not yet been fully discovered. This paper investigates the variance of the spatio-temporal feature. Based on this, a hybrid machine learning method for wind power prediction is designed. First, the training set is divided into several groups according to the variance of the input pattern, and then each group is used to train one or more predictors respectively. Multiple machine learning methods, such as the support vector machine regression and the decision… More >

Lujie Chen¹, Liang Zheng¹, Maosen Lian¹, Shouhua Luo^1,*

Molecular & Cellular Biomechanics, Vol.17, No.2, pp. 85-92, 2020, DOI: 10.32604/mcb.2019.07386

Abstract Micro-CT provides a high-resolution 3D imaging of micro-architecture in a non-invasive way, which becomes a significant tool in biomedical research and preclinical applications. Due to the limited power of micro-focus X-ray tube, photon starving occurs and noise is inevitable for the projection images, resulting in the degradation of spatial resolution, contrast and image details. In this paper, we propose a C-GAN (Conditional Generative Adversarial Nets) denoising algorithm in projection domain for Micro-CT imaging. The noise statistic property is utilized directly and a novel variance loss is developed to suppress the blurry effects during denoising procedure. Conditional Generative Adversarial Networks (C-GAN)… More >

Ling Ding^{1, 2}, Huyin Zhang^{1, *}, Jinsheng Xiao³, Junfeng Lei³, Fang Xu³, Shejie Lu²

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 675-690, 2020, DOI:10.32604/cmes.2020.07987

Abstract The ultimate goal of image denoising from video is to improve the given image, which can reduce noise interference to ensure image quality. Through denoising technology, image quality can have effectively optimized, signal-to-noise ratio can have increased, and the original mage information can have better reflected. As an important preprocessing method, people have made extensive research on image denoising algorithm. Video denoising needs to take into account the various level of noise. Therefore, the estimation of noise parameters is particularly important. This paper presents a noise estimation method based on variance stability transformation, which estimates the parameters of variance stability… More >

Baichun Gong¹, Shuang Li^{1, *}, Lili Zheng², Jinglang Feng³

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 221-234, 2020, DOI:10.32604/cmes.2020.07769

Abstract A closed-form solution to the angles-only initial relative orbit determination (IROD) problem for space rendezvous with non-cooperated target is developed, where a method of hybrid dynamics with the concept of virtual formation is introduced to analytically solve the problem. Emphasis is placed on developing the solution based on hybrid dynamics (i.e., Clohessy-Wiltshire equations and two-body dynamics), obtaining formation geometries that produce relative orbit state observability, and deriving the approximate analytic error covariance for the IROD solution. A standard Monte Carlo simulation system based on two-body dynamics is used to verify the feasibility and evaluate the performance proposed algorithms. The sensitivity… More >

Gaspar-Peralta P¹, JC Carrillo-Rodríguez¹, JL Chávez-Servia, AM Vera-Guzmán², I Pérez-León¹

Phyton-International Journal of Experimental Botany, Vol.81, pp. 15-22, 2012, DOI:10.32604/phyton.2012.81.015

Abstract In order to evaluate the agronomic behavior, genotypic variation, lycopene content, and other components of fruit quality, eight advanced tomato lines were planted in greenhouses during two crop cycles, August-December 2008 and February-July 2009. Tomato lines showed significant differences in leaf length (LL), stem diameter (SD), number of flowers per branch (FLNB), number of fruits per branch (FRNB), locules per fruit (LPF), and fruit length (FRL), and the greatest phenotypic expression in fruit traits was quantified in August-December 2008. Environmental variance was significantly higher than the genotypic and genotype-environment interaction variances in LL, FRNB, fruits per plant, average weight of… More >

Antuna Grijalva O¹, SA Rodríguez Herrera¹, A Espinoza Banda¹, P Cano Ríos¹, G Llaven Valencia², JL Coyac Rodríguez¹, A González Torres¹, DG Reta Sánchez³, M Mendoza Elos⁴, E Andrio Enríquez⁴

Phyton-International Journal of Experimental Botany, Vol.86, pp. 246-251, 2017, DOI:10.32604/phyton.2017.86.246

Abstract Knowledge of the genetic components of agronomic traits is an important factor to characterize landraces of maize to make them useful in plant breeding programs. The objective of this work was to know the genetic action and combining ability of several agronomic traits of five maize races and their crosses. Maize landraces analyzed were Jala, Tuxpeño, Celaya, Pepitilla and Dulce. Plant height, days to male and female flowering date after planting, and dry matter and grain yields were recorded. Those variables showed highly significant differences among genotypes. With the exception of dry matter yield, the other variables showed significant general… More >

Longqing Zhang¹, Liping Bai^1,*, Xinwei Zhang², Yanghong Zhang², Feng Sun², Changcheng Chen²

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1175-1187, 2019, DOI:10.32604/cmc.2019.06075

Abstract Based on the two-dimensional relation table, this paper studies the missing values in the sample data of land price of Shunde District of Foshan City. GeoDa software was used to eliminate the insignificant factors by stepwise regression analysis; NORM software was adopted to construct the multiple imputation models; EM algorithm and the augmentation algorithm were applied to fit multiple linear regression equations to construct five different filling datasets. Statistical analysis is performed on the imputation data set in order to calculate the mean and variance of each data set, and the weight is determined according to the differences. Finally, comprehensive… More >

Dong-Hoon Kim¹, Sang-Wook Lee¹, Dong-Ik Cheon¹, Hwa-Suk Oh¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.11, No.2, pp. 33-34, 2009, DOI:10.3970/icces.2009.011.033

Abstract In general, accurate attitude information is essential to perform the mission. Two algorithms are well-known to determine the attitude through two or more vector observations. One is deterministic method such as TRIAD algorithm, the other is optimal method such as QUEST algorithm. This paper suggests the idea to improve performance of the TRIAD algorithm and to determine the attitude by combination of different sensors. First, we change the attitude matrix to Euler angle instead of using orthogonalization method and also use covariance in place of variance, then apply an unbiased minimum variance formula for more accurate solutions. We also suggest… More >

Judith Su^∗, Ricardo R. Brau^†, Xingyu Jiang^‡, George M. Whitesides^§, Matthew J. Lang^¶, Peter T. C. So^||

Molecular & Cellular Biomechanics, Vol.4, No.2, pp. 105-118, 2007, DOI:10.3970/mcb.2007.004.105

Abstract During migration, asymmetrically polarized cells achieve motion by coordinating the protrusion and retraction of their leading and trailing edges, respectively. Although it is well known that local changes in the dynamics of actin cytoskeleton remodeling drive these processes, neither the cytoskeletal rheological properties of these migrating cells are well quantified nor is it understand how these rheological properties are regulated by underlying molecular processes. In this report, we have used soft lithography to create morphologically polarized cells in order to examine rheological differences between the front and rear zone of an NIH 3T3 cell posed for migration. In addition, we… More >

R. E. Jones^1,*, J. A. Templeton¹, C. M. Sanders¹, J. T. Ostien¹

CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.3, pp. 309-342, 2018, DOI:10.31614/cmes.2018.04285

Abstract We use machine learning (ML) to infer stress and plastic flow rules using data from representative polycrystalline simulations. In particular, we use so-called deep (multilayer) neural networks (NN) to represent the two response functions. The ML process does not choose appropriate inputs or outputs, rather it is trained on selected inputs and output. Likewise, its discrimination of features is crucially connected to the chosen inputoutput map. Hence, we draw upon classical constitutive modeling to select inputs and enforce well-accepted symmetries and other properties. In the context of the results of numerous simulations, we discuss the design, stability and accuracy of… More >