MATLAB Research Articles

Chaos and feasibility analysis of a healthy lifestyle’s sustainability using fractional-order polycystic ovarian syndrome’s effect on infertility

In this study, we developed a fractional-order model for polycystic ovarian syndrome issue transmission in women through four compartments with the Mittag-Leffler kernel. For biological feasibility, we discussed the positivity and boundedness of solutions with fixed point mappings in Banach spaces. Sensitivity analysis is performed using different variables as response functions each time, employing Latin Hyper-cube Sampling (LHS) and Partial Rank Correlation Coefficient (PRCC) with 200 iterations. Further, the reproductive number is determined for the model’s biological feasibility with an analysis of parameter impact through Matlab software. The solutions are examined for global stability using the Lyapunov function with a first derivative. Chaos Control will use the regulate for linear responses approach to bring the system to stabilize according to its points of equilibrium. Numerical solutions are derived by using a Newton polynomial in the generalized form of the Mittag-Leffler kernel, which illustrates the effect of the fractional operator and parameters involved in the system. Results are also analyzed with different assumptions of parameter values and initial conditions to observe the different impacts of treatment to overcome the risk of infertility in women. Such type of investigation will be useful to investigate the spread of disease as well as helpful in developing control strategies to overcome the risk of problems and best management care pre-detection of the issue and for treatment.

Inverse dynamics analysis of 4-DOF stacking robot with closed chain structure

A four-degree-of-freedom PR1300 stacking robot with two parallel quadrilateral structures connected in series at the shoulder was designed. The hybrid robot with local closed chains has the characteristics of compact structure, high stiffness, and high modularity. To solve the dynamic problem of the hybrid robot. Firstly, by analyzing the induced relationship between joints, the stacking robot with a local closed chain structure is transformed into two branch chain mechanisms, and the kinematic model of the robot is established using the D-H parameter method. Secondly, the Kane method is applied to model the dynamics of the two branch chains separately, and the rigid body dynamics Kane equation of the entire 4-DOF stacking robot with a closed chain structure is obtained through the augmented matrix. Finally, the SolidWorks Motion mechanical simulation platform and MATLAB software were used to program dynamic simulations and numerical calculations, and the results were compared to verify the correctness of the dynamic theory derivation. This theory provides a necessary theoretical basis for the subsequent synthesis of robot dynamic scales.

Entropy generation in radiative motion of tangent hyperbolic nanofluid in the presence of gyrotactic microorganisms and activation energy

In this work, entropy generation is optimized through the application of the second law of thermodynamics. The slip mechanisms, Brownian diffusions, and thermophoresis are elaborated using the tangent hyperbolic nanomaterial model. Magnetohydrodynamic (MHD) fluid is taken into consideration. To characterize the impact of activation energy, a unique model involving the binary chemical reaction is deployed. The effects of mixed convection that is nonlinear in nature, bioconvection, and Joule effect are all taken into consideration. The key partial differential equations (PDEs) are reduced into ordinary differential equations (ODEs) by utilizing appropriate similarity transformations and then solved numerically with the help of a built-in ‘bvp4c’ technique of MATLAB software. Varied flow parameters’ impacts on the nanoparticle volume concentration, entropy number, microorganism concentration, temperature, and velocity fields are analyzed using graphs. Various flow variables are taken into consideration to calculate the total rate of entropy generation. The obtained results show that concentration irreversibility, Joule effect irreversibility, viscous dissipation, and heat irreversibility all influence the entropy. The numerical outcomes were observed by fixing the physical parameters as 0.1<α<4.0, 0.1<M<1.2, 0.1<Nr<2.2, 0.1<Le<2.2, 0.1<Nb<0.4, 0.1<Nt<1.0, 2.0<⁡Pr⁡<5.0, and 0.1<Lb<2.0, as well as their impact on the momentum, thermal, concentration, and microorganism density profiles. From results, an increasing estimate of the variable representing chemical reaction indicates a decline in the concentration. The higher the chemical reaction variable, Hartmann number, and Weissenberg number, the higher the entropy number, while the Bejan number has a contrary behavior. Subsequently, all the outcomes are plotted in graphs and discussed in detail, when subjected to the involving physical quantities.

