MATLAB Tool Research Articles

FDI: A MATLAB tool for computing the fractal dimension index of sources reconstructed from EEG data

BackgroundThe fractal dimension (FD) is a valuable tool for analysing the complexity of neural structures and functions in the human brain. To assess the spatiotemporal complexity of brain activations derived from electroencephalogram (EEG) signals, the fractal dimension index (FDI) was developed. This measure integrates two distinct complexity metrics: 1) integration FD, which calculates the FD of the spatiotemporal coordinates of all significantly active EEG sources (4DFD); and 2) differentiation FD, determined by the complexity of the temporal evolution of the spatial distribution of cortical activations (3DFD), estimated via the Higuchi FD [HFD(3DFD)]. The final FDI value is the product of these two measurements: 4DFD × HFD(3DFD). Although FDI has shown utility in various research on neurological and neurodegenerative disorders, existing literature lacks standardized implementation methods and accessible coding resources, limiting wider adoption within the field. MethodsWe introduce an open-source MATLAB software named FDI for measuring FDI values in EEG datasets. ResultsBy using CUDA for leveraging the GPU massive parallelism to optimize performance, our software facilitates efficient processing of large-scale EEG data while ensuring compatibility with pre-processed data from widely used tools such as Brainstorm and EEGLab. Additionally, we illustrate the applicability of FDI by demonstrating its usage in two neuroimaging studies. Access to the MATLAB source code and a precompiled executable for Windows system is provided freely. ConclusionsWith these resources, neuroscientists can readily apply FDI to investigate cortical activity complexity within their own studies.

Segmentand Classify Satellte Images to Analyze The Environment and Ensure Safety, Using Machine Learning

Image segmentation is a difficult task in computer vision. The process includes the classification of visual input to segments to simplify image analysis. There are many types of method for the image segmentation some of the common methods are edge detection based method region-based methods, clustering-based method, partial differential equation-based, watershed-based method, and neural network-based method. The proposed project work is mainly focused on image segmentation. Satellite images are given as the input of the proposed system. Machine learning techniques plan an important role in various domains. Here the remotely sensed data can be segmented by using the K-Means clustering method. Compared with other traditional methods this clustering technique yields better results. The system is implemented using the Matlab tool. Machine learning concepts drastically decrease the time needed to arrange an exact map. the project will be using K Nearest Neighbor (KNN) as existing and Support Vector Machine (SVM) as proposed system for classification and calculates results in terms of accuracy. From the results obtained its proved that proposed SVM works better than existing KNN.

An effective metaheuristic based optimized type‐II fuzzy inference system for fault node identification in wireless sensor network

SummaryDeploying a wireless sensor network (WSN) for accessing the network of distant environments is more crucial. Node defect detection is a core technology of WSN and is essential for most WSN networks. The defective node reduces the overall service quality (OSQ) of the global WSN network system. Therefore, a type II fuzzy inference system (T2_FIS) is proposed for detecting defective nodes in the WSN network. The adaptive genetic algorithm (AGA) and proposed method are introduced for tuning the parameters in the T2_FIS system. The proposed T2_FIS method effectively detects the broken node in the WSN network using the fuzzy rules. In addition, the improved Mud Ring (IMR) optimization algorithm is proposed to replace the faulty node with the neighborhood node in the network. The defective nodes are identified and replaced with the closest nodes based on the membership function (MF) generated by the T2_FIS. Furthermore, the lifetime and throughput of the WSN network are increased by minimizing energy consumption. The overall performance is evaluated using the MATLAB tool, and the implementation results are compared with the existing methods. The total energy consumption for the proposed method is 50.451, with a throughput and lifetime of 153.657 and 22979.25. Furthermore, the performance metrics for the existing and proposed strategies are analyzed, and the accuracy of the proposed method is proven to be 99.3827%, the false alarm rate (FAR) is 0.0008, and the false positive rate (FPR) is 0.0617. The results show the effectiveness and performance of the proposed method.

