Resilience assessment and optimization method of city road network in the post-earthquake emergency period

The post-earthquake emergency period,which is a sensitive time segment just after an event,mainly focuses on saving life and restoring social order.To improve the seismic resilience of city road networks,a resilience evaluation method used in the post-earthquake emergency period is proposed.The road seismic damage index of a city road network can consider the influence of roads,bridges and buildings along the roads,etc.on road capacity after an earthquake.A function index for a city road network is developed,which reflects the connectivity,redundancy,traffic demand and traffic function of the network.An optimization model for improving the road repair order in the post-earthquake emergency period is also developed according to the resilience evaluation,to enable decision support for city emergency management and achieve the best seismic resilience of the city road network.The optimization model is applied to a city road network and the results illustrate the feasibility of the resilience evaluation and optimization method for a city road network in the post-earthquake emergency period.

Reconstruction and stability of Fe_(3)O_(4)(001)surface:An investigation based on particle swarm optimization and machine learning

Magnetite nanoparticles show promising applications in drug delivery,catalysis,and spintronics.The surface of magnetite plays an important role in these applications.Therefore,it is critical to understand the surface structure of Fe_(3)O_(4)at atomic scale.Here,using a combination of first-principles calculations,particle swarm optimization(PSO)method and machine learning,we investigate the possible reconstruction and stability of Fe_(3)O_(4)(001)surface.The results show that besides the subsurface cation vacancy(SCV)reconstruction,an A layer with Fe vacancy(A-layer-V_(Fe))reconstruction of the(001)surface also shows very low surface energy especially at oxygen poor condition.Molecular dynamics simulation based on the iron–oxygen interaction potential function fitted by machine learning further confirms the thermodynamic stability of the A-layer-V_(Fe)reconstruction.Our results are also instructive for the study of surface reconstruction of other metal oxides.

Problem identification and revitalization strategies for the recovery and reconstruction of traditional villages in the Ms 6.8 Luding Earthquake

Post-disaster reconstruction is a topic of global concern,and traditional villages have special heritage attributes and need to face more requirements and obstacles in post-disaster reconstruction.This paper summarizes four concepts based on the research on post-disaster reconstruction both domestically and internationally,as well as the recovery and reconstruction of cultural heritage.Through a field survey of traditional villages in the Ms 6.8 Luding earthquake-stricken area,it is found that there are problems such as insufficient awareness of heritage value,misalignment of scientific reconstruction technology,and insufficient protection of reconstruction elements during the reconstruction process.Traditional villages face the risk of declining or even loss of heritage value.In order to effectively protect traditional villages and inherit the carrier of regional culture,four targeted reconstruction response strategies are proposed,i.e.,to"establish special planning for traditional village preservation","emphasize recovery of the authenticity of village heritage","ensure elements for village heritage recovery"and"promote the activation and utilization of village heritage",based on the problems discovered during the survey and the four concepts summarized in the research on post-disaster reconstruction of traditional villages.The research results hope to provide useful reference for ancient cultural areas affected by earthquakes on how to protect cultural heritage during the post-disaster reconstruction process.

Magnetic diagnostics layout design for CFETR plasma equilibrium reconstruction

Plasma equilibrium reconstruction provides essential information for tokamak operation and physical analysis.An extensive and reliable set of magnetic diagnostics is required to obtain accurate plasma equilibrium.This study designs and optimizes the magnetic diagnostics layout for the reconstruction of the equilibrium of the plasma according to the scientific objectives,engineering design parameters,and limitations of the Chinese Fusion Engineering Test Reactor(CFETR).Based on the CFETR discharge simulation,magnetic measurement data are employed to reconstruct consistent plasma equilibrium parameters,and magnetic diagnostics'number and position are optimized by truncated Singular value decomposition,verifying the redundancy reliability of the magnetic diagnostics layout design.This provides a design solution for the layout of the magnetic diagnostics system required to control the plasma equilibrium of CFETR,and the developed design and optimization method can provide effective support to design magnetic diagnostics systems for future magnetic confinement fusion devices.

A Blade Altering Toolbox for Automating Rotor Design Optimization

The Blade Altering Toolbox(BAT)described in this paper is a tool designed for fast reconstruction of an altered blade geometry for design optimization purposes.The BAT algorithm is capable of twisting a given rotor’s angle of attack and stretching the chord length along the span of the rotor.Several test cases were run using the BAT’s algorithm.The BAT code’s twisting,stretching,and mesh reconstruction capabilities proved to be able to handle reasonably large geometric alterations to a provided input rotor geometry.The test examples showed that the toolbox’s algorithm could handle any stretching of the blade’s chord as long as the blade remained within the original bounds of the unaltered mesh.The algorithm appears to fail when the net twist angle applied the geometry exceeds approximately 30 degrees,however this limitation is dependent on the initial geometry and other input parameters.Overall,the algorithm is a very powerful tool for automating a design optimization procedure.

