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Graphene possesses not only excellent optical, electrical and thermal properties but also outstanding thermoelectric and photothermal conversion capabilities. The application of graphene with functional responses plays a vital role in the development of intelligent materials intended for flexible actuators and intelligent robots. Cellulose paper is foldable and is a hydrophilic network comprised of porous cellulose fibres. In this paper, graphene composites as well as cellulose paper were taken as basic materials, which were further combined with other polymer materials (biaxially oriented polypropylene film (BOPP) and poly (3, 4-ethylenedioxythiophene/polystyrene sulfonate) (PEDOT: PSS). PEDOT: PSS solution can penetrate into the porous network of the paper to form a high-strength nanocomposite structure. A flexible thin film driver capable of multiple stimuli under light, heat and humidity was produced. Through characterization, it was found that the bending ability of the composite film was significantly improved in response to stimulation. [ABSTRACT FROM AUTHOR]

It is assumed that a sheet of paper performs transverse vibrations as a plate having additional stiffness due to static tension in its plane. The first eigenmodes are determined. The setup for experimental investigation of the nodal lines of the standing waves and for the determination of eigenmodes using projection moire is created for the analysis of unsymmetric loading of the paper. The comparison of the theoretical and experimental results of investigations is performed. The obtained results could be used in the process of design of the elements of the printing device. [ABSTRACT FROM AUTHOR]

Fuel cell air filter can absorb harmful impurities and gases to fuel cell and is an important component to ensure the service life of fuel cell. The previous researches mainly focus on the activated carbon and filter paper materials in the laboratory. The object of this paper is the fuel cell air filter product assembly being used by the main engine plant. According to the tests of air filters with different carbon contents, it was found that the adsorption efficiency of current products for NO2 was better than that of C7H8, SO2 and C4H10. Based on the adsorption mechanism of activated carbon for different gases, the adsorption difference was explained. The testes also found that there was no direct relationship between the change of carbon content of products containing activated carbon and the fractional filtration efficiency. The main reason is that the gap between the activated carbon particles is large, which cannot effectively intercept dust particles. The filtering of small size particles still depends on the melt-blown layer material in the air filter element and its electrostatic electret process. It was also found that there was a positive correlation between inlet air resistance and carbon content, and a negative correlation between dust holding capacity and carbon content. This test results can help the main engine factory understand the performance and improvement direction of products. [ABSTRACT FROM AUTHOR]

Damage detection and localization in civil engineering constructions using dynamic analysis has become an important topic in recent years. This paper presents a methodology based on non-destructive detection, localization and quantification of multiple damages in simple and continuous beams, and a more complex structure, namely two-dimensional frame structure. The proposed methodology makes used of Firefly Algorithm and Genetic Algorithm as optimization tools and the Coordinate Modal Assurance Criterion as an objective function. The results show that the proposed combination of Coordinate Modal Assurance Criterion and Firefly Algorithm or Genetic Algorithm can be easily used to identify multiple local structural damages in complex structures. However, the convergence rate becomes slower for the case of multiple damages compared to the case of single damage. The effect of noise on the algorithm is further investigated. It is found that the proposed technique is able to detect the damage location and its severity with high accuracy in the presence of noise, although the convergence rate became slower than in the case when no noise is present. It is also found that the convergence rate of Firefly Algorithm is much faster than that of Genetic Algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a new damage detection and localization technique based on the changes in vibration parameters using BAT and Particle Swarm Optimization algorithm. The finite element method is used to apply damage at specific element(s) of the considered beams. The damage is represented by a reduction in Young's modulus and the identification of damage is formulated as an optimization problem using objective function based on Modal Scale Factor and changes in natural frequencies. A procedure for detecting and locating damage of beam-like structures based on BAT algorithm is used. This approach presents a method that can be used to detect the single and multiple-damage positions and the rate of damage in structural elements with high accuracy after the first iteration. The results obtained using BAT algorithm are compared to those obtained using Particle Swarm Optimization Algorithm. By taking noise into account in the damage detection and localization problem, it is shown that our approach based on BAT algorithm can detect the damage locations with high accuracy. [ABSTRACT FROM AUTHOR]

