地下矿生产日报CAD动态监视与管理系统

本文利用ＣＡＤ技术建立了地下矿生产日报动态监视系统。该系统采用ＣＡＤ技术形象直观地监视地下矿生产动态；应用多级模糊层次综合评价模型和灰色预测模型及时利用生产日报信息，迅速评价当天生产总体效果和准确预测未来生产发展状况。

基于CAD技术在煤矿测量中的技术分析

在中国经济快速发展的今天,煤炭需求增加,中国煤矿得到良好的发展机会。煤矿井下测量应用技术,不仅可以提高测量精度、提高工作效率,而且可以保障煤矿的采掘工作顺利开展。通过分析煤矿井下贯通测量中使用的新技术,针对测量中出现的相关问题进行了探讨。

关于CAD在结构专业的应用

随着高科技的发展,CAD及PKPM系列软件给工程设计领域带来了一场新的技术革命,也给设计人员带来了新的挑战。阐述了CAD在结构专业的应用,并就如何熟练掌握结构CAD提出了若干建议。

The State-of-the-Art Review on Applications of Intrusive Sensing,Image Processing Techniques,and Machine Learning Methods in Pavement Monitoring and Analysis

In modern transportation,pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians.Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users.Therefore,monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance,which in turn ensures public transportation safety.Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions.Advanced technologies can be employed for the collection and analysis of such data,including various intrusive sensing techniques,image processing techniques,and machine learning methods.This review summarizes the state-ofthe-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches.

Machine Learning-based Identification of Contaminated Images in Light Curve Data Preprocessing

Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal.Analyzing light curves to determine attitude is the most commonly used method.In photometric observations,outliers may exist in the obtained light curves due to various reasons.Therefore,preprocessing is required to remove these outliers to obtain high quality light curves.Through statistical analysis,the reasons leading to outliers can be categorized into two main types:first,the brightness of the object significantly increases due to the passage of a star nearby,referred to as“stellar contamination,”and second,the brightness markedly decreases due to cloudy cover,referred to as“cloudy contamination.”The traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive.However,we propose the utilization of machine learning methods as a substitute.Convolutional Neural Networks and SVMs are employed to identify cases of stellar contamination and cloudy contamination,achieving F1 scores of 1.00 and 0.98 on a test set,respectively.We also explore other machine learning methods such as ResNet-18 and Light Gradient Boosting Machine,then conduct comparative analyses of the results.

Lossless Compression Method for the Magnetic and Helioseismic Imager(MHI)Payload

The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.

Wavelet Analysis of Space Solar Telescope Images

The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.

Example-based super-resolution for single-image analysis from the Chang'e-1 Mission

Due to the low spatial resolution of images taken from the Chang＇e-1 （CE-I） orbiter, the details of the lunar surface are blurred and lost. Considering the limited spatial resolution of image data obtained by a CCD camera on CE-1, an example-based super-resolution （SR） algorithm is employed to obtain high- resolution （HR） images. SR reconstruction is important for the application of image data to increase the resolution of images. In this article, a novel example-based algorithm is proposed to implement SR reconstruction by single-image analysis, and the computational cost is reduced compared to other example-based SR methods. The results show that this method can enhance the resolution of images using SR and recover detailed information about the lunar surface. Thus it can be used for surveying HR terrain and geological features. Moreover, the algorithm is significant for the HR processing of remotely sensed images obtained by other imaging systems.

Extraction and Analysis of Coronal High-temperature Components Based on Outlier Detection

The extraction of high-temperature regions in active regions(ARs)is an important means to help understand the mechanism of coronal heating.The important observational means of high-temperature radiation in ARs is the main emission line of Fe XVⅢin the 94?of the Atmospheric Imaging Assembly.However,the diagnostic algorithms for Fe XVⅢ,including the differential emission measure(DEM)and linear diagnostics proposed by Del based on the DEM,have been greatly limited for a long time,and the results obtained are different from the predictions.In this paper,we use the outlier detection method to establish the nonlinear correlation between 94?and 171,193,211?based on the former researches by others.A neural network based on 171,193,211?is constructed to replace the low-temperature emission lines in the ARs of 94?.The predicted results are regarded as the low-temperature components of 94?,and then the predicted results are subtracted from 94?to obtain the outlier component of 94?,or Fe XVⅢ.Then,the outlier components obtained by neural network are compared with the Fe XVⅢobtained by DEM and Del's method,and a high similarity is found,which proves the reliability of neural network to obtain the high-temperature components of ARs,but there are still many differences.In order to analyze the differences between the Fe XVⅢobtained by the three methods,we subtract the Fe XVⅢobtained by the DEM and Del's method from the Fe XVⅢobtained by the neural network to obtain the residual value,and compare it with the results of Fe XIV in the temperature range of 6.1-6.45 MK.It is found that there is a great similarity,which also shows that the Fe XVⅢobtained by DEM and Del's method still has a large low-temperature component dominated by Fe XIV,and the Fe XVⅢobtained by neural network is relatively pure.

