Showing papers in "Nonlinear Engineering in 2023"

Dynamical aspects of transient electro-osmotic flow of Burgers' fluid with zeta potential in cylindrical tube

Abstract: Abstract In this article, we consider the flow of a Burgers’ fluid of transient electro-osmotic type in a small tube with a circular cross-section. Analytical results are found for the transient velocity and, electric potential profile by solving the Navier–Stokes and the linearized Poisson–Boltzmann equations. Moreover, these equations are solved with the help of the integral transform method. We consider cases in which the velocity of the fluid changes with time and those in which the velocity of the fluid does not change with time. Furthermore, special results for classical fluids such as Newtonian, second grade, Maxwell, and Oldroyd-B fluids are obtained as the particular cases of the outcomes of this work and that these results actually strengthen the results of the solution. This study of the nonlinear problem of Burgers’ fluid in a specified physical model will help us to understand the behavior of blood clotting and the block of any kind of problem in which this type of fluid is used. The solution of the complex velocity profile of Burgers’ fluid will help us in the future to solve the problems in which this transient electro-osmotic type of small tube is involved. At the end, numerical results are shown graphically that can help us to understand the complex behavior of the Burgers’ fluid, and also the analysis of the Burgers’ fluid shows dissimilarity with other fluids that are considered in this work.

Analytical and numerical study for the generalized q-deformed sinh-Gordon equation

Abstract: Abstract In this article, we study the generalized q q -deformed sinh-Gordon equation analytically using the new general form of Kudryashov’s approach and numerically using the finite difference method. We develop a general form of the Kudryashov method that contains more than one constant that is used to give more explanations for the solutions that are obtained. The numerical results are also presented using the finite difference approach. We also provide numerous figures to demonstrate the various solitons propagation patterns. The proposed equation has opened up new options for describing physical systems that have lost their symmetry. The equation under study has not been studied extensively, so we completed the lesson that started a short time ago on it.

Investigation of magnetized convection for second-grade nanofluids via Prabhakar differentiation

Abstract: Abstract The application of nanoparticles in the base fluids strongly influences the presentation of cooling as well as heating techniques. The nanoparticles improve thermal conductivity by fluctuating the heat characteristics in the base fluid. The expertise of nanoparticles in increasing heat transference has captivated several investigators to more evaluate the working fluid. This study disputes the investigation of convection flow for magnetohydrodynamics second-grade nanofluid with an infinite upright heated flat plate. The fractional model is obtained through Fourier law by exploiting Prabhakar fractional approach along with graphene oxide ( GO ) ({\rm{GO}}) and molybdenum disulfide ( Mo S 2 ) ({\rm{Mo}}{{\rm{S}}}_{2}) nanoparticles and engine oil is considered as the base fluid. The equations are solved analytically via the Laplace approach. The temperature and momentum profiles show the dual behavior of the fractional parameters ( α , β , γ ) (\alpha ,\beta ,\gamma ) at different times. The velocity increases as Grashof number {\rm{Grashof\; number}} increases and declines for greater values of magnetic parameter and Prandtl number. In the comparison of different numerical methods, the curves are overlapped, signifying that our attained results are authentic. The numerical investigation of governed profiles comparison shows that our obtained results in percentages of 0.2 0.2 ≤ temperature ≤ 4.36 4.36 and velocity 0.48 ≤ 7.53 0.48\le 7.53 are better than those of Basit et al. The development in temperature and momentum profile, due to engine oil–GO is more progressive, than engine oil–MoS2.