Accurate and efficient damage detection in long-term health monitoring for structures still encounters many difficulties due to the effect of environment. Furthermore, recorded big data requires efficient damage detection algorithm. In this study, an efficient and effective damage detection algorithm is proposed using transmissibility along with Mahalanobis distance and Hotelling T-square. A numerically simulated beam and an experimentally tested laboratory structure are used to validate the proposed algorithm. Results demonstrate good performance of the proposed technique in damage detection. [ABSTRACT FROM AUTHOR]

The model for the analysis of vibrations of paper in a printing device is presented. It is assumed that paper performs transverse vibrations as a membrane having stiffness due to static tension in its plane. The first eigenmodes are determined. It is shown that the eigenfrequencies of transverse vibrations of the analyzed paper can be controlled by the static tension in the plane of the paper. The model for the analysis of stability of paper in a printing device is presented. It is assumed that paper moves with constant velocity in a given direction. The analysis is performed using a plate-bending element with the contribution of the forces of inertia from the convective accelerations. This results in the eigenproblem determining the critical velocities and stability eigenmodes. The stand was made for obtaining the experimental investigations. Using it the nodal lines of the standing waves were determined and using projection moiré the eigenmodes were determined. The obtained results are used in the process of design of the elements of the printing device. [ABSTRACT FROM AUTHOR]

The circular cutout is considered as a typical source of stress concentrations in rectangular plate type structures. The proper position of a cutout in a rectangular plate can be significantly affected by the choice of material, cutout size, and various end conditions which are relative to the externally applied force. The research work entitled in this paper deals with the finite element formulation applied to a plate made with isotropic and laminated plates subjected to uniform pressure with various end conditions. The vicinity of stress distribution for the rectangular plate made of these two materials with and without the effect of circular cutouts is discussed. The accuracy of the solution verified with the available literature, and from the comparison, a fairly good agreement seen between the Finite element formulations in this paper with previously available results. [ABSTRACT FROM AUTHOR]

A one-dimensional model for the analysis of compression of a paper in the printing machine is presented. It is assumed that a paper experiences static compression and the problem of initial stability is solved. A two-dimensional model for the analysis of compression of a paper is described and used for the solution of a similar problem. Also an axi-symmetric model for the analysis of compression of a paper is described and used for the solution of a similar problem. A setup for performing experimental investigations of uniaxial unidirectional symmetrically distributed compression of polymeric film is designed and created. For this purpose the method of digital speckle photography is used. During the investigations the images of the stability eigenmodes of the polymeric film HDPE for uniaxial unidirectional compression of the film were determined. The obtained results are used in the design of the elements of the printing machine. [ABSTRACT FROM AUTHOR]

There are cases of endurable books production. Paper proposes an improved mathematical model for calculating the stresses in the adhesive spine layer during the opening of the book. [ABSTRACT FROM AUTHOR]

The need for an effective and efficient maintenance process increases with the level of complexity of modern rotating machinery. This paper introduces a methodology for transforming raw vibration signals into adequate inputs for machine learning classification algorithms in order to identify present faults in rotating machinery. It complements a previous study by the same authors, which covers the processing of vibrational signals by determining the optimal sampling frequency and using appropriate filters for the raw data. The first part of this study covers feature extraction using time and frequency-domain techniques and correlation matrices are plotted to determine which extracted features are significantly connected and what is the level of their correlation. The study continues with the use of Neighborhood Component Analysis (NCA) where weight factors of the features are calculated in terms of recognizing the present rotating machinery faults. Only the ones with the highest level of importance have been used as input for the classification algorithms. The MATLAB Add-in Classification Learner has been used for training and testing various classification algorithms. K-nearest neighbors classifier (KNN), Support vector machines (SVM), and Wide Neural Network (NN) showed the highest accuracy in distinguishing ten different fault conditions. For this case study, the MaFaulda vibration dataset has been used and ten operating conditions have been considered: normal, imbalance, horizontal misalignment, vertical misalignment, and three faults in the underhang bearing and the overhang bearing. [ABSTRACT FROM AUTHOR]

