锦屏一级水电站左岸1601m廊道岩体质量指标研究

岩石质量指标(RQD)是评价岩体质量的一个重要参数,被广泛应用于岩石质量评价,但通过钻孔取芯方式获取RQD存在明显不足,给岩体质量评价带来了一定的误差。以锦屏一级水电站左岸廊道岩体为实例,结合结构面三维网络模拟技术,采用测线法研究了广义RQD_t随测线布置长度与角度的变化情况。在此基础上分析了岩体的尺寸效应和各向异性。研究结果表明:RQD_t存在显著的尺寸效应,随着测线长度增大至10 m,RQD_t收敛于一个稳定的值;随着测线倾向和倾角的变化,RQD_t沿空间不同方向呈现出不同的分布。研究发现锦屏一级水电站左岸1 601 m廊道岩体具有显著的尺寸效应和各向异性,基于广义RQD_t的岩石质量指标能克服传统RQD在这方面的不足。     

油田采出水的精细过滤技术

低渗透油层渗透率〈0．1μm^2，孔喉半径小，容易被堵塞，对注入水质要求高，目前缺乏对含有原油、化学添加剂、粉质颗粒和无机盐的油田采出水适应性强的精细过滤设备。本文介绍了油田采出水回注精细过滤材料试验和采用旋流配水、脉冲水流反洗技术的改性聚四氟乙烯滤芯过滤装置的小试和中试研究情况，研究开发的改性聚四氟乙烯精细过滤装置，当进水含油量〈20mg／L、悬浮物含量〈20mg／L时，出水达到了（《碎屑岩油藏注水水质推荐指标》（SY5329-94）规定的A1级注水水质标准。     

网络通讯在高杆灯监控系统中的应用

针对城市中高杆灯监控系统,设计了一套基于C/S与GPRS的监控系统软件。根据GPRS数据通讯的特点,确定传输帧数据格式、制定了相应的传输协议。将完成端口通信技术应用到服务器软件的网络通信模块设计中,实现高效的系统网络性能。测试表明,所设计的监控系统软件具有较高的数据处理能力,在实际运行中也表现出良好的性能。     

An Intra-Server Interconnect Fabric for Heterogeneous Computing

With the increasing diversity of application needs and computing units, the server with heterogeneous pro- cessors is more and more widespread. However, conventional SMP/ccNUMA server architecture introduces communication bottleneck between heterogeneous processors and only uses heterogeneous processors as coprocessors, which limits the efficiency and flexibility of using heterogeneous processors. To solve this problem, this paper proposes an intra-server inter- connect fabric that supports both intra-server peer-to-peer interconnection and I/O resource sharing among heterogeneous processors. By connecting processors and I/O devices with the proposed fabric, heterogeneous processors can perform direct communication with each other and run in stand-alone mode with shared intra-server resources. We design the proposed fabric by extending the de-facto system I/O bus protocol PCIe （Peripheral Computer Interconnect Express） and implement it with a single chip cZodiac. By making full use of PCIe＇s original advantages, the interconnection and the I/O sharing mechanism are light weight and efficient. Evaluations that have been carried out on both the FPGA （Field Programmable Gate Array） prototype and the cycle-accurate simulator demonstrate that our design is feasible and scalable. In addition, our design is suitable for not only the heterogeneous server but also the high density server.     

基于云端协同计算架构的边缘端I/O密集型虚拟机资源分配方案

大型制造业生产车间业务流程复杂,传统固定资源配置方式将产生负载不均衡的问题。针对此问题,设计并实现了一种基于云端协同架构的边缘端I/O密集型虚拟机资源的分配算法,通过定义计算节点中每个I/O密集型虚拟机三个维度的信息计算得出I/O密集型虚拟机的优先级,并按最大优先级队列实时统一分配硬件资源。实验结果表明,该算法在应对工业机械设备高响应和高通量的要求上有较为明显的提升,为实际生产起到了优化资源配置的作用。     

无隔膜槽中ACF电极成对电解脱色活性艳蓝KN-R

采用恒电流模式,同时以活性炭纤维(ACF)为阳极和阴极,在无隔膜电解槽中研究了不同电流密度下蒽醌染料活性艳蓝KN-R的电化学脱色。结果表明在1.0~1.5mA.cm-2时,电解槽中发生阳极电氧化和阴极电还原同时进行的成对电解脱色。成对电解的发生,可以提高电解槽的工作处理能力。当电流密度为1.1mA.cm-2时,脱色率达到87%。     

An economical synthesis of the major sex attractant of the oak leaf roller—cis-10-tetradecenyl acetate

The major sex attractant of the oak leaf roller (Archips semiferanus Walker),cis-10-tetradecenyl acetate (I), was synthesized in 55–62% overall yield by a highly economical route from inexpensive azelaic acid (II).Authorized as Paper No. 4779 in the Journal Series of the Pennsylvania Agricultural Experiment Station.     

Importance Sampling Microfacet‐Based BSDFs using the Distribution of Visible Normals

We present a new approach to microfacet‐based BSDF importance sampling. Previously proposed sampling schemes for popular analytic BSDFs typically begin by choosing a microfacet normal at random in a way that is independent of direction of incident light. To sample the full BSDF using these normals requires arbitrarily large sample weights leading to possible fireflies. Additionally, at grazing angles nearly half of the sampled normals face away from the incident ray and must be rejected, making the sampling scheme inefficient. Instead, we show how to use the distribution of visible normals directly to generate samples, where normals are weighted by their projection factor toward the incident direction. In this way, no backfacing normals are sampled and the sample weights contain only the shadowing factor of outgoing rays (and additionally a Fresnel term for conductors). Arbitrarily large sample weights are avoided and variance is reduced. Since the BSDF depends on the microsurface model, we describe our sampling algorithm for two models: the V‐cavity and the Smith models. We demonstrate results for both isotropic and anisotropic rough conductors and dielectrics with Beckmann and GGX distributions.     

3D Motion Completion in Crowded Scenes

Crowded motions refer to multiple objects moving around and interacting such as crowds, pedestrians and etc. We capture crowded scenes using a depth scanner at video frame rates. Thus, our input is a set of depth frames which sample the scene over time. Processing such data is challenging as it is highly unorganized, with large spatio‐temporal holes due to many occlusions. As no correspondence is given, locally tracking 3D points across frames is hard due to noise and missing regions. Furthermore global segmentation and motion completion in presence of large occlusions is ambiguous and hard to predict. Our algorithm utilizes Gestalt principles of common fate and good continuity to compute motion tracking and completion respectively. Our technique does not assume any pre‐given markers or motion template priors. Our key‐idea is to reduce the motion completion problem to a 1D curve fitting and matching problem which can be solved efficiently using a global optimization scheme. We demonstrate our segmentation and completion method on a variety of synthetic and real world crowded scanned scenes.     

3D Shape Segmentation and Labeling via Extreme Learning Machine

We propose a fast method for 3D shape segmentation and labeling via Extreme Learning Machine (ELM). Given a set of example shapes with labeled segmentation, we train an ELM classifier and use it to produce initial segmentation for test shapes. Based on the initial segmentation, we compute the final smooth segmentation through a graph‐cut optimization constrained by the super‐face boundaries obtained by over‐segmentation and the active contours computed from ELM segmentation. Experimental results show that our method achieves comparable results against the state‐of‐the‐arts, but reduces the training time by approximately two orders of magnitude, both for face‐level and super‐face‐level, making it scale well for large datasets. Based on such notable improvement, we demonstrate the application of our method for fast online sequential learning for 3D shape segmentation at face level, as well as realtime sequential learning at super‐face level.