Establishment of nonlinear network security situational awareness model based on random forest under the background of big data

Abstract: Abstract In order to explore the establishment of a nonlinear network security situational awareness model based on random forest in the context of big data, a multi-level network security knowledge system evaluation model based on random forest is proposed. This article proposes a multi-level CSSA analysis system and then uses random memory algorithm to create a CSSA evaluation model. Also, it proposes a CSSA multi-level analysis framework and then uses random forest algorithm to build a CSSA evaluation model. A random vector distribution of the same values is used for all forest trees. In this article, the interval [0,1] is used to quantitatively describe the weight of the security level. The training sample ratio of test samples is 110:40, in order to predict the security of the network, the prediction of knowledge is closer to the true value, and the complexity of multi-level security is predicted. Use unusual forests. The tree returns the most recommended part, which is a more realistic assessment of network security. The experimental results show that considering the network security situation, the prediction performance of this method is closer to the actual value, and the performance is better than the other two methods. Therefore, perception of multi-level security situations can be effectively predicted using random access memory. It is proved that random forest is faster and more efficient in network security.

Nonlinear analysis and processing of software development data under Internet of things monitoring system

Abstract: Abstract The most important and core technology of the Internet of things (IoT) is still the internet, and it also includes many other technical fields and is applied to many fields. The various processes of IoT data are the guarantee that the IoT can meet the management and management requirements in a certain application field, so that each application field can better meet the requirements of people’s lives. In order to study the nonlinear analysis and processing of software development data under the IoT monitoring system, this work uses QT software and socket programming to build the detection, control, and transmission module of the system, and uses multiple processes to classify and process the data. The user interface technology is used to display the data in real time. The system can control the type of transmitted data through interface operation. The classified transmission of data is realized, and the transmission speed is guaranteed to be about 50 MB/s. The experimental results show that after the functional design of each module is completed, the whole system is finally tested to determine whether the system can meet the requirements of data transmission, control, and processing. Since these data are simulated data, video playback is used to simulate the occurrence of a real accident. When an abnormal situation occurs, the whole system starts to work. If an accident occurs, a signal is sent after the accident. The system not only ensures the intellectualization of control, but also ensures the rapidity of data transmission.

Influence of the blade size on the dynamic characteristic damage identification of wind turbine blades

Abstract: Abstract In this article, the sensitivity coefficients of dynamic characteristic damage identification of blades with different sizes were investigated. The results show that the first third-order vibration modes of the blade before and after damage are consistent, and the wind turbine blade size has no significant effect on the vibration mode; with the increase of the blade size, the first-, third- and fourth-order natural frequency sensitivity coefficients decrease gradually, while the second-, fifth- and sixth-order natural frequency sensitivity coefficients increase gradually; as the blade size increases, the third-order displacement mode sensitivity coefficient of the blade gradually increases, which indicates that the displacement modes identification effect is better with the increase of the blade size. With the increase of the blade size, the first- and third-order strain modal sensitivity coefficients increase gradually, which indicates that when using first- and third-order strain modes for damage identification, the larger the blade size, the better the identification effect; with the increase of the blade size, the second-order strain modal sensitivity coefficient decreases gradually, which indicates that when using second-order strain mode for damage identification, the larger the blade size, the worse the identification effect. This research could provide a theoretical basis for the application of the dynamic characteristic damage identification method in the damage identification of wind turbine blades of different sizes.

Convolutional neural network for UAV image processing and navigation in tree plantations based on deep learning

Abstract: Abstract In this study, we show a new way for a small unmanned aerial vehicle (UAV) to move around on its own in the plantations of the tree using a single camera only. To avoid running into trees, a control plan was put into place. The detection model looks at the image heights of the trees it finds to figure out how far away they are from the UAV. It then looks at the widths of the image between the trees without any obstacles to finding the largest space. The purpose of this research is to investigate how virtual reality (VR) may improve student engagement and outcomes in the classroom. The emotional consequences of virtual reality on learning, such as motivation and enjoyment, are also explored, making this fascinating research. To investigate virtual reality’s potential as a creative and immersive tool for boosting educational experiences, the study adopts a controlled experimental method. This study’s most significant contributions are the empirical evidence it provides for the efficacy of virtual reality in education, the illumination of the impact VR has on various aspects of learning, and the recommendations it offers to educators on how to make the most of VR in the classroom.

