Windsurfing vs kitesurfing:Injuries at the North Sea over a 2-year period

AIM To analyze all windsurfing and kitesurfing(kiteboarding) injuries presented at our coastal hospital over a 2-year period. METHODS Twenty-five windsurfers(21 male; aged 31 ± 8 years) and 32 kitesurfers(23 male; aged 29 ± 11 years) presented at our hospital during the 2-year study period. Various injury data were recorded,including transport to hospital and treatment. After a median follow-up of 16 mo(range,7-33 mo),18 windsurfers(72%) and 26 kitesurfers(81%) completed questionnaires on the trauma mechanisms,the use of protective gear,time spent on windsurfing or kitesurfing,time to return to sports,additional injuries,and chronic disability. RESULTS Most patients sustained minor injuries but severe injuries also occurred,including vertebral and tibial plateau fractures. The lower extremities were affected the most,followed by the head and cervical spine,the upperextremities,and the trunk. The injury rates were 5.2 per 1000 h of windsurfing and 7.0 per 1000 h of kitesurfing(P = 0.005). The injury severity was the same between groups(P = 1.0). Less than 30% of the study population used protective gear. Kitesurfers had a higher number of injuries,and required transport by ambulance,inpatient hospital stay and operative treatment more often than windsurfers,but these differences were not statistically significant(P > 0.05). The median time to return to windsurfing and kitesurfing was 5 and 4 wk,respectively(P = 0.79). Approximately one-third of the patients in each group experienced chronic symptoms.CONCLUSION Kitesurfing results in a significantly higher injury rate than windsurfing in the same environmental conditions but the severity of the injuries does not differ.

Measurement of associations between mobile calls and mobile-internet surfing

Measuring mobile calls data is an increasingly import issue,which will benefit to the understanding of the behavior of mobile users and assist telecom operators to optimize their business strategies.The existing researches on cell phone data measurement only focus on mobile calls or on mobile-internet surfing and little researches focus on the interactions of behaviors between them.In this paper,some basic factors of the association between mobile calls and mobile-internet surfing are measured.Then first their distributions are compared and the preference of users is quantified.After that experiments on the curve fitting of both the whole and parts of these distributions are done.Through the comparison of the correlation coefficients and Fourier fitting parameters,different behaviors is found between workdays and weekends,as well as Saturdays and Sundays in mobile-call distributions.Besides,the results of our observation show that the mobile-internet traffic does not always monotone increase with the increase of online time,significant changes are observed after 8hours of mobile-internet surfing.

A Surfing Concurrence Transaction Model for Key-Value NoSQL Databases

As more and more application systems related to big data were developed, NoSQL (Not Only SQL) database systems are becoming more and more popular. In order to add transaction features for some NoSQL database systems, many scholars have tried different techniques. Unfortunately, there is a lack of research on Redis’s transaction in the existing literatures. This paper proposes a transaction model for key-value NoSQL databases including Redis to make possible allowing users to access data in the ACID (Atomicity, Consistency, Isolation and Durability) way, and this model is vividly called the surfing concurrence transaction model. The architecture, important features and implementation principle are described in detail. The key algorithms also were given in the form of pseudo program code, and the performance also was evaluated. With the proposed model, the transactions of Key-Value NoSQL databases can be performed in a lock free and MVCC (Multi-Version Concurrency Control) free manner. This is the result of further research on the related topic, which fills the gap ignored by relevant scholars in this field to make a little contribution to the further development of NoSQL technology.

Surfing China’s National Defense

Following the start of its first test run on August 20, 2009, the website www.mod.gov.cn of the Ministry of National Defense (MOD) of the People’s Republic of China has logged more than 2 billion hits, from many countries and regions including China, the United States, the United Kingdom, Japan, Australia and Singapore. China National Defense News reporters recently interviewed Ji Guilin, the website’s Editor in Chief, on its performance and the feedback of netizens.