Over the past few years, there has been a growing interest in this field of Artificial Intelligence (AI). This review paper aims to examine the extent to which AI has been adopted across various domains in different regions of the world. Specifically, this study seeks to explore the effectiveness of AI in areas such as banking, governance, judiciary, and agriculture. While AI's impact on these areas has been studied before, this research focuses on aspects that have not been given much needed attention so far. The study will begin by offering an overview of AI's development from a regional perspective, analyzing 63 articles from leading journals and institutions to identify the most commonly used terminologies, theories, and technologies. The increasing computational power has played a crucial role in the advancement of AI. However, the role of AI in governance, judiciary, and legislature system has not been explored in depth in previous research. Furthermore, most studies tend to focus on single domain, whereas this paper aims to examine several domains and their relationship to AI. The study presents several AI-driven techniques, including Deep Neural Net (DNN), Artificial Neural Net (ANN), Candlestick Plots, Natural Language Processing (NLP), Explainable Deep Neural Net (xDNN), Attentional Maps, Digital Inventory, Deep Learning among others, that can be applied to enhance society's performance in different domains. The research also delves deeper into the judiciary domain, proposing specific AI techniques that could be useful in this field. Additionally, tables summarizing different AI tactics relevant to each domain are presented. [ABSTRACT FROM AUTHOR]

The motors are critical components of the electromechanical transmission in vehicles, and its operating status directly affects the maneuverability of vehicles. To quickly and accurately identify the operating status of motors, this paper proposes a new entropy - Composite Multi-scale Weighted Reverse Slope Entropy (CMWRSlE) for motor fault diagnosis, which is a more interpretable entropy due to its deep exploration of signals. Firstly, the composite multi-scale weighted reverse slope entropy values are extracted from the vibration signals of the motor in different states; Secondly, the extracted features are dimensionally reduced by the manifold learning algorithm - Neighbourhood Preserving Embedding (NPE) and classified by the hierarchical prototype-based approach (HPA) to achieve the fault diagnosis of the motor. Finally, the method proposed in this paper is validated through two sets of experimental data: motor rotor faults and motor bearing faults. The results show that the accuracy of the proposed method in motor fault diagnosis reaches 100 %, which indicates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Fault mechanism analysis is one of the methods in fault diagnosis, and the dynamic modeling of rolling bearing faults plays a crucial role in studying fault mechanisms. Existing dynamic fault models only consider the impact of fault size and bearing speed on the impact force, providing an incomplete description of the impact force. In order to more accurately describe the dynamic fault model of impact forces, this paper focuses on the deep groove ball bearing with outer race faults. Factors such as defect deformation, speed, and fault size are considered, and an instantaneous impact force excitation function is proposed. Based on this proposed excitation function, a dynamic model for the outer race fault of deep groove ball bearings is established. Finally, through simulation and experimental comparison, the results indicate that the fault characteristic frequencies and their harmonics of the model in this paper are closer to the actual fault characteristic frequencies, reducing the error by 1 to 2 Hz. Therefore, the model proposed in this paper is more effective and accurate, providing a more precise rolling bearing fault model for the study of fault mechanisms. [ABSTRACT FROM AUTHOR]