Numerical simulation for MHD slip flow with heat transfer over a stretching bullet‐shaped object

AbstractThis paper investigates magnetohydrodynamic (MHD) boundary layer slip flow with heat transfer over a bullet shaped object. The study addresses a significant problem in fluid dynamics and heat transport with applications in various engineering and industrial domains, including aerospace, material processing, and energy systems. The governing equations are resolved using the bvp4c, an inbuilt MATLAB tool, and the arithmetic computation for the momentum and thermotic equations are executed. The results are exhibited graphically. Numerical outcomes are graphically depicted with the aid of velocity and temperature profiles for several model variables. The achieved results exhibit a promising agreement with the previously established findings available in the open literature. The heat transfer processes and fluid flow are remarkably influenced by means of the ratio of surface thickness and stretching potential. The results obtained designated that the Mixed convection parameter λ increases momentum BL thickness, whereas the temperature profile diminishes. Furthermore, momentum and temperature profile improve for surface thickness parameter . The current investigation highlights the potential utility of heat transport rate and friction factor in the industrial divisions for regulating cooling rates and enhancing the quality of end products.

Hydrothermal properties with entropy generation effects on a hybrid nanofluid considering thermal radiation on a stretching/shrinking sheet

Heat transfer efficiency is a significant area of modern research because it is used in a variety of engineering domains, improving the performance of thermal systems such as solar collectors. In this article, a statistical optimization of hybrid nanofluid flow through a stretching/shrinking inclined surface inside the solar-powered ship with entropy generation is investigated by utilizing copper and alumina as a tinny-sized nanomaterial in base fluid water. Copper is also corrosion-resistant with a high thermal conductivity that can be useful in marine environments where salted water and humidity damage the other materials. Coating or a catalyst for solar thermal systems aluminum oxide can be utilized to generate steam or hot water by using the heat coming from the sun. The significance of thermal radiation is considered as the heat source. The developed mathematical model in the form of the partial differential equation is transformed to nonlinear coupled Ordinary Differential Equations (ODEs) by using similarity variables. The reduced equations are solved numerically by applying the shooting algorithm with the bvp4c tool of MATLAB. The surface response methodology is utilized for the statistical optimization of experimental design parameters. The entropy generation rises with the increase of Reynolds number and Brinkmann number. The highest entropy value is found for the Cu-Al2O3/water with λ = 1.0 for Re = 15 and Br = 15. No significant change is reported in the local Nusselt number for changing the Eckert number value. The Response Surface Modeling (RSM) result shows that the experimental input parameter rises with “a factor.”

Thermal analysis of radiative Sutterby nanofluid flow over stretching curved surface

In this analysis, Sutterby fluid model over a curved surface is considered. The main mechanisms that contribute to the improvement of the convection characteristics of the nanofluid are categorized as Brownian motion and thermophoresis. The radiation and slip mechanism have been studied at curved stretchable surface. The suction/injection impacts also studied. The partial differential equations are converted into ordinary differential equations through transformations.The numerical solution of the specified mathematical model is obtained using the built-in bvp4c tool in MATLAB. The effects of various parameters related to the system of ordinary differential equations are illustrated in the graphs. The influence of some intended parameters through the physical quantities are presented through tabular form.

Quantitative analysis of malignant brain tumor on MRI images

Longitudinal relaxation time (T1)- weighted, Transverse relaxation time (T2)- weighted and flair Magetic Resonance Imaging (MRI) sequences are used for the study of high grade malignant brain tumors and their surrounding edemas. This study aimed to examine the characteristic of MRI on malignant brain tumor and to evaluate the benefits of Flair and T2 (Transverse relaxation time) -weighted over the T1(Longitudinal relaxation time) -weighted sequence. A total of 25 patients of malignant brain tumors were selected for analysis including 16 women aged 1 to 75 (mean age, 38.31 years) and 9 men aged 1 to 75 (mean age, 19.5 years). All patients had the T1- weighted, T2- weighted and Flair MRI sequences. A Region based segmentation of MATLAB software was performed on each type of tumor and 3D volume was calculated by spheroid volume tool of MATLAB. For all the patients tumor volume was calculated in cubic millimeter and compared with other sequences.The Flair and T2- weighted images volumes were significantly larger than the T1 – weighted image volume. There was also statistical difference of volume occurred in MRI sequences. T2- weighted and Flair MRI sequences showed 100% more volume than T1- weighted in the age group between 51 to 75 years. Similarly, both T2-weighted and Flair MRI sequence showed 61% volume more than T1-weighted in the age groups betrwen 26 to 75 years. Our findings suggest that the volume produced by these techniques are distinct and not interchangeable. Flair and T2-weighted images proved efficient for the measurement of abnormal tissues and CSF fluid in the brain. On the other hand T1-weighted images efficiently locate the tumor in fat and white matter of the brain.