Application of septal wire surfing technology in retrograde intervention of chronic total occlusion

Background Septal Surfing Technology （SST） is one of the most important techniques for collateral channels （CCs） crossing in retrograde chronic total occlusion （CTO） of percutaneous coronary intervention （PCI）. We ex- amined this technique＇ s usefulness in retrograde CTO-PCI cases. Methods We retrospective analyzed 728 con-secutive CTO-PCI cases from January 2014 to September 2016. One hundred and forty-two patients who had un- dergone retrograde PCIs using septal collateral channels （CCs） were collected. Univariate and multivariate analyses were conducted to identify independent predictors for SST CCs crossing success. Results The CCs crossing success rate was 89.4% during retrograde PCI. Three factors were figured out as independent predictors, includ- ing CCs tortuosity （OR 0.164, 95%CI： 0.041-0.657; P=0.011）, diameter of distal CTO lesion （2.035, 95%CI： 1.011-4.099; P=0.047） and LAD-CTO （OR 0.244, 95%CI：0.067-0.894; P=0.033）. There were complications of CCs injury in 23.2% cases and 2.1% cases had cardiac tamponade without any in-hospital death. Conclusion SST is an effective method in collateral crossing during retrograde CTO-PCI. It has high successful rate regard-less of the Werner Collateral Class of interventional collaterals, especially in invisible collaterals. This technolo- gy is feasible in daily practice of retrograde PCI.

基于改进SURF的图像特征点匹配算法

为了提升图像在三维重建过程中特征点匹配时的准确率,提出了一种基于改进SURF(speeded-up robust features)的图像特征点匹配算法。首先,将SURF的64维度描述符提升至128维度;其次,在SURF算法引入KD-Tree模块,利用BBF(best bin first)最近邻查询机制实现特征点匹配;最后,通过对同一数据集进行旋转、缩小,并利用传统算法和改进SURF算法分别对图像进行特征点匹配实验,验证改进SURF算法的有效性。结果表明:改进SURF算法的特征点匹配正确率达到了89.19%,相较于传统SURF算法提高了17.62个百分点;特征错误匹配数由85减少至31,显著降低了特征点的匹配误差;运行时间由1.956 s缩短至1.647 s,进一步提升了算法的运行速度。改进后的SURF算法具备正确率高、误差小、速度快的特点,可为三维重建特征匹配工作提供重要的参考。

基于改进的SURF算法的机械臂识别定位及抓取研究

针对采用传统SURF算法对机械臂工作区域内的目标进行识别时出现的运行速度较慢、匹配准确度较低等问题,提出一种基于改进的SURF算法的机械臂识别定位及抓取方法。首先,利用传统SURF算法提取目标的尺度不变性特征点;随后,通过rBRIEF描述子与低方差过滤分别对提取特征实施描述及降维,再进行基于Hamming距离的2-NN特征点交叉匹配,并采用RANSAC算法剔除错误匹配对;最后,结合双目立体视觉三维重建获取目标的空间三维坐标,并将机械臂逆运动学求解得到的各个关节驱动角输入控制系统,驱使舵机带动机械臂末端执行器完成对目标的抓取作业。实验结果表明,采用改进的SURF算法,较SIFT、传统SURF算法提高了目标特征点的识别速度与匹配准确度,有效提升了机械臂抓取的实时性及精准性。

基于SURF的遥感图像配准优化算法

针对遥感图像配准中易出现的信息量巨大和误匹配问题,通过改进SURF算法,提出了一种用于遥感图像配准的优化算法。优化算法引入特征点图像熵,通过去除携带信息量不足的误选取特征点,提高了特征点选取以及后续特征点匹配的准确性。在特征点描述阶段,算法实现了描述子降维,并将降维后的特征点描述子与FLANN算法相结合,降低了算法特征点误匹配率,同时减少了因描述子降维而带来的影响。实验表明,该优化算法相较于传统SURF算法,待配准图像特征点选取率下降10.9%,特征点误匹配率下降17.5%,并得到精确的遥感图像配准效果。

