NEW SAR IMAGE INTERPRETATION METHOD OF AIRCRAFT BASED ON JOINT TIME-FREQUENCY ANALYSIS

With the continuous improvement of Synthetic Aperture Radar(SAR) resolution, interpreting the small targets like aircraft in SAR images becomes possible and turn out to be a hot spot in SAR application research. However, due to the complexity of SAR imaging mechanism, interpreting targets in SAR images is a tough problem. This paper presents a new aircraft interpretation method based on the joint time-frequency analysis and multi-dimensional contrasting of basic structures. Moreover, SAR data acquisition experiment is designed for interpreting the aircraft. Analyzing the experiment data with our method, the result shows that the proposed method largely makes use of the SAR data information. The reasonable results can provide some auxiliary support for the SAR images manual interpretation.

Clinical application of improved 2D computer-assisted fluoroscopic navigation through simulating a 3D vertebrae image to guide pedicle screw internal fixation

Objective To study the effect of using improved 2D computer-assisted fluoroscopic navigation through simulating 3D vertebrae image to guide pedicle screw internal fixation.Methods Posterior pedicle screw internal fixation,distraction

Image interpretation of weak-coupling N-mer adsorbate's STM system

Up to now, there have been many indistinctive points in the image interpretation of scanning tunnelhng microscopy (STM) system, and the problems have attracted almost all STM scientists’ attention. In 1992, Kenkre proposed the new programme which describes the behaviour of the electrons moving in the STM tunnelling by the method of exciton dynamics, and the programme not only breaks through the restrictions of Tersoff-Hamann theory, but also can be applied conveniently to discussing the effects of the tip structure, adsorbate structure, substrate structure, temperature, tunneling voltage, and the degree of coherence of elec-

Image interpretation: mining the visible and syntactic correlation of annotated words

Automatic web image annotation is a practical and effective way for both web image retrieval and image understanding. However, current annotation techniques make no further investigation of the statement-level syntactic correlation among the annotated words, therefore making it very difficult to render natural language interpretation for images such as "pandas eat bamboo". In this paper, we propose an approach to interpret image semantics through mining the visible and textual information hidden in images. This approach mainly consists of two parts: first the annotated words of target images are ranked according to two factors, namely the visual correlation and the pairwise co-occurrence; then the statement-level syntactic correlation among annotated words is explored and natural language interpretation for the target image is obtained. Experiments conducted on real-world web images show the effectiveness of the proposed approach.

Optimized Non-hyperbolic Stack Imaging Based on Interpretation Model

In complex media, especially for seismic prospecting in deep layers in East China and in the mountainous area in West China, due to the complex geological condition, the common-mid-point （CMP） gather of deep reflection event is neither hyperbolic, nor any simple function. If traditional normal move-out （NMO） and stack imaging technology are still used, it is difficult to get a clear stack image. Based on previous techniques on non-hyperbolic stack, it is thought in this paper that no matter how complex the geological condition is, in order to get an optimized stack image, the stack should be non time move-out stack, and any stacking method limited to some kind of curve will be restricted to application conditions. In order to overcome the above-mentioned limit, a new method called optimized non-hyperbolic stack imaging based on interpretation model is presented in this paper. Based on CMP/CRP （Common-Reflection-Point） gather after NMO or pre-stack migration, this method uses the interpretation model of reflectors as constraint, and takes comparability as a distinguishing criterion, and finally forms a residual move-out correction for the gather of constrained model. Numerical simulation indicates that this method could overcome the non hyperbolic problem and get fine stack image.

The Only Possible Mirror Image of Interpreting by Means of Understanding in Modem Westem Philosophy

Interpreting is one of the studies that is in the phase of its theoretical bottleneck. The difficulty comes from the lack of a possible holistic understanding of the phenomenon of interpreting, not to mention the mirror image of interpreting. Different linguistic studies could do nothing since nowadays their respective studies are mostly suffering their own research bottlenecks. Furthermore, it is impossible for individual linguistic studies to elaborate on the complicated interpreting practice. The only possible mirror is Modem Western Philosophy, which can present the image of interpreting. Such a mirror image is by no means possible without the full-fledged development of language study, and in particular, the uncovering of human understanding, in Modem Western Philosophy.

