Coverage of Femoral Head at Weight-Bearing Interface of the Hip Joint in Children: An MRI Analysis

Objective: To analyze the features of coverage of femoral head at weight-bearing interface of the hip joints in children. Material and Methods: MRI scans of the hips were performed in 95 normal children aged from 1 to 8 years. Radial scans of the hip joints were performed using FFE sequence. Review the morphological features of weight-bearing interface of the acetabulum and the femoral head. Total covering angle (TCA), acetabular covering angle (ACA) and labral covering angle (LCA) were measured, inter-group comparison and correlation analysis were done. Result: The acetabulum and the femoral head had congruent articulating surface at each weight-bearing position. There was no statistical TCA difference at each position. Average ACA increased, while average LCA decreased from anterior to posterior. TCA correlated with LCA, ACA negatively correlated with LCA. Conclusion: TCA is a good index in indicating stability of the hip joint. Cartilage ossifies slower at posterior than anterior positions. Cartilage acetabulum and the labrum serve as complementary structures that contribute in total stabilizing of the hip joint in development.

Multi-class classification of pathological myopia based on fundus photography

Pathological myopia(PM)is a severe ocular disease leading to blindness.As a traditional noninvasive diagnostic method,fundus color photography(FCP)is widely used in detecting PM due to its highfidelity and precision.However,manual examination of fundus photographs for PM is time-consuming and prone to high error rates.Existing automated detection technologies have yet to study the detailed classification in diagnosing different stages of PM lesions.In this paper,we proposed an intelligent system which utilized Resnet101 technology to multi-categorically diagnose PM by classifying FCPs with different stages of lesions.The system subdivided different stages of PM into eight subcategories,aiming to enhance the precision and efficiency of the diagnostic process.It achieved an average accuracy rate of 98.86%in detection of PM,with an area under the curve(AUC)of 98.96%.For the eight subcategories of PM,the detection accuracy reached 99.63%,with an AUC of 99.98%.Compared with other widely used multi-class models such as VGG16,Vision Transformer(VIT),EfficientNet,this system demonstrates higher accuracy and AUC.This artificial intelligence system is designed to be easily integrated into existing clinical diagnostic tools,providing an efficient solution for large-scale PM screening.

Warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography

High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.

A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

Recently,there has been a notable surge of interest in scientific research regarding spectral images.The potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable attention.One encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image classification.As a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent beneficiaries.This paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and vegetables.By meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical use.Additionally,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural context.The findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in agriculture.Nevertheless,we also shed light on the various issues and limitations of working with spectral images.This comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

光照不均匀条件下无人机航拍低照度图像增强方法

增强图像时高低频参数未增强,没有更好地保留图像的细节和平衡图像的亮度,因此,提出一种光照不均匀条件下无人机航拍低照度图像增强方法。首先通过高斯滤波预处理无人机航拍图像,实现无人机航拍图像中的噪声抑制,将预处理后的图像通过小波分解得到图像的高频参数和低频参数,分别通过双边滤波算法、软阈值方法和直方图对图像的低频参数和高频参数进行增强,采用小波重构对增强后的图像高频参数和低频参数进行重构,得到增强后的无人机航拍图像。通过实验验证,该方法能够实现一种效果较好的图像增强,在原始图像基础上,通过文中方法增强原始亮度8.14%、对比度提高了37.90%以及清晰度增加了31.01%,使得图像的整体质量得到了显著提升,为后续的图像分析、处理提供了更加准确、丰富的信息。

无人机倾斜摄影测量技术在土地整理中的应用分析

无人机倾斜摄影测量技术可以实现自动快速获取各种复杂的地形图和高程特征点,进而快速完成土方量计算。本文以某区域为例,使用大疆精灵四RTK无人机进行“井”字形飞行获取倾斜摄影数据,利用Context Capture建模软件对数据进行处理,得到三维模型和正射影像数据,在EPS软件中利用三维模型等数据进行土方量计算,快速得到土方量计算结果。以RTK实测数据为真值,检验无人机倾斜摄影测量土方量计算结果的可靠性和准确性。两种测量方法计算的填方量相对误差2.7%、挖方量相对误差7.8%,小于10%的限差范围,均符合土方工程规范要求。以上结果表明,利用无人机倾斜摄影计算土方量,其结果满足土方工程规范要求,且工作效率高、成本低,可为相关土地整理项目提供技术参考。

Investigating Jet Appearance in Different Background Lights with High-Speed Frame Photography

Shaped charge jet formation process is studied under the conditions of different background lights by means of high speed frame photography. In order to shoot true jet appearance, the glass tube in which jet moves is vacuumized. The experiment results show that observing jet appearance with the double reflecting mirrors system is feasible as long as the vacuum of the glass tube can meet the requirement of experiment.