Transverse Velocity Field Measurements in High-resolution Solar Images Based on Deep Learning

To address the problem of the low accuracy of transverse velocity field measurements for small targets in highresolution solar images,we proposed a novel velocity field measurement method for high-resolution solar images based on PWCNet.This method transforms the transverse velocity field measurements into an optical flow field prediction problem.We evaluated the performance of the proposed method using the Hαand TiO data sets obtained from New Vacuum Solar Telescope observations.The experimental results show that our method effectively predicts the optical flow of small targets in images compared with several typical machine-and deeplearning methods.On the Hαdata set,the proposed method improves the image structure similarity from 0.9182 to0.9587 and reduces the mean of residuals from 24.9931 to 15.2818;on the TiO data set,the proposed method improves the image structure similarity from 0.9289 to 0.9628 and reduces the mean of residuals from 25.9908 to17.0194.The optical flow predicted using the proposed method can provide accurate data for the atmospheric motion information of solar images.The code implementing the proposed method is available on https://github.com/lygmsy123/transverse-velocity-field-measurement.

Assessing the Pilling of Fabric by Image Analysis

In this paper, firstly, the image of pilling was pre - pro-cessed by image analysis technique, which based on the image’s gray- scale statistical characters or mathemati-cal morphology. Then, the pilling of fabric was assessed synthetically by the size of pilling A,number of pilling N and morphology of pitting S. At the end, we tested the practicability of this method by testing knitgoods as a sample, and the result was satisfiable.

应用于人脑胶质淋巴系统的磁共振成像技术研究进展

胶质淋巴系统是神经科学领域近期发现的解剖结构,具有调节间质液运动、废物清除和潜在的大脑免疫等功能,在中枢神经系统的生理及病理中发挥重要作用。随着影像学技术的发展,越来越多的磁共振成像(MRI)技术被应用于人脑胶质淋巴系统的研究,目前常用的MRI技术有动态对比增强磁共振成像技术、沿血管周围间隙扩散张量成像分析技术及新型多模态超快速磁共振技术等,本文就这些技术在脑胶质淋巴系统的应用现状进行汇总综述,以期为胶质淋巴系统的影像学研究提供参考。

西安汉墓出土铜铁箭镞的中子成像分析

汉代箭镞有多种类型,制作工艺也各不相同。本文采用中子成像和超景深显微照相技术,对西安雅荷中央广场M36西汉墓葬出土的铁铤铜镞和铁镞进行无损分析研究。结果表明,铜镞与铁铤采用铸接方式相连,铁铤外部推测先涂刷胶结物,后用竹木片和细线包裹捆扎,并涂刷黑漆。铁镞与铁铤为分铸后机械连接,连接部位有竹木材料填充。铜镞保存较好,铜腐蚀物分布于镞外表面和镞内铸造孔洞周围。铁镞整体和铜镞中铁铤均腐蚀严重,其中3个箭镞几乎无铁基体残留。本文为中国先进研究堆(CARR)中子成像装置在文物领域的初步尝试,为探明箭镞内部结构和腐蚀特征,首次提供了影像学依据,有助于文物价值的认知和保护修复措施的制定,并对中子技术在文物领域的应用研究具有借鉴意义。

白癜风皮肤影像学诊断研究进展

白癜风是一种慢性、获得性自身免疫性、色素减退性皮肤病,大多数情况下可以通过临床确诊。遇到难以辨认的白癜风时可能还需要皮肤活检这种有创方式进行病理组织学诊断。随着近年来皮肤影像学的发展,目前已有多种倍受医生和患者青睐的设备可以实现无创检查来确诊白癜风。本文归纳总结了数码摄影、伍德灯、皮肤镜、反射式共聚焦显微镜、计算机辅助成像分析等无创诊断技术在白癜风中的应用与发展现状。

三维可视化技术辅助肝细胞癌消融治疗有效性及安全性的Meta分析

目的系统性评价三维可视化技术辅助肝细胞癌消融治疗的有效性和安全性。方法本研究根据PRISMA指南完成,PROSPERO注册号:CRD42023488398。计算机检索PubMed、Embase、Web of Science、Cochrane Library、中国知网数据库、万方数据库、维普数据库和中国生物医学文献数据库中公开发表的有关三维可视化技术辅助肝细胞癌消融治疗的所有中、英文文献,检索时间为自建库至2023年3月。对纳入的研究进行质量评价和数据提取后,采用RevMan 5.4软件进行Meta分析。结果最终纳入11篇文献,共972例患者,其中447例采用三维可视化技术辅助消融(3D组),525例采用常规二维影像技术辅助消融(2D组)。Meta分析结果显示,3D组首次治疗成功率(OR=5.43,95%CI:2.64~11.18,P<0.001)、技术有效率(OR=6.15,95%CI:3.23~11.70,P<0.001)、完全消融率(OR=2.50,95%CI:1.08~5.78,P=0.03)均显著高于2D组;在安全性方面,严重并发症发生率(OR=0.45,95%CI:0.24~0.87,P=0.02)、局部复发率(OR=0.35,95%CI:0.17~0.72,P=0.004)和局部肿瘤进展率(OR=0.29,95%CI:0.16~0.50,P<0.001)均明显低于2D组;两组的轻度并发症发生率比较,差异无统计学意义(P>0.05)。结论三维可视化技术辅助肝细胞癌消融治疗安全可行,可以提高消融率,并降低严重并发症发生率、局部复发率及局部肿瘤进展率,在临床中有重要应用价值。