Multiplier-less Broadband and Linear Phase Digital Hilbert Transformers

The Hilbert transformation for generating the analytic signal or signal envelope is widely used in modern communication receivers, in radar and sonar systems. It introduces a 90∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$90^{\\circ }$$\\end{document} phase shift of the input signal. Since the impulse response of the ideal Hilbert transformer is non-causal, it must be approximated by an FIR or IIR filter. This paper shows results of novel algorithms for designing broadband digital IIR Hilbert transformers and its implementation. The designs employ Galerkin or collocation techniques. The transfer function of the Hilbert transformer is a rational polynomial of low order and exhibits approximately linear phase. The filters match the 90∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$90^{\\circ }$$\\end{document} phase shift requirement of Hilbert transformers almost perfectly and exhibit approximately constant group delay in the passband. The achieved image rejection ratio is typically larger than 50 dB. The quantization of the filter coefficients is realized by a Canonical Signed Digit (CSD) representation, reducing the hardware resources compared with two’s complement. The resulting filters are multiplier-less, which is crucial for high-speed signal processing and low power consumption. The design techniques and the CSD representation are realized in a MATLAB toolbox. The filters were moreover implemented in VHDL and SystemC. Additionally, a MATLAB tool for automatically generating a VHDL package containing the filter parameters has been implemented.

Optimizing material circularity pathways in industrial waste streams: A decision-making model

The increasing pressures of environmental regulation and the introduction of new policy frameworks by various nations have accelerated the popularization of industrial solid waste management and recovery, underscoring the transition towards a circular economy. This paradigm shift emphasizes the importance of material recovery, reuse, and recycling of industrial waste to minimize environmental impact and enhance sustainability. Despite the availability of individual approaches for waste recovery, there exists a significant gap in the systematic selection of optimal recovery pathways that facilitate the reintegration of materials into the production cycle. Addressing this gap, our study introduces a novel optimization model designed to identify the most efficient material circularity routes that leverage both the technical and biological cycles of the circular economy framework. Utilizing the Genetic Algorithm optimization tool in MATLAB, our model prioritizes pathways that maximize material recovery and profit generation simultaneously. This dual-objective function serves as the cornerstone of our analysis, ensuring a balanced approach to environmental sustainability and economic viability. The model's efficacy was tested on pre-calculated quantities of fabric waste generated by the Biyagama Export Processing Zone, providing a practical case study for its application. Our findings reveal diverse scenarios under which the model can allocate varying weights to each objective, demonstrating its flexibility and utility as a decision-making tool for stakeholders in the waste management sector. The results indicate that the model is not only capable of optimizing waste circularity pathways for maximum material recovery and profit generation but also offers a customizable framework that can adapt to the specific priorities of different stakeholders. This research contributes to the existing body of knowledge by filling a critical gap in the selection of sustainable waste recovery pathways, offering a practical, optimized, and scalable solution that can significantly advance the goals of the circular economy in the industrial sector.•Decision-making model for stakeholders in the waste management sector.•Model selects the best material recovery pathways.•Textile industrial fabric waste stream used as a pilot to test the model's effectiveness.

Mathematical Analysis of Nonlinear Differential Equations in Polymer Coated Microelectrodes

A theoretical analysis is conducted on the electrochemical behaviour of micro disk electrodes coated with thin coatings of electroactive polymers. The main focus of efforts to characterize the planar diffusion chemical reaction within polymer-modified ultra-microelectrodes is the creation of a theoretical model that explicitly takes into account the potential for the polymer film to cover the inlaid micro disc support surface. Approximate formulae for the steady-state amperometric response and formulation of the boundary value problem are given. The impact of substrate concentration, mediator concentration and current responsiveness in the solution besides the polymer film is also investigated. Akbari-Ganji method (AGM) and differential transformation method (DTM), two adequate and widely available analytical methods, were utilized to determine the steady-state non-linear diffusion equation. The approximate analytical solution for the substrate concentration and mediator concentration and the current for the small experimental kinetic values and diffusion coefficients are presented. We additionally determine the problem’s numerical solution using the MATLAB tool. A satisfactory agreement can be seen when the numerical outcomes verify with the analytical findings.

