Thomas Leduc, Xenia Stavropulos-Laffaille, Ignacio Requena-Ruiz

Revue Internationale de Géomatique, Vol.31, No.2, pp. 241-263, 2022, DOI:10.3166/RIG.31.241-263©2022

Abstract The adaptation of public spaces to episodes of intense heat is now a major challenge for cities. With this in mind, this article presents a contribution aimed at delineating and handling the shadows on the ground or in a horizontal plane at a given height, whether it comes from buildings, street furniture or the tree cover. After a comparison with shadows obtained via two reference tools, we present two urban sites that mix shadows of different origins and, in addition, different indicators. The results of the simulations are compared with pyranometric surveys carried out on site. The aim of these… More >

Borja Bordel Sánchez^1,*, Ramón Alcarria², Tomás Robles¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3189-3218, 2023, DOI:10.32604/cmc.2023.039466

Abstract Cyber-Physical Systems are very vulnerable to sparse sensor attacks. But current protection mechanisms employ linear and deterministic models which cannot detect attacks precisely. Therefore, in this paper, we propose a new non-linear generalized model to describe Cyber-Physical Systems. This model includes unknown multivariable discrete and continuous-time functions and different multiplicative noises to represent the evolution of physical processes and random effects in the physical and computational worlds. Besides, the digitalization stage in hardware devices is represented too. Attackers and most critical sparse sensor attacks are described through a stochastic process. The reconstruction and protection mechanisms are based on a weighted… More >

Tao Yin¹, Changgen Peng^2,*, Weijie Tan³, Dequan Xu⁴, Hanlin Tang⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 827-843, 2024, DOI:10.32604/cmes.2023.029039

Abstract In the assessment of car insurance claims, the claim rate for car insurance presents a highly skewed probability distribution, which is typically modeled using Tweedie distribution. The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset, when the data is provided by multiple parties, training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge. To address this issue, this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos. The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection… More >

Sunil Kumar Suryawanshi¹, Usha Chouhan², Jyoti Kant Choudhari^2,*

Molecular & Cellular Biomechanics, Vol.19, No.4, pp. 191-208, 2022, DOI:10.32604/mcb.2022.023911

Abstract Cancer is the second biggest cause of death globally, and the use of therapeutic peptides to specifically target and destroy cancer cells has gotten much interest. Cancer peptides or vaccinations are utilized to treat cancer nowadays, apart from chemotherapy, which has significant discomfort, side effects and costly. It is time demanding to identify and predict potential anticancer peptides using computational biology approaches. Thus, 3-D molecular modeling is being used to find possible ACP candidates. In this research, Curcuma longa has predicted peptide sequences were docked on breast cancer receptors and used a molecular docking technique to assess the anticipated peptides’… More >

Heba A. Elzeheiry^*, Sherief Barakat, Amira Rezk

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1283-1305, 2022, DOI:10.32604/cmc.2022.027345

Abstract Electronic Health Records (EHRs) are the digital form of patients’ medical reports or records. EHRs facilitate advanced analytics and aid in better decision-making for clinical data. Medical data are very complicated and using one classification algorithm to reach good results is difficult. For this reason, we use a combination of classification techniques to reach an efficient and accurate classification model. This model combination is called the Ensemble model. We need to predict new medical data with a high accuracy value in a small processing time. We propose a new ensemble model MDRL which is efficient with different datasets. The MDRL… More >

Prem Junswang¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Soheil Salahshour⁴, Thongchai Botmart^5,*, Wajaree Weera⁵

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5823-5843, 2022, DOI:10.32604/cmc.2022.027629

Abstract A novel design of the computational intelligent framework is presented to solve a class of host-vector-predator nonlinear model governed with set of ordinary differential equations. The host-vector-predator nonlinear model depends upon five groups or classes, host plant susceptible and infected populations, vectors population of susceptible and infected individuals and the predator population. An unsupervised artificial neural network is designed using the computational framework of local and global search competencies of interior-point algorithm and genetic algorithms. For solving the host-vector-predator nonlinear model, a merit function is constructed using the differential model and its associated boundary conditions. The optimization of this merit… More >

JUAN CARLOS STOCKERT^1,2,*, ALFONSO BLÁZQUEZ-CASTRO³

BIOCELL, Vol.46, No.6, pp. 1391-1415, 2022, DOI:10.32604/biocell.2022.019493

Abstract

Melanins represent one of the most ancient and important group of natural macromolecular pigments. They have multiple biological roles in almost all organisms across the Phyla, examples being photoprotection, anti-oxidative action, radical scavenger activity, and heavy metal removal. From the biomedical point of view, melanocytes are involved in the origin of melanoma tumors, and the main therapeutic advances for their treatment have been revised in Part 1 of this review. The chemical structure of eumelanin is a biological concern of great importance, and therefore, exploring theoretical molecular models and synthesis mechanisms will be here described, as well as molecular orbital… More >

Bei Liu¹, Xian Zhang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1547-1563, 2022, DOI:10.32604/cmes.2022.018130

Abstract During high-intensity focused ultrasound (HIFU) treatment, the accurate identification of denatured biological tissue is an important practical problem. In this paper, a novel method based on the improved variational mode decomposition (IVMD) and autoregressive (AR) model was proposed, which identified denatured biological tissue according to the characteristics of ultrasonic scattered echo signals during HIFU treatment. Firstly, the IVMD method was proposed to solve the problem that the VMD reconstruction signal still has noise due to the limited number of intrinsic mode functions (IMF). The ultrasonic scattered echo signals were reconstructed by the IVMD to achieve denoising. Then, the AR model… More >

Van-Phuong Ta^*, Dinh-Nhon Truong, Nguyen-Thanh Nhan

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1605-1615, 2022, DOI:10.32604/iasc.2022.022374

Abstract Water Distribution System (WDS) is one of the important phases of the Water Treatment Plant (WTP) and plays a crucial role in plant, animal, and human life. The WDS aims not only to supply a continuous, stable water amount but also to reduce energy consumption as little as possible during operation. To keep the continuous, stable water amount, the water pressure in the pipe network of the WDS must be maintained at desired set points under the effecting of uncertainties, disturbances, and noises. For saving the energy requirement, a Variable Frequency Driver (VFD) was utilized to control the speed of… More >

Zulqurnain Sabir¹, Muhammad Umar¹, Muhammad Asif Zahoor Raja^2,*, Dumitru Baleanu^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 227-251, 2021, DOI:10.32604/cmes.2021.016611

Abstract The presented research aims to design a new prevention class (P) in the HIV nonlinear system, i.e., the HIPV model. Then numerical treatment of the newly formulated HIPV model is portrayed handled by using the strength of stochastic procedure based numerical computing schemes exploiting the artificial neural networks (ANNs) modeling legacy together with the optimization competence of the hybrid of global and local search schemes via genetic algorithms (GAs) and active-set approach (ASA), i.e., GA-ASA. The optimization performances through GA-ASA are accessed by presenting an error-based fitness function designed for all the classes of the HIPV model and its corresponding… More >