基于点云特征的改进RANSAC地面分割算法

针对室外复杂场景下,轻量级和地面优化的激光雷达里程计与测图(LeGO-LOAM)算法由于地面分割不精确而导致算法定位精度降低的问题,提出一种基于改进随机一致性采样(RANSAC)的多线程地面分割算法:相较于传统RANSAC算法,该算法舍弃从全部原始数据中随机选取种子点拟合地面模型的迭代方式,首先利用点云高程、曲率等点特征信息挑选出所有小于高程、曲率等阈值的种子点以构建种子点集合,并根据种子点集合中的种子点数量判断是否需要多线程处理;然后根据判断结果从种子点集合中选择种子点子集进行地面拟合;最后比较各地面模型所包含的点云数量以获得最优地面模型参数以及地面点云集;地面分割精度的提高有效地降低了LeGO-LOAM算法的定位误差。实验结果表明,在室外复杂场景下所提出的地面分割算法分割效果更好,杂点更少;相较于原LeGO-LOAM算法,改进算法的定位误差降低至3.73 m,平面均方根误差降低了20.8%。

基于RANSAC的圆拟合算法在螺纹孔检测中的应用

在视觉检测过程中,针对多残缺、多噪声圆周的拟合精度不佳的问题,提出了一种基于RANSAC的圆拟合算法。首先对图像进行边缘检测,使用基于Scharr算子的Canny算法可获得高质量的边缘分布图;使用霍夫梯度法在边缘分布图中对目标圆弧进行粗定位,并提取包含目标圆弧的点集;提取到的点集中含有大量无关边缘像素点,使用RANSAC算法剔除点集中的异常数据,得到有效样本数据构成的待拟合圆周点集;最后采用LIN算法对待拟合圆周点集进行拟合,得出最终的拟合结果。算法在椒盐噪声和曲线噪声抗干扰实验中表现优异,有着较强的抗干扰能力。已经成功应用到了螺纹孔圆周的拟合,精度和实时性均可满足实际生产要求。

基于改进RANSAC的本质矩阵求解方法

针对在单目系统大尺寸测量场景下使用RANSAC算法求解本质矩阵时稳定性和求解精度不高的问题,提出了一种改进RANSAC的本质矩阵求解方法,首先在所有匹配特征点中,通过当前内点求得的本质矩阵对剩余匹配特征点进行重投影误差,并采用相对判别法通过这些误差的值大小来确定当前内点是否为高质量内点,之后在此基础上采用二分法动态调整阈值从若干本质矩阵中寻找最优值。最后,设计了多组视角不同误匹配率下的仿真实验和实际拍摄的实验,实验证明,相较于传统与其他改进的RANSAC算法及LMedS算法,本文改进的算法能够快速确定初始内点并自适应调整阈值,同时求出较好的本质矩阵,满足求解稳定性与精度的要求。

基于改进RANSAC-ICP算法的点云配准方法

针对点云配准时重叠区域小,难以提取特征,配准精度较低的问题,提出了一种结合改进的随机采样一致性(RANSAC)算法和改进的迭代最近点(ICP)算法的点云配准算法。首先,采用快速点特征直方图(FPFH)描述子对点云进行特征描述;其次通过融合几何一致性,采用改进随机采样一致性的算法,及时删除匹配过程中的误匹配点对,保持着对应点之间的优质关系,使其在低重叠率的点云以及含噪声的点云下也能找到具有对应关系的点,进行点云粗配准;最后针对点云数据量大时ICP配准耗时长的问题,采用KD-Tree搜索,将无序的点云进行有序化排列,进行点云精配准。采用激光雷达扫描的真实点云数据进行实验验证,并与主流点云配准算法进行比较分析。实验结果表明,对于较低重叠率、含噪声的点云,能够快速、精确地求得最优变换,具有较好的配准效果。

Theoretical and experimental study of a bi-stable piezoelectric energy harvester under hybrid galloping and band-limited random excitations

