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  • Open Access


    Impact of the Railway Vehicle Characteristics in Its Runnability in the Presence of Strong Winds

    Pedro Montenegro1,*, Raphael Heleno2, Hermes Carvalho2, Diogo Ribeiro3, Rui Calçada1, Chris Baker4

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.24, No.1, pp. 1-2, 2022, DOI:10.32604/icces.2022.08678

    Abstract This work consists of evaluating the impact of the most relevant characteristics of railway vehicles, namely geometric, mechanical and aerodynamic properties, in their runnability in the presence of strong winds, more precisely in the risk of derailment. Such objective is achieved by performing several dynamic with a non-linear vehicle-structure interaction model developed by the authors [1,2] and used in other works in this field [3,4], which allows the evaluation of the wheel-rail contact forces and, consequently, the unloading index, as suggested by the European Norm EN 14067-6 [5]. The calculations are carried out for several scenarios characterized by different train… More >

  • Open Access


    Strategy for Rapid Diabetic Retinopathy Exposure Based on Enhanced Feature Extraction Processing

    V. Banupriya1,*, S. Anusuya2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5597-5613, 2023, DOI:10.32604/cmc.2023.038696

    Abstract In the modern world, one of the most severe eye infections brought on by diabetes is known as diabetic retinopathy (DR), which will result in retinal damage, and, thus, lead to blindness. Diabetic retinopathy (DR) can be well treated with early diagnosis. Retinal fundus images of humans are used to screen for lesions in the retina. However, detecting DR in the early stages is challenging due to the minimal symptoms. Furthermore, the occurrence of diseases linked to vascular anomalies brought on by DR aids in diagnosing the condition. Nevertheless, the resources required for manually identifying the lesions are high. Similarly,… More >

  • Open Access


    An Endogenous Feedback and Entropy Analysis in Machine Learning Model for Stock’s Return Forecast

    Edson Vinicius Pontes Bastos1,*, Jorge Junio Moreira Antunes2, Lino Guimarães Marujo1, Peter Fernandes Wanke2, Roberto Ivo da Rocha Lima Filho1

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3175-3190, 2023, DOI:10.32604/iasc.2023.034582

    Abstract Stock markets exhibit Brownian movement with random, non-linear, uncertain, evolutionary, non-parametric, nebulous, chaotic characteristics and dynamism with a high degree of complexity. Developing an algorithm to predict returns for decision-making is a challenging goal. In addition, the choice of variables that will serve as input to the model represents a non-triviality, since it is possible to observe endogeneity problems between the predictor and the predicted variables. Thus, the goal is to analyze the endogenous origin of the stock return prediction model based on technical indicators. For this, we structure a feed-forward neural network. We evaluate the endogenous feedback between the… More >

  • Open Access


    Robust Image Watermarking Using LWT and Stochastic Gradient Firefly Algorithm

    Sachin Sharma1,*, Meena Malik2, Chander Prabha3, Amal Al-Rasheed4, Mona Alduailij4, Sultan Almakdi5

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 393-407, 2023, DOI:10.32604/cmc.2023.033536

    Abstract Watermarking of digital images is required in diversified applications ranging from medical imaging to commercial images used over the web. Usually, the copyright information is embossed over the image in the form of a logo at the corner or diagonal text in the background. However, this form of visible watermarking is not suitable for a large class of applications. In all such cases, a hidden watermark is embedded inside the original image as proof of ownership. A large number of techniques and algorithms are proposed by researchers for invisible watermarking. In this paper, we focus on issues that are critical… More >

  • Open Access


    Optimal Strategies Trajectory with Multi-Local-Worlds Graph

    Xiang Yu1, Chonghua Wang2, Xiaojing Zheng3,*, Chaoyu Zeng4, Brij B. Gupta5,6,7

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2079-2099, 2023, DOI:10.32604/cmc.2023.034118

    Abstract This paper constructs a non-cooperative/cooperative stochastic differential game model to prove that the optimal strategies trajectory of agents in a system with a topological configuration of a Multi-Local-World graph would converge into a certain attractor if the system’s configuration is fixed. Due to the economics and management property, almost all systems are divided into several independent Local-Worlds, and the interaction between agents in the system is more complex. The interaction between agents in the same Local-World is defined as a stochastic differential cooperative game; conversely, the interaction between agents in different Local-Worlds is defined as a stochastic differential non-cooperative game.… More >