This paper attempts to utilize lower order harmonics and modes of vibration consisting of "square ratios of frequency variations" as structural damage susceptibility characteristics. This is followed by the development of the frequency-based method. Firstly, this paper derives the theoretical formulation of the square ratio of frequency variation method. Secondly, a finite element model of a single column platform is established. Then the damage is simulated using the reduced modulus of elasticity to localize the damage. The result is shown to be feasible. Thirdly, a model of the offshore single column platform is constructed, and the damage is simulated using cracks on the column. The "frequency variation square ratio" is valid, so the method can be used in reality. This method is applied to the single column platform model, suitable for a beam structure. It is very effective for the single column damage identification at different damage levels, and can also initially locate the damage. This method has high practical application value and reference value for future studies. [ABSTRACT FROM AUTHOR]

The paper focuses on two kinds of rotating machinery, miniature table drilling machine and automobile engine, as the research object. Traditional machine learning has the need for manual feature extraction, and is very dependent on expert diagnostic experience and expertise, but also has the disadvantages of low accuracy, low timeliness, low efficiency, etc. For the traditional rotating machinery fault diagnosis method is more based on the traditional machine learning model, this paper puts forward a one-dimensional convolutional neural network-based fault identification method. According to the characteristics of the miniature table drilling machine and the automobile engine which are not detachable, the corresponding faults are set up respectively, Vibration signals of the attitude sensor are obtained by using the signal collector, and the collected data are preprocessed, then the CNN model is built for fault identification, and the network structure is constantly optimized to obtain the optimal network model with high accuracy (up to 100 %) and robustness. The results show that the one-dimensional convolutional neural network model improves the fault recognition accuracy and reduces the cost compared with the traditional machine learning SVM model when the original signal is used as the input signal. [ABSTRACT FROM AUTHOR]

Aiming to address the low efficiency of current deep learning algorithms for segmenting citrus in complex environments, this paper proposes a study on citrus segmentation algorithms based on a multi-scale attention mechanism. The DeepLab V3+ network model was utilized as the primary framework and enhanced to suit the characteristics of the citrus dataset. In this paper, we will introduce a more sophisticated multi-scale attention mechanism to enhance the neural network's capacity to perceive information at different scales, thus improving the model's performance in handling complex scenes and multi-scale objects. The DeepLab V3+ network addresses the challenges of low segmentation accuracy and inadequate refinement of segmentation edges when segmenting citrus in complex scenes, and the experimental results demonstrate that the improved algorithm in this paper achieves 96.8 % in the performance index of MioU and 98.4 % in the performance index of MPA, which improves the segmentation effectiveness to a significant degree. [ABSTRACT FROM AUTHOR]

This paper gives a review on the bio-inspired optimization methodology known as mayfly (MA) algorithm in order to resolve issues in optimization techniques. It is a newly formed meta-heuristic optimization algorithm that focuses on the movements of masculine and feminine mayflies. It is encouraged from flying behaviour also the methods of mating in mayflies. With the help of a realistic-world separate flow planning issue along with the coupling behaviour in numerous objective optimizations, the performance of the mayfly algorithm (MA) is well evaluated. Some of the implementations of this algorithm are discussed in this paper: Bearing fault diagnosis based on the mayfly algorithm, optimizing the performance of PEMFC, Covid diagnosis, wind speed optimization, improving the scheduling of solar wind speed using mayfly optimization, detecting fault in the wind turbine gearboxes, patterning in the array antennas with the help of optimization and so on. One of the main advantages of the MA is that it combines the other optimization algorithms namely swarm optimization (PSO) with the evolutionary optimizations (GA). The motion of the mayflies that resemble nuptial dance model along with the arbitrary flight helps in the improvement of the stability within the exploration and exploitation methods. In addition, allows escape from the community peak. All the above work reviewed shows promising results from the algorithm. More work can be carried out using this algorithm in future. [ABSTRACT FROM AUTHOR]

The design principles of strength test support methods for aircraft structural components were introduced in this paper. Aiming at the vertical tail static test of a certain type of aircraft, a supporting stiffness simulation method was invented, and a support fixture was designed. The supporting stiffness was accurately simulated by stiffness strength. The research results of this paper provide an important reference for the research of static test support methods for similar aircraft structural components. [ABSTRACT FROM AUTHOR]