In the practical environment,it is very common for the simultaneous occurrence of base excitation and crosswind.Scavenging the combined energy of vibration and wind with a single energy harvesting structure is fascinating.For this purpose,the effects of the wind speed and random excitation level are investigated with the stochastic averaging method(SAM)based on the energy envelope.The results of the analytical prediction are verified with the Monte-Carlo method(MCM).The numerical simulation shows that the introduction of wind can reduce the critical excitation level for triggering an inter-well jump and make a bi-stable energy harvester(BEH)realize the performance enhancement for a weak base excitation.However,as the strength of the wind increases to a particular level,the influence of the random base excitation on the dynamic responses is weakened,and the system exhibits a periodic galloping response.A comparison between a BEH and a linear energy harvester(LEH)indicates that the BEH demonstrates inferior performance for high-speed wind.Relevant experiments are conducted to investigate the validity of the theoretical prediction and numerical simulation.The experimental findings also show that strong random excitation is favorable for the BEH in the range of low wind speeds.However,as the speed of the incoming wind is up to a particular level,the disadvantage of the BEH becomes clear and evident.

基于RANSAC算法的工业机器人运动学参数标定

为提升工业机器人末端绝对定位精度,文中提出一种基于RANSAC算法的运动学参数标定算法。首先采用D-H模型建立末端位置运动学误差模型;通过RANSAC算法对标定点集进行筛选,剔除误差较大的粗差点;最后采用抗差岭估计辨识运动学参数,减少测量扰动、粗差和法方程病态性等因素的影响。试验结果表明,机器人绝对定位精度的RMS误差由0.999 mm降低至0.229 mm,误差下降77.08%。相比于传统的标定算法,文中算法辨识运动学参数准确性更好,标定精度更高。

Enhancing the resolution of sparse rock property measurements using machine learning and random field theory

The travel time of rock compressional waves is an essential parameter used for estimating important rock properties,such as porosity,permeability,and lithology.Current methods,like wireline logging tests,provide broad measurements but lack finer resolution.Laboratory-based rock core measurements offer higher resolution but are resource-intensive.Conventionally,wireline logging and rock core measurements have been used independently.This study introduces a novel approach that integrates both data sources.The method leverages the detailed features from limited core data to enhance the resolution of wireline logging data.By combining machine learning with random field theory,the method allows for probabilistic predictions in regions with sparse data sampling.In this framework,12 parameters from wireline tests are used to predict trends in rock core data.The residuals are modeled using random field theory.The outcomes are high-resolution predictions that combine both the predicted trend and the probabilistic realizations of the residual.By utilizing unconditional and conditional random field theories,this method enables unconditional and conditional simulations of the underlying high-resolution rock compressional wave travel time profile and provides uncertainty estimates.This integrated approach optimizes the use of existing core and logging data.Its applicability is confirmed in an oil project in West China.

Immune cell signatures and causal association with irritable bowel syndrome:A mendelian randomization study

BACKGROUND The mucosal barrier's immune-brain interactions,pivotal for neural development and function,are increasingly recognized for their potential causal and therapeutic relevance to irritable bowel syndrome(IBS).Prior studies linking immune inflammation with IBS have been inconsistent.To further elucidate this relationship,we conducted a Mendelian randomization(MR)analysis of 731 immune cell markers to dissect the influence of various immune phenotypes on IBS.Our goal was to deepen our understanding of the disrupted brain-gut axis in IBS and to identify novel therapeutic targets.AIM To leverage publicly available data to perform MR analysis on 731 immune cell markers and explore their impact on IBS.We aimed to uncover immunophenotypic associations with IBS that could inform future drug development and therapeutic strategies.METHODS We performed a comprehensive two-sample MR analysis to evaluate the causal relationship between immune cell markers and IBS.By utilizing genetic data from public databases,we examined the causal associations between 731 immune cell markers,encompassing median fluorescence intensity,relative cell abundance,absolute cell count,and morphological parameters,with IBS susceptibility.Sensitivity analyses were conducted to validate our findings and address potential heterogeneity and pleiotropy.RESULTS Bidirectional false discovery rate correction indicated no significant influence of IBS on immunophenotypes.However,our analysis revealed a causal impact of IBS on 30 out of 731 immune phenotypes(P<0.05).Nine immune phenotypes demonstrated a protective effect against IBS[inverse variance weighting(IVW)<0.05,odd ratio(OR)<1],while 21 others were associated with an increased risk of IBS onset(IVW≥0.05,OR≥1).CONCLUSION Our findings underscore a substantial genetic correlation between immune cell phenotypes and IBS,providing valuable insights into the pathophysiology of the condition.These results pave the way for the development of more precise biomarkers and targeted therapies for IBS.Furthermore,this research enriches our comprehension of immune cell roles in IBS pathogenesis,offering a foundation for more effective,personalized treatment approaches.These advancements hold promise for improving IBS patient quality of life and reducing the disease burden on individuals and their families.