水下管口附近脉动气泡溃灭及射流特性实验和数值研究

通过实验和数值方法研究水下管口附近脉动气泡溃灭及射流特性.在实验方面,采用电火花放电技术产生厘米级脉动气泡,并利用高速摄影捕捉气泡的瞬态动力学行为;在数值方面,采用基于势流理论的边界积分方法模拟气泡与管壁的耦合作用.实验发现,脉动气泡在管口附近溃灭过程中会产生指向管内的射流,进而威胁水中管道设备的结构安全,数值模拟结果和实验现象吻合良好.通过对气泡距管口距离与管口半径之比γ和气泡的最大半径与管口半径之比λ两个无量纲参数进行系统研究发现:当γ≤1.5时,气泡溃灭阶段只会产生指向管内的射流,当γ>1.5时,气泡产生指向管内射流的趋势随λ的增加而增加;总体而言,气泡产生向下射流的速度随λ的增加而增加,随γ的增大先增大后减小.当γ<0时,射流速度随λ和γ的变化很小,但射流宽度随两者的增加而增加;当γ>0时,射流速度随γ的增大先增大后减小.研究结论为水下管口附近气泡溃灭的动力学行为提供了重要参考.

综合交通枢纽工程智能建造关键技术研究与应用

北京城市副中心站工程体量巨大,有6个施工难点,施工质量和施工进度不易控制,施工技术难度和智能建造水平要求高,智能建造关键技术的研发与应用必要性强。因此,本研究以北京城市副中心站综合交通枢纽工程为例,探讨BIM技术、物联网技术、倾斜摄影技术及建筑机器人技术在实际工程项目中的研究与应用,可为同类工程的施工和管理提供经验,为传统建筑业数字化与智能化转型升级提供参考。

基于倾斜摄影的高速公路路面平整度检测方法

针对传统路面平整度检测低效率、整体评价水平差、高成本的的缺点,本文基于无人机倾斜摄影测量技术提出一种高效率、高精度、低成本的新型公路工程路面平整度检测方法,该检测方法是借助LSV图新软件将航拍构建出的倾斜实景模型进行高程提取,利用虚拟3 m直尺包络线法,得出测量路面的最大深度值,以标准偏差来反映路面平整度。通过对乌玛高速2 km试验段的验证,发现基于倾斜摄影技术的高速公路路面平整度检测方法,在检测精度、成本等方面与传统路面平整度检测相比有较大的优势,为后期进一步研究公路工程路面平整度研究提供参考。

基于手机拍照结合Image J软件对干辣椒外观品质的分级研究

干辣椒外观形状和色泽是其品质分类的重要指标。目前GB 10465—1989《辣椒干》中对干辣椒外观形状和色泽的检测方式还停留在人工检测阶段,通常受到主观感知、误差、视觉生理等多种因素影响,未形成科学标准化的检测方法。该研究利用手机拍照对干辣椒获取图像,通过Image J软件进行图像处理,提出了一种便捷、快速、准确的干辣椒外观形状相关特征量的测定方法。与游标卡尺法、剪纸法等人工测量相比,该方法更方便快速,可用于干辣椒的长度、宽度、面积等表型指标的测量。同时,通过构建红绿蓝(RGB)色彩模型获得干辣椒的外观颜色特征参数,色泽分选采用R/(G+B)比率为分级依据,结合干辣椒宽长比和面积可以将干辣椒分为优质、合格、不合格3个等级。

空化水射流研究方法综述

鉴于空化水射流技术的重要性,对空化水射流的产生和作用机理进行了分析,并从空化水射流的流场观测分析、冲蚀作用测量、数值计算仿真三个方面对近年来空化水射流技术研究过程中采用的试验和数值计算研究方法进行了综述,归纳研究热点为设计喷嘴结构、拓展观测和测量实验方法、优化数值计算方法,并从提高空化水射流观察和测量能力和运用人工智能技术优化数值计算方法等方面提出展望,为空化水射流技术的研究和应用提供参考。

Problems and improvement strategies of photography education in Colleges and Universities

In recent years, with the development of social economy, college photography education career has been developing rapidly, but at the same time, some problems have appeared. In the construction of photography specialty, a series of problems, such as unreasonable course arrangement, outdated hardware facilities and imperfect teaching software system, are hindering the de-velopment of photography education in universities. Therefore, college educators should seriously sum up the problems existing in college photography education, and carry out photography teaching reasonably and scientifically.

