Khaoula Ben Abdellafou¹, Kamel Zidi², Ahamed Aljuhani¹, Okba Taouali^1,*, Mohamed Faouzi Harkat³

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 3007-3023, 2025, DOI:10.32604/cmc.2025.063146 - 16 April 2025

Abstract Environmental protection requires identifying, investigating, and raising awareness about safeguarding nature from the harmful effects of both anthropogenic and natural events. This process of environmental protection is essential for maintaining human well-being. In this context, it is critical to monitor and safeguard the personal environment, which includes maintaining a healthy diet and ensuring plant safety. Living in a balanced environment and ensuring the safety of plants for green spaces and a healthy diet require controlling the nature and quality of the soil in our environment. To ensure soil quality, it is imperative to monitor and… More >

Xinrong Zhang¹, Bo Chang^2,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5079-5095, 2025, DOI:10.32604/cmc.2025.059469 - 06 March 2025

Abstract In the RSSI-based positioning algorithm, regarding the problem of a great conflict between precision and cost, a low-power and low-cost synergic localization algorithm is proposed, where effective methods are adopted in each phase of the localization process and fully use the detective information in the network to improve the positioning precision and robustness. In the ranging period, the power attenuation factor is obtained through the wireless channel modeling, and the RSSI value is transformed into distance. In the positioning period, the preferred reference nodes are used to calculate coordinates. In the position optimization period, Taylor… More >

Jianing Hao¹, Dan Yang², Guanxiong Ren¹, Ying Zhao³, Rangling Cao^4,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.1, pp. 141-159, 2025, DOI:10.32604/fdmp.2024.054469 - 24 January 2025

Abstract This study presents an innovative approach to calculating the failure probability of slopes by incorporating fuzzy limit-state functions, a method that significantly enhances the accuracy and efficiency of slope stability analysis. Unlike traditional probabilistic techniques, this approach utilizes a least squares support vector machine (LSSVM) optimized with a grey wolf optimizer (GWO) and K-fold cross-validation (CV) to approximate the limit-state function, thus reducing computational complexity. The novelty of this work lies in its application to one-dimensional (1D), two-dimensional (2D), and three-dimensional (3D) slope models, demonstrating its versatility and high precision. The proposed method consistently achieves… More > Graphic Abstract

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 >

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

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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 >