Causal associations between gastroesophageal reflux disease and essential hypertension: A bidirectional Mendelian randomization study

BACKGROUND Clinical studies have reported that patients with gastroesophageal reflux disease(GERD)have a higher prevalence of hypertension.AIM To performed a bidirectional Mendelian randomization(MR)analysis to investi-gate the causal link between GERD and essential hypertension.METHODS Eligible single nucleotide polymorphisms(SNPs)were selected,and weighted median,inverse variance weighted(IVW)as well as MR egger(MR-Egger)re-gression were used to examine the potential causal association between GERD and hypertension.The MR-Pleiotropy RESidual Sum and Outlier analysis was used to detect and attempt to reduce horizontal pleiotropy by removing outliers SNPs.The MR-Egger intercept test,Cochran’s Q test and“leave-one-out”sen-sitivity analysis were performed to evaluate the horizontal pleiotropy,heterogen-eities,and stability of single instrumental variable.RESULTS IVW analysis exhibited an increased risk of hypertension(OR=1.46,95%CI:1.33-1.59,P=2.14E-16)in GERD patients.And the same result was obtained in replication practice(OR=1.002,95%CI:1.0008-1.003,P=0.000498).Meanwhile,the IVW analysis showed an increased risk of systolic blood pressure(β=0.78,95%CI:0.11-1.44,P=0.021)and hypertensive heart disease(OR=1.68,95%CI:1.36-2.08,P=0.0000016)in GERD patients.Moreover,we found an decreased risk of Barrett's esophagus(OR=0.91,95%CI:0.83-0.99,P=0.043)in essential hypertension patients.CONCLUSION We found that GERD would increase the risk of essential hypertension,which provided a novel prevent and therapeutic perspectives of essential hypertension.

基于RANSAC和三维谱峰分析的全姿态散射中心建模

全姿态散射中心模型是一种性能优良的光学区复杂目标电磁散射参数化模型。针对传统的基于候选点筛选和聚类的全姿态散射中心建模方法易出现虚假散射中心和遗漏真实散射中心的问题,该文提出了一种基于目标三维空间电磁散射强度场谱峰分析的建模方法。首先,基于目标多视一维散射中心参数,利用随机采样一致性(RANSAC)方法和Parzen窗函数方法估计目标在三维空间中的电磁散射强度场。然后,通过谱峰分析、散射中心关联和多视量测融合,得到全姿态三维散射中心的位置。最后,利用二值形态学处理修正全姿态散射中心的角度可见性,估计全姿态散射中心的散射系数和类型参数。仿真结果表明,该文方法所提取的全姿态散射中心与目标几何结构具有极强的关联性,相较传统方法,在缩减三维散射中心数量的同时提升了模型的表示精度。

Genetically predicted fatty liver disease and risk of psychiatric disorders: A mendelian randomization study

