基于改进的深度卷积神经网络的单图像超分辨率重建

为解决现有的超分辨率模型不能很好的恢复图像的纹理细节和模型训练困难等问题,结合现有的残差网络和GoogleNet中的Inception模块对其进行改进。通过将5×5的卷积核替换为两个级联的3×3的卷积核、使用LeakyReLU作为激活函数和删除池化层等方法对原始的Inception模块进行改进,然后在模型中多次级联改进后的Inception模块。实验结果表明,与双三次插值算法、SRCNN和VDSR算法相比,改进后的模型能获得更高的峰值信噪比(PSNR)和结构相似性指数(SSIM),并且在视觉效果上也有明显的改善。     

基于优化YOLOv5s的老人跌倒检测算法

针对跌倒对老年人安全性问题造成的影响，以及现有目标检测模型在人物跌倒时易漏检、鲁棒性和泛化能力差等问题，对YOLOv5s算法进行优化，提出一种老人跌倒检测算法。使用改进的RepVGG模块代替YOLOv5s算法中的3×3卷积模块，优化损失函数，选择K-means++算法对所用数据集进行聚类优化。结果表明，所提算法的鲁棒性好、泛化能力强，平均准确率比YOLOv3,YOLOv4,YOLOv5s, CBAM-YOLOv5s模型分别提高了9%,8%,3%和1.2%。所提出的算法能够满足现实中不同场景对老人跌倒行为的检测需求，可以应用于移动设备或者监控设备中，在老年人安全保障领域发挥重要作用。     

多尺度卷积与双注意力机制融合的入侵检测方法

为提高互联网入侵检测方法的准确率,提出一种卷积神经网络与注意力机制结合的入侵检测方法。利用Borderline-SMOTE过采样算法和Min Max归一化对数据进行预处理,有效缓解入侵数据量差异较大问题,提升非平衡数据检测性能;使用卷积神经网络Inception结构多尺度对数据进行特征提取,并配合注意力机制进行维度更新,提高模型处理海量数据时特征表达的准确性。研究结果表明：入侵检测方法的平均准确率为99.57%;相较于SVM方法、CNN方法、RNN方法、BLS-GMM方法,准确率分别提升了4.48%、1.35%、1.62%和0.04%,召回率分别提高了4.48%、1.36%、1.62%和0.14%。     

云边协同的轻量级网络结构人脸识别方法

为了解决人脸识别因采用复杂度较高的卷积神经网络导致在计算与存储资源受限的物联网(IoT)边缘设备中无法部署的问题，提出了可通过云边协同技术部署在物联网边缘设备上的轻量级Mobile MTCNN人脸检测与识别算法，以减少物联网边缘设备资源开销.在人脸检测算法中使用轻量级子网络获取人脸框位置和人脸关键点坐标，并在人脸识别算法中设计了基于Mobile-Inception与Mobile-Resent结构的IMobileNet网络模型.实验结果表明：人脸检测算法在较现有算法准确率平均下降1%的情况下，虽然漏检率平均增加1%,但运行时间平均减少20%以上；人脸识别算法在达到MobileNet V2网络相同准确率情况下，设计并选用的IMobileNet-Small网络平均识别时间减少12%以上.因此，轻量级人脸检测与识别算法可维持识别精确度，同时满足边缘设备部署要求.     

多尺度卷积核U-Net模型的视网膜血管分割方法

针对病变视网膜血管结构的计算机辅助诊断问题,提出了一种多尺度卷积核U-Net模型的视网膜血管分割方法.在U-Net模型基础上设计了融合Inception模块和最大索引值上采样方法的多尺度卷积神经网络结构.在网络训练阶段,采取旋转、镜像等操作进行数据集扩充,运用CLAHE算法进行图像预处理;训练后得到的双通道特征图,进行Softmax归一化;最后通过改进的代价损失函数对归一化结果迭代优化,得到完整的视网膜血管分割模型.实验结果表明,所提方法在DRIVE数据集上分割的准确率达到0.9694,灵敏性达到0.7762,特异性达到0.9835,比U-Net模型具有更优的分割效果和泛化能力,与其他现存方法相比具有一定的竞争力.     

基于特征金字塔模型的高分辨率遥感图像船舶目标检测

以舰船为研究对象,研究高分辨遥感图像的多尺度多目标检测中的关键技术,主要解决多尺度多目标识别和细粒度分类准确率低等问题.在目标定位方面,利用特征金字塔深度网络定位多目标区域,创建一个在所有尺度上均具有语义信息的特征金字塔,有效解决多尺度多目标数据定位准确率低这一关键问题;在目标识别方面,利用共享CNN网络重建输入图像、优化多任务损失函数提取细粒度分类目标结构特征,提高细分目标识别准确率.与GoogLeNet、Faster R-CNN和Yolo三种目标检测算法对比实验表明,利用特征金字塔和重建输入图像可有效检测多目标多尺度的细粒度船舶对象,漏检率为1.5%,细粒度分类识别平均准确率为92.67%.     