Research on the evaluation method for safety cognitive ability of workers in high-risk construction positions

PurposeSafety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of factors influencing safety cognition and lack a quantitative evaluation system of safety cognitive ability. The purpose of this paper is to find out the deficiencies in the safety cognition of workers in high-risk construction positions and to provide practical suggestions for improving their safety cognitive ability and reducing unsafe behavior.Design/methodology/approachBased on the iceberg model, the factors influencing the safety cognitive ability of workers in high-risk construction positions and their hierarchical relationship were determined, and an evaluation index system consisting of four primary indicators and 20 secondary indicators was constructed. The game theory algorithm was used to optimize the subjective and objective weights of the indicators calculated by the sequential analysis method (G1) and the entropy weighting method (EWM) to obtain the optimal combination weight value. The Matlab software was used for cloud mapping and similarity calculation to determine the safety cognitive ability level of the object to be evaluated.FindingsThe research results indicate that the comprehensive level of safety cognitive ability of scaffolders in this construction project is at “Level III”, the fundamental factors and compliance factors are at “Level IV”, the auxiliary factors and driving factors are at “Level III”. This conclusion aligns with the situation learned from the previous field investigation, which validates the feasibility and scientificity of the proposed evaluation method.Research limitations/implicationsConsidering that the safety cognitive ability of construction workers is constantly changing, this study has not yet delved into the specific impacts of various influencing factors on the level of safety cognitive ability. Future research can utilize simulation software, such as MATLAB and Vensim, to construct dynamic simulation models that accurately simulate the changing rules of construction workers’ safety cognitive ability under the influence of different factors.Practical implicationsThis research broadens the application scope of the iceberg model, enriches the analysis model of the factors influencing the safety cognitive ability of workers in high-risk construction positions and provides a novel perspective for similar research. The safety cognitive ability evaluation method proposed in this paper can not only accurately evaluate the safety cognitive ability level of workers in high-risk positions such as scaffolders but also provide practical suggestions for improving the safety cognitive ability of workers, which is of great significance to improve the safety management level and reduce unsafe behavior in the construction field.Originality/valueThis research fills the research gap of workers in high-risk construction positions and the quantification of safety cognitive ability. The iceberg model is used to realize the hierarchical division of the factors influencing safety cognitive ability. Additionally, an evaluation method for the safety cognitive ability of workers in high-risk construction positions based on the game theory combination weighting method and cloud model is proposed, which realizes the quantitative evaluation of safety cognitive ability.

Improving Dynamic Performance of a Small Rhizome Chinese Herbs Harvesting Machine via Analysis, Testing, and Experimentation

The small rhizome Chinese herbal medicine harvesting machine is used for excavating the underground rhizomes of Chinese medicinal plants. The reliability of an existing machine of this type was found to be suboptimal due to high vibration levels, as confirmed by direct measurements. To remedy this issue, the differential equation of motion was derived, solved, and visualized using MATLAB software (R2017a). The impact of various parameters on the equation of motion was analyzed through both time and frequency domain plots, as well as experimental analysis. The parameters studied included the rotational speed of the tractor’s power take-off (PTO) shaft, the machine’s overall mass and stiffness, the transmission ratio, and the excitation force generated by the machine’s reciprocating parts. To reduce vibration in the non-resonant state and avoid resonance as the natural frequency changes, several modifications were necessary: the PTO speed needed to be controlled, the stiffness of the machine had to be increased, and the mass of the reciprocating parts had to be decreased. Additionally, expanding the transmission-ratio range of the operational machinery was essential. Sandbags were added to the machine’s frame to increase its overall mass. The above measures have reduced the vibration speed of the harvester during operation. The vibration speeds Vmax and VRMS of the harvester under both working and non-working conditions have decreased by half compared to their original values, reducing the occurrence of resonance in the harvester and effectively mitigating vibration damage, thereby enhancing operational reliability.