The energy conversion efficiency of wave energy device is one of the key problems in the large-scale utilization of wave energy. The study of the maximum output POWER of PTO (Power-Take-Off) system provides a theoretical reference for the efficient utilization of energy. In this paper, genetic algorithm and adaptive differential evolution algorithm based on neighborhood search are used to optimize the two-objective multi-order differential equations for the maximum output power of PTO system, and the global optimal solution is obtained. Compared with the traversal algorithm, the algorithm involved in this paper is efficient and the optimal output power obtained can provide a scientific basis for the structural optimization design and material selection of the wave energy device. [ABSTRACT FROM AUTHOR]

Traditional flatness detection method with 2-m ruler and feeler gauge can only manually measure to obtain data at sparse locations. Terrestrial Laser Scanning (TLS) has been widely used in the detection task of small-scale components. To overcome the time-consuming and laborious problem of traditional method and extend the application of TLS-based method, an efficient, full-coverage and intelligent TLS-based flatness detection method applicable to large-scale floors is presented in this paper to help with the acceptance of emery floor. An algorithm is designed to find the optimal position of ruler above the ground profile and measure the deviation between ruler and ground. The results of two comparison experiments demonstrates that the TLS-based method proposed in this paper has a high detection accuracy. In the detection task of a super-flat emery floor, floor plan labeled with pass rates can be easily obtained. Color maps marked with unqualified areas can be used as a guide for concrete polishing. By comparing row detection and column detection results, the pass rate is significantly directional in some conditions. [ABSTRACT FROM AUTHOR]

Aiming to reduce the impact of substation noise on the lives of surrounding residents, improving the low and middle frequencies acoustic performance of traditional resistive mufflers in indoor substations is significant. The paper is based on the resonance sound absorption mechanism, and for the first time applies multi-frequency resonance noise reduction technology to the research field of indoor substation noise control, proposing a multi-frequency resonant muffling structure. The acoustic performance of the proposed muffler unit is investigated through theoretical and numerical analysis. The measured noise data of the indoor substation is used as sound excitation in the numerical analysis. The results show that at frequencies of 100 Hz, 200 Hz, 300 Hz, 400 Hz, and 500 Hz, the noise in indoor substations is significantly reduced by the multi-frequency resonant muffling structure. The paper provides references for the application of multi-frequency resonant mufflers in the field of noise control of indoor substations. [ABSTRACT FROM AUTHOR]

The planetary-type vibration exciters are relatively novel and prospective types of actuators for various vibratory technological equipment. Numerous research papers substantiated the possibilities of implementing such exciters for generating circular, elliptical, and rectilinear oscillations of the working members of different technological machines. The present research continues the authors’ previous investigations dedicated to kinematics and dynamics of planetarytype vibration exciters and is focused on the analysis of forces, moments, and torques acting upon the elements of the corresponding actuating mechanisms. The research methodology contains the development of the simplified dynamic diagrams of two different designs of planetary-type mechanisms, derivation of the analytical expressions describing force parameters of the considered mechanical systems, performing the mathematical modeling and computer simulation of the mechanism motion in order to analyze the corresponding forces, moments, and torques. The obtained results present the time dependencies of the mentioned force parameters under different operational conditions and design parameters of the planetary-type mechanism. The major scientific novelty of the paper consists in defining the minimal required torque of the motor needed to be applied for driving the mechanism at different conditions. The research outcomes can be effectively used by engineers while developing new and improving existent vibratory technological machines equipped with the considered planetary-type vibration exciter. [ABSTRACT FROM AUTHOR]