Research and implementation of non-linear management and monitoring system for classified information network

Abstract: Abstract In order to better realize the secret-related information monitoring system, an algorithm based on a nonlinear network is proposed and is combined with the traditional algorithm. This article mainly analyzes the theory of nonlinear networks, designs and trains new network parameters according to their own needs, and combines the nonlinear network as a feature extractor with the existing intrusion detection and wandering detection algorithms, which greatly improves the recognition ability of traditional algorithms. The main feature of a nonlinear network is that it can extract the positional features of objects from the network while also extracting object features, that is, positioning and classification are realized in the same network. As a feature extractor, this network can not only have a higher recognition rate than background difference, hog, and other algorithms but also have a greater ability to extract position information than other convolutional neural networks. The successful application of nonlinear production network systems in TV stations at all levels has greatly improved the editing and production capability and efficiency of TV programs. How to ensure the safe, reliable, stable, orderly, and efficient operation of nonlinear production network systems requires vendors and TVS Taiwan technical staff to jointly conduct in-depth research and summarize their findings. In this article, from the perspective of TV users, information components in nonlinear production network systems are analyzed, including class, title management mode, storage space management, material management, security management, and workflow management in nonlinear systems. Make some analysis, discussion, and summaries of network system and operation management problems. The experimental results show that the nonlinear algorithm in this article has a significant advantage over the original tracking algorithm; that is, most tracking algorithms do not have the ability of category recognition during the initial tracking process, which means that these tracking algorithms cannot accurately know what they are tracking. Because the nonlinear network has the ability to output categories, whether it is initial tracking or tracking loss recovery, nonlinearity has fundamentally better advantages than other tracking algorithms. Therefore, it can be predicted that there is a strong recognition ability in the later monitoring and wandering detection. It has been proved that the nonlinear algorithm can be effectively applied to the secret information monitoring system.

Cilia and electroosmosis induced double diffusive transport of hybrid nanofluids through microchannel and entropy analysis

Abstract: Abstract A mathematical model is presented to analyze the double diffusive transport of hybrid nanofluids in microchannel. The hybrid nanofluids flow is driven by the cilia beating and electroosmosis in the presence of radiation effects and activation energy. Cu–CuO/blood hybrid nanofluids are considered for this analysis. Phase difference in the beatings of mimetic cilia arrays emerge symmetry breaking pump walls to control the fluid stream. Analytical solutions for the governing equations are derived under the assumptions of Debye–Hückel linearization, lubrication, and Rosseland approximation. Dimensional analysis has also been considered for applying the suitable approximations. Entropy analysis is also performed to examine the heat transfer irreversibility and Bejan number. Moreover, trapping phenomena are discussed based on the contour plots of the stream function. From the results, it is noted that an escalation in fluid velocity occurs with the rise in slippage effects near the wall surface. Entropy inside the pump can be eased with the provision of activation energy input or by the consideration of the radiated fluid in the presence of electroosmosis. The results of the present study can be applicable to develop the emerging thermofluidic systems which can further be utilized for the heat and mass transfer at micro level.

Cross-modal multi-label image classification modeling and recognition based on nonlinear

Abstract: Abstract Recently, it has become a popular strategy in multi-label image recognition to predict those labels that co-occur in a picture. Previous work has concentrated on capturing label correlation but has neglected to correctly fuse picture features and label embeddings, which has a substantial influence on the model’s convergence efficiency and restricts future multi-label image recognition accuracy improvement. In order to better classify labeled training samples of corresponding categories in the field of image classification, a cross-modal multi-label image classification modeling and recognition method based on nonlinear is proposed. Multi-label classification models based on deep convolutional neural networks are constructed respectively. The visual classification model uses natural images and simple biomedical images with single labels to achieve heterogeneous transfer learning and homogeneous transfer learning, capturing the general features of the general field and the proprietary features of the biomedical field, while the text classification model uses the description text of simple biomedical images to achieve homogeneous transfer learning. The experimental results show that the multi-label classification model combining the two modes can obtain a hamming loss similar to the best performance of the evaluation task, and the macro average F1 value increases from 0.20 to 0.488, which is about 52.5% higher. The cross-modal multi-label image classification algorithm can better alleviate the problem of overfitting in most classes and has better cross-modal retrieval performance. In addition, the effectiveness and rationality of the two cross-modal mapping techniques are verified.