A hybrid approach based energy management of hybrid energy systems with efficient economic model

ABSTRACT This paper proposes a hybrid AHO-SNN-based energy management (EM) of hybrid energy systems (HES) with an efficient economic model. The proposed hybrid method is combined with the Archerfish Hunting Optimizer (AHO) and Spiking Neural Network (SNN). Commonly, it is named as AHO-SNN technique. The major aim of the AHO-SNN method is the efficient economical modeling of HES and the study of sizing and EM. The comprehensive approach for describing the ideal size EM system (EMS) combination for HES is presented in this paper. The HESs, like fuel cell (FC), electrolyzer (EL), PV, battery energy system (BES), diesel generator (DSL), and hydrogen tank (HT). To determine the ideal size-EMS combination, this new EMS is employed to re-use the analytical as well as economic sizing. The AHO-SNN technique is implemented in the MATLAB software and is compared to various existing techniques. The AHO-SNN method provides an optimum outcome than the existing Particle Swarm optimization (PSO), Heap based optimizer (HBO), and Wild horse optimizer (WHO) methods. The power comparison of the existing technique HBO achieved power is 30 W, WHO is 20 W, WHO is around 10 W. In the proposed technique, the power generated is 40 W, which is way higher than the existing techniques. After implementing the integrated framework, the size of PV is cut in half, from 140 to 60 kW, which reduces the electrolyzer and the size of the hydrogen tank in also cut in half. In addition to a 35% decrease in diesel generator working hours and a 40% reduction in the leveled energy cost, PV degrades at a rate of 0.5%.

Optimization of Fuzzy Mathematical Model of Regular Octagon-Shaped Parking Space

In the vigorous development of the city population, there is a need to set up clear dimensions for the parking space. Car parking plays a significant part in the residential apartments and commercial buildings. Roadside parking spaces will create a huge traffic problem if the parking lots are not properly designed. Sometimes, it leads to the accident. Hence, keeping all these causes in mind, the flexible parking space is the necessary of the time. In the proposed research work, the parking space considered in the problem is of a regular octagon shape, and the mathematical model is developed under a fuzzy environment. LINGO Optimization Software is used to solve the mathematical model and MATLAB(Matrix Laboratory) is used to define the fuzzy variable. At the outset, the results will reveal the importance of making the length of the parking lot under fuzzy environment.

Numerical study of magneto convective ag (silver) graphene oxide (GO) hybrid nanofluid in a square enclosure with hot and cold slits and internal heat generation/absorption

Energy transmission is widely used in various engineering industries. In recent times, the utilization of hybrid nanofluids has become one of the most popular choices in various industrial fields to increase thermal performance and enhance power generation, entropy reduction, solar collectors, and solar systems. Motivated by this wide range of applications, the present article explores the mixed convection flow and heat transfer of magnetohydrodynamic \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:Ag$$\\end{document} (Silver) and \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:GO$$\\end{document} (Graphene) nanofluids hybrid nanofluids in a square enclosure with heat generation/absorption by using the MAC method. The vertical walls of the enclosure are assumed to be adiabatic. The horizontal walls are also assumed adiabatic except for the center portion of the top and bottom walls of the cavity. The center portion of the horizontal upper wall is maintained as a cold is \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:{(T}_{c})$$\\end{document}and the lower wall is maintained as hot \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\left({T}_{h}\\right)$$\\end{document}. The dimension equations are transformed into dimensionless form and then discretized and solved with the finite difference Marker and cell (MAC) method. Numerical modelling is implemented, by changing Richardson number \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\left(Ri\\right)$$\\end{document}, The results are located graphically using MATLAB software. The Nusselt number graph was displayed for the Reynolds number (Re), Richardson number\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\:\\left(Ri\\right)$$\\end{document}, and Hartmann number \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:\\left(Ha\\right)$$\\end{document}. The findings show that enhancing the values of the Richardson number and Reynolds number enhances the Nusselt number values except for the Hartmann number. The findings indicate that the combination of the new model is very good at predicting thermal conductivity and correlates experimental results well. The augmenting strength of magnetic force diminishes fluid flow. Developing the coefficients for the heat source and sink improves energy transmission and heat transfer enhancement. Hybrid nanofluids like \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\:Ag-GO$$\\end{document} enhance heat transfer and efficiency. They improve cooling in heat exchangers, radiators, and electronics, boost solar energy systems, aid in cancer treatment and drug delivery, enhance geothermal and wind turbine efficiency, and improve manufacturing processes. Overall, they optimize thermal management in various applications.

