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Solving fractional optimal control problems by new Bernoulli wavelets operational matrices

OPTIMAL CONTROL APPLICATIONS & METHODS 2020年第4期41卷 1188-1210页

作者： Barikbin, Zahra Keshavarz, Elham Imam Khomeini Int Univ Dept Appl Math Fac Sci Qazvin *** Iran

In this article, a new numerical method based on Bernoulli wavelet basis has been applied to give the approximate solution of the fractional optimal control problems. The new operational matrices of multiplication and fractional integration are constructed. The proposed method is applied to reduce the problem to the solution of a system of algebraic equations. The fractional derivative is considered in the Caputo sense. Convergence of the algorithm is proved and some results concerning the error analysis are obtained. Approximate solutions are given and in the cases when we have an exact solution, a comparison with the exact solution is presented to demonstrate the validity and applicability of the proposed method. In addition, we compare the obtained results with the results of other methods. Comparison shows the more accuracy of presented technique in comparison to other published methods.

关键词： Bernoulli wavelets computational algorithm fractional optimal control numerical solution

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Dynamic analysis of the suspended composite pipelines conveying pulsating fluid

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JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING 2020年 75卷 103148-000页

作者： Khudayarov, B. A. Komilova, Kh M. Turaev, F. Zh Tashkent Inst Irrigat & Agr Mechanizat Engineers Dept Higher Math Tashkent 100000 Uzbekistan Dept Higher Math Str Kari Niyazova 39 Tashkent 100000 Uzbekistan

The problems of oscillations of a viscoelastic pipeline conveying fluid flow are considered in the paper. Mathematical models of these problems are constructed in a one-dimensional statement. The motion of a pipeline completely filled with a flowing fluid is studied. The transverse oscillations of a pipeline interact with the pipe walls, changing the nature of system oscillations. It is assumed that a pulsating fluid flows in the pipeline. Though the effect of flowing fluid on the pipe motion is considered in the paper, the effect of the pipe on fluid flow is not taken into account here. The mathematical model of the problem is described by the systems of partial integro-differential equations (IDE) with corresponding initial and boundary conditions. Partial IDE obtained using the Bubnov-Galerkin method under considered boundary conditions are reduced to solving ordinary IDE systems with constant coefficients relative to time function. The integration of systems of equations obtained on the basis of a polynomial approximation of deflections was carried out numerically. Based on this method, the algorithms are developed for numerically solving one-dimensional problems of oscillation and stability of viscoelastic pipes conveying fluid flow. It was found that an increase in internal pressure parameter leads to a decrease in critical flow rate. It was shown that an increase in the singularity parameter and the rigidity parameter of continuous layer of a base leads to an increase in critical flow rate. It was revealed that an increase in transverse stationary external load leads to an increase in the amplitude of pipe oscillations.

关键词： Numerical simulation computational algorithm Viscoelasticity Pipeline Vibration Pulsating fluid

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TECHNOLOGY OF REGENERATION OF THE BONE TISSUE IN A ROTATIONAL BIOREACTOR: FLUID FLOW SIMULATION AND LASER-INDUCED FLUORESCENCE DIAGNOSTICS

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JOURNAL OF APPLIED MECHANICS AND TECHNICAL PHYSICS 2020年第5期61卷 776-786页

作者： Tsibulskaya, E. O. Maslov, N. A. Larionov, P. M. Ganimedov, V. L. Russian Acad Sci Khristianovich Inst Theoret & Appl Mech Siberian Branch Novosibirsk 630090 Russia Novosibirsk State Univ Novosibirsk 630090 Russia