  • Open Access


    Home Automation-Based Health Assessment Along Gesture Recognition via Inertial Sensors

    Hammad Rustam1, Muhammad Muneeb1, Suliman A. Alsuhibany2, Yazeed Yasin Ghadi3, Tamara Al Shloul4, Ahmad Jalal1, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2331-2346, 2023, DOI:10.32604/cmc.2023.028712

    Abstract Hand gesture recognition (HGR) is used in a numerous applications, including medical health-care, industrial purpose and sports detection. We have developed a real-time hand gesture recognition system using inertial sensors for the smart home application. Developing such a model facilitates the medical health field (elders or disabled ones). Home automation has also been proven to be a tremendous benefit for the elderly and disabled. Residents are admitted to smart homes for comfort, luxury, improved quality of life, and protection against intrusion and burglars. This paper proposes a novel system that uses principal component analysis, linear discrimination analysis feature extraction, and… More >

  • Open Access


    Stochastic Analysis for the Dynamics of a Poliovirus Epidemic Model

    Ali Raza1, Dumitru Baleanu2,3,4, Zafar Ullah Khan5, Muhammad Mohsin6,*, Nauman Ahmed7, Muhammad Rafiq8, Pervez Anwar9

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 257-275, 2023, DOI:10.32604/cmes.2023.023231

    Abstract Most developing countries such as Afghanistan, Pakistan, India, Bangladesh, and many more are still fighting against poliovirus. According to the World Health Organization, approximately eighteen million people have been infected with poliovirus in the last two decades. In Asia, still, some countries are suffering from the virus. The stochastic behavior of the poliovirus through the transition probabilities and non-parametric perturbation with fundamental properties are studied. Some basic properties of the deterministic model are studied, equilibria, local stability around the stead states, and reproduction number. Euler Maruyama, stochastic Euler, and stochastic Runge-Kutta study the behavior of complex stochastic differential equations. The… More >

  • Open Access


    A Stochastic Framework for Solving the Prey-Predator Delay Differential Model of Holling Type-III

    Naret Ruttanaprommarin1, Zulqurnain Sabir2,3, Rafaél Artidoro Sandoval Núñez4, Emad Az-Zo’bi5, Wajaree Weera6, Thongchai Botmart6,*, Chantapish Zamart6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5915-5930, 2023, DOI:10.32604/cmc.2023.034362

    Abstract The current research aims to implement the numerical results for the Holling third kind of functional response delay differential model utilizing a stochastic framework based on Levenberg-Marquardt backpropagation neural networks (LVMBPNNs). The nonlinear model depends upon three dynamics, prey, predator, and the impact of the recent past. Three different cases based on the delay differential system with the Holling 3rd type of the functional response have been used to solve through the proposed LVMBPNNs solver. The statistic computing framework is provided by selecting 12%, 11%, and 77% for training, testing, and verification. Thirteen numbers of neurons have been used based… More >

  • Open Access


    Quasi Controlled -Metric Spaces over -Algebras with an Application to Stochastic Integral Equations

    Ouafaa Bouftouh1, Samir Kabbaj1, Thabet Abdeljawad2,3,*, Aziz Khan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2649-2663, 2023, DOI:10.32604/cmes.2023.023496

    Abstract Generally, the field of fixed point theory has attracted the attention of researchers in different fields of science and engineering due to its use in proving the existence and uniqueness of solutions of real-world dynamic models. C*-algebra is being continually used to explain a physical system in quantum field theory and statistical mechanics and has subsequently become an important area of research. The concept of a C*-algebra-valued metric space was introduced in 2014 to generalize the concept of metric space. In fact, It is a generalization by replacing the set of real numbers with a C*-algebra. After that, this line… More >

  • Open Access


    Effective and Efficient Video Compression by the Deep Learning Techniques

    Karthick Panneerselvam1,2,*, K. Mahesh1, V. L. Helen Josephine3, A. Ranjith Kumar2

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1047-1061, 2023, DOI:10.32604/csse.2023.030513

    Abstract Deep learning has reached many successes in Video Processing. Video has become a growing important part of our daily digital interactions. The advancement of better resolution content and the large volume offers serious challenges to the goal of receiving, distributing, compressing and revealing high-quality video content. In this paper we propose a novel Effective and Efficient video compression by the Deep Learning framework based on the flask, which creatively combines the Deep Learning Techniques on Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN). The video compression method involves the layers are divided into different groups for data processing, using… More >

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