Investigation of the Electrical Characteristics of AlGaN/AlN/GaN Heterostructure MOS-HEMTs with TiO2 High-k Gate Insulator

This paper investigates the impact of TiO2 high-k gate insulator on the electrical characteristics of AlGaN/AlN/GaN MOS-HEMT transistors using MATLAB and Atlas-TCAD simulation software. The physical analytical model of the MOS-HEMTs is used for simulation from Al2O3, HfO2, and TiO2 as the gate dielectric materials, which provide higher performance and reliability of the MOS-HEMT devices. The device shows a good improvement in its result of the DC and AC characteristics with different permittivity of insulator materials. Thus, the DC and AC performance of GaN MOS-HEMTs is higher than with other insulators, such as Al2O3 and HfO2 by using TiO2 as the gate dielectric. Moreover, the simulation results proved that TiO2 is the better gate dielectric material to enhance the electrical reliability of the power switching devices for high-temperature applications such as electric automobiles.

New hybrid system of PV/T, solar collectors, PEM electrolyzer, and HDH for hydrogen and freshwater production: Seasonal performance investigation

A new hybrid energy system of PV/T, flat plate collector, PEM electrolyzer, and humidification-dehumidification desalination is introduced here. A comprehensive mathematical model for the system seasonal performance is constructed and solved numerically using MATLAB software. A year-round comparison between the traditional PV/T performance and its concentrated counterpart indicates that the latter performs better compared to power, hydrogen, and freshwater production and system overall efficiency. The maximum monthly achieved PV/T efficiency, electrolyzer efficiency, desalination system Gain Output Ratio, and overall system efficiency are 52 %, 62 %, 4.8 %, and 44 %, respectively at a concentration ratio of 4 and maximum allowable PV temperature. The system produces 82,200 kWh of energy annually and provides 77,700 kWh and 1500 kWh to the electrolyzer and the electric heater, respectively. Moreover, the system produces an annual freshwater production of about 52,700 kg, out of which approximately 10,000 kg are consumed in the electrolysis process, and an annual hydrogen production of approximately 1120 kg.

Irreversibility analysis of radiative TiO2+Al2O3+Cu/H2O ternary nanofluid flow over a bidirectional stretching sheet with cattaneo-christov heat flux: nanotechnology applications

Ternary nanofluids demonstrate better heat transfer characteristics in contrast to conventional liquids and typical hybrid nanofluids. These are applied in sophisticated cooling systems for electronics, heat exchangers, and automotive engines, along with renewable energy systems such as solar collectors, where efficient heat transfer plays a crucial role. The aim of this research is to investigate the movement of a Casson ternary nanofluid passing through a bidirectional exponential sheet by employing the innovative Cattaneo-Christov heat flux concept. The utilization of the energy equation considers thermal radiation, viscous dissipation, and heat source/sink effects, with the integration of chemical reaction effects into the concentration equation. An analysis of entropy generation is utilized to evaluate the thermodynamic irreversibility within the system. The conversion of transport equations involves a transformation from partial to ordinary differential equations, followed by a numerical solution utilizing the BVP4C solver embedded in the MATLAB package R2022b. The impacts of developed factors on thermal, concentration, and velocity behavior, as well as engineering quantities, are thoroughly explored graphically. The outcome reveals that the velocity gradients diminish as magnetic fields intensify, while it amplified by the Hall factor. The rise in temperature of ternary nanofluid correlates with elevated levels of radiation, and Brownian motion. Concentration intensifies with the rapid development of thermophoresis influences. Heightened values of the Reynolds and Brinkman numbers give rise to amplified entropy production but a decrease in the Bejan number. The ternary nanofluid displays a remarkable 8.92% increase in skin friction on the x-axis and y-axis, influenced by the potent Darcy-Forchheimer factor. The rates of mass and heat transfer in nanofluids undergo a decrease of 8.58% and 12.52%, respectively, due to the heightened influence of Brownian motion and Eckert number. The results could provide valuable insights into the performance of ternary nanofluids in various industrial environments under specific conditions.

