高速大容量存储系统的关键技术实现

介绍了一种高速大容量存储系统的实现方案,该系统以75MB/s的速度实时存储容量为64 GB的图像数据,并可通过扩展Flash阵列满足更高速度和更大容量的存储要求.     

井下仪器高可靠性大容量实时存储系统设计

数据实时存储是随钻仪器设计中的难点也是核心。本文介绍了一种适用于随钻仪器中高可靠性存储系统的设计方法。以M25P64为基本存储单元构成冗余存储阵列,通过采用相应的算法实现了数据高速大容量的实时存储。经过大量实验及应用效果表明,该设计方法能够满足井下各类仪器的数据存储需求。     

图像压缩研究

随着计算机时代的发展,人们可以利用多媒体计算机存储图像、听音频、做文件等等,因此计算机需要存储大量的数据信息,人们往往希望用最少的存储空间来存储更多的数据信息,利用数据压缩可以实现把一些冗余去掉。图像作为数据信息的一部分,在计算机中有着不可替代的存储形式,论文介绍了图像压缩标准JPEG和改进后的JPEG2000标准以及动态图像压缩各个标准MPEG的特点。压缩之后的解压图像往往希望失真较小,使人眼很难分辨与原图像的差别。压缩就是以最少的符号空间来表述更加丰富多彩的内容,这种思想在日常生活领域得到了广泛的应用。     

光盘技术的发展与应用

随着多媒体计算机技术的兴起和发展,计算机已由单纯的数字、文字处理进化成为能处理数据、文字、声音、图形、图像、动画、视频等多种信息的综合系统。而与此同时,计算机要处理的声音、图像、视顿等多媒体信息的数据量急剧增长,传统的存储媒体已不能满足这种高密度、大容量信息的存储需求。由于光盘具有记录密度高、存储容量大、存储成本低、保仔时间长、检索     

持续高速数据采集与过程控制并行工作的单机系统设计

设计了一种基于乒乓共享数据存储区的宿主式单机系统。该系统采集与控制部分完全由硬件电路组成，具有存储数据区自动切换，公用存储器访问权自动仲裁，Ａ／Ｄ与Ｄ／Ａ过程同步，通过主机能进行通道预置等功能，可广泛应用于化工，机械，生物医学等行业中多蹼我通道持续高速采集与并行处理系统中。     

岩屑图像采集分析技术在海拉尔盆地的应用

岩屑图像采集分析技术具有岩屑成像、自动求取荧光百分含量功能,是在白光和荧光光源下采集岩屑图像,存储数码图像和数据。通过该技术在海拉尔盆地的推广和笔者实际工作中的应用分析,总结出了该技术不仅消除了人为描述的误差,资料保存的长期性,同时也可在后期的录井综合解释评价上发挥重大作用。     

惠普光盘库应用在医疗-PACS系统

PACS（Picture Archiving and Comuniations System）即图像存储与传输系统，是应用于医院的数字医疗设备如CT、MR（核磁共振）、US（超声成像）、X光机、DSA（数字减影）、CR（计算机成像）等设备所产生的数字化医学图像信息的采集、存储、管理、诊断、信息处理的综合应用系统。PACS系统以高速计算机设备为相关基础，     

Panasonic 1.5GB可擦写光盘驱动器

LF—7300E外置式光盘驱动器和LF—7304内置式光盘驱动器是Panasonic最新相变光盘驱动器系列产品。这些产品利用先进的相变直接重写技术,可高速读写大量计算机数据,并可通过SCSI—2接口同各种计算机平台相连接,是理想的海量数据存储及备份的设备。     

存载全息数据的新材料

全息数据存储是一个令人感兴趣的话题，想象一下将美国国会图书馆的资料压缩到一块糕点大小的系统中的情景。借助当前的全息影像技术，相交的激光束产生负载数据的干扰图像，这种图像被记录在存储介质中，而这些数据信息可用更多的光束再复原出来。     