A technology of bone tissue cultivation on a thin scaffold in a rotational bioreactor is developed. An optimal regime of cell material cultivation is determined for testing the method, and an optical method for diagnostics of the bone growth dynamics during its cultivation is found. Numerical simulations of the fluid flow in the bioreactor make it possible to significantly simplify the medical experiment and to choose the optimal values of the rotation frequencies and shear stresses acting on the cell material placed on the scaffold. The optical diagnostics of the scaffold samples in the course of dynamic cultivation in the bioreactor is performed by the method of laser-induced fluorescence. An algorithm based on the principal component analysis is applied to analyze the spectral data;as a result, the spectra of excitation and fluorescent emission of the basic fluorescent substances in the sample (tyrosine and tryptophan amino acids, structural protein (collagen), and fluorescent structures of polycaprolactone) are calculated. It is found that the contribution of the component corresponding to collagen in the samples increases in the process of dynamic cultivation, which testifies to effective formation of the extracellular matrix of the bone.

关键词： mathematical modeling computational algorithm rotational bioreactor Taylor vortices Navier– Stokes equations laminar flow regime shear stress scaffold laser-induced fluorescence principal component analysis

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Prostate cancer in omics era

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CANCER CELL INTERNATIONAL 2022年第1期22卷 274-274页

作者： Gholami, Nasrin Haghparast, Amin Alipourfard, Iraj Nazari, Majid Tabriz Univ Med Sci Hematol & Oncol Res Ctr Tabriz Iran GenomeFan Tehran Iran Univ Silesia Inst Biol Biotechnol & Environm Protect Fac Nat Sci Katowice Poland Shahid Sadoughi Univ Med Sci Dept Med Genet Fac Med Yazd Iran POB 14155-6117 Shiraz Iran

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

关键词： Prostate cancer Genomics Proteomics Metabolomics Diagnosis computational algorithm

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Efficiency of the Method for Detecting Normal Mixture Signals with Pre-Estimated Gaussian Mixture Noise

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PATTERN RECOGNITION AND IMAGE ANALYSIS 2020年第3期30卷 470-479页

作者： Gorshenin, A. K. Shcherbinina, A. A. Russian Acad Sci Fed Res Ctr Comp Sci & Control Moscow 119333 Russia Lomonosov Moscow State Univ Moscow 119991 Russia

The paper discusses the effectiveness of the method for determining the parameters of the useful signal in the sliding window mode, provided that it is possible to obtain preliminary estimates for the noise distribution. For the statistical experiment, samples had been generated with different ratios between the signal and noise parameters. Implementation of the computational procedures for the adaptive method in the Python programming language is proposed. For the test samples, it is demonstrated that the magnitude of the error in evaluating the parameters in the vast majority of cases does not exceed value 1 (in terms of the standard RMSE metrics). In addition, an effective two-pass method for detecting the moment of the appearance of a meaningful signal in the noisy data is proposed. The results of its operation are also demonstrated on the example of the mentioned test samples.

关键词： finite normal mixtures method of moving separation of mixtures detection signal noise EM algorithm computational algorithm

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An increasing variables singular system of fractional q-differential equations via numerical calculations

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ADVANCES IN DIFFERENCE EQUATIONS 2020年第1期2020卷 1-32页

作者： Samei, Mohammad Esmael Baleanu, Dumitru Rezapour, Shahram Bu Ali Sina Univ Dept Math Hamadan 65178 Hamadan Iran Cankaya Univ Dept Math Ogretmenler Cad 14 06530 Ankara Turkey Inst Space Sci Bucharest Romania Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam Duy Tan Univ Fac Nat Sci Da Nang 550000 Vietnam China Med Univ China Med Univ Hosp Dept Med Res Taichung Taiwan

We investigate the existence of solutions for an increasing variables singular m-dimensional system of fractional q-differential equations on a time scale. In this singular system, the first equation has two variables and the number of variables increases permanently. By using some fixed point results, we study the singular system under some different conditions. Also, we provide two examples involving practical algorithms, numerical tables, and some figures to illustrate our main results.