Vibrations Control of a SODF Structure Using TMD and MR Damper with Fuzzy Logic Algorithm Based on Velocity

In this study, the effects of using a passive tuned mass damper (TMD) with optimal parameters and a semi-active magnetorheological damper (MR damper) have been evaluated separately and simultaneously to control seismic vibrations of a linear single degree of freedom system, which was a simple "mass-spring-damper" model. OpenSEES software was used to model the single degree of freedom system and TMD, and MATLAB software was used to model MR damper. Fuzzy logic algorithm was used by MATLAB to determine the appropriate voltage for MR damper. By solving the dynamic equation of the damper, its force was calculated and this force was applied to the single degree of freedom system by OpenSEES. In the following, incremental dynamic analysis (IDA) has been performed using 7 earthquake records with maximum acceleration of 0.1g to1.0g with incremental step of 0.1g. Earthquakes are applied to four models without dampers, equipped with optimized TMD, equipped with MR damper, and equipped with both TMD and MR damper. The results showed that the simultaneous use of TMD and MR damper had the greatest effect on controlling the vibration of the system and reduced the maximum displacement by 22.36% and the maximum base shear by 21.85% compared to the case without dampers. Also, using only MR damper had a greater effect than using only TMD on reducing the seismic responses of the single degree of freedom system.

MHD Free Convection Boundary Layer Flow on a Horizontal Circular Cylinder in a Williamson Hybrid Ferrofluid with Viscous Dissipation

The present research examined the flow of a horizontal circular cylinder immersed in a Williamson hybrid ferrofluid via free convection boundary layer flow. The fluid flow is modelled by means of governing partial differential equations that incorporate viscous dissipation and magnetohydrodynamic (MHD) effects. Prior to being converted into a more practical partial differential equation, these dimensional equations are reduced to a non-dimensional form by utilising appropriate dimensionless variables. The Keller-box approach is then used to solve these equations with fewer dependent variables numerically. Graphical representations are generated, and the impacts of different interested factors are analysed using MATLAB software. According to the results, the hybrid ferrofluid outperformed ferrofluid with the same particle volume fraction in terms of skin friction and convective heat transfer capabilities.

A Novel Approach for Chronic Kidney Disease Identification Empowered with Fuzzy Logic

Chronic kidney disease (CKD) is a non-communicable condition that often leads to renal failure, which is when the kidneys are no longer able to filter waste and excess fluid from the body's circulation. Early detection of CKD can slow the progression of the illness and reduce the overall cost of treatment. In this work, a novel approach for identifying CKD using a fuzzy logic system is proposed. The fuzzy system includes eight input parameters such as weight, age, serum creatinine, diastolic blood pressure, systolic blood pressure, glomerular filtration rate, blood glucose, and smoking. The output variable describes a specific patient’s stage of chronic renal disease based on these input factors. The output will indicate the current stage of a patient’s kidney disease. This system can therefore assist specialists in determining the stage of chronic renal disease. The MATLAB software is used to create the fuzzy system. The proposed system is tested on a real data set of patients and the results obtained are promising.