Derivation of septic B-spline function in n-dimensional to solve n-dimensional partial differential equations

Abstract: Abstract In this study, a new structure for the septic B-spline collocation algorithm in n-dimensional is presented as a continuation of generating B-spline functions in n-dimensional to solve mathematical models in n-dimensional. The septic B-spline collocation algorithm is displayed in three forms: one dimensional, two dimensional, and three dimensional. In various domains, these constructs are essential for solving mathematical models. The effectiveness and correctness of the suggested method are demonstrated using a few two- and three-dimensional test problems. The proposed new structure provides better results than other methods because it deals with a larger number of points than the field. To create comparisons, we use different numerical approaches accessible in the literature.

Self-optimization examination system based on improved particle swarm optimization

Abstract: Abstract Artificial intelligence has been applied to many fields successfully and saved many human and material resources. The intelligent examination system is a typical application case, which makes teachers can not only master the study situation of every candidate at any time but also design further study plans with the help of the examination system. A self-optimization examination system is shown in this paper, which is carried out by an improved particle swarm optimization. The intelligent examination system can surmount two difficulties shown in the construction of the traditional examining system, one is the setting of the attributes of the examination questions, and another is the maintenance of the database of the examination questions. The experiment shows that the novel method can not only optimize the attributes of the questions in the examination database intelligently but also maintain the examination database effectively through massive training.

An iterative approach using Sawi transform for fractional telegraph equation in diversified dimensions

Abstract: Abstract In the present study, 1D, 2D, and 3D fractional hyperbolic telegraph equations in Caputo sense have been solved using an iterative method using Sawi transform. These equations serve as a model for signal analysis of electrical impulse transmission and propagation. Along with a table of Sawi transform of some popular functions, some helpful results on Sawi transform are provided. To demonstrate the effectiveness of the suggested method, five examples in 1D, one example in 2D, and one example in 3D are solved using the proposed scheme. Error analysis comparing approximate and exact solutions using graphs and tables has been provided. The proposed scheme is robust, effective, and easy to implement and can be implemented on variety of fractional partial differential equations to obtain precise series approximations.

Research on optimization of crane fault predictive control system based on data mining

Abstract: Abstract To ensure the safe functioning of lifting equipment, a data mining-based optimization study of a crane failure predictive control system is provided. To diagnose lifting machinery faults, the system employs decision tree categorization. Using association rules, a correlation study of hoisting machinery defect and failure was performed. When the minimal confidence and support degree are entered, a total of 244 instances of 18 frequent itemset A9 (safety protection device) may be obtained, indicating that lifting machinery does not perform well in this category. A6 (main parts) and A9 appeared a total of 98 times, with support and confidence of 29.4 and 35.6, respectively, indicating that the main parts can detect that the safety protection device is also having problems. A7 (electrical control system) and A9 appeared a total of 67 times, with support and confidence of 20.1 and 27.3, respectively, indicating that the electrical control system can detect that the safety protection device is also having problems; the correlation between them was also quite large. The system’s feasibility and efficacy shows that it has some application value.

Performance evaluation and optimization of fixture adapter for oil drilling top drives

Abstract: Abstract A top drive is an essential mechanical device in oil field drilling since it provides the necessary torque for the drilling operations. Manufacturers in the oil and gas industry typically perform in-housing testing and classify the Safe Working Load of top drives. Testing a top drive requires a unique test stand, thus making testing top drives from other manufacturers a difficult challenge. A fixture adapter can be designed using geometric constraints and intuition to make testing apparatus semi-universal, yet they are often bulky and heavy, posing more significant safety concerns. This study aims to first numerically assess the existing fixture adapter and then structurally optimize it for enhancing its structural integrity and efficiency under various severe working environments. Therefore, finite element analysis (FEA) was performed on the existing fixture adapter, and compliance minimization topology optimization was employed. Four load and boundary conditions were used from the three most frequent operation scenarios for the fixture adapters: (i) drilling standby, (ii) staging area, (iii) drilling make-up, and (iv) break-up. The FEA results indicated that no safety factor was compromised with a 50% and 60% mass retention constraint via topology optimization compared to the original fixture adapter. The optimized fixture adapter was also tested under compression using printed 3D prototypes to validate the finite analysis and topology optimization processes.