For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

Reviews on Post-earthquake Reconstruction of Qiang Culture: Three-dimensional Pattern

Through the introduction of disaster situation of Qiang Culture after Wenchuan Earthquake, the paper emphasized that carriers of Qiang Culture had been seriously damaged, the inheritance of Qiang Culture had been affected, and the environment for Qiang Culture was difficult to recover. It highlighted that three-dimensional reconstruction of Qiang Culture should stress the core task and timely and effectively rescue endangered cultural heritages of Qiang Nationality from the perspectives of material and spiritual life. It had explained focuses of three-dimensional pattern construction in detail. In terms of spatial reconstruction, it should reconstruct native culture and history while material culture was constructed, and reconstruct Qiang culture highland by depending on aborigines; in terms of cluster reconstruction, it should give support to large tourism enterprises and perfect tourism chain; in terms of ecological reconstruction, it should enhance construction and demonstration of "ecological protection pilot area of Qiang culture"; in terms of development reconstruction, it should realize coordinated unity between protection and development according to classification protection, characteristic protection and key protection, so as to form the virtuous circle of post-disaster recovery protection and sustainable development.

Image reconstruction from few views by l_0-norm optimization

In the medical computer tomography （CT） field, total variation （TV）, which is the l1-norm of the discrete gradient transform （DGT）, is widely used as regularization based on the compressive sensing （CS） theory. To overcome the TV model＇s disadvantageous tendency of uniformly penalizing the image gradient and over smoothing the low-contrast structures, an iterative algorithm based on the l0-norm optimization of the DGT is proposed. In order to rise to the challenges introduced by the l0-norm DGT, the algorithm uses a pseudo-inverse transform of DGT and adapts an iterative hard thresholding （IHT） algorithm, whose convergence and effective efficiency have been theoretically proven. The simulation demonstrates our conclusions and indicates that the algorithm proposed in this paper can obviously improve the reconstruction quality.

Application of Reconstruction and Optimization Algorithms in Optical Tomography

Optical tomography is a non-invasive technique that uses visible or near infrared radiation to analyze biological tissues. Researchers take immense attention towards advancement in optical tomography because of its low cost and an advantage of providing anatomical information. Based on the information of optical characteristics, forward and inverse problem of tomography are solved. In this research, finite element method is employed for forward problem and gradient-based optimization algorithm is developed for inverse problem of optical tomography. It is found from simulations that information about imaging is processed more distinctly and in less computational time. Normal and abnormal conditions in imaging are readily distinguished.?Simulations are carried out in Matlab. Different scenarios are developed and are simulated to validate the performance of reconstruction and optimization algorithms in optical tomography.

Green’s Function Technique and Global Optimization in Reconstruction of Elliptic Objects in the Regular Triangle

The reconstruction problem for elliptic voids located in the regular (equilateral) triangle is studied. A known point source is applied to the boundary of the domain, and it is assumed that the input data is obtained from the free-surface input data over a certain finite-length interval of the outer boundary. In the case when the boundary contour of the internal object is unknown, we propose a new algorithm to reconstruct its position and size on the basis of the input data. The key specific character of the proposed method is the construction of a special explicit-form Green's function satisfying the boundary condition over the outer boundary of the triangular domain. Some numerical examples demonstrate good stability of the proposed algorithm.

Measures for the Optimization of Subgrade and Pavement Design in the Reconstruction and Expansion of Highways

In comparison to the construction of modern highway engineering,several of China’s early pavement construction concerns,such as pavement collapse,are rather clear.Limited by historical and technical factors,the subgrade and pavement design for highways lacks scientificity,thus inducing potential safety problems in the operation.In order to comprehensively improve the subgrade and pavement design as well as ensure the quality and safety of highway engineering projects,this paper takes the reconstructed and expanded highway projects as research subjects and focuses on proposing optimization measures for the subgrade and pavement design of reconstructed and expanded highways,so as to provide adequate reference.