Frequency experimental identification approach for single-phase induction motor common-mode parameters

Introduction. The presence of broad-spectrum and high-amplitude electromagnetic interference (EMI) within a single-phase induction motor (SPIM) drive poses a significant threat to both the system and other electronic equipment. High-frequency (HF) models of electrical motors play a critical role in overcoming these challenges, as they are essential for characterizing electromagnetic compatibility (EMC) in drives and designing effective EMI filters. The novelty of this study proposes an enhanced HF motor model based on transfer functions (TFs) to accurately represent the motor’s behavior at HFs for frequency-domain analyses in the range of 100 Hz to 30 MHz. Purpose. The equivalent HF model for a SPIM is discussed in this paper. The suggested equivalent circuit describes a motor’s common-mode (CM) properties. Methodology. HF model was developed by a frequency-domain analysis utilizing an experimental setup and MATLAB software. The motor impedance analysis is based on the measurement of variations in motor characteristics as a function of frequency in the CM setup. Originality. TF has been tuned using an asymptotic identification method of Bode to match the behavior of the real impedances of the motor parameters as a function of the frequency in the CM configuration. This tuned TFs are then synthesized into a comprehensive wideband EMC equivalent circuit model using the Foster network technique, which can be then simulated in any Spice-based simulator tools. Results. The proposed mathematical model was employed to conduct simulations, and the resulting predictions were validated against experimental data. CM response of the EMC equivalent circuit at low, medium, and HFs were compared between simulations and experimental measurements using Lt-Spice simulator software. Practical value. It is observed that results show satisfactory agreement with the measurements over a large frequency bandwidth [100 Hz–30 MHz], and the equivalent model of SPIM can be cascaded with other electronic and electrical modules to form a complete single-phase electric drive system model for fast analysis and prediction of system level EMI and electromagnetic sensitivity. References 37, table 5, figures 13.

Thermodynamical interactions in a double porosity model with diffusion and microtemperatures

This manuscript investigates the disruptions occurring in a two-dimensional homogeneous, isotropic, thermoelastic medium with diffusion, double porosity and microtemperatures under Lord and Shulman (LS) theory of generalized thermoelasticity. A mechanical load is applied at the outer free surface of the solid half-space. To procure the exact expressions for various field variables, normal mode analysis is utilized. Numerical computations are performed for a particular material and the acquired results are visualized through graphical representations with the aid of MATLAB software. Comparisons are carried out to elucidate the influences of diffusion parameter, time, double porosity and intensity of load on the resulting quantities. 2010 MSC: 74A15, 80A20.

Hybrid trajectory tracking control of wheeled mobile robots using predictive kinematic control and dynamic robust control

AbstractTrajectory tracking control of wheeled mobile robots (WMRs) is still a remarkable problem for many applications. In the present paper, a hybrid control is presented based on dynamic and kinematic equations of motion for wheeled mobile robots in the presence of the sum of the external disturbances and parametric uncertainty. The designed control for the WMR utilizes control and guidance to reach the reference path. In many studies, a control strategy is normally employed for WMR. However, in this study, hybrid control was used for the mentioned purpose. Akin to other studies, the kinematic control scheme here was based on the predictive control, and the dynamic control scheme was designed based on the robust control. Therefore, in this article, having introduced the kinematic model, a nonlinear predictive control was proved and designed. In the next step, a finite‐time integral type terminal sliding mode control (FITSMC) was designed based on the nonlinear dynamic model in order to automatically adjust the control gain and eliminate online disturbances and destructive chattering phenomena completely. In particular, a finite‐time disturbance observer was designed to estimate the external disturbances. The proof of the new proposed control scheme was presented using Lyapunov stability theory and numerical results. The mentioned integrated scheme, including predictive control (outer loop) and nonlinear adaptive control (inner loop), ensures the convergence and optimal tracking performance of all signals, as a result of which the tracking errors can arbitrarily converge to the origin in a finite time. In the final step, the simulation results were presented to show the effectiveness of the proposed scheme using MATLAB software, and the introduced control design was compared with a similar controller quantitatively and qualitatively.

Iowa Brain-Behavior Modeling Toolkit: An Open-Source MATLAB Tool for Inferential and Predictive Modeling of Imaging-Behavior and Lesion-Deficit Relationships.