Optimization of information acquisition security of broadband carrier communication based on linear equation

Abstract: Abstract In order to study the optimization of information acquisition security of broadband carrier communication and solve the problem of low baud rate of data acquisition in traditional communication operation data acquisition systems, this article reconstructs the required arrangement of communication operation data signals in the acquisition path by taking broadband carrier communication in the station area as an example through the linear equation method of genetic algorithm. The baud rate of the designed acquisition system is significantly higher than that of the control group, and the acquisition accuracy is 100% by using phase shift key modulation and high carrier frequency. It can solve the problem of low baud rate of data acquisition in traditional communication operation data acquisition systems and improve the security of information acquisition. The security (loss, anti-interference) of broadband carrier communication information collection based on the improved legacy algorithm is better than that of the traditional genetic algorithm, indicating that the security of broadband carrier communication information collection based on the improved legacy algorithm does not increase with the number of iterations and decrease.

Research on indoor localization algorithm based on time unsynchronization

Abstract: Abstract Due to the influence of crystal vibration, clock offset, and clock skew, time synchronization error will be caused. This study introduces several algorithms to reduce or eliminate the influence of time synchronization error on positioning results, including iterative time-of-arrival algorithm, linear position line algorithm, classical CHAN algorithm, quadratic programming algorithm, and an improved algorithm for quadratic programming problem using weighted least squares algorithm. They are applied to two-dimensional (2D) single target, 2D multi-target, three-dimensional, and various positioning scenarios considering the influence of clock skew and clock offset for the simulation test, which overcomes the defect that the previous algorithm simulation test has few application scenarios. The results show that the iterative time-of-arrival algorithm has smaller root mean square error, higher positioning accuracy, and stable positioning results, and the algorithm has universal applicability to each positioning scene with time synchronization error.

A novel hybrid ensemble convolutional neural network for face recognition by optimizing hyperparameters

Abstract: Abstract A fully fledged face recognition system consists of face detection, face alignment, and face recognition. Facial recognition has been challenging due to various unconstrained factors such as pose variation, illumination, aging, partial occlusion, low resolution, etc. The traditional approaches to face recognition have some limitations in an unconstrained environment. Therefore, the task of face recognition is improved using various deep learning architectures. Though the contemporary deep learning techniques for face recognition systems improved overall efficiency, a resilient and efficacious system is still required. Therefore, we proposed a hybrid ensemble convolutional neural network (HE-CNN) framework using ensemble transfer learning from the modified pre-trained models for face recognition. The concept of progressive training is used for training the model that significantly enhanced the recognition accuracy. The proposed modifications in the classification layers and training process generated best-in-class results and improved the recognition accuracy. Further, the suggested model is evaluated using a self-created criminal dataset to demonstrate the use of facial recognition in real-time. The suggested HE-CNN model obtained an accuracy of 99.35, 91.58, and 95% on labeled faces in the wild (LFW), cross pose LFW, and self-created datasets, respectively.

Dynamics and attitude control of space-based synthetic aperture radar

Abstract: Abstract This work tackles the problem of attitude control of a space-based synthetic aperture radar with a deployable reflector antenna, representing a lightly damped uncertain vibratory system with highly nonlinear dynamics. A control strategy based on two identifiable in-orbit vector parameters is proposed to make the robust controller less conservative. The first parameter is used in the feedforward loop to achieve a trade-off between the energy efficiency of maneuvers and the amplitudes of the oscillatory response. The feedback loop utilizes the second parameter to accurately handle the controller-structure interactions by adaptive notch filters. The notch filters are included in the augmented plant at the design stage to guarantee closed-loop robustness against disturbances, unmodeled dynamics, and parametric uncertainty. The system’s robustness and specified requirements are confirmed by formal criteria and numerical simulations using a realistic model of the flexible spacecraft.