Application of central composite design (CCD)-response surface methodology (RSM) for optimization of heat transfer in dusty nanofluid flow with velocity slip

Background and Purpose The consequence of thermal radiation is scrutinized on the heat transport of Nano-diamond/silicon oil and silver/silicon oil nanofluids through a stretching endless plate. The single phase (Tiwari and Das) model is employed for nanofluid. The major objective of this study is to optimize the RSM-based Central composite design modeling to optimization of the heat transfer in dusty Oldroyd-B nanofluid across stretching surface. Additionally the velocity slip effect is considered. The dust particle phase is also taken into account. The significance of viscous dissipation, joule heating, inclined magnetic field with convective condition is investigated. Methodology The partial differential equations are developed under consideration, then transform to ODE’s by utilizing similarity tools. The transformed model of ODE’s is tackled numerically via bvp4c MATLAB tool with shooting algorithm. The effect of magnetic parameter, fluid interaction parameter, nanoparticle volume fraction, slip parameter and temperature interaction parameter on velocity field and temperature distribution of fluid phase and dust phase is investigated. Furthermore the Nusselt number on the wall is observed for interactive parameters of mass concentration of dust particles, fluid particles interaction parameter for velocity and unsteady parameters utilizing the face-centered Central Composite design (CCD) of the Response Surface Methodology (RSM). Additionally, Analysis of Variance (ANOVA) algorithm and 3D plots are utilized to examine the consequence of experimental design parameters via the response. The recommended model significance has been analyzed in conditions of correlation coefficient ( R 2 ), mean square error (MSE), root means square error (RMSE), prediction standard error to acknowledge the most excellent strong. Results The difference between the Predicted R2 of 0.9467 and the Adjusted R2 of 0.9867 is less than 0.2, which is assumed to be a reasonable concurrence. Furthermore results of the current analysis indicate that velocity gradient for nanofluid is diminishes for larger fluid particle interaction parameter for velocity, while the dust phase velocity is improved. The increment in Temperature gradients is observed via increasing values of the nanoparticle fraction and temperature base fluid particle interaction parameter. From the results it is concluded that skin friction coefficient is reduced with larger magnetic parameter for both mono nanofluids. Furthermore the heat transfer rate is increased by increasing the thermal radiation parameter for both mono nanofluids. It is concluded that silver/silicon oil nanofluid play a higher role in heat transportation as compare to Nano-diamond/silicon oil.

Exact solutions of the (2+1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(2+1)$$\\end{document}-dimensional Zoomeron model arising in nonlinear optics via mapping method

The Zoomeron model covers particular kinds of solitons with distinctive properties that appear in several physical scenarios, such as, fluid dynamics, nonlinear optics and laser physics. First time utilising the mapping method, we determine the analytical solution to the described model, including several novel dynamical behaviours. Through symbolic computation, we are able to derive the breather waves, kink waves, dark soliton, singular soliton, periodic soliton and bright soliton of this model. Additionally, we encounter single kink waves and single breather waves. We find novel hyperbolic trigonometric, rational and elliptic functions. Modelling our observations with MATLAB tools and producing many 3D graphs. The results obtained will be crucial for further research on complicated nonlinear models.

Non-similar analysis of suction/injection and Cattaneo-Christov model in 3D viscoelastic non-Newtonian fluids flow due to Riga plate: A biological applications

Bioconvective non-Newtonian fluids with motile microorganisms have diverse applications in biology and medicine, offering numerous research opportunities. This article presents a comprehensive investigation into the non-similar analysis of bio-convective micropolar flow induced by a Darcy-Forchheimer exponentially stretchable sheet, considering the effects of suction/injection and thermal radiation in a three-dimensional framework. The fluid under scrutiny is a viscoelastic tangent hyperbolic nanofluid, the impact of Cattaneo-Christov heat subjected to Riga plate is considered for novelty. The role of activation energy and heat source are also computed. The governing equations of viscoelastic tangent hyperbolic nanofluids are transformed into couple of ordinary differential equations via similarity approximations. The resulting ODEs are tackled numerically via bvp4c tool of MATLAB. The impression of appropriate parameters like magnetic parameter, bio-convection parameter, viscoelasticity parameter suction/injection parameter etc. on involved profiles are computed via graphical and tabulated trends. It is observed that velocity layer f′ is dwindled for growing value of Forchheimer number Fr, while reverse relation in velocity curve is noted for developing value of mixed convection parameter δ. Micropolar fluids find biomedical engineering applications in modeling blood flow in microvessels, understanding cerebrospinal fluid dynamics, and optimization of biomedical devices and therapies and simulating drug delivery in tissues.