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)and alcohol-related liver disease(Ar-LD)constitute the primary forms of chronic liver disease,and their incidence is progressively increasing with changes in lifestyle habits.Earlier studies have do-cumented a correlation between the occurrence and development of prevalent mental disorders and fatty liver.AIM To investigate the correlation between fatty liver and mental disorders,thus ne-cessitating the implementation of a mendelian randomization(MR)study to elu-cidate this association.METHODS Data on NAFLD and ArLD were retrieved from the genome-wide association studies catalog,while information on mental disorders,including Alzheimer's disease,schizophrenia,anxiety disorder,attention deficit hyperactivity disorder(ADHD),bipolar disorder,major depressive disorder,multiple personality dis-order,obsessive-compulsive disorder(OCD),post-traumatic stress disorder(PTSD),and schizophrenia was acquired from the psychiatric genomics consor-tium.A two-sample MR method was applied to investigate mediators in signifi-cant associations.RESULTS After excluding weak instrumental variables,a causal relationship was identified between fatty liver disease and the occurrence and development of some psychia-tric disorders.Specifically,the findings indicated that ArLD was associated with a significantly elevated risk of developing ADHD(OR:5.81,95%CI:5.59-6.03,P<0.01),bipolar disorder(OR:5.73,95%CI:5.42-6.05,P=0.03),OCD(OR:6.42,95%CI:5.60-7.36,P<0.01),and PTSD(OR:5.66,95%CI:5.33-6.01,P<0.01).Meanwhile,NAFLD significantly increased the risk of developing bipolar disorder(OR:55.08,95%CI:3.59-845.51,P<0.01),OCD(OR:61.50,95%CI:6.69-565.45,P<0.01),and PTSD(OR:52.09,95%CI:4.24-639.32,P<0.01).CONCLUSION Associations were found between genetic predisposition to fatty liver disease and an increased risk of a broad range of psychiatric disorders,namely bipolar disorder,OCD,and PTSD,highlighting the significance of preven-tive measures against psychiatric disorders in patients with fatty liver disease.

融合PCA+RANSAC的激光雷达点云直线特征提取

直线特征是测量场景中的普遍特征,也是点云智能化处理的基础数据。针对目前直线特征提取算法复杂、精度有限的问题,提出了一种融合PCA和RANSAC算法的直线特征提取算法。首先,构建点云的协方差矩阵,并采用PCA算法求解特征值和曲面变分,用曲面变分筛选出特征区域点云;然后,再次使用PCA算法求解特征区域点云,根据特征值分布规律和曲面变分协同精化出直线特征区域点云;最后,利用RANSAC算法逐条分割出直线特征点云,并根据局内点坐标计算空间直线的方向和点坐标参数。试验结果表明,本文方法提取了block模型的全部12条直线特征并获取了正确的直线参数,直线特征点云的召回率为97.0%,精度为99.7%。本文算法有效可靠,可快速准确地提取点云直线特征。

一种基于KMeans与Random Forest的异常温升捕捉方法

针对线路老化、线路过载的火灾频发问题,分析了线路老化、线路过载与异常温升之间的关联性,以电流值、线缆温度作为输入,利用KMeans聚类算法划分可能存在异常温升的区间,通过Random Forest算法识别线路过载问题,可以提前通知用户整改线路,预防火灾的发生。

结合改进RANSAC算法的建筑物点云色彩增强方法

针对彩色三维点云中因建筑物阴影导致可视化效果不好的问题,提出了一种以建筑物面分割为基础对建筑物局部进行色彩增强的方法。首先采用改进随机抽样一致性(RANSAC)算法对建筑物进行表面分割,并提出光照向量的概念将表面分割结果分为阴面与阳面;再单独针对阴面进行色彩增强。实验表明,该方法有效改善了三维点云建筑物的视觉效果,在保证建筑物风格一致的前提下提高了建筑物点云的整体亮度与对比度,可在一定程度上消除建筑物阴影对可视化效果的影响,适用于各类以建筑物为主体的点云实景三维工程。

区域增长与RANSAC模型结合的机载点云平面分割方法

针对现有的建筑物点云分割数据效率低、抗噪性弱等问题,提出了一种区域增长与RANSAC模型结合的点云平面分割方法,该方法以种子点的曲率、法向量及其邻域点到法平面的欧氏距离为生长约束条件,通过不断扩展种子面提取符合平面模型的初始样本点集,然后采用基于RANSAC平面拟合的稳健参数估计方法估计出高精度的平面参数。试验证明该方法具有可行性。

Exploring the Impact of Alcohol Consumption and Smoking on Primary Open Angle Glaucoma: A Mendelian Randomization Study