关键词： computational algorithm Singularity System of q-differential equations The Caputo q-derivative 34A08 39A13 39B72

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Linear and nonlinear machine learning correlation of transition metal cluster characteristics

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JOURNAL OF NANOPARTICLE RESEARCH 2021年第8期23卷 157-157页

作者： Kokabi, Alireza Nasiri Mahd, Zahra Naghibi, Zohreh Hamedan Univ Technol Dept Elect Engn Hamadan 65155 Hamadan Iran Hamedan Univ Technol Dept Comp Engn Hamadan Hamadan Iran

The correlation between the properties of fourth-row transition element small clusters is studied using linear and nonlinear machine learning (ML) methods. The feature space, or equivalently called descriptors, is defined based on a wide range of electronic, mass and atomic properties. Considering the similarities between these clusters, the possibility of predicting some special characteristics such as formation energy and low-frequency vibrational modes using the ML techniques is reported by an accuracy of more than 99%. Interestingly, such fascinating results have been obtained using even linear ML techniques as well as nonlinear ones by significantly lower computational cost. This observation further reveals the correlative characteristics of transition metal clusters. However, the considered methods include linear regression and support vector machine methods as two well-known linear and nonlinear techniques, respectively. Based on the obtained results, most correlating factors are extracted. In this regard, it is found that the valence band energy and bond lengths of any combination of nine different transition metal clusters can predict their corresponding parameters in the tenth one. This result seems to be fascinating since the dependency between the cluster energy and bond length might be less expected as opposed to the dependency between the valence band energy and cluster energy.

关键词： Transition metal cluster Density functional theory Machine learning Coefficient of determination computational algorithm

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A computational Tool for Enhancing Ischemic Stroke in Computed Tomography Examinations

A Computational Tool for Enhancing Ischemic Stroke in Comput...

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IUPESM World Congress on Medical Physics and Biomedical Engineering

作者： Fattori Alves, Allan Felipe Menegatti Pavan, Ana Luiza Jennane, Rachid Macedo de Freitas, Carlos Clayton Abdala, Nitamar Carrasco Altemani, Joao Mauricio Pina, Diana Sao Paulo State Univ Phys & Biophys Botucatu SP Brazil Univ Orleans Lab I3MTO Orleans France Sao Paulo State Univ Trop Dis & Diagnost Imaging Botucatu SP Brazil Univ Fed Sao Paulo Diagnost Imaging Sao Paulo Brazil Univ Estadual Campinas Radiol Campinas SP Brazil

ISBN: (纸本)9789811090356;9789811090349

Stroke is a cardio-vascular disease that currently ranks in the fifth position among all causes of death worldwide. Computed tomography is the first radiologic examination performed in emergency decisions to diagnose stroke. The earliest signs of ischemic stroke are quite subtle in CT, thus image-processing tools can be used to enhance ischemic areas and to aid physicians during diagnosis. This study aimed to enhance the ischemic stroke visual perception in computed tomography examinations. A cohort of 45 exams were used during this study, with 28 patients previously diagnosed with ischemic stroke and 17 control patients. Stroke cases were obtained within 4.5 h of symptom onset and with mean NIHSS of 13.6 +/- 5.5. The complete series of non-enhanced images were obtained in DICOM format and all processing was performed in Matlab software R2017a. The main steps of the computed algorithm were as follows: an image averaging was performed to reduce the noise and redundant information within each slice;then a variational decomposition model was applied to keep the relevant component for our analysis;then three different segmentation methods were used to enhance the ischemic stroke area. The segmentation methods used were expectation maximization method, K-means and mean-shift. We determined a test to evaluate the performance of six observers (physicians) in a clinical environment with and without the aid of enhanced images. According to the opinion of the observers who participated in this study the enhanced images were particularly useful when displayed together with the original images. The overall sensitivity of the observer's analysis changed after the evaluation of the enhanced images with the expectation maximization method. The overall specificity also increased. The improvement was even more remarkable for the three least experienced physicians.

