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Yield Stress Prediction Model of RAFM Steel Based on the Improved GDM-SA-SVR Algorithm
Get PDFWith the development of society and the exhaustion of fossil energy, researcher need to identify new alternative energy sources. Nuclear energy is a very good choice, but the key to the successful application of nuclear technology is determined primarily by the behavior of nuclear materials in reactors. Therefore, we studied the radiation performance of the fusion material reduced activation ferritic/martensitic (RAFM) steel. The main novelty of this paper are the statistical analysis of RAFM steel data sets through related statistical analysis and the formula derivation of the gradient descent method (GDM) which combines the gradient descent search strategy of the Convex Optimization Theory to get the best value. Use GDM algorithm to upgrade the annealing stabilization process of simulated annealing algorithm. The yield stress performance of RAFM steel is successfully predicted by the hybrid model which is combined by simulated annealing (SA) with support vector machine (SVM) as the first time. The effect on yield stress by the main physical quantities such as irradiation temperature, irradiation dose and test temperature is also analyzed. The related prediction process is: first, we used the improved annealing algorithm to optimize the SVR model after training the SVR model on a training data set. Next, we established the yield stress prediction model of RAFM steel. The model can predict up to 96% of the data points with the prediction in the test set and the original data point in the 2σ range. The statistical test analysis shows that under the condition of confidence level α=0.01, the calculation results of the regression effect significance analysis pass the T-test
Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine
Get PDFAn explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods
Non-Contact Real-Time Heart Rate Measurement Algorithm Based on PPG-Standard Deviation
Get PDFHeart rate is an important physiological parameter for clinical diagnosis, it can infer the health of the human body. Thus, efficient and accurate heart rate measurement is important for disease diagnosis and health monitoring. There are two ways to measure heart rate. One is contact type and the other is non-contact. Contact measurement methods include pulse cutting, electrocardiogram, etc. Because of the inconvenience of this method, a non-contact heart rate method has been proposed. Traditional non-contact measurement method based on image is collecting RGB three-channel signals in continuous video and selecting the average value of the green channel pixels as the heart rate signal for processing. However, this method is not accurate when the pixel values are changing greatly. To overcome this problem, non-contact real-time heart rate measurement method is proposed in this paper based on pixel standard deviation. Because of the changes in skin color caused by heart rate, the standard deviation signal of the green channel pixels in the region of interest (ROI) is filtered and extracted by the forward and inverse Fourier transform respectively, measuring the heart rate. The experimental results show that the improved algorithm can measure heart rate with faster speed and higher accuracy comparing to traditional methods. And we hope that our algorithm can apply in intelligent elder caring
Analyzing Dynamic Change in Social Network Based on Distribution-Free Multivariate Process Control Method
Get PDFSocial organizations can be represented by social network because it can mathematically quantify and represent complex interrelated organizational behavior. Exploring the change in dynamic social network is essential for the situation awareness of the corresponding social organization. Social network usually evolves gradually and slightly, which is hard to be noticed. The statistical process control techniques in industry field have been used to distinguish the statistically significant change of social network. But the original method is narrowed due to some limitation on measures. This paper presents a generic framework to address the change detection problem in dynamic social network and introduces a distribution-free multivariate control charts to supervise the changing of social network. Three groups of network parameters are integrated together in order to achieve a comprehensive view of the dynamic tendency. The proposed approaches handle the non-Gaussian data based on categorizing and ranking. Experiments indicate that nonparametric multivariate procedure is promising to be applied to social network analysis
An Efficient Crossing-Line Crowd Counting Algorithm with Two-Stage Detection
Get PDFCrowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting a line sampling process, a temporal slice image can be obtained for pedestrian counting without the need for visual tracking. Only ten low level features are extracted from the input image to establish a feature vector. As a result, our algorithm is more efficient and accurate than existing methods. Pedestrians in the temporal slice image are then located by the two-stage detection algorithm, which is largely based on support vector machine and affinity propagation clustering. Moreover, a novel algorithm is proposed to determine the moving directions of pedestrians by comparing the centers of them in two temporal slice images. Extensive experiments reveal that our system achieves satisfaction performances in terms of both robustness and efficiency
Optimization of a Centrifugal Pump Used as a Turbine Impeller By Means of an Orthogonal Test Approach