Impact of solar radiation in the presence of temperature-dependent thermal conductivity of non-Newtonian Casson flow on natural convection heat transfer in plume generated due to the combined effects of heat source and aligned magnetic field

Understanding the non-Newtonian Casson fluid is crucial for addressing various challenges in industrial, biological, and environmental applications. In this novel research, Casson fluid with temperature-dependent variable thermal conductivity is analyzed by a natural convective plume generated by horizontal line heat source. The plume system is under the influence of solar radiation and an aligned magnetic field. The momentum equation is transmuted for Casson fluid, while energy equation transmuted for solar radiation and variable thermal conductivity. The coupled partial differential equations changed into ordinary differential equation by employing stream function formulation. For computational evaluation, bvp4c built-in tool of MATLAB is employed in combination with Shooting technique in order to analyze both missing and specified boundary conditions. The upshots of Casson parameter β 1 , thermal conductivity variable γ 1 , radiation parameter Rd , magnetic force parameter S , Prandtl number Pr and magnetic Prandtl number γ on specified and missing conditions are highlighted in the graphical illustrations. The computed outcomes for missing conditions depicts that for Casson parameter β 1 velocity f ′ and temperature θ drops while current density increased with increment in β 1 . Whereas, for specified boundary conditions, the skin friction f ″ and magnetic flux ϕ ′ decreases while heat transfer rate θ ′ enhances for increasing β 1 . For missing conditions, the increasing thermal conductivity variable γ 1 causes velocity f ′ , current density ϕ ″ , and temperature θ to drop. While for specified conditions, the skin friction f ″ , magnetic flux ϕ ′ increases but heat transfer rate θ ′ exhibits reverse trend with enhancing γ 1 . Additionally, a validation analysis has been performed by comparing the values of f ′ ( 0 ) for various values of Pr with prior work, while excluding the other parameters to check its limitations at the boundary layer.

Melting heat transfer and irreversibility analysis in Darcy-Forchheimer flow of Casson fluid modulated by EMHD over cone and wedge surfaces

The present mathematical model analyses the melting heat transfer and irreversibility in Darcy-Forchheimer flow of Casson fluids modulated by the electroosmosis and magnetohydrodynamic mechanisms over the wedge and cone surfaces. The effects of thermal radiation, thermal buoyancy and heat generation/absorption are taken into consideration. Appropriate similarity transformations are utilized to establish a system of ordinary differential equations which are non-linear. The model has been numerically simulated using shooting approach in conjunction with the fourth order Runge-Kutta method under the bvp4c tool of MATLAB. Numerical results are computed for fluid velocity, fluid temperature, Nusselt number and Bejan number for analysing the fluid flow behaviour and heat transfer characteristics for the Casson fluid. A comparative analysis is performed to determine the irreversibility and heat transfer in the absence and presence of melting parameters, respectively. Variations in skin friction coefficient, local Nusselt number and Bejan number have also been examined under the effects of key parameters. Key findings of the present study indicate enhanced velocity distribution with increasing zeta potential and electric field parameters, while it diminishes with higher Prandtl number and Forchheimer terms. Moreover, fluid temperature reduces with rising zeta potential, while the Bejan number escalates with greater thermal radiation in the core region of geometries. The findings of the model may be useful in various applications of thermal systems.

Design and Implementation of Digital Down Converter for WiFi Network

This paper introduces a field-programmable gate array (FPGA)-based digital down converter (DDC) processing a sampling frequency of about 3.64 GHz to a down-converted frequency of 28.4375 MHz to match the IEEE 802.11ah Wi-Fi HaLow standard. The proposed DDC uses a polyphase mixer(PM) and a resampling filter. The PM adopts parallel coordinate rotation digital computer (CORDIC) processors and lowpass filter arrays to reduce high-speed data rates with minimum resource utilization. Again, the resampling filter employs a cascaded integrator comb (CIC) filter associated with a parallel prefixed adder (PPA) and a multi-channel systolic finite impulse response (FIR) filter implemented with canonical expression, attaining optimum hardware cost. Converting floating-point to fixed-point data types provides significant resource savings. Finally, the improved design is coded in the Xilinx Vivado synthesis tool and successfully tested on the FPGA Kintex-7 device. In contrast to other recent architectures, the proposed design substantially reduces area requirements and power utilization. The Matlab tool verifies the design to achieve an acceptable spurious-free dynamic range (SFDR) of 115 dB.