关键词： Stroke Image processing computational algorithm Enhanced images

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A simulation model for thermal performance prediction of a coal-fired power plant

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INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES 2019年第2期14卷 122-134页

作者： Kumar, Ravinder Jilte, Ravindra Ahmadi, Mohammad H. Kaushal, Rajneesh Lovely Profess Univ Dept Mech Engn Phagwara 144411 Punjab India Shahrood Univ Technol Fac Mech Engn Shahrood *** Iran Natl Inst Technol Dept Mech Engn Kurukshetra 136119 Haryana India

This study deals with the simulation modeling of a 250 MW capacity coal-based power plant at different load conditions. The plant under study is subcritical, reheating and regenerative type situated in northern part of India. At present, computer-based programming and advanced software used in simulation, modeling and optimization used in process industries playing an important role. The present work related with the semi-empirical modeling for thermal performance analysis of a coal-fired power plant. The model basically includes the mass, energy balance equations. A typical thermodynamic property relation with empirical correlations using steam bled pressure extracted from turbine at various points in plant has been used. The necessary data collected from plant and model are applied in a general programming form for plant analysis. The process-based simulation model with the integration of steam generator, turbine, pump, condenser and feedwater heaters in the plant has been successfully run using the MATLAB calculation tool. The validation of the model has been done by comparing overall plant efficiency, coal consumption rate and mass flow rate of steam at various load conditions for 250 MW capacity plant under operating conditions. The results achieved through simulation model are found to be satisfactory. It is expected that this simulation model will help out to those engineers and researchers who are dealing with the improvement of design, analysis and optimization of coal-fired power plant.

关键词： thermodynamic modeling thermal power plant plant efficiency steam turbine computational algorithm

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Estimating pro-environmental potential for the development of mobility-based informational intervention: a data-driven algorithm

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PERSONAL AND UBIQUITOUS COMPUTING 2019年第5-6期23卷 653-668页

作者： Ahmed, Shiraz Adnan, Muhammad Janssens, Davy Brattich, Erika Yasar, Ansar-ul-Haque Kumar, Prashant di Sabatino, Silvana Shakshuki, Elhadi M. UHasselt Hasselt Univ Transportat Res Inst IMOB Agoralaan B-3590 Diepenbeek Belgium Univ Bologna Alma Mater Studiorum Dept Phys & Astron Bologna Italy Univ Surrey Fac Engn & Phys Sci Global Ctr Clean Air Res GCARE Dept Civil & Environm Engn Guildford GU2 7XH Surrey England Acadia Univ Jodrey Sch Comp Sci Wolfville NS Canada

Informational interventions are important to bring positive changes in attitudes and perception among individuals. In relation to the individual's mobility behavior, habits, attitudes, and perceptions are difficult to change. Therefore, it is vital to identify relatively soft aspects of travel behavior with a potential to reduce the negative impacts of mobility on the environment and individual health. This paper provides a methodological framework and describes the development of a computational algorithm that helps to identify soft changes in the travel behavior. The algorithm is based on a variety of different data sources such as activity-travel diaries and related constraint information, meteorological conditions, bicycle and public transport supply data, and emissions and air pollutant concentrations data. A variety of rules that are part of the algorithm are derived from the transport modeling literature, where constraints and factors were examined for activity-travel decisions. Three major aspects of activity-travel behavior, such as reduced car use, cold start of car engines, and participation in non-mandatory outdoor activities are considered in assessing pro-environmental potential. The algorithm is applied to collected small datasets from citizens of Hasselt (Belgium), Bologna (Italy), and Guildford (UK). A significant replaceable potential for car trips within 3 km to cycling and car trips to public transport has been found. The replaceable potential of excessive cold starts and participation in non-mandatory outdoor activities were also found, to some extent, to bring positive changes in the environment. In future research, these identified potentials are reported back to individuals with their consequence as part of a mobility-based informational intervention.

关键词： Pro-environmental potential Activity-travel behavior Informational intervention computational algorithm

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