Xiaorui Zhang^1,2,*, Jiali Duan¹, Wei Sun², Tong Xu¹, Sunil Kumar Jha³

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 117-133, 2021, DOI:10.32604/cmes.2021.012034 - 30 March 2021

Abstract The cutting simulation of soft tissue is important in virtual surgery. It includes three major challenges in computation: Soft tissue simulation, collision detection, and handling, as well as soft tissue models. In order to address the earlier challenges, we propose a virtual cutting system based on the mass-spring model. In this system, MSM is utilized to simulate the soft tissue model. Residual stress is introduced to the model for simulating the shrinking effect of soft tissue in cutting. Second, a cylinder-based collision detection method is used to supervise the collision between surgical tools and soft More >

Caili Li¹, Dalin Tang^2,*,3, Jing Yao^4,*, Christopher Baird⁵, Haoliang Sun⁶, Chanjuan Gong⁷, Luyao Ma⁶, Yanjuan Zhang⁴, Liang Wang², Han Yu², Chun Yang⁸, Yongfeng Shao⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 159-174, 2021, DOI:10.32604/cmes.2021.014580 - 30 March 2021

Abstract Aortic valve replacement (AVR) remains a major treatment option for patients with severe aortic valve disease. Clinical outcome of AVR is strongly dependent on implanted prosthetic valve size. Fluid-structure interaction (FSI) aortic root models were constructed to investigate the effect of valve size on hemodynamics of the implanted bioprosthetic valve and optimize the outcome of AVR surgery. FSI models with 4 sizes of bioprosthetic valves (19 (No. 19), 21 (No. 21), 23 (No. 23) and 25 mm (No. 25)) were constructed. Left ventricle outflow track flow data from one patient was collected and used as… More >

Lijuan Kong^1,2, Haiye Yu^1,2, Zhaojia Piao^1,2, Meichen Chen^1,2, Jingmin Dang¹, Lei Zhang^1,2, Yuanyuan Sui^1,2,*

Phyton-International Journal of Experimental Botany, Vol.90, No.3, pp. 1015-1030, 2021, DOI:10.32604/phyton.2021.014190 - 30 March 2021

Abstract Haze is mainly caused by the suspended particulate matters in the air, of which the particulate matters pollution harms leaf vegetables. In this paper, oilseed rapes at four different growing periods were investigated in a simulated particulate pollution environment. In combination of hyper-spectral technology and micro examination, the response of hyper-spectral characteristics of the leaf to particulate matters was investigated in-depth. The hyperspectral, chlorophyll content, net photosynthetic rate and stomatal conductance of leaf were obtained. The deposition and adsorption of particulate matters on the leaf were observed by Environmental Scanning Electron Microscope (ESEM). Normalized difference… More >

Xueping Fan^*, Guanghong Yang, Zhipeng Shang, Xiaoxiong Zhao, Yuefei Liu^*

Structural Durability & Health Monitoring, Vol.15, No.1, pp. 69-83, 2021, DOI:10.32604/sdhm.2021.011922 - 22 March 2021

Abstract This article presented a new data fusion approach for reasonably predicting dynamic serviceability reliability of the long-span bridge girder. Firstly, multivariate Bayesian dynamic linear model (MBDLM) considering dynamic correlation among the multiple variables is provided to predict dynamic extreme deflections; secondly, with the proposed MBDLM, the dynamic correlation coefficients between any two performance functions can be predicted; finally, based on MBDLM and Gaussian copula technique, a new data fusion method is given to predict the serviceability reliability of the long-span bridge girder, and the monitoring extreme deflection data from an actual bridge is provided to More >

Haibo Liu^1,*, Yujie Dong², Fuzhong Wang¹

Energy Engineering, Vol.118, No.3, pp. 679-689, 2021, DOI:10.32604/EE.2021.014630 - 22 March 2021

Abstract For the problems of nonlinearity, uncertainty and low prediction accuracy in the gas outburst prediction of coal mining face, the least squares support vector machine (LSSVM) is proposed to establish the prediction model. Firstly, considering the inertia coefficients as global parameters lacks the ability to improve the solution for the traditional particle swarm optimization (PSO), an improved PSO (IPSO) algorithm is introduced to adjust different inertia weights in updating the particle swarm and solve the fitness to stagnate. Secondly, the penalty factor and kernel function parameter of LSSVM are searched automatically, and the regression accuracy More >