R-YOLO轨道人员目标检测模型

针对现有铁路人员入侵识别准确率不高、实时性较差的问题，在YOLOv4模型的基础上提出一种R-YOLO轨道人员目标检测模型。首先，用轻量级骨干网络ResNet50代替原有的CSPDarknet53网络，利用深度可分离卷积替代PANet中的标准卷积，减少网络层数以及模型体积，加快模型的识别速度。其次，在加强特征提取网络的3个特征层分别加入有效通道注意力模块，采用K-means++聚类算法重新对数据集进行聚类和分析，提高目标检测模型的精度；在模型训练方面，采用迁移学习和混合数据集联合训练，解决人员识别精度不理想以及误检漏检等问题。最后，利用R-YOLO轨道人员目标检测模型对真实铁路人员入侵数据集进行测试。结果表明，R-YOLO模型在真实铁路人员入侵数据集上的平均识别精度达到了92.12%,较传统YOLOv4算法高出1.89%,帧速率由38.74 f·s^-1提升到47.73 f·s^-1。R-YOLO模型部分解决了铁路入侵人员误检漏检问题，提高了铁路人员入侵识别的实时性和准确率，为铁路安全运行提供了保障。     

基于改进的RetinaNet医药空瓶表面气泡检测

医药空瓶在生产过程中瓶身表面会产生大量的气泡缺陷,但现有的方法对医药空瓶表面气泡检测存在各种问题,例如对复杂场景变化的鲁棒性不强,抗噪声干扰能力弱等.针对现有医药空瓶表面的气泡缺陷,提出了一种改进的深度学习目标检测算法RetinaNet对瓶身气泡进行检测.对原始RetinaNet算法中的特征金字塔网络结构进行了优化,在特征融合过程中引入了特征增强模块,用来提高网路对图像语义特征的提取,增强网络特征提取能力.为了减少模型的参数数目和计算时间,考虑到空瓶表面气泡均为小目标缺陷,去掉原始特征金字塔网络中用于检测大目标的网络结构,提高了算法检测速度.通过对标准的ResNet50网络进行重新组合,并引进了膨胀卷积模块,扩大特征图感受野,提高了模型检测的精度.通过在注塑空瓶数据集上对本文的方法进行了验证,其准确率为99.72%,漏检率为0.12%,误检率为016%,mAP为99.49%,相比原始的RetinaNet的mAP提高了接近2.4%.     

基于深度卷积网络的工程车辆检测算法

为了解决传统的小尺度密集工程车辆检测算法存在检测速度慢、鲁棒性差、识别准确率低等问题,采用基于改进型YOLO v3的卷积神经网络工程车辆检测算法,使用目标框与真实框交并比作为损失函数替代聚类算法中的欧式距离,同时结合工程车辆检测时标注真实框的特点,对候选框进行聚类;改进评估模型的损失函数,构建适合小尺度密集车辆的网络结构.在自制数据集上进行试验,结果表明,该方法对小尺度密集工程车辆的检测精度明显提高,准确率能够达到81.1%,召回率能达到95.9%.     

基于注意力特征融合的SqueezeNet细粒度图像分类模型

针对现有细粒度图像分类算法普遍存在的模型结构复杂、参数多、分类准确率较低等问题,提出一种注意力特征融合的SqueezeNet细粒度图像分类模型.通过对现有细粒度图像分类算法和轻量级卷积神经网络的分析,首先使用3个典型的预训练轻量级卷积神经网络,对其微调后在公开的细粒度图像数据集上进行验证,经比较后选择了模型性能最佳的SqueezeNet作为图像的特征提取器;然后将两个具有注意力机制的卷积模块嵌入至SqueezeNet网络的每个Fire模块;接着提取出改进后的SqueezeNet的中间层特征进行双线性融合形成新的注意力特征图,与网络的全局特征再融合后分类;最后通过实验对比和可视化分析,网络嵌入Convolution Block Attention Module(CBAM)模块的分类准确率在鸟类、汽车、飞机数据集上依次提高了8.96%、4.89%和5.85%,嵌入Squeeze-and-Excitation(SE)模块的分类准确率依次提高了9.81%、4.52%和2.30%,且新模型在参数量、运行效率等方面比现有算法更具优势.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

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An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

Integrating GIS Web services based on mediating architecture

The geographic information service is enabled by the advancements in general Web service technology and the focused efforts of the OGC in defining XML-based Web GIS service. Based on these models, this paper addresses the issue of services chaining,the process of combining or pipelining results from several interoperable GIS Web Services to create a customized solution. This paper presents a mediated chaining architecture in which a specific service takes responsibility for performing the process that describes a service chain. We designed the Spatial Information Process Language (SIPL) for dynamic modeling and describing the service chain, also a prototype of the Spatial Information Process Execution Engine (SIPEE) is implemented for executing processes written in SIPL. Discussion of measures to improve the functionality and performance of such system will be included.