Hui-min Cao^1,2, Han-jun Zhao^2,3, Xin-e Yan^1,4

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.40, No.2, pp. 1-6, 2024, DOI:10.23967/j.rimni.2024.04.002 - 18 April 2024

Abstract Based on the Pasternak two-parameter foundation model, this study establishes a dynamic model for analyzing the deflection of slabs under moving loads. The variational method and reciprocal equal work theorem are employed to obtain the deflection solution, while the Matlab program is utilized with practical examples to calculate the foundation response modulus considering transfer shear force, bending moment, and their combined effects. By fitting measured dynamic deflections with theoretical predictions using the least square method, the response modulus K of the foundation is determined, demonstrating that our proposed model effectively captures the realistic behavior of More >

Xin Liu^1,*, Kai Yan², Bo Fang³, Xiaoyu Sun³, Daqiang Feng⁴, Li Yin⁵

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1539-1552, 2024, DOI:10.32604/fdmp.2024.047922 - 23 July 2024

Abstract In response to the complex characteristics of actual low-permeability tight reservoirs, this study develops a meshless-based numerical simulation method for oil-water two-phase flow in these reservoirs, considering complex boundary shapes. Utilizing radial basis function point interpolation, the method approximates shape functions for unknown functions within the nodal influence domain. The shape functions constructed by the aforementioned meshless interpolation method have δ-function properties, which facilitate the handling of essential aspects like the controlled bottom-hole flow pressure in horizontal wells. Moreover, the meshless method offers greater flexibility and freedom compared to grid cell discretization, making it simpler… More >

Wenyuan Chen¹, Tao Zhang², Yantao Yang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.09754

Abstract Based on the moving-least-squares immersed boundary method, we proposed a new technique to improve the calculation of the volume force representing the body boundary. For boundary with simple geometry, we theoretically analyze the error between the desired volume force at boundary and the actual force applied by the original method. The ratio between the two forces is very close to a constant and exhibits a very narrow distribution. A spatially uniform coefficient is then introduced to correct the force and can be fixed by the least-square method over all boundary markers. Such method is explicit… More >

Ting Cui, Xianfeng Zhou^*, Yufeng Huang, Yanting Guo, Yunrui Lin, Leyi Song, Jingcheng Zhang

Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2633-2648, 2023, DOI:10.32604/phyton.2023.029259 - 28 July 2023

Abstract Accurate assessment of canopy carotenoid content (CC_x+cC) in crops is central to monitor physiological conditions in plants and vegetation stress, and consequently supporting agronomic decisions. However, due to the overlap of absorption peaks of carotenoid (C_x+c) and chlorophyll (C_a), accurate estimation of carotenoid using reflectance where carotenoid absorb is challenging. The objective of present study was to assess CC_x+cC in winter wheat (Triticum aestivum L.) with ground- and aircraft-based hyperspectral measurements in the visible and near-infrared spectrum. In-situ hyperspectral reflectance were measured and airborne hyperspectral data were acquired during major growth stages of winter wheat in five consecutive… More >

Jiali Wang¹, Bing Li², Chengyu Qiu¹, Xinyun Zhang¹, Yuting Cheng¹, Peihua Wang¹, Ta Zhou³, Hong Ge², Yuanpeng Zhang^1,3,*, Jing Cai^3,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4843-4866, 2023, DOI:10.32604/cmc.2023.037457 - 29 April 2023

Abstract Epilepsy is a central nervous system disorder in which brain activity becomes abnormal. Electroencephalogram (EEG) signals, as recordings of brain activity, have been widely used for epilepsy recognition. To study epileptic EEG signals and develop artificial intelligence (AI)-assist recognition, a multi-view transfer learning (MVTL-LSR) algorithm based on least squares regression is proposed in this study. Compared with most existing multi-view transfer learning algorithms, MVTL-LSR has two merits: (1) Since traditional transfer learning algorithms leverage knowledge from different sources, which poses a significant risk to data privacy. Therefore, we develop a knowledge transfer mechanism that can More >

Giovanny Morocho, Diego Carrión¹

Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería, Vol.38, No.1, pp. 1-17, 2022, DOI:10.23967/j.rimni.2022.03.010 - 30 March 2022

Abstract The present research proposes to design and apply a state estimator algorithm in electrical power systems, applying the Weighted Least Squares methodology, through a process called non-linear hybrid estimator, the same one that uses measurements from PMUs and conventional measurements. in addition, to find the optimal PMU locations respecting the observability and redundancy restrictions for the Electric Power Systems, through mixed integer linear programming, considering the N-1 contingencies in the SEP. The proposed state estimator is adjusted to the measurements obtained, in the presence of contingencies in the SEP. The simulations obtained as a result More >

Mansour F. Yassen^1,2,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1691-1706, 2022, DOI:10.32604/cmc.2022.029701 - 18 May 2022

Abstract Quantifying the tool–tissue interaction forces in surgery can be utilized in the training of inexperienced surgeons, assist them better use surgical tools and avoid applying excessive pressures. The voltages read from strain gauges are used to approximate the unknown values of implemented forces. To this objective, the force-voltage connection must be quantified in order to evaluate the interaction forces during surgery. The progress of appropriate statistical learning approaches to describe the link between the genuine force applied on the tissue and numerous outputs obtained from sensors installed on surgical equipment is a key problem. In More >

P. R. Varshini^*, S. Baskar, M. Varatharajan, S. Sadhana

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1787-1799, 2022, DOI:10.32604/iasc.2022.024192 - 24 March 2022

Abstract

Flexibility and robust performance have made the FOPID (Fractional Order PID) controllers a better choice than PID (Proportional, Integral, Derivative) controllers. But the number of tuning parameters decreases the usage of FOPID controllers. Using synthetic data in available FOPID tuners leads to abnormal controller performances limiting their applicability. Hence, a new tuning methodology involving real-time data and overcomes the drawbacks of mathematical modeling is the need of the hour. This paper proposes a novel FOPID controller tuning methodology using machine learning algorithms. Feed Forward Back Propagation Neural Network (FFBPNN), Multi Least Squares Support Vector Regression

More >

M. Kavitha^*, M. Sujaritha

Computer Systems Science and Engineering, Vol.43, No.1, pp. 245-257, 2022, DOI:10.32604/csse.2022.023320 - 23 March 2022

Abstract Sensing the content of macronutrients in the agricultural soil is an essential task in precision agriculture. It helps the farmers in the optimal use of fertilizers. It reduces the cost of food production and also the negative environmental impacts on atmosphere and water bodies due to indiscriminate dosage of fertilizers. The traditional chemical-based laboratory soil analysis methods do not serve the purpose as they are hardly suitable for site specific soil management. Moreover, the spectral range used in the chemical-based laboratory soil analysis may be of 350–2500 nm, which leads to redundancy and confusion. Developing sensors… More >

Songlin Yang^1,2, Xingjin Han^1,2, Chufeng Kuang^1,2, Weihua Fang³, Jianfei Zhang⁴, Tiantang Yu^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 49-72, 2022, DOI:10.32604/cmes.2022.018325 - 24 January 2022

Abstract The deformation prediction models of Wuqiangxi concrete gravity dam are developed, including two statistical models and a deep learning model. In the statistical models, the reliable monitoring data are firstly determined with Lahitte criterion; then, the stepwise regression and partial least squares regression models for deformation prediction of concrete gravity dam are constructed in terms of the reliable monitoring data, and the factors of water pressure, temperature and time effect are considered in the models; finally, according to the monitoring data from 2006 to 2020 of five typical measuring points including J₂₃ (on dam section ),… More >