Improvement of Binocular Reconstruction Algorithm for Measuring 3D Pavement Texture Using a Single Laser Line Scanning Constraint

The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function.To form dense mandatory constraints and improve matching accuracy,the traditional binocular reconstruction technology was improved threefold.First,a single moving laser line was introduced to carry out global scanning constraints on the target,which would well overcome the difficulty of installing and recognizing excessive laser lines.Second,four kinds of improved algorithms,namely,disparity replacement,superposition synthesis,subregion segmentation,and subregion segmentation centroid enhancement,were established based on different constraint mechanism.Last,the improved binocular reconstruction test device was developed to realize the dual functions of 3D texture measurement and precision self-evaluation.Results show that compared with traditional algorithms,the introduction of a single laser line scanning constraint is helpful in improving the measurement’s accuracy.Among various improved algorithms,the improvement effect of the subregion segmentation centroid enhancement method is the best.It has a good effect on both overall measurement and single pointmeasurement,which can be considered to be used in pavement function evaluation.

A New Three-Dimensional(3D)Printing Prepress Algorithm for Simulation of Planned Surgery for Congenital Heart Disease

Background:Three-dimensional printing technology may become a key factor in transforming clinical practice and in significant improvement of treatment outcomes.The introduction of this technique into pediatric cardiac surgery will allow us to study features of the anatomy and spatial relations of a defect and to simulate the optimal surgical repair on a printed model in every individual case.Methods:We performed the prospective cohort study which included 29 children with congenital heart defects.The hearts and the great vessels were modeled and printed out.Measurements of the same cardiac areas were taken in the same planes and points at multislice computed tomography images(group 1)and on printed 3D models of the hearts(group 2).Pre-printing treatment of the multislice computed tomography data and 3D model preparation were performed according to a newly developed algorithm.Results:The measurements taken on the 3D-printed cardiac models and the tomographic images did not differ significantly,which allowed us to conclude that the models were highly accurate and informative.The new algorithm greatly simplifies and speeds up the preparation of a 3D model for printing,while maintaining high accuracy and level of detail.Conclusions:The 3D-printed models provide an accurate preoperative assessment of the anatomy of a defect in each case.The new algorithm has several important advantages over other available programs.They enable the development of customized preliminary plans for surgical repair of each specific complex congenital heart disease,predict possible issues,determine the optimal surgical tactics,and significantly improve surgical outcomes.

Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

Feature extraction is the most critical step in classification of multispectral image.The classification accuracy is mainly influenced by the feature sets that are selected to classify the image.In the past,handcrafted feature sets are used which are not adaptive for different image domains.To overcome this,an evolu-tionary learning method is developed to automatically learn the spatial-spectral features for classification.A modified Firefly Algorithm(FA)which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose.For extracting the most effi-cient features from the data set,we have used 3-D discrete wavelet transform which decompose the multispectral image in all three dimensions.For selecting spatial and spectral features we have studied three different approaches namely overlapping window(OW-3DFS),non-overlapping window(NW-3DFS)adaptive window cube(AW-3DFS)and Pixel based technique.Fivefold Multiclass Support Vector Machine(MSVM)is used for classification purpose.Experiments con-ducted on Madurai LISS IV multispectral image exploited that the adaptive win-dow approach is used to increase the classification accuracy.

基于改进麻雀搜索算法的3DDV-Hop定位算法

针对经典3DDV-Hop算法定位精度不高的问题,提出一种基于改进麻雀搜索算法优化的改进的3DDV-Hop算法;算法首先通过多通信半径优化传感器节点之间跳数,并且在平均跳距计算过程中引入动态加权因子提高平均跳距计算精度,其次在麻雀搜索算法的基础上融合反向学习策略与萤火虫算法分别对麻雀搜索算法的种群与位置更新迭代进行优化,最后将未知节点坐标计算问题转化成改进后的麻雀搜索算法寻优问题,利用改进后的麻雀搜索算法替代最小二乘法计算未知节点坐标,进一步提高未知节点位置计算精度;经过MATLAB仿真验证,改进算法对比于经典3DDV-Hop算法和相关算法,定位精度得到有效提高。

Construction of Ship Target Image Library Based on 3DS MAX and AP Algorithm

To achieve accurate classification and recognition of ship target types,it is necessary to establish a sample library of ship targets to be identified.On the basis of exploring the principles of building a ship target image library,the paper determines the sample set.Using 3DS MAX software as the platform,combined with the accurate 3D model of the ship in an offline state,the software fully utilizes its own rendering and animation functions to achieve the automatic generation of multi-view and multi-scale views of ship targets.To reduce the storage capacity of the image database,a construction method of the ship target image database based on the AP algorithm is presented.The algorithm can obtain the optimal cluster number,reduce the data storage capacity of the image database,and save the calculation amount for the subsequent matching calculation.