Customized reconstructive prosthesis design based on topological optimization to treat severe proximal tibia defect

A novel reconstructive prosthesis was designed with topological optimization(TO)and a lattice structure to enhance biomechanical and biological properties in the proximal tibia.The biomechanical performance was validated through finite element analysis(FEA)and biomechanical tests.The tibia with inhomogeneous material properties was reconstructed according to computed tomography images,and different components were designed to simulate the operation.Minimum compliance TO subject to a volume fraction constraint combined with a graded lattice structure was utilized to redesign the prosthesis.FEA was performed to evaluate the mechanical performances of the tibia and implants after optimization,including stress,micromotion,and strain energy.The results were analyzed by paired-samples t tests,and p<0.05 was considered significant.Biomechanical testing was used to verify the tibial stresses.Compared to the original group(OG),the TO group(TOG)exhibited lower stress on the stem,and the maximum von Mises stresses were 87.2 and 53.1 MPa,respectively,a 39.1%reduction(p<0.05).Conversely,the stress and strain energy on the tibia increased in the TOG.The maximum von Mises stress values were 16.4 MPa in the OG and 22.9 MPa in the TOG with a 39.6%increase(p<0.05),and the maximum SED value was 0.026 MPa in the OG and 0.042 MPa in the TOG,corresponding to an increase of 61.5%(p<0.05).The maximum micromotions in the distal end of the stem were 135μm in the OG and 68μm in the TOG,almost a 50%reduction.The stress curves of the biomechanical test coincided well with the FEA results.The TO approach can effectively reduce the whole weight of the prosthesis and improve the biomechanical environment of the tibia.It could also pave the way for next-generation applications in orthopedics surgery.

Sparse Reconstructive Evidential Clustering for Multi-View Data

Although many multi-view clustering(MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, these existing algorithms create only the hard and fuzzy partitions for multi-view objects,which are often located in highly-overlapping areas of multi-view feature space. The adoption of hard and fuzzy partition ignores the ambiguity and uncertainty in the assignment of objects, likely leading to performance degradation. To address these issues, we propose a novel sparse reconstructive multi-view evidential clustering algorithm(SRMVEC). Based on a sparse reconstructive procedure, SRMVEC learns a shared affinity matrix across views, and maps multi-view objects to a 2-dimensional humanreadable chart by calculating 2 newly defined mathematical metrics for each object. From this chart, users can detect the number of clusters and select several objects existing in the dataset as cluster centers. Then, SRMVEC derives a credal partition under the framework of evidence theory, improving the fault tolerance of clustering. Ablation studies show the benefits of adopting the sparse reconstructive procedure and evidence theory. Besides,SRMVEC delivers effectiveness on benchmark datasets by outperforming some state-of-the-art methods.

Optimized CUDA Implementation to Improve the Performance of Bundle Adjustment Algorithm on GPUs

The 3D reconstruction pipeline uses the Bundle Adjustment algorithm to refine the camera and point parameters. The Bundle Adjustment algorithm is a compute-intensive algorithm, and many researchers have improved its performance by implementing the algorithm on GPUs. In the previous research work, “Improving Accuracy and Computational Burden of Bundle Adjustment Algorithm using GPUs,” the authors demonstrated first the Bundle Adjustment algorithmic performance improvement by reducing the mean square error using an additional radial distorting parameter and explicitly computed analytical derivatives and reducing the computational burden of the Bundle Adjustment algorithm using GPUs. The naïve implementation of the CUDA code, a speedup of 10× for the largest dataset of 13,678 cameras, 4,455,747 points, and 28,975,571 projections was achieved. In this paper, we present the optimization of the Bundle Adjustment algorithm CUDA code on GPUs to achieve higher speedup. We propose a new data memory layout for the parameters in the Bundle Adjustment algorithm, resulting in contiguous memory access. We demonstrate that it improves the memory throughput on the GPUs, thereby improving the overall performance. We also demonstrate an increase in the computational throughput of the algorithm by optimizing the CUDA kernels to utilize the GPU resources effectively. A comparative performance study of explicitly computing an algorithm parameter versus using the Jacobians instead is presented. In the previous work, the Bundle Adjustment algorithm failed to converge for certain datasets due to several block matrices of the cameras in the augmented normal equation, resulting in rank-deficient matrices. In this work, we identify the cameras that cause rank-deficient matrices and preprocess the datasets to ensure the convergence of the BA algorithm. Our optimized CUDA implementation achieves convergence of the Bundle Adjustment algorithm in around 22 seconds for the largest dataset compared to 654 seconds for the sequential implementation, resulting in a speedup of 30×. Our optimized CUDA implementation presented in this paper has achieved a 3× speedup for the largest dataset compared to the previous naïve CUDA implementation.

Optimum Combination Test of Erosion Gully in Black Soil Regions by Coal Gangue Reconstruction Soil

The black soil area in northeast China is greatly affected by hydraulic erosion.To inhibit the development of gully cutting and the secondary erosion on farmland,different size coal gangues and covering soils with change thicknesses combinations were selected to fill in-situ gully for hydraulic performance experiment.The hydraulic performance indexes of different combinations of large and small size gangue thicknesses and covering soil thicknesses were analyzed by the extreme learning machine(ELM)and particle swarm optimization(PSO).The results showed that the structure of large and small size coal gangues and surface soil under different thicknesses was affected by hydraulic and gravity.With the change of the thicknesses of coal gangue and covering soil,its effective channel and vertical infiltration process became more and more stable with the increase in drainage time,while the structure of small size coal gangue was the main hydraulic factor in reconstructed soil structure(p=0.016).The overall drainage performance showed a single peak trend,the optimal combination of drainage parameters and structure thickness was relatively concentrated;the drainage time parameters of different composite structures were found to have a certain linear relationship;the Pareto optimum of drainage performance was determined.The optimum thickness was 30-40 cm for large-sized gangue,30-60 cm for small-sized gangue,and 50-70 cm for covering soil,to meet the relatively good drainage performance and to ensure that secondary erosion was reduced,so as to achieve the purpose of controlling the gully.