3-D Seismic Imaging and Morpho-tectonical Interpretation of Saucerlike Dykes of the Tarim Flood Basalt Province, NW China

The detailed structures of the plumbing system of the early Permian Tarim flood basalt were investigated by 3-D seismic imaging.The images show that the Tarim flood basalt mainly erupted from central volcanoes distributed

A comparative study of the morphometry of sperm head components in cattle, sheep, and pigs with a computer-assisted fluorescence method

The aim of this study was to compare the sperm nuclear and acrosomal morphometry of three species of domestic artiodactyls; cattle （Bos taurus）, sheep （Ovis aries）, and pigs （Sus scrofa）. Semen smears of twenty ejaculates from each species were fixed and labeled with a propidium iodide-Pisum sativum agglutinin （PI/PSA） combination. Digital images of the sperm nucleus, acrosome, and whole sperm head were captured and analyzed. The use of the PI/PSA combination and CASA-Morph fluorescence-based method allowed the capture, morphometric analysis, and differentiation of most sperm nuclei, acrosomes and whole heads, and the assessment of acrosomal integrity with a high precision in the three species studied. For the size of the head and nuclear area, the relationship between the three species may be summarized as bull 〉 ram 〉 boar. However, for the other morphometric parameters （length, width, and perimeter）, there were differences in the relationships between species for sperm nuclei and whole sperm heads. Bull sperm acrosomes were clearly smaller than those in the other species studied and covered a smaller proportion of the sperm head. The acrosomal morphology, small in the bull, large and broad in the sheep, and large, long, and with a pronounced equatorial segment curve in the boar, was species-characteristic. It was concluded that there are clear variations in the size and shape of the sperm head components between the three species studied, the acrosome being the structure showing the most variability, allowing a clear distinction of the spermatozoa of each species.

An Interpretable CNN for the Segmentation of the Left Ventricle in Cardiac MRI by Real-Time Visualization

The interpretability of deep learning models has emerged as a compelling area in artificial intelligence research.The safety criteria for medical imaging are highly stringent,and models are required for an explanation.However,existing convolutional neural network solutions for left ventricular segmentation are viewed in terms of inputs and outputs.Thus,the interpretability of CNNs has come into the spotlight.Since medical imaging data are limited,many methods to fine-tune medical imaging models that are popular in transfer models have been built using massive public Image Net datasets by the transfer learning method.Unfortunately,this generates many unreliable parameters and makes it difficult to generate plausible explanations from these models.In this study,we trained from scratch rather than relying on transfer learning,creating a novel interpretable approach for autonomously segmenting the left ventricle with a cardiac MRI.Our enhanced GPU training system implemented interpretable global average pooling for graphics using deep learning.The deep learning tasks were simplified.Simplification included data management,neural network architecture,and training.Our system monitored and analyzed the gradient changes of different layers with dynamic visualizations in real-time and selected the optimal deployment model.Our results demonstrated that the proposed method was feasible and efficient:the Dice coefficient reached 94.48%,and the accuracy reached 99.7%.It was found that no current transfer learning models could perform comparably to the ImageNet transfer learning architectures.This model is lightweight and more convenient to deploy on mobile devices than transfer learning models.

Photographic Image: Thematization of Its Discourses

This paper deals with thematization as a fundamental step towards the determination of photography image discourses in order to index them. It deals with questions related to photographic reality, polysemy, denotation and connotation, whose comprehension is fundamentally important for the interpretation of photography discourses. It also approaches aspects that have influenced photography analysis towards its thematization, such as the characterization of an image bank, the functions performed by photos, as well as technical and visual quality.

Anisotropy interpretation and the coherence research between resistivity and acoustic anisotropy in tight sands

Aiming at the problem of anisotropy inversion of tight sands, a new method for extracting resistivity anisotropy from array laterolog and micro-resistivity scanning imaging logging is proposed, and also the consistency of electric and acoustic anisotropy is discussed. Array laterolog includes resistivity anisotropy information, but numerical simulation shows that drilling fluid invasion has the greatest influence on the response, followed by the relative dip angle θ and electrical anisotropy coefficient λ. A new inversion method to determine ri, Rxo, Rt and λ is developed with the given θ and initial values of invasion radius ri, flushed zone resistivity Rxo, in-situ formation resistivity Rt. Micro-resistivity image can also be used for describing the resistivity distribution information in different directions, and the electrical characteristics from micro-resistivity log in different azimuths, lateral and vertical, can be compared to extract electric anisotropy information. Directional arrangement of mineral particles in tight sands and fracture development are the intrinsic causes of anisotropy, which in turn brings about anisotropy in resistivity and acoustic velocity, so the resistivity anisotropy and acoustic velocity anisotropy are consistent in trends. Analysis of log data of several wells show that the electrical anisotropy and acoustic anisotropy extracted from array laterolog, micro-resistivity imaging and cross-dipole acoustic logs respectively are consistent in trend and magnitude, proving the inversion method is accurate and the anisotropies of different formation physical parameters caused by the intrinsic structure of tight sand reservoir are consistent. This research provides a new idea for evaluating anisotropy of tight sands.

