Batch Nearest Neighbor Search for Video Retrieval

To retrieve similar videos to a query clip from a large database, each video is often represented by a sequence of high- dimensional feature vectors. Typically, given a query video containing m feature vectors, an independent nearest neighbor (NN) search for each feature vector is often first performed. After completing all the NN searches, an overall similarity is then computed, i.e., a single content-based video retrieval usually involves m individual NN searches. Since normally nearby feature vectors in a video are similar, a large number of expensive random disk accesses are expected to repeatedly occur, which crucially affects the overall query performance. Batch nearest neighbor (BNN) search is stated as a batch operation that performs a number of individual NN searches. This paper presents a novel approach towards efficient high-dimensional BNN search called dynamic query ordering (DQO) for advanced optimizations of both I/O and CPU costs. Observing the overlapped candidates (or search space) of a pervious query may help to further reduce the candidate sets of subsequent queries, DQO aims at progressively finding a query order such that the common candidates among queries are fully utilized to maximally reduce the total number of candidates. Modelling the candidate set relationship of queries by a candidate overlapping graph (COG), DQO iteratively selects the next query to be executed based on its estimated pruning power to the rest of queries with the dynamically updated COG. Extensive experiments are conducted on real video datasets and show the significance of our BNN query processing strategy.     

物流配送车辆计划调度系统的设计与实现

深入探讨了物流配送系统信息支撑台的要求与结构,详细介绍了作者开发的财政物流配送车辆计划调度系统的设计和实现过程,最后介绍了该计划调度系统的主要功能。     

对重催I/A'S系统三冲量控制回路的探讨

本文主要对广州石油化工总厂重油催化裂化装置的复杂回路——三冲量控制在I/A'S系统的实现进行探讨和实施。     

渗透蒸发的原理和应用（下）

本文介绍一种新的膜分离技术－渗透蒸发的原理和特点，及操作条件对分离性质的影响，并对其关键构件和设备即渗蒸发膜和渗透池作了专门叙述，结合具体实例从有机溶剂的脱水及水溶液中回收有机溶剂两个方面介绍了该技术在工业上应用的效果。     

江苏省水利地理信息系统三维展示平台构建与实现

江苏省水利地理信息系统三维展示平台在Skyline技术的基础上,加载了全省DOM数据、DEM数据及重点水利设施、建筑及景观三维模型数据,并集成了基于VR技术的大型水利三维虚拟场景,实现了高效率、高精度、精细化三维地形数据的组织、发布和应用,为三维GIS技术在水利信息化建设中提供了广阔的应用前景。     

Predicting dam failure risk for sustainable flood retention basins: A generic case study for the wider Greater Manchester area

This study aims to provide a rapid screening tool for assessment of sustainable flood retention basins (SFRBs) to predict corresponding dam failure risks. A rapid expert-based assessment method for dam failure of SFRB supported by an artificial neural network (ANN) model has been presented. Flood storage was assessed for 110 SFRB and the corresponding Dam Failure Risk was evaluated for all dams across the wider Greater Manchester study area. The results show that Dam Failure Risk can be estimated by using the variables Dam Height, Dam Length, Maximum Flood Water Volume, Flood Water Surface Area, Mean Annual Rainfall (based on Met Office data), Altitude, Catchment Size, Urban Catchment Proportion, Forest Catchment Proportion and Managed Maximum Flood Water Volume. A cross-validation R² value of 0.70 for the ANN model signifies that the tool is likely to predict variables well for new data sets. Traditionally, dams are considered safe because they have been built according to high technical standards. However, many dams that were constructed decades ago do not meet the current state-of-the-art dam design guidelines. Spatial distribution maps show that dam failure risks of SFRB located near cities are higher than those situated in rural locations. The proposed tool could be used as an early warning system in times of heavy rainfall.     

机载电缆作战损毁后智能化诊断系统

从技战术实际需要出发,给出了某型飞机作战损毁后机载电缆的智能化诊断系统的硬件结构框图。根据硬件系统模拟开关组件的原理,定义了电缆的连接矩阵、测量矩阵以及断口的映像矩阵运算,给出了断头查找的算法。计算表明,系统可在20 min内完成一个循环的断头查找并给出故障定位。     

Least squares recursive projection twin support vector machine for classification

In this paper we formulate a least squares version of the recently proposed projection twin support vector machine (PTSVM) for binary classification. This formulation leads to extremely simple and fast algorithm, called least squares projection twin support vector machine (LSPTSVM) for generating binary classifiers. Different from PTSVM, we add a regularization term, ensuring the optimization problems in our LSPTSVM are positive definite and resulting better generalization ability. Instead of usually solving two dual problems, we solve two modified primal problems by solving two systems of linear equations whereas PTSVM need to solve two quadratic programming problems along with two systems of linear equations. Our experiments on publicly available datasets indicate that our LSPTSVM has comparable classification accuracy to that of PTSVM but with remarkably less computational time.