3-D Reconstruction and Visualization of Laser-Scanned Trees by Weighted Locally Optimal Projection and Accurate Modeling Method

This paper presents a method to reconstruct 3-D models of trees from terrestrial laser scan(TLS)point clouds.This method uses the weighted locally optimal projection(WLOP)and the AdTree method to reconstruct detailed 3-D tree models.To improve its representation accuracy,the WLOP algorithm is introduced to consolidate the point cloud.Its reconstruction accuracy is tested using a dataset of ten trees,and the one-sided Hausdorff distances between the input point clouds and the resulting 3-D models are measured.The experimental results show that the optimal projection modeling method has an average one-sided Hausdorff distance(mean)lower by 30.74%and 6.43%compared with AdTree and AdQSM methods,respectively.Furthermore,it has an average one-sided Hausdorff distance(RMS)lower by 29.95%and 12.28%compared with AdTree and AdQSM methods.Results show that the 3-D model generated fits closely to the input point cloud data and ensures a high geometrical accuracy.

Investigation of prior image constrained compressed sensing-based spectral X-ray CT image reconstruction

To improve spectral X-ray CT reconstructed image quality, the energy-weighted reconstructed image xbins^W and the separable paraboloidal surrogates（SPS） algorithm are proposed for the prior image constrained compressed sensing（PICCS）-based spectral X-ray CT image reconstruction. The PICCS-based image reconstruction takes advantage of the compressed sensing theory, a prior image and an optimization algorithm to improve the image quality of CT reconstructions.To evaluate the performance of the proposed method, three optimization algorithms and three prior images are employed and compared in terms of reconstruction accuracy and noise characteristics of the reconstructed images in each energy bin.The experimental simulation results show that the image xbins^W is the best as the prior image in general with respect to the three optimization algorithms; and the SPS algorithm offers the best performance for the simulated phantom with respect to the three prior images. Compared with filtered back-projection（FBP）, the PICCS via the SPS algorithm and xbins^W as the prior image can offer the noise reduction in the reconstructed images up to 80. 46%, 82. 51%, 88. 08% in each energy bin,respectively. M eanwhile, the root-mean-squared error in each energy bin is decreased by 15. 02%, 18. 15%, 34. 11% and the correlation coefficient is increased by 9. 98%, 11. 38%,15. 94%, respectively.

Investigation and optimization of sampling characteristics of light field camera for flame temperature measurement

It is essential to investigate the light field camera parameters for the accurate flame temperature measurement because the sampling characteristics of the flame radiation can be varied with them. In this study, novel indices of the light field camera were proposed to investigate the directional and spatial sampling characteristics of the flame radiation. Effects of light field camera parameters such as focal length and magnification of the main lens, focal length and magnification of the microlens were investigated. It was observed that the sampling characteristics of the flame are varied with the different parameters of the light field camera. The optimized parameters of the light field camera were then proposed for the flame radiation sampling. The larger sampling angle(23 times larger) is achieved by the optimized parameters compared to the commercial light field camera parameters. A non-negative least square(NNLS) algorithm was used to reconstruct the flame temperature. The reconstruction accuracy was also evaluated by the optimized parameters. The results suggested that the optimized parameters can provide higher reconstruction accuracy for axisymmetric and non-symmetric flame conditions in comparison to the commercial light field camera.

Comparison of signal reconstruction under different transforms

A newalgorithm, called Magnitude Cut, to recover a signal from its phase in the transform domain, is proposed.First, the recovery problem is converted to an equivalent convex optimization problem, and then it is solved by the block coordinate descent（ BCD） algorithm and the interior point algorithm. Finally, the one-dimensional and twodimensional signal reconstructions are implemented and the reconstruction results under the Fourier transform with a Gaussian random mask（ FTGM）, the Cauchy wavelets transform（ CWT）, the Fourier transform with a binary random mask（ FTBM） and the Gaussian random transform（ GRT） are also comparatively analyzed. The analysis results reveal that the M agnitude Cut method can reconstruct the original signal with the phase information of different transforms; and it needs less phase information to recover the signal from the phase of the FTGM or GRT than that of FTBM or CWT under the same reconstruction error.