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  • Articles  (453)
  • Electrical Engineering, Measurement and Control Technology  (453)
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  • Articles  (453)
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  • Electrical Engineering, Measurement and Control Technology  (453)
  • Computer Science  (453)
  • 11
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    Integrating Data Mining Techniques for Naïve Bayes Classification: Applications to Medical Datasets (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-09-13
    Description: In this study, we designed a framework in which three techniques—classification tree, association rules analysis (ASA), and the naïve Bayes classifier—were combined to improve the performance of the latter. A classification tree was used to discretize quantitative predictors into categories and ASA was used to generate interactions in a fully realized way, as discretized variables and interactions are key to improving the classification accuracy of the naïve Bayes classifier. We applied our methodology to three medical datasets to demonstrate the efficacy of the proposed method. The results showed that our methodology outperformed the existing techniques for all the illustrated datasets. Although our focus here was on medical datasets, our proposed methodology is equally applicable to datasets in many other areas.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
    Published by Molecular Diversity Preservation International
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  • 12
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    Understanding the Origin of Structural Diversity of DNA Double Helix (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-09-11
    Description: Deciphering the contribution of DNA subunits to the variability of its 3D structure represents an important step toward the elucidation of DNA functions at the atomic level. In the pursuit of that goal, our previous studies revealed that the essential conformational characteristics of the most populated “canonic” BI and AI conformational families of Watson–Crick duplexes, including the sequence dependence of their 3D structure, preexist in the local energy minima of the elemental single-chain fragments, deoxydinucleoside monophosphates (dDMPs). Those computations have uncovered important sequence-dependent regularity in the superposition of neighbor bases. The present work expands our studies to new minimal fragments of DNA with Watson–Crick nucleoside pairs that differ from canonic families in the torsion angles of the sugar-phosphate backbone (SPB). To address this objective, computations have been performed on dDMPs, cdDMPs (complementary dDMPs), and minimal fragments of SPBs of respective systems by using methods of molecular and quantum mechanics. These computations reveal that the conformations of dDMPs and cdDMPs having torsion angles of SPB corresponding to the local energy minima of separate minimal units of SPB exhibit sequence-dependent characteristics representative of canonic families. In contrast, conformations of dDMP and cdDMP with SPB torsions being far from the local minima of separate SPB units exhibit more complex sequence dependence.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
    Published by Molecular Diversity Preservation International
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  • 13
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    Physics-Based Neural Network Methods for Solving Parameterized Singular Perturbation Problem (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-09-06
    Description: This work is devoted to the description and comparative study of some methods of mathematical modeling. We consider methods that can be applied for building cyber-physical systems and digital twins. These application areas add to the usual accuracy requirements for a model the need to be adaptable to new data and the small computational complexity allows it to be used in embedded systems. First, we regard the finite element method as one of the “pure” physics-based modeling methods and the general neural network approach as a variant of machine learning modeling with physics-based regularization (or physics-informed neural networks) and their combination. A physics-based network architecture model class has been developed by us on the basis of a modification of classical numerical methods for solving ordinary differential equations. The model problem has a parameter at some values for which the phenomenon of stiffness is observed. We consider a fixed parameter value problem statement and a case when a parameter is one of the input variables. Thus, we obtain a solution for a set of parameter values. The resulting model allows predicting the behavior of an object when its parameters change and identifying its parameters based on observational data.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
    Published by Molecular Diversity Preservation International
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  • 14
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    Performance of the Boost Converter Controlled with ZAD to Regulate DC Signals (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-09-04
    Description: This paper presents the performance of a boost converter controlled with a zero average dynamics technique to regulate direct current signals. The boost converter is modeled in a compact form, and a variable change is performed to depend only on the γ parameter. A new sliding surface is proposed, where it is possible to regulate both the voltage and the current with low relative errors with respect to the reference signals. It is analytically demonstrated that the approximation of the switching surface by a piecewise linear technique is efficient in controlling the system. It is shown numerically that for certain operating conditions, the system is evolved into a chaotic attractor. The zero average dynamics technique implemented in the boost converter has good regulation, due to the presence of zones in the bi-parametric space. Furthermore, the zero average dynamics technique regulates the voltage well and presents a chaotic attractor with low steady-state error.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
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  • 15
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    Is There a Quadruple Fe-C Bond in FeC(CO)3? (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-08-30
    Description: A recent computational paper (Kalita et al., Phys. Chem. Chem. Phys. 2020, 22, 24178–24180) reports the existence of a quadruple bond between a carbon and an iron atom in the FeC(CO)3 molecule. In this communication, we perform several computations on the same system, using both density functional theory and post-Hartree–Fock methods and find that the results, and in particular the Fe-C bond length and stretching frequency depend strongly on the method used. We ascribe this behavior to a strong multireference character of the FeC(CO)3 ground state, which explains the non-conclusive results obtained with single-reference methods. We therefore conclude that, while the existence of a Fe-C quadruple bond is not disproved, further investigation is required before a conclusion can be drawn.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