The Differences between Chinese and Western Cultures based on the Animal Images in Idioms

Chinese idioms,like English proverbs,are a language form,with a certain philosophical motive and ideological basis,given meaning through people's lifelong experiences.Throughout the ages,a wide range of beliefs,customs and natural scenery have been condensed into text forms in both Chinese idioms and English proverbs that display certain aspects of the essence of the two cultures.This paper focuses on the study of animal images in idioms,and elaborates on the different interpretations of specific images caused by the differences in history,regions,customs,and values of the two cultures.The purpose of this research is to provide a breakthrough more relevant to students who devote themselves to the study and research of Chinese and English languages and culture from the perspective of cultural contrast and analysis,so as to make a more thorough understanding of differences between Chinese and Western customs,culture and ideology.Therefore,language translations and cultural communications can be improved through a more accurate understanding of the Chinese and Western cultures.

Classification and structural characteristics of amorphous materials based on interpretable deep learning

Defining the structure characteristics of amorphous materials is one of the fundamental problems that need to be solved urgently in complex materials because of their complex structure and long-range disorder.In this study,we develop an interpretable deep learning model capable of accurately classifying amorphous configurations and characterizing their structural properties.The results demonstrate that the multi-dimensional hybrid convolutional neural network can classify the two-dimensional(2D)liquids and amorphous solids of molecular dynamics simulation.The classification process does not make a priori assumptions on the amorphous particle environment,and the accuracy is 92.75%,which is better than other convolutional neural networks.Moreover,our model utilizes the gradient-weighted activation-like mapping method,which generates activation-like heat maps that can precisely identify important structures in the amorphous configuration maps.We obtain an order parameter from the heatmap and conduct finite scale analysis of this parameter.Our findings demonstrate that the order parameter effectively captures the amorphous phase transition process across various systems.These results hold significant scientific implications for the study of amorphous structural characteristics via deep learning.

矩形空洞探地雷达成像曲线厚度变化规律研究

由于城市基础建设不断地翻新改造,引发城市地下空洞滋生问题。通过探地雷达扫描技术,对地下矩形空洞整个探测过程进行研究,将探测过程划分为四个阶段,研究了成像曲线厚度变化规律。对探地雷达水平运行时矩形空洞的成像曲线厚度变化规律进行分析,对不同大小下的矩形空洞点测时曲线厚度进行研究,并通过实际探测案例来解释矩形空洞成像曲线厚度变化规律,结果表明探地雷达探测矩形空洞时其成像曲线厚度为先增加后减小的对称曲线,其曲线厚度最大处在图像上为水平弧段两端,位于实际矩形空洞对角线附近;雷达点测时成像曲线厚度随矩形空洞变大而增加,在图像上表现为空洞越大线条越粗。

矿物组分识别与智能解释在不同岩性之间的信息共享与迁移学习

在地球科学领域,岩石微观观测数据的采集过程繁琐且效率低下,这不仅增加了研究成本,降低了可靠性,同时也限制了数据的开源共享。此外,由于岩性的多样性和观测手段的差异,单一数据集的规模通常较小,这对于依赖大规模数据集的深度学习框架而言是一大挑战。为此,本研究探索迁移学习如何促进不同岩性间的信息共享,并通过此机制提高矿物组分识别与智能解释任务的模型性能。通过采集不同区域、岩性、矿物组分和偏光模式下的铸体薄片样本,本文深入研究了深度学习模型在不同观测对象和手段下的迁移学习机制,并聚焦于探索地质信息的深层表征。研究成果不但揭示了迁移学习在促进地质学领域信息共享与模型性能提升中的关键作用,还为自动化和智能化地质认识融合奠定了基础。实验结果显示,通过迁移学习,本文模型在智能解释任务中的准确率显著提高,从53.3%提高至98.73%,而在矿物组分识别任务中,准确率也实现了近10%的提升。这些成果证明了迁移学习在地质学领域内解决实际问题和提高模型泛化能力、性能和稳定性方面的巨大潜力。

Extravasated contrast volumetric assessment on computed tomography angiography in gastrointestinal bleeding:A useful predictor of positive angiographic findings

