两种简化的侧凹抽芯机构

对于制品的内侧凹 ,在采用滑块、斜摆杆等一般抽芯机构较难实现时 ,通过改变抽芯机构的动作和复位形式 ,设计出两种简化的侧凹抽芯机构 ,并且制造方便,缩短了加工周期 ,实践证明该机构可有效地完成抽芯动作。     

Mo在水溶液中的耐腐蚀性能

综述了Mo在不同溶液中的电化学行为、电池作用腐蚀 行为，并从技术的角度总结了它在各种碱性溶液、酸性溶液、无机盐溶液以及海水中的耐蚀性能.最后对研究工作进行了展望.     

Stress－rupture Property and Microstructure of Yttria Dispersion Strengthened Alloy MA956

Ｓｔｒｅｓｓ－ｒｕｐｔｕｒｅＰｒｏｐｅｒｔｙａｎｄＭｉｃｒｏｓｔｒｕｃｔｕｒｅｏｆＹｔｔｒｉａＤｉｓｐｅｒｓｉｏｎＳｔｒｅｎｇｔｈｅｎｅｄＡｌｌｏｙＭＡ９５６ＳｈａＷｅｉ（沙维）（ＤｅｐａｒｔｍｅｎｔｏｆＣｉｖｉｌＦｎｇｉｎｅｅｒｉｎｇ，ＴｈｅＱｗｅ...     

BT16钛合金紧固件加工工艺分析

分析了不同规格俄制BT16钛合金自锁螺母显微组织、流线和显微硬度，并与俄制该合金φ8min丝材进行对比。研究结果表明：BT16钛合金紧固件显微组织为单相区变形获得的超细片状组织；其组织形态与退火态丝材一致，表明紧固件是在退火状态下直接使用的，未经过固溶时效强化处理；BT16钛合金紧固件采用了冷变形制造工艺。     

基于关键资源优先的三级装卸搬运分时协调策略

研究基于关键资源优先的单元化“装卸、搬运、装卸” 三级作业链的调度问题. 在已知关键资源调度方案的条件下, 将两个非关键各作业级的调度问题分别转化为最小单位流问题, 并建立相应的0/1 整数规划模型求解. 为求解大规模问题, 提出三级装卸搬运的分时协调策略. 参照宁波港码头数据, 设计面向集装箱码头的仿真算例, 实验结果验证了所提出模型和策略的有效性.

     

基于曲线拟合和SVM的眼动信号分类算法研究

为提高基于EOG的眼动信号分类算法精度,改进基于EOG的人—机交互系统性能,提出了一种基于曲线拟合(curve fitting)与支持向量机(SVM)的眼动信号分类算法(CF-SVM),并设计了新的实验范式,增加了“扫视保持”环节.该算法采用曲线拟合方法进行特征提取,在此基础上,使用SVM分类器对眼动信号进行分类.实验室环境下,对9名眼部活动正常的受试者进行了眼动数据采集与识别,CF-SVM算法的平均分类准确率达到98.3％,与其他几种眼动识别方法相比较,其平均正确率分别提升了9.4％、5.9％、1.0％.实验结果表明,CF-SVM算法在眼动信号识别中表现了良好的性能,具有高的分类精度和鲁棒性.     

High-quality image restoration from partial mixed adaptive-random measurements

A novel framework to construct an efficient sensing (measurement) matrix, called mixed adaptive-random (MAR) matrix, is introduced for directly acquiring a compressed image representation. The mixed sampling (sensing) procedure hybridizes adaptive edge measurements extracted from a low-resolution image with uniform random measurements predefined for the high-resolution image to be recovered. The mixed sensing matrix seamlessly captures important information of an image, and meanwhile approximately satisfies the restricted isometry property. To recover the high-resolution image from MAR measurements, the total variation algorithm based on the compressive sensing theory is employed for solving the Lagrangian regularization problem. Both peak signal-to-noise ratio and structural similarity results demonstrate the MAR sensing framework shows much better recovery performance than the completely random sensing one. The work is particularly helpful for high-performance and lost-cost data acquisition.     

Exploring cell tower data dumps for supervised learning-based point-of-interest prediction (industrial paper)

Exploring massive mobile data for location-based services becomes one of the key challenges in mobile data mining. In this paper, we investigate a problem of finding a correlation between the collective behavior of mobile users and the distribution of points of interest (POIs) in a city. Specifically, we use large-scale cell tower data dumps collected from cell towers and POIs extracted from a popular social network service, Weibo. Our objective is to make use of the data from these two different types of sources to build a model for predicting the POI densities of different regions in the covered area. An application domain that may benefit from our research is a business recommendation application, where a prediction result can be used as a recommendation for opening a new store/branch. The crux of our contribution is the method of representing the collective behavior of mobile users as a histogram of connection counts over a period of time in each region. This representation ultimately enables us to apply a supervised learning algorithm to our problem in order to train a POI prediction model using the POI data set as the ground truth. We studied 12 state-of-the-art classification and regression algorithms; experimental results demonstrate the feasibility and effectiveness of the proposed method.     

面向军事行动的后勤保障系统架构与关键技术

为了解决传统系统忽略后勤保障与军事行动间交互作用的局限性,从后勤保障对军事行动的感知与响应视角,对面向军事行动的后勤保障系统进行研究.在分析系统需求的基础上,构建响应灵敏和柔韧健壮的系统架构,给出系统实现关键技术,动态捕捉后勤保障对军事行动的协同效应.该系统的研究可为后勤保障提供决策信息,对于提高后勤保障力度具有重要作用.