Three-dimensional(3D)parametric measurements of individual gravels in the Gobi region using point cloud technique

Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.

基于神经网络的未来3天Kp指数预报建模与可解释AI应用

当前业务中对未来3天Kp指数预报需求强烈.但地磁暴中多参数耦合导致难以量化各预报因子对Kp值的贡献,制约了预报精度提升.本文构建了神经网络3天Kp指数预报模型,并使用人工智能(AI)可解释性算法定量化各因子贡献.结果显示,行星际磁场南向分量在提前3 h对Kp指数的贡献为37.15%,为主要因子,说明模型能捕捉符合物理特征的主要预报因子.Kp指数历史特征贡献随提前量逐渐增加,提前3天总体贡献占68.06%,验证了对冕洞高速流引起的地磁暴事件的预报能力.对2015和2017年特大地磁暴进行贡献分析,模型准确捕捉了地磁暴多参数耦合的复杂特性.研究表明,可解释AI算法在一定程度上能定量化各预报因子对Kp指数的预报贡献,有助于改进未来3天Kp指数AI预报模型.

复杂测量环境下BDS-3/GPS组合RTK测量性能分析

为比较分析城市道路观测环境下BDS-3/GPS组合RTK测量性能,探讨一种基于卡尔曼滤波算法的RTK测量模型。在统一BDS-3/GPS组合RTK测量时空基准的基础上,建立RTK观测方程模型,利用LAMBDA算法快速确定双差整周模糊度,并基于卡尔曼滤波算法求解RTK观测方程模型测量结果;基于Visual Studio 2020平台,运用C/C++编程语言,设计和开发RTK数据处理软件(KalRTK),并比较分析BDS-3/GPS组合RTK测量结果。通过城市道路实测数据分析结果表明,BDS-3系统沿东西向跟踪卫星能力要略弱于GPS系统;BDS-3/GPS组合RTK测量的平面精度与高程精度均优于1.6cm,点位精度优于2.2cm,与GPS双频RTK测量精度基本相当,但优于BDS-3双频RTK测量精度。

基于3D-NDT的移动机器人定位算法研究

移动机器人定位是移动机器人自主导航的基本问题,在室外环境,GPS作为成熟方案被广泛使用,但在存在遮挡、有强电磁干扰等环境下,GPS定位的精度、稳定性及可靠性受到很大影响。本文详细阐述了三维激光点云3D-NDT匹配方法,在此基础上提出了融合里程计与3D-NDT点云匹配方法的移动机器人实时定位方法,解决了移动机器人在室外弱GPS环境下定位精度无法保证的问题。利用自主研发的移动机器人平台,在大范围室外环境中进行了测试,实验结果验证了本文所提算法的有效性。

Unfolding analysis of LaBr3:Ce gamma spectrum with a detector response matrix constructing algorithm based on energy resolution calibration

With respect to the gamma spectrum, the energy resolution improves with increase in energy. The counts of full energy peak change with energy, and this approximately complies with the Gaussian distribution. This study mainly examines a method to deconvolve the LaBr_3:Ce gamma spectrum with a detector response matrix constructing algorithm based on energy resolution calibration.In the algorithm, the full width at half maximum(FWHM)of full energy peak was calculated by the cubic spline interpolation algorithm and calibrated by a square root of a quadratic function that changes with the energy. Additionally, the detector response matrix was constructed to deconvolve the gamma spectrum. Furthermore, an improved SNIP algorithm was proposed to eliminate the background. In the experiment, several independent peaks of ^(152)Eu,^(137)Cs, and ^(60)Co sources were detected by a LaBr_3:Ce scintillator that were selected to calibrate the energy resolution. The Boosted Gold algorithm was applied to deconvolve the gamma spectrum. The results showed that the peak position difference between the experiment and the deconvolution was within ± 2 channels and the relative error of peak area was approximately within 0.96–6.74%. Finally, a ^(133) Ba spectrum was deconvolved to verify the efficiency and accuracy of the algorithm in unfolding the overlapped peaks.