基于改进SURF的增强现实图像匹配方法

针对传统增强现实图像匹配算法鲁棒性不强且效率不高的问题,提出一种改进的SURF匹配算法。首先,使用SURF算法进行特征点检测,并通过Haar小波模板确定特征主方向,在得到特征主方向后构建特征描述符;由于传统SURF算法采用高达64维的矩形描述符,导致算法的计算量非常大,并且鲁棒性不强。因此,该文使用DAISY圆形描述符替代原始算法中的矩形描述符,DAISY是三层同心圆结构,每层包含8个采样点,可以得到25个维度的描述符,这种结构使得算法的鲁棒性大大增强并且降低了计算复杂度;接着,使用特征描述符计算欧氏距离进行特征点匹配;最后,对得到的匹配点集使用随机抽样一致(RANSAC)与三角不规则网络(TIN)算法进行优化,剔除误匹配点。实验结果表明,该算法虽然略微增加了时间复杂度,但鲁棒性变得更强,并且算法的效率和匹配精度也大大提高,平均精度达到了95%以上。

基于SURF-OKG特征匹配的三维重建技术

为了解决结构光三维重建中传统立体匹配存在的特征点匹配错误、匹配缺失和匹配重复等问题,本文将SURF算法中高斯滤波改进为自适应中值滤波结合小波变换,并提出了一种基于OKG算法的二次特征匹配方法。该算法首先使用自适应中值滤波结合小波变换算法对图像进行平滑和降噪处理,再进行初步特征点提取和匹配,然后将构建的尺度空间划分成多个网格,在每个网格内使用FAST算法提取尺度空间特征点,使用ORB算子提取左右图像的特征点,用BRIEF描述子对其进行描述,采用K-D树最近邻搜索法限制特征点选取,通过GMS算法剔除误匹配点。最后,将本文SURF-OKG算法与传统特征匹配算法进行对比分析,并对阶梯块进行三维重建来验证本文算法的有效性。实验结果表明:SURF-OKG算法的正确匹配率为92.47%;对阶梯宽度为40 mm,精度为0.02 mm的阶梯块进行三维重建,实验测得阶梯宽度的误差均值为1.312 mm,最大误差值不超过1.72 mm,基本满足结构光三维重建系统的实验要求。

基于无人机的风机叶片智能巡检及缺陷检测

提出并设计风机叶片自动化检测与图像识别方法。通过大疆Mobile SDK与MATLAB联合设计,分割叶片图像缺陷特征,再根据混乱背景利用特征点匹配来识别裂纹和损伤等缺陷,并对缺陷进行分类,从而方便后续输出对叶片质量的分析,实现风力发电机叶片表面缺陷的自动检测功能。通过实例验证了该方法在风力发电机叶片表面缺陷检测中的准确性与稳定性。

基于改进ORB-FLANN算法的工件图像识别方法

针对传统图像识别算法匹配正确率低、运行时间较长等问题,文中提出了基于改进ORB-FLANN(Oriented FAST and Rotated BRIEF-Fast Library for Approximate Nearest Neighbors)的工件图像识别方法。对ORB算法特征描述、图像特征匹配算法进行修改,解决传统图像识别算法在图像存在尺度和旋转变换情况下存在的弊端并降低误匹配率。该方法对ORB算法检测到的特征点采用SURF(Speeded Up Robust Features)算法添加方向信息并完成特征描述,得到旋转尺度不变性的特征点,结合FLANN算法并引入双向匹配策略进行特征点粗匹配,最后利用渐进采样一致算法进一步剔除误匹配点对完成精匹配。实验结果表明,与其他方法相比,改进算法在处理尺度、旋转等变换图像时,匹配正确率分别提高了2.6%~18.8%和29.5%~43.9%,运行时长均在4 s以内,提高了对工件图像的识别效率和精准性。