Vin Cent Tai^1,*, Yong Chai Tan¹, Nor Faiza Abd Rahman¹, Hui Xin Che², Chee Ming Chia², Lip Huat Saw³, Mohd Fozi Ali⁴

Energy Engineering, Vol.118, No.3, pp. 715-725, 2021, DOI:10.32604/EE.2021.014865 - 22 March 2021

Abstract Electricity demand is also known as load in electric power system. This article presents a Long-Term Load Forecasting (LTLF) approach for Malaysia. An Artificial Neural Network (ANN) of 5-layer Multi-Layered Perceptron (MLP) structure has been designed and tested for this purpose. Uncertainties of input variables and ANN model were introduced to obtain the prediction for years 2022 to 2030. Pearson correlation was used to examine the input variables for model construction. The analysis indicates that Primary Energy Supply (PES), population, Gross Domestic Product (GDP) and temperature are strongly correlated. The forecast results by the proposed… More >

Lu Li¹, Yuzhen Fan², Xinglang Su^1,*, Gefei Qiu¹

Energy Engineering, Vol.118, No.3, pp. 565-580, 2021, DOI:10.32604/EE.2021.014627 - 22 March 2021

Abstract Because of the randomness and uncertainty, integration of large-scale wind farms in a power system will exert significant influences on the distribution of power flow. This paper uses polynomial normal transformation method to deal with non-normal random variable correlation, and solves probabilistic load flow based on Kriging method. This method is a kind of smallest unbiased variance estimation method which estimates unknown information via employing a point within the confidence scope of weighted linear combination. Compared with traditional approaches which need a greater number of calculation times, long simulation time, and large memory space, Kriging More >

Chunhua Jin, Hanqing Hu^*

Energy Engineering, Vol.118, No.3, pp. 655-665, 2021, DOI:10.32604/EE.2021.014281 - 22 March 2021

Abstract With the increase of total energy consumption, eco-environmental quality drops sharply, which has attracted concerns from all circles. It has become the top priority of construction of socialist ecological civilization to clarify the influences of energy consumption on the level of eco-environmental pollution. Ecological environmental pollution control cannot be one size fits all. It can avoid resource depletion and environmental deterioration via adjusting measures to local conditions to coordinate ecological environmental pollution and energy consumption problems. In this essay, entropy method is adopted to measure the composite indexes of eco-environmental pollution of 30 provinces and… More >

Yi-Ming Huang¹, Xiao-Yu Li^1,*, Yi-Xuan Zhu¹, Hang Lei¹, Qing-Sheng Zhu², Shan Yang³

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 789-803, 2021, DOI:10.32604/cmc.2021.016663 - 22 March 2021

Abstract Quantum machine learning (QML) is a rapidly rising research field that incorporates ideas from quantum computing and machine learning to develop emerging tools for scientific research and improving data processing. How to efficiently control or manipulate the quantum system is a fundamental and vexing problem in quantum computing. It can be described as learning or approximating a unitary operator. Since the success of the hybrid-based quantum machine learning model proposed in recent years, we investigate to apply the techniques from QML to tackle this problem. Based on the Choi–Jamiołkowski isomorphism in quantum computing, we transfer… More >

Hegazy Rezk^1,2,*, Mohammed Mazen Alhato³, Mohemmed Alhaider¹, Soufiene Bouallègue^3,4

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 185-199, 2021, DOI:10.32604/cmc.2021.016175 - 22 March 2021

Abstract In this research paper, an improved strategy to enhance the performance of the DC-link voltage loop regulation in a Doubly Fed Induction Generator (DFIG) based wind energy system has been proposed. The proposed strategy used the robust Fractional-Order (FO) Proportional-Integral (PI) control technique. The FOPI control contains a non-integer order which is preferred over the integer-order control owing to its benefits. It offers extra flexibility in design and demonstrates superior outcomes such as high robustness and effectiveness. The optimal gains of the FOPI controller have been determined using a recent Manta Ray Foraging Optimization (MRFO) More >