倾斜摄影技术在不动产权籍测量中的应用

为了提升不动产权籍测量的精度与效率,本文介绍了倾斜摄影技术在特定研究区域的应用。内容涵盖无人机倾斜摄影测量的外业数据采集、内业数据处理、数据质量检查等环节,并详细分析了该技术在测量中的应用效果。作者认为,倾斜摄影技术能够全面捕捉地物信息,有效减少外业工作量。研究结果表明,倾斜摄影技术在不动产权籍测量中具有较高的精度和显著的效率优势,为不动产管理提供了有力的技术支持。

On the Improvement Method of Photography Practice Teaching

Photography teaching is different from general culture teaching.There are obvious differences in teaching methods and teachers' teaching styles.To this end,photography teaching should be innovative,really interested in students,love the photography course,and put photography knowledge into practice.At present,some photography teachers have some problems in the way of explai-ning photography knowledge,which makes it difficult for students to really grasp the practical knowledge of photography,and is not conducive to arousing students' interest in learning. The reason is that photography teachers do not attach importance to practical teaching.

基于线性特征边界线的实景三维动态更新关键技术研究

实景三维中国建设是落实数字中国、平安中国、数字经济战略的重要举措,是新时期国家重要新型基础设施,是服务生态文明建设和经济社会发展的基础支撑。“十四五”以来,各地已经陆续开展了一定规模的实景三维建设项目,积累了不同尺度的实景三维底板数据。如何充分利用已有建设成果,且持续保障实景三维数据的时效性、可用性,已经成为下一个亟需解决的问题。文章针对实景三维数据的场景特征属性,提出一种线性特征边界线的实景三维动态更新和场景融合的方案。基于原有场景数据,将目标更新区域最邻近线性特征边界线作为实际更新范围,对其进行切割、拼接、调色、融合等处理,实现多期实景三维数据的无缝融合。

叙事的变迁:喜龙仁摄影对近代中国园林研究的形塑

[目的]摄影术作为中国园林记录的新方法,对园林研究影响至深,但对二者交互关系的研究较少,摄影作为一种新的理解和观看园林的方式,探究摄影驱动园林研究发生转向的影响机制具有重要意义。[方法]以喜龙仁的中国园林摄影图像为研究对象,从两条路径展开研究:1)以摄影技术、摄影图像为切入点,进行摄影图像影调阈值分析,以显现喜龙仁摄影的特殊性;2)基于喜龙仁的研究经历和研究文本展开比对研究,探究图像技术对园林记忆和园林理解的反向形塑。[结果]通过分析喜仁龙的中国园林摄影图像,发现喜龙仁在拍摄过程中通过运用大画幅相机、中焦距镜头,以及与区域曝光法(zone system)类似的技术理念,增加了图像影调的密度,对细节进行了深描,并对空间进行了压缩。[结论]喜龙仁巧妙地解决了摄影术受技术条件制约的问题,这也是其作品区别于早期常见园林摄影,成为价值卓越的艺术作品的原因。园林摄影图像具有强大的叙事能力,这种叙事能力反向影响了园林研究的视角——多重细节叠加而空间压缩的视角、空间主角与空间叙事转化的视角,并潜移默化地影响了园林研究的走向。这种影响与西方空间研究杂糅,形成了极为常见的园林研究范式。

无人机倾斜摄影在农村不动产测量中的应用

为了提升农村不动产测量的精度与效率,本文通过介绍无人机倾斜摄影技术在农村测区的应用,详细阐述了测区基本情况、无人飞行倾斜摄影测量的技术方案与参数设定、像控点的科学布置与测量、内业数据处理流程以及数字线划图的制作方法。通过对测量结果的深入分析,本文提出了无人机倾斜摄影技术在农村不动产测量中的优势与改进建议。研究结果表明,该技术能够显著提高测量数据的准确性和完整性,为农村不动产管理提供了强有力的技术支持,展现了其在现代测绘领域的广阔应用前景。

无人机倾斜摄影在实景三维模型构建中的应用研究

为了探索无人机倾斜摄影技术在实景三维模型构建中的高效应用,本文通过介绍研究区概况、无人机数据采集的详细流程(包括布置像控点、设计倾斜环绕航线与数据采集)、图像预处理的关键步骤(图像修复与匀光处理),以及实景三维模型的建立过程,深入分析了该技术在实际应用中的技术细节与优势。研究结果表明,无人机倾斜摄影技术能够显著提升三维模型构建的精度与效率,为城市规划、灾害评估、环境监测等领域提供了更为精准、全面的空间信息支持,展现出广阔的应用前景。

无人机航向对倾斜摄影测量精度影响研究

无人机倾斜摄影采集过程中,由于建筑物高低不一和地形复杂的原因,导致部分建筑物结构和植被未能采集到,例如,房屋的边缘角和被植被覆盖的地面细节,致使最后建出的模型出现纹理缺失和模型空洞等问题。针对上述问题,本文研究无人机不同航向角飞行采集数据对三维模型质量的影响,基于垂直交叉和对角线飞行路径的无人机航向规划,通过实际案例,探索其对三维模型纹理和几何精度的影响。研究结果表明,垂直航向角较对角线航向角,实景三维纹理细节更清晰,效果更好。