基于伪Zernike矩与SURF特征的自适应水印算法

针对目前多数图像水印算法水印的嵌入区域固定不变带来的安全性问题,且水印的抗旋转攻击能力弱,提出一种基于伪Zernike矩和SURF的自适应水印算法。首先,利用SURF(Speed Up Robust Features)算法对图像进行特征提取,然后采用RANSAC(Random Sample Consensus)算法筛选出稳定的特征点,根据特征点位置构建合适的水印嵌入区域。最后,采用SWT变换和SVD分解将水印信息嵌入在构造区域内。利用伪Zernike矩估计旋转角度对图像进行旋转校正。实验结果表明,该水印算法可以有效地抵抗旋转攻击,水印的安全性得到提高。

海上舰船目标可见光/红外图像匹配方法

为改善传统SURF算法匹配海上舰船图像存在计算时间长、配准精度低等不足,提出一种改进Canny-SURF-RANSAC算法。针对起伏海浪导致传统Canny算法产生大量非舰船目标边缘的问题,提出改进的Canny算法进行海面舰船边缘检测。通过引入形态学滤波中的开运算和闭运算的复合操作,以及使用Otsu阈值方法进行自适应阈值设置,优化了舰船的边缘连续性并消除了无关噪点。在舰船目标边缘信息的基础上,运用SURF算法提取特征点,进行特征匹配,在传统的RANSAC算法采用动态调整阈值即自适应RANSAC算法消除匹配结果中错误匹配点,提高匹配的准确率。实验证明,文章图像匹配技术匹配算法在同一传感器不同帧中、不同视角出现的同一舰船、可见光/红外传感器采集到的同一舰船目标的复杂场景下,比传统方法具有更快的匹配时间、更高的匹配正确率。完成匹配后,框定相同舰船目标连通域,得到舰船检测结果。

基于改进YOLOv5的双目视觉测距算法研究

针对SURF算法因其较高的计算复杂度和内存需求导致在资源受限的嵌入式系统或移动设备上使用受限的问题,本文融合改进的YOLOv5和SURF算法,提出YOLOv5_mobilenet主干网络构建目标检测模型,并引入了SE注意力机制和特征融合策略,在KITTI数据集上的识别率达到了88.50%,相比于改进前YOLOv5上升了0.7%,参数量下降了81.94%,浮点数运算量下降了86.14%。通过目标检测识别感兴趣区域,对感兴趣区域进行立体匹配并计算视差。实验结果表明,在500张立体图像上运行SURF算法,整幅图像平均视差计算时间为0.574秒,而采用感兴趣区域的SURF算法的平均计算时间仅为0.035秒,计算效率提高了15倍。此外,通过多次实验计算,得出平均误差率为2.23%。

Semantic Segmentation and YOLO Detector over Aerial Vehicle Images

Intelligent vehicle tracking and detection are crucial tasks in the realm of highway management.However,vehicles come in a range of sizes,which is challenging to detect,affecting the traffic monitoring system’s overall accuracy.Deep learning is considered to be an efficient method for object detection in vision-based systems.In this paper,we proposed a vision-based vehicle detection and tracking system based on a You Look Only Once version 5(YOLOv5)detector combined with a segmentation technique.The model consists of six steps.In the first step,all the extracted traffic sequence images are subjected to pre-processing to remove noise and enhance the contrast level of the images.These pre-processed images are segmented by labelling each pixel to extract the uniform regions to aid the detection phase.A single-stage detector YOLOv5 is used to detect and locate vehicles in images.Each detection was exposed to Speeded Up Robust Feature(SURF)feature extraction to track multiple vehicles.Based on this,a unique number is assigned to each vehicle to easily locate them in the succeeding image frames by extracting them using the feature-matching technique.Further,we implemented a Kalman filter to track multiple vehicles.In the end,the vehicle path is estimated by using the centroid points of the rectangular bounding box predicted by the tracking algorithm.The experimental results and comparison reveal that our proposed vehicle detection and tracking system outperformed other state-of-the-art systems.The proposed implemented system provided 94.1%detection precision for Roundabout and 96.1%detection precision for Vehicle Aerial Imaging from Drone(VAID)datasets,respectively.