联合光度立体视觉和图像校正的磨粒三维形貌重建

分析铁谱技术在机械装备磨损状态检测中发挥了重要作用,但其仅能提供磨粒二维图像,导致磨粒形貌信息不足。为实现磨粒三维形貌的精确重建,联合光度立体视觉和图像校正,为精确重建磨粒的三维形貌,联合光度立体视觉和图像。该方法首先采用大津阈值法由全光源图像识别磨粒与背景区域;然后为消除LED发光强度差异对磨粒形貌重建的影响,结合平面形状和朗伯反射模型确定背景区域的理想成像亮度,并校正各光度图像序列的亮度;最后根据光度立体视觉方法,由校正后光度图像序列重建磨粒的三维形貌。以不同类型的磨粒为测试样本,将所提出的方法的重建结果与激光共聚焦显微镜的测量结果进行对比。结果表明:重建磨粒的形貌参数误差小于15%,表明提出的方法能够精确重建磨粒的三维形貌。

复杂网络分析技术在阿尔兹海默症患者脑结构和功能影像中的应用进展

对复杂网络分析技术在阿尔兹海默症(AD)脑影像研究中的应用进展进行综述,总结分析该技术在揭示AD患者脑结构和功能异常等方面的研究成果,并探讨其在AD早期诊断和病程监测中的潜在价值,以及当前研究的局限性和挑战,并总结未来研究方向,包括新网络分析技术开发、多模态影像数据整合及机器学习技术等。

Analysis of the geomorphology surrounding the Chang'e-3 landing site

Chang＇e-3 （CE-3） landed on the Mare Imbrium basin in the east part of Sinus Iridum （19.51°W, 44.12°N）, which was China＇s first soft landing on the Moon and it started collecting data on the lunar surface environment. To better understand the environment of this region, this paper utilizes the available high-resolution topography data, image data and geological data to carry out a detailed analysis and research on the area surrounding the landing site （Sinus Iridum and 45 km×70 km of the landing area） as well as on the topography, landform, geology and lunar dust of the area surrounding the landing site. A general topographic analysis of the surrounding area is based on a digital elevation model and digital elevation model data acquired by Chang＇e-2 that have high resolution; the geology analysis is based on lunar geological data published by USGS; the study on topographic factors and distribution of craters and rocks in the surrounding area covering 4km^4km or even smaller is based on images from the CE-3 landing camera and images from the topographic camera; an analysis is done of the effect of the CE-3 engine plume on the lunar surface by comparing images before and after the landing using data from the landing camera. A comprehensive analysis of the results shows that the landing site and its surrounding area are identified as typical lunar mare with flat topography. They are suitable for maneuvers by the rover, and are rich in geological phenomena and scientific targets, making it an ideal site for exploration.

Reconstructing the landing trajectory of the CE-3 lunar probe by using images from the landing camera

An accurate determination of the landing trajectory of Chang＇e-3 （CE-3） is significant for verifying orbital control strategy, optimizing orbital planning, accu- rately determining the landing site of CE-3 and analyzing the geological background of the landing site. Due to complexities involved in the landing process, there are some differences between the planned trajectory and the actual trajectory of CE-3. The land- ing camera on CE-3 recorded a sequence of the landing process with a frequency of 10 frames per second. These images recorded by the landing camera and high-resolution images of the lunar surface are utilized to calculate the position of the probe, so as to reconstruct its precise trajectory. This paper proposes using the method of trajectory reconstruction by Single Image Space Resection to make a detailed study of the hov- ering stage at a height of 100 m above the lunar surface. Analysis of the data shows that the closer CE-3 came to the lunar surface, the higher the spatial resolution of im- ages that were acquired became, and the more accurately the horizontal and vertical position of CE-3 could be determined. The horizontal and vertical accuracies were 7.09 m and 4.27 m respectively during the hovering stage at a height of 100.02 m. The reconstructed trajectory can reflect the change in CE-3＇s position during the powered descent process. A slight movement in CE-3 during the hovering stage is also clearly demonstrated. These results will provide a basis for analysis of orbit control strategy, and it will be conducive to adjustment and optimization of orbit control strategy in follow-up missions.