Bond performance between recycled concrete and steel bar after high temperature

Abstract: Abstract To investigate the influence of high temperatures on the bond performance of recycled concrete and steel bar, this article considers the influence of different concrete types (ordinary concrete and recycled concrete) and different temperatures (20, 100, 150, 200, 250, and 300°C) on the concrete compressive strength and the bond performance of concrete and steel bar. On this basis, the calculation formula of bond strength and bond slip between concrete and steel bar after the high temperature is established. The test results show that the concrete compressive strength presents a downward trend with the increase in temperature; the compressive strength loss of recycled concrete is higher than that of ordinary concrete; when the temperature reached 300°C, the compressive strength loss of ordinary concrete is 24.4%, while that of recycled concrete is 41.6%. The bond strength of pull-out specimens decreases with the increase of temperature, while the bond slip increases with the increase of temperature; the bond strength between recycled concrete and steel bar is lower than that between ordinary concrete and steel bar, while the bond slip between recycled concrete and steel bar is higher than that between ordinary concrete and steel bar. This article can provide a theoretical basis for the application of recycled concrete in high-temperature environment.

Overlapping grid SQLM for third-grade modified nanofluid flow deformed by porous stretchable/shrinkable Riga plate

Abstract: Abstract The improvement in thermal performance of fluid and the control of energy loss are equitably significant. Therefore, the purpose of this study is to analyze entropy generation, stagnation point flow, and thermal characteristics of non-Newtonian third-grade modified hybrid nanofluid generated by a stretchable/shrinkable Riga plate in a porous medium with varying flow viscosity. In this analysis, a modification of hybrid nanofluid is considered by using pure water as a base fluid and three various nanomaterials (aluminium oxide, copper, and nickel) as nanoparticles in the characterization of heat transfer. Furthermore, the contribution of heat source/sink and viscous dissipation are accounted for in the model. The suited transformations are enforced to remodel the governing mathematical equations to produce ordinary differential equations that are conveniently tackled via spectral quasilinearization method (SQLM) along with the overlapping grid idea to yield numerical solutions. The preference of this approach over others has been justified through discussion of error bound theorems, residual and solution errors, computational time, and conditioning of matrices. The physical significance of disparate governing parameters on flow variables, velocity gradient, thermal rate, and entropy generation are scrutinized through graphs and tables. Crucial findings of the study include that temperature of the modified hybrid nanofluid enhances quickly (better thermal conductor) than temperature of single nanofluid, hybrid nanofluid, and conventional third-grade fluid for higher Biot number, variable viscosity, and heat source parameters. Mass suction enhances fluid flow and physical quantities of interest, but suppresses the fluid temperature. An increase in variable fluid viscosity, modified Hartmann number, and third-grade parameters enhances the wall drag coefficient while lowering the rate of heat transfer, and the opposite is true for porous media. More entropy is generated in the system by high variable fluid viscosity, suction, viscous dissipation, modified Hartman number, and non-Newtonian parameters. Owing to high velocity and temperature associated with modified hybrid nanoparticles, modified hybrid technology is recommended in enhancing the physical attributes of the fluid with minimal cost effects. In engineering and industrial point of view, this study can contribute significantly in thermal improvement of the working fluid.

Deformable Laplace transform and its applications

Abstract: Abstract Recently, the deformable derivative and its properties have been introduced. In this work, we have investigated the concept of deformable Laplace transform (DLT) in more detail. Furthermore, some classical properties of the DLT are also included. The Heaviside expansion formula and convolution theorem for deformable inverse Laplace transform are also discussed. Furthermore, some illustrative numerical examples are also discussed to validate the applicability of the proposed DLT and finally conclude the theory.