Hanning FIR window filtering analysis for EEG signals

The window function is a mathematical function in signal processing that is multiplied by a signal to lessen or eliminate the impact of undesired characteristics such as spectral leakage and edge effects that might arise while analyzing finite-duration signals. The Hanning window is just one of several window functionalities available. It is designed to gradually taper the endpoints of a signal to zero, reducing spectral leakage in the frequency domain. Filtering is commonly employed in Electroencephalography (EEG) signal processing to remove noise, artifacts, or undesired frequency components while retaining the desired information. Filtering techniques include band pass, low pass, and high pass and band reject filtering. Hanning window technique using low pass, high pass, band pass, and band reject is used for filtering of EEG signal. The response time analysis for the Hanning window is calculated using low, high, band pass, and band-reject filters for different types of EEG waves alpha, beta gamma, theta, and delta using the signal processing simulation tool MATLAB 2023. The response time for delta wave using a low pass filter has a low response time of 14.125 sec which is comparatively less than another filter. For theta wave high pass filter has a low response time of 11.965 seconds. For alpha wave low pass filter has a low response time of 16.706 seconds whereas for beta wave low pass filter has a low response time of 15.202 seconds. For gamma waves high pass filter has a low response time of 11.349 seconds. Hanning band-reject filter has proven low response time for delta, theta, and gamma waveforms of 16.475 seconds, 16.182 seconds, and 17.743 seconds respectively. The novelty of the work is that the Hanning window improves frequency resolution by balancing the main lobe width with side lobe attenuation Hanning band-reject filter is suited best to figure out the widest main-lobe peak and highest peak for different EEG waveforms.

MATLAB-based Image Super-resolution Technique

This thesis provides an in-depth study of MATLAB-based image super-resolution techniques, covering the application of traditional methods (Fourier Transform, Wavelet Transform, Sparse Representation, Bicubic) and deep learning methods (SwinIR, NAFnet, Path-Restore). In the section on the background and significance of image super-resolution techniques, the wide range of applications of MATLAB in the field of image processing is explored. In the technical foundation section, the principles of image super-resolution technology are detailed, relevant image processing functions and tools in MATLAB are introduced, and the key steps of the technology are described. In the practical application, the comparative analysis of different methods is demonstrated through an example of image super-resolution in a real scene, including the effect diagram and MATLAB code. In the conclusion, the advantages and disadvantages of each method are summarized, which provides a certain reference for the future development of image super-resolution technology.

Examining stagnation-point flow impinging on a deforming cylinder in Reiner-Rivlin fluid with integrated heat and mass transfer

Here the Reiner-Rivlin model is applied to explore non-Newtonian flow in stagnation-point region around a stretching cylinder. Under the influence of viscous heating and thermos-diffusion, the phenomena of combined heat and mass transport are investigated. To explore the intrinsic irreversible nature of transport phenomena, the current work incorporates an analysis of entropy generation. Additionally, prescribed wall temperature and concentration are taken into consideration when developing the computational framework, and it will be shown later that these assumptions are essential to achieving self-similar analysis. Numerical computations are developed by the MATLAB tool “bvp4c” while analytical solutions are found by the optimal homotopy approach embedded in the routine “BVPh 2.0” of MATHEMATICA. For a reasonable choice of embedded parameters, both techniques produce the same numerical results. For various regulating parameters, the importance of curvature effects on the boundary layers is explained. Flow visualization utilizing streamlines and isotherms reveals interesting patterns for both Newtonian and non-Newtonian flows. The force required by the stretching cylinder is analyzed by evaluating skin friction coefficient, in the case of Reiner-Rivlin fluid. Furthermore, surface cooling rate and mass flux are scrutinized graphically and in tabular form. The cooling rate of the cylindrical boundary is higher than that of the flat plate boundary. Furthermore, a noticeable reduction in surface cooling rate is found for increasing values of Reiner-Rivlin fluid parameter.

A Study on Unified Modelling Approach for Memristor: Next Generation Semiconductor Devices

This research investigates the voltage-current (V-I) characteristics of three distinct memristor models, each representing a unique composition and behaviour. The model, denoted as TiN-TiOx-HfOx-Pt-Bilayered Memristor model, is a compact representation designed for Metal–Oxide Resistive Random Access Memory (RRAM). Matlab tool is used for the simulation to analyse V-I characteristics of Memristor. Through comprehensive analysis and simulations, we aim to provide a detailed insight into the intrinsic behaviours of the memristor models. Understanding the V-I characteristics of these models is crucial for their potential applications in emerging memory technologies. This Study elaborate the mathematical modelling of memristor with the outcome untuned V-I Characteristics - DC Switching characteristics. The findings contribute to the broader field of memristor research, fostering advancements in electronic memory devices and computational systems