The dynamic failure and ultimate capacity analysis of rectangular girder under bending moment has not been fully studied. In this paper, a rectangular girder scaled from actual ship deck structure is selected as the study objective to analyze the dynamic failure and ultimate flexure capacity. The dynamic response under hammer drop impact is studied, and then two criteria of dynamic ultimate flexure capacity of the girder are proposed based on the bending moment in section and permanent deformation. The novelty of this paper is the proposed evaluation criterion of dynamic ultimate capacity. [ABSTRACT FROM AUTHOR]

The paper presents the results of computational analysis of the stress-strain state of reinforced concrete spans of the railway (single-track railway line) overpass over the highway, under specified loads using spatial finite element models. The static load consists of a cohesion of three TEM-18 diesel locomotives and two loaded gondola cars (up to 25 tons per axle). The purpose of this study was to ensure reliable and safe operation of artificial structures on the railroads, as there is a constant increase in transit freight trains from China through the territory of Kazakhstan to near and far abroad, and often the load on the axle reaches 25 tons, and sometimes larger values – up to 27 tons per axle. The results of the study are recommended to be used for inspections and tests of typical girder bridge spans, as well as in the case of monitoring their technical condition with increasing operational loads. [ABSTRACT FROM AUTHOR]

Atmospheric air pollution with fine particles PM2.5 and PM10 is one of the main environmental problems of the city. This paper presents the results of the study of quantitative and structural components of solid particles’ emissions in the city of Almaty, released during the operation of cars: by an engine with exhaust gases, by tire abrasion, by braking devices (linings) and road pavement wear. РM solid particles in the amount of 543.2 tons are released annually into the atmospheric air of Almaty by motor transport. The bulk PM10 is released totally from the tires, brakes and road – 65.4 %, from the engine – 34.6 %. On diesel buses and trucks, the bulk РM particles’ emissions are released from the exhaust gas engines. Recommendations are given to reduce PM particles emitted by motor transport. [ABSTRACT FROM AUTHOR]

Mobile robotic systems are currently of significant interest due to the wide range of possible applications. Among a great variety of mobile robots, specific attention is paid to the wheeled ones. The main purpose of this research consists in substantiating the possibilities of improving the vibration-driven robot equipped with the unidirectionally rotating wheels. The methodology of the present study contains the development of the robot's 3D-model in the SolidWorks software, constructing the simplified dynamic diagram of the robot's oscillatory system, and developing its simulation model in the MapleSim software. The research results are obtained by numerical solving of the motion equations in the MapleSim software, by simulating the robot locomotion conditions in the SolidWorks software, and by conducting experiments. The results present the main kinematic characteristics of the robot motion under different operational conditions. The major scientific novelty of this paper consists in developing the improved design of the wheeled robot driven by the centrifugal (inertial) vibration exciter and substantiating its operational peculiarities. The obtained results can be effectively used while creating the production prototypes of mobile robotic systems, particularly those for cleaning the pipelines and monitoring (inspecting) their inner surfaces, welds, joints, couplings, etc. [ABSTRACT FROM AUTHOR]

The aim of the experiment described in the paper was to determine the possibility of using an optical 3D scanner to measure the macro-geometry of cutting tools. To verify this possibility, a precise component was measured, and the accuracy of optical 3D scanner was compared to a tactile coordinate measurement machine. A precise cemented carbide rod was used as a reference part and the measurement data were compared with the measurement result from the ZEISS Prismo coordinate measurement machine. The data obtained from the measurements were evaluated and compared. The experiment was carried out so that the use of an optical 3D scanner to measure cutting tools could be verified based on the desired requirements. Both dimensions and geometrical tolerancing - circularity were measured. The experiment has shown that an optical 3D scanner can achieve sufficient accuracy for the purpose of measuring macro-geometry of cutting tools. [ABSTRACT FROM AUTHOR]