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  • 16
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    Stable, Explicit, Leapfrog-Hopscotch Algorithms for the Diffusion Equation (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-08-20
    Description: In this paper, we construct novel numerical algorithms to solve the heat or diffusion equation. We start with 105 different leapfrog-hopscotch algorithm combinations and narrow this selection down to five during subsequent tests. We demonstrate the performance of these top five methods in the case of large systems with random parameters and discontinuous initial conditions, by comparing them with other methods. We verify the methods by reproducing an analytical solution using a non-equidistant mesh. Then, we construct a new nontrivial analytical solution containing the Kummer functions for the heat equation with time-dependent coefficients, and also reproduce this solution. The new methods are then applied to the nonlinear Fisher equation. Finally, we analytically prove that the order of accuracy of the methods is two, and present evidence that they are unconditionally stable.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
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  • 17
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    Parameter Estimation of Partially Observed Turbulent Systems Using Conditional Gaussian Path-Wise Sampler (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-08-13
    Description: Parameter estimation of complex nonlinear turbulent dynamical systems using only partially observed time series is a challenging topic. The nonlinearity and partial observations often impede using closed analytic formulae to recover the model parameters. In this paper, an exact path-wise sampling method is developed, which is incorporated into a Bayesian Markov chain Monte Carlo (MCMC) algorithm in light of data augmentation to efficiently estimate the parameters in a rich class of nonlinear and non-Gaussian turbulent systems using partial observations. This path-wise sampling method exploits closed analytic formulae to sample the trajectories of the unobserved variables, which avoid the numerical errors in the general sampling approaches and significantly increase the overall parameter estimation efficiency. The unknown parameters and the missing trajectories are estimated in an alternating fashion in an adaptive MCMC iteration algorithm with rapid convergence. It is shown based on the noisy Lorenz 63 model and a stochastically coupled FitzHugh–Nagumo model that the new algorithm is very skillful in estimating the parameters in highly nonlinear turbulent models. The model with the estimated parameters succeeds in recovering the nonlinear and non-Gaussian features of the truth, including capturing the intermittency and extreme events, in both test examples.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
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  • 18
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    Effects of Fractional Derivatives with Different Orders in SIS Epidemic Models (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-08-08
    Description: We study epidemic Susceptible–Infected–Susceptible (SIS) models in the fractional setting. The novelty is to consider models in which the susceptible and infected populations evolve according to different fractional orders. We study a model based on the Caputo derivative, for which we establish existence results of the solutions. Furthermore, we investigate a model based on the Caputo–Fabrizio operator, for which we provide existence of solutions and a study of the equilibria. Both models can be framed in the context of SIS models with time-varying total population, in which the competition between birth and death rates is macroscopically described by the fractional orders of the derivatives. Numerical simulations for both models and a direct numerical comparison are also provided.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
    Published by Molecular Diversity Preservation International
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  • 19
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    Application of a Deep Neural Network to Phase Retrieval in Inverse Medium Scattering Problems (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-04-28
    Description: We address the inverse medium scattering problem with phaseless data motivated by nondestructive testing for optical fibers. As the phase information of the data is unknown, this problem may be regarded as a standard phase retrieval problem that consists of identifying the phase from the amplitude of data and the structure of the related operator. This problem has been studied intensively due to its wide applications in physics and engineering. However, the uniqueness of the inverse problem with phaseless data is still open and the problem itself is severely ill-posed. In this work, we construct a model to approximate the solution operator in finite-dimensional spaces by a deep neural network assuming that the refractive index is radially symmetric. We are then able to recover the refractive index from the phaseless data. Numerical experiments are presented to illustrate the effectiveness of the proposed model.
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
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  • 20
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    Potential Water Recovery from Biomass Boilers: Parametric Analysis (2021)
    Molecular Diversity Preservation International
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    Publication Date: 2021-04-27
    Description: A fundamental component of the losses of convection boilers is localized in the warm fumes that are expelled. In the warm fumes, not only energy is lost, but water is also formed from the combustion reaction in the form of steam which is expelled through the exhaust. Modern fuel boilers recover both the heat from the fumes and the latent heat of condensation from water vapor. Depending on the chemical composition of the fuel, different amounts of steam are produced together with heat and different combustion conditions, such as air in excess. In this article, a computational tool was established to simulate a combustion system mainly (but not only) focusing on the prediction of the amount of water produced. In fact, while steam in fossil fuel boilers is commonly condensed, this is not so when the fuel is a biomass. Furthermore, biomasses could contain moisture in different amounts, thus affecting the production of water and the heat of combustion. The study shows that a ten-fold amount of water is formed from biomass combustion with respect to fossil fuels (when the same energy output is produced). As a result, the recovery of water is amenable in biomasses, both from the energetic point of view and for liquid water production. In fact, the water recovered from the fumes might be also reused in other processes such as the cleaning of fumes or agriculture (after treatment).
    Electronic ISSN: 2079-3197
    Topics: Electrical Engineering, Measurement and Control Technology , Computer Science
    Published by Molecular Diversity Preservation International
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