Objective: Utilizing Mendelian Randomization, this study employs Single Nucleotide Polymorphisms (SNPs) as instrumental variables to explore the causal relationships between bibulosity, smoking, and Primary Open Angle Glaucoma (POAG). Methods: GWAS data for bibulosity, smoking, and POAG were obtained from the Social Science Genetic Association Consortium website and the IEU OpenGWAS Project website, respectively. Using a P-value threshold of −8, a linkage disequilibrium coefficient (r2) of 0.001, and a linkage disequilibrium region width of 10,000 kb, the data were aggregated, resulting in 6 SNPs for bibulosity and 253 SNPs for smoking. Three regression models, MR-Egger, Weighted Median Estimator (WME), and Random-Effects Inverse-Variance Weighted (IVW) were applied to analyze the causal impact of bibulosity and smoking on POAG. Results: The GWAS data for alcohol consumption and smoking were derived from European populations, while the GWAS data for Primary Open-Angle Glaucoma (POAG) were sourced from East Asian populations, with no gender restrictions. Analysis using three different regression models revealed that neither excessive alcohol consumption nor smoking significantly increased the risk of developing POAG. Specifically, the odds ratios with 95% confidence intervals for the alcohol consumption group were 0.854 (0.597 - 1.221) in MR-Egger regression, 0.922 (0.691 - 1.231) in WME regression, and 0.944 (0.711 - 1.252) in IVW regression. For the smoking group, the odds ratios were 1.146 (0.546 - 2.406) in MR-Egger regression, 0.850 (0.653 - 1.111) in WME regression, and 0.939 (0.780 - 1.131) in IVW regression. Given the significant heterogeneity in the SNPs associated with smoking, the focus was primarily on the results from the IVW regression model. Conclusion: Alcohol consumption and smoking are not significant risk factors for the development of POAG.

Python语言random库经典案例教学

Python是一种计算生态语言,也是开源的语言,具有丰富和强大的类库,语法简洁、清晰明了。随着物联网、大数据、人工智能等技术的兴起,Python位于PYPL全球编程语言排行榜的榜首,成为受人们欢迎的编程语言。主要阐述利用Python的random库解决一些实际问题,既提高学习者的兴趣和积极性,又能提高学习者利用所学知识分析和处理实际问题的能力。

Understanding the educational inequalities in suicide attempts and their mediators:a Mendelian randomisation study

Background Educational inequalities in suicide have become increasingly prominent over the past decade.Elucidating modifiable risk factors that serve as intermediaries in the impact of low educational attainment on suicide has the potential to reduce health disparities.Aims To examine the risk factors that mediate the relationship between educational attainment and suicide attempts and quantify their contributions to the mediation effect.Methods We conducted a two-sample Mendelian randomisation(MR)analysis to estimate the causal effect of educational attainment on suicide attempts,utilising genome-wide association study summary statistics from the Integrative Psychiatric Research(iPSYCH;6024 cases and 44240 controls)and FinnGen(8978 cases and 368299 controls).We systematically evaluated 42 putative mediators within the causal pathway connecting reduced educational attainment to suicide attempts and employed two-step and multivariable MR to quantify the proportion of the mediated effect.Results In the combined analysis of iPSYCH and FinnGen,each standard deviation(SD)decrease in genetically predicted educational attainment(equating to 3.4 years of education)was associated with a 105%higher risk of suicide attempts(odds ratio(OR):2.05;95%confidence interval(Cl):1.81 to 2.31).0f the 42 risk factors analysed,the two-step MR identified five factors that mediated the association between educational attainment and suicide attempts.The respective proportions of mediation were 47%(95%Cl:29%to 66%)for smoking behaviour,36%(95%Cl:0%to 84%)for chronic pain,49%(95%Cl:36%to 61%)for depression,35%(95%Cl:12%to 59%)for anxiety and 26%(95%Cl:18%to 34%)for insomnia.Multivariable MR implicated these five mediators collectively,accounting for 68%(95%Cl:40%to 96%)of the total effect.Conclusions This study identified smoking,chronic pain and mental disorders as primary intervention targets for attenuating suicide risk attributable to lower educational levels in the European population.