Numerical analysis of vibration response of elastic tube bundle of heat exchanger based on fluid structure coupling analysis

Abstract: Abstract A tube bundle heat exchanger is a typical heat exchange equipment that exchanges heat between two fluids with different temperatures. Through this equipment, one fluid can be cooled down and another fluid can be heated up to meet their respective needs. The equipment is widely used in chemical, petroleum, pharmaceutical, energy, and other industrial sectors, and is one of the indispensable and important equipments in chemical production. To improve the heat transfer performance and service life of the heat exchanger, a numerical analysis of the vibration response of the elastic tube bundle in the heat exchanger based on fluid–structure coupling analysis is proposed. Using the weak coupling method of fluid–structure coupling, the vibration response of multiple rows of elastic tube bundles induced by shell side fluid in a heat exchanger with different tube row spacing and different tube row numbers is studied numerically, and the effects of shell side fluid and tube side fluid on the vibration response of elastic tube bundles are compared and analyzed. The results show that the maximum relative error of monitoring point amplitude is 43.36% when H = 40 mm and 10.17% when H = 70 mm. For connection IV, the maximum relative error of monitoring point amplitude is 31.71% when H = 40 mm and 24.08% when H = 70 mm. This is because when H is small, the interaction between rows of tube bundles is strong, so the amplitude changes violently with the number of the tube bundle. The step-by-step calculation strategy of rough calculation and actuarial calculation proposed in this article can greatly reduce the calculation time and improve the calculation efficiency.

Simulations of fractional time-derivative against proportional time-delay for solving and investigating the generalized perturbed-KdV equation

Abstract: Abstract In this study, the Caputo-type fractional time-derivative is simulated by inserting a proportional time-delay into the field function of the perturbed-KdV equation. Two effective methods have been adapted to obtain analytical solutions for this model. Then, independently, the effect of the fractional derivative and the proportional delay on the topological shape of the pKdV propagation was extrapolated. The significant conclusions of the current article reveal that the fractional derivative plays the same role as the presence of a proportional delay in the time coordinate if it is assigned as a substitute for it. With this, from a practical mathematical point of view, we have provided one of the geometric explanations of the fractional derivative. Finally, via the obtained approximate solution, we studied the impact of the perturbed coefficient on propagating the waves of the proposed KdV model.

Exhaustive study on post effect processing of 3D image based on nonlinear digital watermarking algorithm

Abstract: Abstract In this work, an exhaustive study on post effect processing of three-dimensional (3D) image is carried to solve the problem of nonlinear digital watermarking algorithm. First, through the feature space decomposition method of the host image, the embedded watermark is constructed with the full row or column rank of the matrix, and then the public key is constructed by using the existence of the unitary matrix of the full row rank and column rank matrix, so that the algorithm can embed and extract the watermark in an asymmetric way. Watermark extraction correlation coefficient (ρ) value is 1. When the deformation amplitude of the model is slight and the noise intensity is σ = 0.0001, the watermark can be extracted successfully, and the watermark extraction correlation coefficient (ρ) is 0.92. In addition, the security of the algorithm is analyzed from many angles, the theoretical analysis is given, and verified by the experimental results. The proposed 3D watermarking methods are used to examine the information capacity of various 3D meshes. The 3D watermarking methods’ resistance to noise perturbation and object cropping is also investigated.

Numerical simulation of Burgers’ equations via quartic HB-spline DQM

Abstract: Abstract Via modified quartic hyperbolic B-spline DQM, Burgers’ equation is numerically approximated in the current study. Ten numerical instances are discussed, and the findings are compared with those already in existence and with exact results. Error norms are assessed, and findings are shown in tabular as well as graphical formats, to validate the resilience and applicability portion of established numerical system. Matrix stability analysis approach is used to discuss proposed scheme’s stability. The current plan is robust, precise, and simple to put into action.