Get PDFA prototype centrifugal pump with a specific speed of 110 is used to investigate and optimize the performances of a turbine for power generation. Particular attention is given to the design of the internal impeller. The internal flow field is simulated in the framework of a commercial computational fluid dynamics software (ANSYS). Four geometrical parameters of the impeller are considered, i.e., the inlet diameter, the inlet width, the blade number, and the blade angle. The optimization is carried out on the basis of a three-level approach relying on an orthogonal test method. The results of the numerical simulations show good agreement with the experimental tests under different flow conditions. In accordance with the L9 (34) design table, the head and efficiency under the rated flow rate of the nine designed schemes are calculated and processed with the method of range analysis to obtain an optimized model
A Geometric Approach to Solve Fuzzy Linear Systems
No full textIn this paper, linear systems with a crisp real coefficient matrix and with a vector of fuzzy triangular numbers on the right-hand side are studied. A new method, which is based on the geometric representations of linear transformations, is proposed to find solutions. The method uses the fact that a vector of fuzzy triangular numbers forms a rectangular prism in n-dimensional space and that the image of a parallelepiped is also a parallelepiped under a linear transformation. The suggested method clarifies why in general case different approaches do not generate solutions as fuzzy numbers. It is geometrically proved that if the coefficient matrix is a generalized permutation matrix, then the solution of a fuzzy linear system (FLS) is a vector of fuzzy numbers irrespective of the vector on the right-hand side. The most important difference between this and previous papers on FLS is that the solution is sought as a fuzzy set of vectors (with real components) rather than a vector of fuzzy numbers. Each vector in the solution set solves the given FLS with a certain possibility.
The suggested method can also be applied in the case when the right-hand side is a vector of fuzzy numbers in parametric form. However, in this case, alpha-cuts of the solution cannot be determined by geometric similarity and additional computations are needed
Some Fundamental Properties of Lattice Boltzmann Equation for Two Phase Flows
No full textDue to the mesoscopic and kinetic nature, the lattice Boltzmann equation (LBE) method has become an efficient and powerful tool for modeling and simulating interfacial dynamics of multi-phase flows. In this work we discuss several fundamental properties of two-phase LBE models. Particularly, the effects of force discretization, spurious currents in the vicinity of interfaces, and checkerboard effects with the underlying lattices, are investigated
A New Algorithm for the Thermo-Mechanical Coupled Frictional Contact Problem of Polycrystalline Aggregates Based on Plastic Slip Theory
No full textThis paper presents a new numerical algorithm for thermal-mechanical coupled analysis of polycrystalline aggregates based on the plastic slip theory inside crystals and the frictional contact on their interfaces. It involves the mechanics and heat conduction behaviors caused by both force loads and temperature changing within crystal and contact interfaces between crystals. Firstly, the constitutive relationship inside single crystal, and the moment equations and energy equations are derived by means of rate-dependent plastic deformation theory and the formulation of elastic-plastic tangent modulus depended on temperature. Secondly, the contact conditions with friction, including frictional heat generation and heat transfer across the contact interface, are discussed. And then based on the ABAQUS software, the subroutines to calculate thermo-mechanical behaviors of polycrystalline copper are coded, and a polycrystalline body composed by four grains within 16 contact interfaces is simulated under the torsion and bending loadings. The numerical results show that crack propagation path are associated with loading ways and temperature change through the contact interfaces in addition to the friction heat generation. The displacement jumps are related to the contact pressure. The modeling approach presented in this work can be extended to more complicated systems with the interaction of a number of grains
Centrifuge Model Tests and Numerical Simulations of the Impact of Underwater Explosion on an Air-Backed Steel Plate
Get PDFDamage and threats to hydraulic and submarine structures by underwater explosions (UNDEXs) have raised much attention. The centrifuge model test, compared to prototype test, is a more promising way to examine the problem while reducing cost and satisfying the similitude requirements of both Mach and Froude numbers simultaneously. This study used a systematic approach employing centrifuge model tests and numerical simulations to investigate the effects of UNDEXs on an air-backed steel plate. Nineteen methodical centrifuge tests of UNDEXs were conducted. The shock wave pressure, bubble oscillation pressure, acceleration and the strain of the air-backed steel plate were recorded and compared with numerical studies using the finite element analysis (FEA) commercial software ABAQUS. By implementing empirically derived and physically measured pressures into the numerical models, the effects of the shock wave and bubble oscillation on the steel plate were investigated. Generally, the numerical results were in agreement with the experimental results. These results showed that the peak pressure of an UNDEX has a significant effect on the peak acceleration of the steel plate and that the impulse of the UNDEX pressure governs the peak strain of the steel plate