The traditional analytical framework taken by neuroimaging studies in general, and lesion-behavior studies in particular, has been inferential in nature and has focused on identifying and interpreting statistically significant effects within the sample under study. While this framework is well-suited for hypothesis testing approaches, achieving the modern goal of precision medicine requires a different framework that is predictive in nature and that focuses on maximizing the predictive power of models and evaluating their ability to generalize beyond the data that were used to train them. However, few tools exist to support the development and evaluation of predictive models in the context of neuroimaging or lesion-behavior research, creating an obstacle to the widespread adoption of predictive modeling approaches in the field. Further, existing tools for lesion-behavior analysis are often unable to accommodate categorical outcome variables and often impose restrictions on the predictor data. Researchers therefore often must use different software packages and analytical approaches depending on whether they are addressing a classification vs. regression problem and on whether their predictor data correspond to binary lesion images, continuous lesion-network images, connectivity matrices, or other data modalities. To address these limitations, we have developed a MATLAB software toolkit that supports both inferential and predictive modeling frameworks, accommodates both classification and regression problems, and does not impose restrictions on the modality of the predictor data. The toolkit features both a graphical user interface and scripting interface, includes implementations of multiple mass-univariate, multivariate, and machine learning models, features built-in and customizable routines for hyper-parameter optimization, cross-validation, model stacking, and significance testing, and automatically generates text-based descriptions of key methodological details and modeling results to improve reproducibility and minimize errors in the reporting of methods and results. Here, we provide an overview and discussion of the toolkit features and demonstrate its functionality by applying it to the question of how expressive and receptive language impairments relate to lesion location, structural disconnection, and functional network disruption in a large sample of patients with left hemispheric brain lesions. We find that impairments in expressive vs. receptive language are most strongly associated with left lateral prefrontal and left posterior temporal/parietal damage, respectively. We also find that impairments in expressive vs. receptive language are associated with partially overlapping patterns of fronto-temporal structural disconnection, and that the associated functional networks are also similar. Importantly, we find that lesion location and lesion-derived network measures are highly predictive of both types of impairment, with predictions from models trained on these measures explaining ~30-40% of the variance on average when applied to data from patients not used to train the models. We have made the toolkit publicly available, and we have included a comprehensive set of tutorial notebooks to support new users in applying the toolkit in their studies.

Impact of Employment Salary Level of Graduates from Higher Education Institutions in China

Based on the analysis of questionnaire survey data on college graduates, we constructed a multiple linear regression model using Matlab software to study the factors affecting the salary level of graduates, such as University rank and geographical locations, which provides a reference basis for the employment planning of college students. The results indicate that the nature of the university and the ranking of geographical regions have a significant impact on the salary level of college graduates. We utilize the proposed method to study typical two universities in China, demonstrating the effectiveness of our analysis. Finally, from the perspective of talent employment in universities, feasible and effective measures to improve the salary level of college graduates were discussed.

Analysis of relaxation characteristics of multi-bolted connections under the transverse cyclic load

A modeling method under lateral cyclic loading is proposed for the complex multi-bolt connection loosening problem. Firstly, the thread stress surface is divided into n small sectors, and the self-relaxation mechanical model of multi-bolt connection is established considering the interaction between bolts. Secondly, the self-relaxation model is solved by MATLAB software and compared with Nassar model to verify the correctness of the model. Finally, considering the influence of different bolt number, hole clearance and connection spacing, the relaxation characteristics of multi-bolt connection are studied. The results show that during the loosening process, the bolt head undergoes a bending-sliding-bending cycle process, and the bolt tension shows a wave downward trend. When multiple bolts are connected, the number of loosening cycles decreases linearly with the increase of hole clearance. With the equidistant increase of bolt connection spacing, the number of bolt loosening cycles shows a decreasing trend. Compared with the number of bolts, the change of bolt hole clearance and connection spacing is more likely to affect bolt loosening.