Investigating the Genetic Bases of Growth Regulation by E2F3 in Dwarf Surf Clams Mulinia lateralis

Bivalve aquaculture plays a crucial role in the aquaculture industry due to the economic value of many bivalve species.Understanding the underlying genetic basis of bivalve growth regulation is essential for enhancing germplasm innovation and ensuring sustainable development of the industry.Though numerous candidate genes have been identified,their functional validation remains challenging.Fortunately,the dwarf surf clam(Mulinia lateralis)serves as a promising model organism for investigating genetic mechanisms underlying growth regulation in bivalves.The GWAS study in the Yesso scallop(Patinopecten yessoensis)has pinpointed the E2F3 gene as a key regulator of growth-related traits.However,the specific role of E2F3 in bivalve growth remains unclear.This study aimed to further confirm the regulatory function of the E2F3 gene in the dwarf surf clam through RNA interference experiments.Our results revealed several genes are associated with individual growth and development,including CTS7,HSP70B2,and PGLYRP3,as well as genes involved in lipid metabolism such as FABP2 and FASN.Functional enrichment analysis indicated that E2F3 primarily modulates critical processes like amino acid and lipid metabolism.These findings suggest that E2F3 likely regulates growth in the dwarf surf clam by influencing amino acid and lipid metabolism.Overall,this study advances our understanding on the function of E2F3 gene in growth regulation in bivalves,providing valuable insights for future research in this field.

Observing eddy dye patches induced by shear instabilities in the surf zone on a plane beach

The effects of surf zone eddy generated by alongshore currents on the deformation and transport of dye are still poorly understood,and related tracer release experiments are lacking.Therefore,a tracer release laboratory experiment was conducted under monochromatic,unidirectional incident waves with a large incident angle(30°)on a plane beach with a 1:100 slope in a large wave basin.A charge-coupled device suspended above the basin recorded the dye patch image.The evolution of eddy dye patch was observed and the transport and diffusion were analyzed based on the collected images.Subsequently,a linear instability numerical model was adopted to calculate the perturbation velocity field at the initial stage.The observation and image processing results show that surf zone eddy patches occurred and were separated from the original dye patches.Our numerical analysis results demonstrate that the structure of the perturbation velocity field is consistent with the experimental observations,and that the ejection of eddy patches shoreward or offshore may be ascribed to the double vortex.

大尺寸圆形零部件尺寸高精度视觉测量方法

圆环类零部件,在进行环形光源和条形光源照射方式下的圆环直径尺寸测量时,通常存在零部件倒角特征成像出现宽边缘、受厚度影响导致圆环边界呈现阴影、表面纹理及擦痕影响图像处理效率、相机视野不足无法单次采集大尺寸圆形零部件高分辨率全景图像等问题。本文提出一种基于改进SURF图像拼接的圆形零部件尺寸测量方法,通过光照优化、图像拼接和亚像素边缘检测实现零部件尺寸的高精度测量。首先,分别提出条形光源45°布置、环形光源垂直向下和条形光源45°组合布置的照射方式,用以消除在零部件成像中存在的宽边缘、阴影、纹理及擦痕等对尺寸测量的影响。其次,改进SURF特征匹配法,定位拼接图像重叠区域进行特征点粗匹配。接着,提出RANSAC算法对特征点进行精匹配,改进图像配准法,等尺寸扩充零部件拼接图像,补充缺失背景区域。然后,提出加权平均融合算法对拼接图像进行平滑处理,获取高分辨率零部件全景图像。最后,改进最小二乘法拟合圆方法,以实现图像中边缘圆环的拟合,通过像素尺寸转化获取零部件实际尺寸值。实验结果表明,该方法相比传统视觉测量方法精度更高,与三坐标测量仪测量参考值相对误差在0.0444%以内。