Different effects of 24 dietary intakes on gastroesophageal reflux disease: A mendelian randomization

BACKGROUND In observational studies,dietary intakes are associated with gastroesophageal re-flux disease(GERD).AIM To conduct a two-sample mendelian randomization(MR)analysis to determine whether those associations are causal.METHODS To explore the relationship between dietary intake and the risk of GERD,we extracted appropriate single nucleotide polymorphisms from genome-wide asso-ciation study data on 24 dietary intakes.Three methods were adopted for data analysis:Inverse variance weighting,weighted median methods,and MR-Egger's method.The odds ratio(OR)and 95%confidence interval(CI)were used to eva-luate the causal association between dietary intake and GERD.RESULTS Our univariate Mendelian randomization(UVMR)results showed significant evidence that pork intake(OR,2.83;95%CI:1.76-4.55;P=1.84×10–5),beer intake(OR,2.70,95%CI:2.00-3.64;P=6.54×10–11),non-oily fish intake(OR,2.41;95%CI:1.49-3.91;P=3.59×10–4)have a protective effect on GERD.In addition,dried fruit intake(OR,0.37;95%CI:0.27-0.50;6.27×10–11),red wine intake(OR,0.34;95%CI:0.25-0.47;P=1.90×10-11),cheese intake(OR,0.46;95%CI:0.39-0.55;P=3.73×10-19),bread intake(OR,0.72;95%CI:0.56-0.92;P=0.0009)and cereal intake(OR,0.45;95%CI:0.36-0.57;P=2.07×10-11)were negatively associated with the risk of GERD.There was a suggestive asso-ciation for genetically predicted coffee intake(OR per one SD increase,1.22,95%CI:1.03-1.44;P=0.019).Multi-variate Mendelian randomization further confirmed that dried fruit intake,red wine intake,cheese intake,and cereal intake directly affected GERD.In contrast,the impact of pork intake,beer intake,non-oily fish intake,and bread intake on GERD was partly driven by the common risk factors for GERD.However,after adjusting for all four elements,there was no longer a suggestive association between coffee intake and GERD.CONCLUSION This study provides MR evidence to support the causal relationship between a broad range of dietary intake and GERD,providing new insights for the treatment and prevention of GERD.

Dissecting the association between gut microbiota,body mass index and specific depressive symptoms:a mediation Mendelian randomisation study

Background Observational studies highlight the association between gut microbiota(GM)composition and depression;however,evidence for the causal relationship between GM and specific depressive symptoms remains lacking.Aims We aimed to evaluate the causal relationship between GM and specific depressive symptoms as well as the mediating role of body mass index(BMI).Methods We performed a two-sample Mendelian randomisation(MR)analysis using genetic variants associated with GM and specific depressive symptoms from genome-wide association studies.The mediating role of BMI was subsequently explored using mediation analysis via two-step MR.Results MR evidence suggested the Bifidobacterium genus(β=0.03;95%CI-0.05 to-0.02;p<0.001 andβ=0.03;95%CI-0.05 to-0.02;p<0.001)and Actinobacteria phylum(β=-0.04;95%CI-0.06 to-0.02;p<0.001 andβ=-0.03;95%CI-0.05 to-0.03;p=0.001)had protective effects on both anhedonia and depressed mood.The Actinobacteria phylum also had protective effects on appetite changes(β=-0.04;95%CI-0.06 to-0.01;p=0.005),while the FamilyⅪhad an antiprotective effect(β=0.03;95%CI 0.01 to 0.04;p<0.001).The Bifidobacteriaceae family(β=-0.01;95%CI-0.02 to-0.01;p=0.001)and Actinobacteria phylum(β=-0.02;95%CI-0.03 to-0.01;p=0.001)showed protective effects against suicidality.The two-step MR analysis revealed that BMl also acted as a mediating moderator between the Actinobacteria phylum and appetite changes(mediated proportion,34.42%)and that BMI partially mediated the effect of the Bifidobacterium genus(14.14%and 8.05%)and Actinobacteria phylum(13.10%and 8.31%)on both anhedonia and depressed mood.Conclusions These findings suggest a potential therapeutic effect of Actinobacteria and Bifidobacterium on both depression and obesity.Further studies are required to translate these findings into clinical practice.