Simple Insulin Dose Adjustment Using 3-3-1 Algorithm in Japanese Patients with Type 2 Diabetes: Start Kanazawa Study (Self-Titration Aggressive Algorithm with Glargine Trial)

We implemented a 3-3-1 algorithm in order to provide safe and simple self-titration in patients who newly initiated BOT as well as who were already on BOT and evaluated its utility in clinical setting. A total of 46 patients, 21 patients in the newly-initiated group and 25 patients in the existing BOT group performed dose adjustment using 3-3-1 algorithm. HbA1c was significantly improved 4 weeks after the initiation from 8.5% ± 1.2% at baseline to 7.3% ± 0.7% at the final evaluation (p 0.01, vs. Baseline). The average daily insulin units increased throughout the study period from 10.1 ± 6.7 at baseline to 14.6 ± 8.9 units at the final evaluation. Weight didn’t significantly change throughout the study (p = 0.12). The incidents of hypoglycemia were 0.8/month during the insulin dose self-adjustment period and 0.4/month during the follow-up period. The 3-3-1 algorithm using insulin glargine provided a safe and simple dose adjustment and demonstrated its utility in patients who were newly introduced to insulin treatment as well as who were already on BOT.

Using MC Algorithm to Implement 3D Image Reconstruction for Yunnan Weather Radar Data

3D image reconstruction for weather radar data can not only help the weatherman to improve the forecast efficiency and accuracy, but also help people to understand the weather conditions easily and quickly. Marching Cubes (MC) algorithm in the surface rendering has more excellent applicability in 3D reconstruction for the slice images;it may shorten the time to find and calculate the isosurface from raw volume data, reflect the shape structure more accurately. In this paper, we discuss a method to reconstruct the 3D weather cloud image by using the proposed Cube Weighting Interpolation (CWI) and MC algorithm. Firstly, we detail the steps of CWI, apply it to project the raw radar data into the cubes and obtain the equally spaced cloud slice images, then employ MC algorithm to draw the isosurface. Some experiments show that our method has a good effect and simple operation, which may provide an intuitive and effective reference for realizing the 3D surface reconstruction and meteorological image stereo visualization.

Adaptive tracking algorithm based on 3D variable turn model

Satisfactory results cannot be obtained when three-dimensional (3D) targets with complex maneuvering characteristics are tracked by the commonly used two-dimensional coordinated turn (2DCT) model. To address the problem of 3D target tracking with strong maneuverability, on the basis of the modified three-dimensional variable turn (3DVT) model, an adaptive tracking algorithm is proposed by combining with the cubature Kalman filter (CKF) in this paper. Through ideology of real-time identification, the parameters of the model are changed to adjust the state transition matrix and the state noise covariance matrix. Therefore, states of the target are matched in real-time to achieve the purpose of adaptive tracking. Finally, four simulations are analyzed in different settings by the Monte Carlo method. All results show that the proposed algorithm can update parameters of the model and identify motion characteristics in real-time when targets tracking also has a better tracking accuracy.

基于ISS-3DSC的NDT三维点云配准算法研究

工件形貌的三维扫描需求在车间自动化装备中越来越多,其中点云配准作为三维数据处理的重要步骤。现有三维点云配准存在特征点对误配、配准时间长、配准精度差等问题,提出了一种基于内部形状描述子-三维形状上下文特征(ISS-3DSC)的NDT三维点云配准算法。首先通过内部形状描述子(ISS)算法提取三维点云关键点,提高配准效率;然后结合三维形状上下文特征(3DSC)进行关键点的特征描述,并根据特征点对中值距离法剔除错误点对,采用SVD分解计算初始变换矩阵;最后使用NDT算法完成精配准。测试实验结果表明:算法在鞋面、鞋底点云数据配准时的精度可达到0.025 cm,相比传统SAC-IA+NDT算法配准效率提升明显,具有一定的工程应用价值。

Estimation of Crop Biomass Using GF-3 Polarization SAR Data Based on Genetic Algorithm Feature Selection