BACKGROUND Gastrointestinal bleeding(GIB)is a severe and potentially life-threatening condition,especially in cases of delayed treatment.Computed tomography angiography(CTA)plays a pivotal role in the early identification of upper and lower GIB and in the prompt treatment of the haemorrhage.AIM To determine whether a volumetric estimation of the extravasated contrast at CTA in GIB may be a predictor of subsequent positive angiographic findings.METHODS In this retrospective single-centre study,35 patients(22 men;median age 69 years;range 16-92 years)admitted to our institution for active GIB detected at CTA and further submitted to catheter angiography between January 2018 and February 2022 were enrolled.Twenty-three(65.7%)patients underwent endoscopy before CTA.Bleeding volumetry was evaluated in both arterial and venous phases via a semi-automated dedicated software.Bleeding rate was obtained from volume change between the two phases and standardised for unit time.Patients were divided into two groups,according to the angiographic signs and their concordance with CTA.RESULTS Upper bleeding accounted for 42.9%and lower GIB for 57.1%.Mean haemoglobin value at the admission was 7.7 g/dL.A concordance between positive CTA and direct angiographic bleeding signs was found in 19(54.3%)cases.Despite no significant differences in terms of bleeding volume in the arterial phase(0.55 mL vs 0.33 mL,P=0.35),a statistically significant volume increase in the venous phase was identified in the group of patients with positive angiography(2.06 mL vs 0.9 mL,P=0.02).In the latter patient group,a significant increase in bleeding rate was also detected(2.18 mL/min vs 0.19 mL/min,P=0.02).CONCLUSION In GIB of any origin,extravasated contrast volumetric analysis at CTA could be a predictor of positive angiography and may help in avoiding further unnecessary procedures.

拉普拉斯卷积的双路径特征融合遥感图像智能解译方法

由于遥感图像存在多尺度变化和目标边缘模糊等问题,对其进行智能解译仍然是一项极具挑战性的工作。传统的语义分割方法在处理这些问题时存在局限性,难以有效捕捉全局和局部信息。针对上述问题,文中提出一种双路径特征融合分割方法 DFNet。首先,使用Swin Transformer作为主干提取全局语义特征,以处理像素之间的长距离依赖关系,从而促进对图像中不同区域相关性的理解;其次,将拉普拉斯卷积嵌入到空间分支,以捕获局部细节信息,加强目标地物边缘信息表达;最后,引入多尺度双向特征融合模块,充分利用图像中的全局和局部信息,以增强多尺度信息的获取能力。在实验中,使用了三个公开的高分辨率遥感图像数据集进行验证,并通过消融实验验证了所提模型不同模块的作用。实验结果表明,所提方法在Uavid数据集、Potsdam数据集、LoveDA数据集的mIoU达到了71.32%、85.58%、54.01%,提高了语义分割的性能,使分割结果更为精细。

ISO 11798:2023《信息与文献纸张上书写、打印和复印图像的耐久性和耐用性要求与测试方法》标准解读

ISO11798:2023规定了长期保存在图书馆、档案馆等可控环境中纸质文献的书写、打印、复印图像的耐久性和耐用性的要求与测试方法,不仅为图书馆、档案馆等单位更好地开展纸质文献保护工作提供助力,同时也为出版印刷行业提高印刷质量提供了重要参考。本文详细介绍了最新版ISO11798标准的修订背景、修订过程以及主要修订内容,希望能为相关从业人员研究新标准文本及制定相应国家标准提供帮助。

基于改进HRNet的遥感影像冬小麦语义分割方法

冬小麦在影像中呈现田块碎小且分布零散等空间特征,同时影像包含的复杂地物对冬小麦识别造成干扰,易出现识别精度低且边界分割模糊等问题。为及时准确获取大范围冬小麦空间分布信息,该研究以高分二号卫星影像作为数据源,提出一种CAHRNet(change attention high-resolution Net)语义分割模型。采用HRNet(high-resolution Net)替换ResNet作为模型的主干网络,网络的并行交互方式易获取高分辨率的特征信息;联合OCR(object-contextual representations)模块聚合上下文信息,以增强像素点与目标对象区域的关联性;3)引入坐标注意力(coordinate attention)机制,使网络模型充分利用有效的空间位置信息,以保留分割区域的边缘细节,提高对分布零散、形状多变的冬小麦田块的特征提取能力。试验结果表明,在自制的高分辨率遥感数据集上,CAHRNet模型的平均交并比(mean intersection over union,MIoU)和像素准确率(pixel accuracy, PA)分别达到81.72%和97.08%,MIoU相较U-Net、DeepLabv3+分别提高了9.09、2.44个百分点;PA相较U-Net、DeepLabv3+分别提高6.80、1.59个百分点,说明CAHRNet模型具有较高的分割识别精度,可为进一步准确获取冬小麦作物分布信息提供技术支撑。