Multiwireless sensors for electrical measurement based on nonlinear improved data fusion algorithm

Abstract: Abstract In order to improve the accuracy of collected data and avoid table lookup, the adaptive weighted fusion algorithm is improved. According to the characteristics of the median and the mean value in the normal distribution, a new method of preprocessing to remove outliers is proposed to improve the accuracy of the final fusion result. The algorithm is used to calculate the temperature data to be processed in a greenhouse. The results showed that the fusion result after average processing was X ˆ \hat{X} = 15.77°C. The standard deviation is σ \sigma = 0.1194°C. After the treatment of the Grabbs criterion, the fusion result is X ˆ \hat{X} = 15.73°C and the standard deviation is σ \sigma = 0.1110°C. The fusion result of the improved algorithm is X ˆ \hat{X} = 15.74°C. The standard deviation is σ \sigma = 0.0959°C. Advantages of various preprocessing algorithms: improved algorithm > Grubbs method > no preprocessing. From the processing results of group A1 data, it can be seen that the improved algorithm can effectively suppress the ipsilateral shielding effect. Compared with the traditional Grubbs method to eliminate outliers and other algorithms, the improved algorithm can make the standard deviation of the fusion result smaller, and the fusion result can better represent the overall distribution, and there is no need to look up the table.

The regularization of spectral methods for hyperbolic Volterra integrodifferential equations with fractional power elliptic operator

Abstract: Abstract In this study, a numerical approach is presented to solve the linear and nonlinear hyperbolic Volterra integrodifferential equations (HVIDEs). The regularization of a Legendre-collocation spectral method is applied for solving HVIDE of the second kind, with the time and space variables on the basis of Legendre-Gauss-Lobatto and Legendre-Gauss (LG) interpolation points, respectively. Concerning bounded domains, the provided HVIDE relation is transformed into three corresponding relations. Hence, a Legendre-collocation spectral approach is applied for solving this equation, and finally, ill-posed linear and nonlinear systems of algebraic equations are obtained; therefore different regularization methods are used to solve them. For an unbounded domain, a suitable mapping to convert the problem on a bounded domain is used and then apply the same proposed method for the bounded domain. For the two cases, the numerical results confirm the exponential convergence rate. The findings of this study are unprecedented for the regularization of the spectral method for the hyperbolic integrodifferential equation. The result in this work seems to be the first successful for the regularization of spectral method for the hyperbolic integrodifferential equation.

Influence of joint flexibility on buckling analysis of free–free beams

Abstract: Abstract In this work, an application of two noded beam finite element methodology, which is demonstrated in the previous research work for vibration analysis of beam with a flexible joint problem, has been further extended here to investigate the buckling behaviour of free–free beam subjected to an in-plane compressive load. Joint is modelled as rotational spring, where the rotational spring stiffness governs the behaviour of the flexible joint. Variation of first five non-dimensional buckling loads of free–free beam with reference to the joint location as well as joint stiffness parameters are briefly presented. It is understood that looseness of the joint can significantly influence the buckling behaviour of free–free beam and plays an important role in accurately determining the buckling behaviour of jointed beams subjected to an in-plane compressive loads.

Safety decision analysis of collapse accident based on “accident tree–analytic hierarchy process”

Abstract: Abstract To reduce the hazards of collapse accidents in the construction process and to ensure that the lives, health, and property of construction workers are protected, this study used the theory of safety system engineering to identify the hazards of collapse accidents, analyze the hazards, predict the consequences, evaluate the systemic risks, and evaluate the effects and improve them. At the same time, the risk factors of collapse were evaluated qualitatively and quantitatively by using the analysis methods of fault tree analysis (FTA) and the analytic hierarchy process (AHP). Finally, according to the evaluation results, the main factors causing collapse accidents were found; this provided a reliable and practical basis for the prevention of collapse accidents. Then, according to the decisive factors, corresponding measures were taken in advance to achieve the aim of preventing and controlling collapse accidents. The results show that equipment maintenance, material inspection, and construction site safety management play an important role in preventing collapse accidents.