The increasing demand for polymers in additive manufacturing (AM) has led to a significant increase in plastic waste, with over 300 million metric tons used in recent years. This research article explores the use of Poly Lactic Acid (PLA) as a biodegradable thermoplastic recycled material for 3D printed components, comparing its properties with virgin PLA and discussing solutions for variation and mechanical features improvement. Fused Deposition Modeling (FDM) is a widely used additive manufacturing process that allows for the creation of three-dimensional objects by depositing molten material layer by layer. This study investigates the impact of infill density, layer thickness, and raster angle for recycled 3D printing material, focusing on their dimensions and their influence on processing efficiency. This research paper aims to investigate the mechanical effects of recycled 3d printed components which are printed by using FDM with the combination of different process parameters compared with virgin PLA. From results optimal process parameters are found to enhancing quality and performance of recycled 3D printed components. Later results are compared by Analysis of Variance (ANOVA) as a statistical tool and also with ANN technique, which minimizes error deviation. [ABSTRACT FROM AUTHOR]

The paper proposes a feedback force and velocity control of an arm exoskeleton to assist user motion. The original published control so-called feedback hybrid force and position control was based on the force and position control and was designed to assist user motion. This original control was successful at providing assist for the user's arm. This article presents an improved control scheme called the feedback force and velocity control. The proposed control is designed to regulate the velocities of joints of the exoskeleton and the feedback forces on links to assist user motion. The design and optimization of the feedback force and velocity control are realized by the Balancing Composite Motion Optimization (BCMO). The numerical method is realized in the paper to show that the proposed control is better than the original control in terms of less oscillation and fast response. [ABSTRACT FROM AUTHOR]

Mechanical progressions in different spaces have widened the application skyline of advanced mechanics to an unbelievable degree. Packaging and processing are some of the important aspects involved in the food industry. As the global population continues to rise with increasing consumer demand for a wider variety of food products, food manufacturing is exploring various strategies, techniques, and methods to meet the demand and adapt to the change. Industrial robots are being integrated into every part of the food manufacturing sector to increase production rates and improve food quality and hygiene. The introduction of more stringent legislation is forcing the food sector to update its production process. On the vigorous review of 50 papers, this paper provides a comprehensive review of robotics in food processing and investigates its analysis in terms of the level of automation applied in various food processing industries. The expectation of food-Robo in the food sectors and robotics with an optimized protocol to fetch various ingredients and shape them into a final product. [ABSTRACT FROM AUTHOR]

This paper mainly studies a reverse engineering of material parameters through finite element optimization algorithm based on free modal test results, focusing on free modal test and establishment of finite element optimization model. The elastic modulus and density of the material can be solved by the finite element optimization algorithm to ensure the accuracy of the simulation results. When the accurate material parameters are obtained, the accuracy of abnormal sound simulation can be improved. It plays a guiding role in the development of vehicle BSR performance, so as to improve the ride comfort of the vehicle. [ABSTRACT FROM AUTHOR]

At present, in the medical field, drug screening is usually performed using in vivo drug experiments. However, it is very time-consuming and laborious to conduct in vivo experiments on a large number of drugs to be screened one by one. This paper attempts to propose using machine learning algorithms to perform preliminary screening of a large number of compounds to be screened and their molecular structures to reduce the workload of in vivo experiments. Among them, it is internationally recognized that there is an important association between breast cancer progression and the alpha subtype of the estrogen receptor. Anti-breast cancer drug candidates with excellent efficacy need to contain compounds that can better antagonize ERa activity. In this paper, the research object is narrowed down from compounds to the molecular structure of the compounds, and then the random forest regression algorithm is used to develop the molecular structure-ERa activity prediction model. Molecular structures with significant effects on biological activity were screened from molecular structure descriptors in numerous compounds. Four different kernel functions were used to conduct comparative experiments, and finally a support vector regression algorithm based on radial basis kernel function was established, which realized the quantitative prediction of compounds on biological activity of ERa, and could find potential compounds beneficial to breast cancer treatment. This is a novel, computer-based method for preliminary drug screening, which can help medical researchers effectively narrow the scope of experiments and achieve more accurate optimization of drugs. [ABSTRACT FROM AUTHOR]