In recent years,Polarization SAR(PolSAR)has been widely used in the filed of crop biomass estimation.However,high dimensional features extracted from PolSAR data will lead to information redundancy which will result in low accuracy and poor transfer ability of the estimation model.Aiming at this problem,we proposed a estimation method of crop biomass based on automatic feature selection method using genetic algorithm(GA).Firstly,the backscattering coefficient,the polarization parameters and texture features were extracted from PolSAR data.Then,these features were automatically pre-selected by GA to obtain the optimal feature subset.Finally,based on this subset,a support vector regression machine(SVR)model was applied to estimate crop biomass.The proposed method was validated using the GaoFen-3(GF-3)QPSΙ(C-band,quad-polarization)SAR data.Based on wheat and rape biomass samples acquired from a synchronous field measurement campaign,the proposed method achieve relative high validation accuracy(over 80%)in both crop types.For further analyzing the improvement of proposed method,validation accuracies of biomass estimation models based on several different feature selection methods were compared.Compared with feature selection based on linear correlation,GA method has increased by 5.77%in wheat biomass estimation and 11.84%in rape biomass estimation.Compared with the method of recursive feature elimination(RFE)selection,the proposed method has improved crops biomass estimation accuracy by 3.90%and 5.21%,respectively.

A New 3D Wireless Directional Sensing Model and Coverage Enhancement Algorithm

Coverage control for each sensor is based on a 2D directional sensing model in directional sensor networks conventionally. But the 2D model cannot accurately characterize the real environment. In order to solve this problem,a new 3D directional sensor model and coverage enhancement algorithm is proposed. We can adjust the pitch angle and deviation angle to enhance the coverage rate. And the coverage enhancement algorithm is based on an improved gravitational search algorithm. In this paper the two improved strategies of GSA are directional mutation strategy and individual evolution strategy. A set of simulations show that our coverage enhancement algorithm has a good performance to improve the coverage rate of the wireless directional sensor network on different number of nodes,different virtual angles and different sensing radius.

Fragile Watermarking of 3D Models Using Genetic Algorithms

This paper describes a novel algorithm for fragile watermarking of 3D models. Fragile watermarking requires detection of even minute intentional changes to the 3D model along with the location of the change. This poses a challenge since inserting random amount of watermark in all the vertices of the model would generally introduce perceptible distortion. The proposed algorithm overcomes this challenge by using genetic algorithm to modify every vertex location in the model so that there is no perceptible distortion. Various experimental results are used to justify the choice of the genetic algorithm design parameters. Experimental results also indicate that the proposed algorithm can accurately detect location of any mesh modification.

A Study on Parallel Computation Based on 3D Forward Algorithm of Gravity

Interpretation of geophysical material is the prospecting method. Interpretation of Gravity-megnetic data is based on data processing and inversion. When the grid is divided into several million cells, the computing task is heavy and time-consuming. In order to increase efficiency of the 3D forward modeling, the paper will adopt MPI parallel algorithm and the several processes will deal with data in the method. Finally, we can gather the result. Through comparing the result of sequence algorithm with the result of MPI parallel algorithm, we can see the result is the same. When the number of processes is 2 to 8, the speed-up ratio is 1.97 to 5. The MPI parallel algorithm is very efficient.

Research on a bifurcation location algorithm of a drainage tube based on 3D medical images

Based on patient computerized tomography data,we segmented a region containing an intracranial hematoma using the threshold method and reconstructed the 3D hematoma model.To improve the efficiency and accuracy of identifying puncture points,a point-cloud search arithmetic method for modified adaptive weighted particle swarm optimization is proposed and used for optimal external axis extraction.According to the characteristics of the multitube drainage tube and the clinical needs of puncture for intracranial hematoma removal,the proposed algorithm can provide an optimal route for a drainage tube for the hematoma,the precise position of the puncture point,and preoperative planning information,which have considerable instructional significance for clinicians.

An improved micro-expression recognition algorithm of 3D convolutional neural network

The micro-expression lasts for a very short time and the intensity is very subtle.Aiming at the problem of its low recognition rate,this paper proposes a new micro-expression recognition algorithm based on a three-dimensional convolutional neural network(3D-CNN),which can extract two-di-mensional features in spatial domain and one-dimensional features in time domain,simultaneously.The network structure design is based on the deep learning framework Keras,and the discarding method and batch normalization(BN)algorithm are effectively combined with three-dimensional vis-ual geometry group block(3D-VGG-Block)to reduce the risk of overfitting while improving training speed.Aiming at the problem of the lack of samples in the data set,two methods of image flipping and small amplitude flipping are used for data amplification.Finally,the recognition rate on the data set is as high as 69.11%.Compared with the current international average micro-expression recog-nition rate of about 67%,the proposed algorithm has obvious advantages in recognition rate.