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  • Open Access


    Short-Term Prediction of Photovoltaic Power Generation Based on LMD Permutation Entropy and Singular Spectrum Analysis

    Wenchao Ma*

    Energy Engineering, Vol.120, No.7, pp. 1685-1699, 2023, DOI:10.32604/ee.2023.025404

    Abstract The power output state of photovoltaic power generation is affected by the earth's rotation and solar radiation intensity. On the one hand, its output sequence has daily periodicity; on the other hand, it has discrete randomness. With the development of new energy economy, the proportion of photovoltaic energy increased accordingly. In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation, this paper proposes the short-term prediction of photovoltaic power generation based on the improved multi-scale permutation entropy, local mean decomposition and singular spectrum analysis algorithm.… More >

  • Open Access


    Fusing Supervised and Unsupervised Measures for Attribute Reduction

    Tianshun Xing, Jianjun Chen*, Taihua Xu, Yan Fan

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 561-581, 2023, DOI:10.32604/iasc.2023.037874

    Abstract It is well-known that attribute reduction is a crucial action of rough set. The significant characteristic of attribute reduction is that it can reduce the dimensions of data with clear semantic explanations. Normally, the learning performance of attributes in derived reduct is much more crucial. Since related measures of rough set dominate the whole process of identifying qualified attributes and deriving reduct, those measures may have a direct impact on the performance of selected attributes in reduct. However, most previous researches about attribute reduction take measures related to either supervised perspective or unsupervised perspective, which are insufficient to identify attributes… More >

  • Open Access


    Temperature-Triggered Hardware Trojan Based Algebraic Fault Analysis of SKINNY-64-64 Lightweight Block Cipher

    Lei Zhu, Jinyue Gong, Liang Dong*, Cong Zhang

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5521-5537, 2023, DOI:10.32604/cmc.2023.037336

    Abstract SKINNY-64-64 is a lightweight block cipher with a 64-bit block length and key length, and it is mainly used on the Internet of Things (IoT). Currently, faults can be injected into cryptographic devices by attackers in a variety of ways, but it is still difficult to achieve a precisely located fault attacks at a low cost, whereas a Hardware Trojan (HT) can realize this. Temperature, as a physical quantity incidental to the operation of a cryptographic device, is easily overlooked. In this paper, a temperature-triggered HT (THT) is designed, which, when activated, causes a specific bit of the intermediate state… More >

  • Open Access



    Olanrewaju M. Oyewolaa,b,*, Samuel I. Afolabib

    Frontiers in Heat and Mass Transfer, Vol.19, No.1, pp. 1-8, 2022, DOI:10.5098/hmt.19.20

    Abstract This paper investigates numerically the problem of convective heat transfer and entropy generation by two adiabatic obstacles positioned inside a square cavity heated at the left wall and cooled on the right wall while horizontal walls are adiabatic. The inclination angle of the cavity orientation investigated are 30, 60 and 90 degrees. Rayleigh numbers ranging from 103 to 106 were calculated for two vertical obstacles. The method of Galerkin finite element was employed to solve the conservation equations of mass, momentum and energy. The cavity is assumed to be filled with air with Prandtl number of 0.71. It was observed… More >

  • Open Access



    P.S.S. Nagalakshmi, N. Vijaya*

    Frontiers in Heat and Mass Transfer, Vol.19, No.1, pp. 1-18, 2022, DOI:10.5098/hmt.19.17

    Abstract The main emphasis of this study is to examine the entropy generation of the spatial-temporal state of Bingham visco-plastic nanofluid flow between parallel plates are solved numerically using adequate similarity solutions. Python with BVP solver is used to interpret the results of the adopted model. Heat and mass transfer rate with respect to yield stress was investigated. The results report that the entopy generation of nanofluids exploring single and multiwalled carbon nanotubes dims with the increasing local thermal Peclet number nearer the lower and upper plates. Researchers have established that entropy generation can be reduced by increasing Fourier’s number (Fe)… More >

  • Open Access



    Girma Tafesse , Mitiku Daba, Vedagiri G. Naidu

    Frontiers in Heat and Mass Transfer, Vol.20, No.1, pp. 1-12, 2023, DOI:10.5098/hmt.20.27

    Abstract Innovative technologies necessitate extra energy, which can be captured from environmentally sustainable, renewable solar energy. Here, heat and mass transfer through stirring nanofluids in solar collectors for direct absorption of sunlight are pronounced. The similarity transformation served to turn mathematically regulated partial differential equations into sets of nonlinear higher-order ordinary differential equations. These equations have been resolved by the homotopy analysis method manipulating, BVPh2.0 package in Mathematica 12.1. Validations are justified through comparison. Afterward, stronger magnetic field interactions delay the nanofluids mobility. Temperature increases with thermal radiation and Biot numbers. Entropy formation and nanoparticle concentration dwindle when Schmidt’s number surges. More >

  • Open Access


    Degree-Based Entropy Descriptors of Graphenylene Using Topological Indices

    M. C. Shanmukha1, Sokjoon Lee2,*, A. Usha3, K. C. Shilpa4, Muhammad Azeem5

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 939-964, 2023, DOI:10.32604/cmes.2023.027254

    Abstract Graph theory plays a significant role in the applications of chemistry, pharmacy, communication, maps, and aeronautical fields. The molecules of chemical compounds are modelled as a graph to study the properties of the compounds. The geometric structure of the compound relates to a few physical properties such as boiling point, enthalpy, π-electron energy, molecular weight. The article aims to determine the practical application of graph theory by solving one of the interdisciplinary problems describing the structures of benzenoid hydrocarbons and graphenylene. The topological index is an invariant of a molecular graph associated with the chemical structure, which shows the correlation… More >

  • Open Access


    Facial Emotion Recognition Using Swarm Optimized Multi-Dimensional DeepNets with Losses Calculated by Cross Entropy Function

    A. N. Arun1,*, P. Maheswaravenkatesh2, T. Jayasankar2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3285-3301, 2023, DOI:10.32604/csse.2023.035356

    Abstract The human face forms a canvas wherein various non-verbal expressions are communicated. These expressional cues and verbal communication represent the accurate perception of the actual intent. In many cases, a person may present an outward expression that might differ from the genuine emotion or the feeling that the person experiences. Even when people try to hide these emotions, the real emotions that are internally felt might reflect as facial expressions in the form of micro expressions. These micro expressions cannot be masked and reflect the actual emotional state of a person under study. Such micro expressions are on display for… 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


    Deep Learning Framework for Landslide Severity Prediction and Susceptibility Mapping

    G. Bhargavi*, J. Arunnehru

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1257-1272, 2023, DOI:10.32604/iasc.2023.034335

    Abstract Landslides are a natural hazard that is unpredictable, but we can prevent them. The Landslide Susceptibility Index reduces the uncertainty of living with landslides significantly. Planning and managing landslide-prone areas is critical. Using the most optimistic deep neural network techniques, the proposed work classifies and analyses the severity of the landslide. The selected experimental study area is Kerala’s Idukki district. A total of 3363 points were considered for this experiment using historic landslide points, field surveys, and literature searches. The primary triggering factors slope degree, slope aspect, elevation (altitude), normalized difference vegetation index (NDVI), and distance from road, lithology, and… More >

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