多媒体动画制作中的分形方法

三维动画以其独特的表现形式、赏心悦目的效果、低廉的制作成本在电视广告和节目片头中广泛采用。在制作的过程中,图形图像的设计与存储、丰富图形图像库的建立是一个重要问题。大容量图像、材质库的提供可大大节省用户的开发时间,但存储这些图像需要很大的存储空间,如软件3DS专门提供有光盘存储材质库,因此压缩图像数据是不容忽视的。图像数据压缩方法一直是计算机图像处理、信号传输中的重要课题。传统图像处理的方法是真实图像输入后,数据压缩采取的方法是无失真或有失真的压缩方法,如游程长度(RLE)编码、Huffman编码和自适应编码方法等,     

REDUCTION OF TOMOGRAPHIC DATA FOR USE IN THE CONTROL OF MULTIPHASE PROCESSES

Tomograhic sensors are ideally suited to the on-line control of multiphase processes. Little work to date however has been undertaken to determine what type and style of information is required from an image to provide effective process control. In this paper, a possible strategy is presented; namely, a combination of Principal Component Analysis (PCA) and Neural Networks (NN) is used to convert multivariate data from tomographic images into useful information suitable for the control and optimization of chemical processes.     

Quantification of the Immune Content in Neuroblastoma: Deep Learning and Topological Data Analysis in Digital Pathology

We introduce here a novel machine learning (ML) framework to address the issue of the quantitative assessment of the immune content in neuroblastoma (NB) specimens. First, the EUNet, a U-Net with an EfficientNet encoder, is trained to detect lymphocytes on tissue digital slides stained with the CD3 T-cell marker. The training set consists of 3782 images extracted from an original collection of 54 whole slide images (WSIs), manually annotated for a total of 73,751 lymphocytes. Resampling strategies, data augmentation, and transfer learning approaches are adopted to warrant reproducibility and to reduce the risk of overfitting and selection bias. Topological data analysis (TDA) is then used to define activation maps from different layers of the neural network at different stages of the training process, described by persistence diagrams (PD) and Betti curves. TDA is further integrated with the uniform manifold approximation and projection (UMAP) dimensionality reduction and the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm for clustering, by the deep features, the relevant subgroups and structures, across different levels of the neural network. Finally, the recent TwoNN approach is leveraged to study the variation of the intrinsic dimensionality of the U-Net model. As the main task, the proposed pipeline is employed to evaluate the density of lymphocytes over the whole tissue area of the WSIs. The model achieves good results with mean absolute error 3.1 on test set, showing significant agreement between densities estimated by our EUNet model and by trained pathologists, thus indicating the potentialities of a promising new strategy in the quantification of the immune content in NB specimens. Moreover, the UMAP algorithm unveiled interesting patterns compatible with pathological characteristics, also highlighting novel insights into the dynamics of the intrinsic dataset dimensionality at different stages of the training process. All the experiments were run on the Microsoft Azure cloud platform.     

多源遥感影像融合的基本原理和实现方法

为满足遥感影像处理的实际需要,需要将单一传感器或不同类别传感器获取的多源遥感影像信息进行综合,提高遥感影像的利用效益。本文以SPOT与TM影像的融合为例,探讨如何将高分辨率全色影像与多光谱影像融合从而获取更有利于进行地物判别的、兼具高空间分辨率与多光谱信息特性的影像的原理与方法。     

The role of the latent image in a new dual image,aqueous developable,thermally stable photoresist

A new dual image, aqueous developable photoresist can be processed to yield either positive or negative images that are crosslinked and thermally stable to temperatures >300°C. Positive images have similar resolution and processing parameters to conventional positive novolak resists. Negative resists from this system have a number of new and interesting properties that surpass the capabilities of their positive counterparts. In addition to producing highly resolved submicron images, thick coatings of resist can be used to form images with high aspect ratios. By adjusting the exposure of the resist, images with inward sloping wall profiles can be realized. As a result of the images being crosslinked and Insoluble in the resist coating solution, images can be recoated and new images formed over the top of existing patterns to form structures. A hypothetical mechanism that suggests that resist defects caused by dust on the mask or photoresist surface can be reduced In negative mode processing is also presented.