高效水基乳液型清蜡剂的研制

主乳化剂与具有综合效能的多种表面活性剂复配乒改变乳化方式,可以在减少表面活性剂用量的同时提高所得乳液的稳定、润湿、渗透、分散等性能。确定了多种高效、多功能、低成本的水基乳液型清蜡剂配方。探讨了影响清蜡效果的若干因素和清蜡机理。通过与常用升温破乳型水基乳液清蜡剂的比较,提出了在清蜡条件下呈稳定状态的水基乳液的清蜡作用:乳液润温、渗透、分散以至剥离积蜡,溶剂的溶蜡作用不是主要的清蜡机理。     

一种新多波束发射机

本文详细介绍了一种新多波束发射机的设计方案,不采用微波大功率单刀双掷开关而采用前后向发射机获得双向发射功能。本文给出这种发射机等效辐射功率的计算公式,并与传统多波束发射机相比较,讨论这种新发射机的优缺点。     

Computational statistics for cell survival curves. I. Evaluation of the colony-forming ability of a single cell strain by the APL function CFALINE

An interactive program for the statistical analysis of cell survival curves by a linear regression approach is described. It allows for the computational determination of the linear part of a cell survival curve and the determination of a common slope estimate in the presence of repeated experiments for a particular cell strain with the appropriate variance estimates and confidence intervals.     

LIGA工艺在工程中的两类应用

本文从LIGA工艺的工程应用角度，简要介绍微小型安全密码锁机构、微小型加速开关结构的基本设计问题和工艺问题，初步分析了这两类组件制造对LIGA工艺的需求与要求。     

Scalable Data Assignment Algorithm of Parallel I/O for Distributed Heterogeneous Computing

In order to improve the efficiency of storing files to disks and meet the demands of,high availability and scalability on distributed heterogeneous computing environment, two new file assignment strategies are proposed. One is named the available percent decision-making, and the other is the combination of subsection select and awailable percent decision-making. Experimental results show the advantages of new algorithms.     

发展中的文字识别理论与技术

文字识别的理论与技术在强大社会需求的推动下发展，以功能实现为目标的理论已初步形成，技术成果已开始走向实用，尽管理论和技术仍不太成熟，但无论是脑机能研究的进展还是计算机性能的提高都会不断促进文字识别理论与技术的发展并最终达到理想目标。     

基于组合权重分析的引信失效诊断技术

基于组合权重分析的引信失效诊断技术,包括由构造递阶层次、构造成对比较矩阵、计算权重及一致性检验等步骤组成的准则层重要度分析技术;由通过构造成对比较矩阵、计算权重及一致性检验得以完成的安全性重要度分析技术;以及由计算系统组合权向量和系统组合一致性检验两步构成的系统组合权向量分析技术.     

细胞因子联合应用对急性辐射损伤小鼠的保护作用

采用60Coγ射线10 Gy全身照射雄性ICR小鼠,观察各组小鼠30天存活率,在照后不同时间测定体重、血液学指标、凝血指标、脏器系数、骨髓指标。结果表明,细胞因子对小鼠的辐射损伤有保护作用,其中G-CSF+IL-Ⅱ+TPO联合应用和G-CSF+TPO+干扰素α2β联合应用优于单种细胞因子。     

Improved non-maximum suppression for object detection using harmony search algorithm

Non-maximum suppression (NMS) plays a key role in many modern object detectors. It is responsible to remove detection boxes that cover the same object. NMS greedily selects the detection box with maximum score; other detection boxes are suppressed when the degree of overlap between these detection boxes and the selected box exceeds a predefined threshold. Such a strategy easily retain some false positives, and it limits the ability of NMS to perceive nearby objects in cluttered scenes. This paper proposes an effective method combining harmony search algorithm and NMS to alleviate this problem. This method regards the task of NMS as a combination optimization problem. It seeks final detection boxes under the guidance of an objective function. NMS is applied to each harmony to remove imprecise detection boxes, and the remaining boxes are used to calculate the fitness value. The remaining detection boxes in a harmony with highest fitness value are chosen as the final detection results. The standard Pattern Analysis, Statistical Modeling and Computational Learning Visual Object Classes dataset and the Microsoft Common Objects in Context dataset are used in all of the experiments. The proposed method is applied to two popular detection networks, namely Faster Region-based Convolutional Neural Networks and Region-based Fully Convolutional Networks. The experimental results show that the proposed method improves the average precision of these two detection networks. Moreover, the location performance and average recall of these two detectors are also improved.