某水源地地下水四氯化碳污染特征分析

通过对某水源地地下水的四氯化碳污染调查和日常监测数据分析,研究了该水源地四氯化碳污染晕的形态和变化特征,并选取典型水源井对其四氯化碳动态特征进行了分析。在污染发现初期,污染面积为2.73 km2,最高污染浓度为249.7μg/L,随着后期污染治理工作的开展,污染面积减小到1.24 km2,最高污染浓度下降到3.62μg/L。分析认为,污染晕形态在空间分布上主要受地下水流场的控制,同时受降水量、地下水位标高及开采量等多种因素控制,污染物由北区井群向南区井群扩散。单井四氯化碳含量动态则呈现出南北区的相反特征:在北区,四氯化碳含量随着地下水位的上升而上升,并随地下水流向南扩散;在南区,四氯化碳含量随着地下水位的上升而下降,并随地下水流向地下水漏斗中心汇集。这是由于赋存于SD1井附近包气带中的四氯化碳尚未清除造成的。     

An efficient accelerator for attribute reduction from incomplete data in rough set framework

Feature selection (attribute reduction) from large-scale incomplete data is a challenging problem in areas such as pattern recognition, machine learning and data mining. In rough set theory, feature selection from incomplete data aims to retain the discriminatory power of original features. To address this issue, many feature selection algorithms have been proposed, however, these algorithms are often computationally time-consuming. To overcome this shortcoming, we introduce in this paper a theoretic framework based on rough set theory, which is called positive approximation and can be used to accelerate a heuristic process for feature selection from incomplete data. As an application of the proposed accelerator, a general feature selection algorithm is designed. By integrating the accelerator into a heuristic algorithm, we obtain several modified representative heuristic feature selection algorithms in rough set theory. Experiments show that these modified algorithms outperform their original counterparts. It is worth noting that the performance of the modified algorithms becomes more visible when dealing with larger data sets.     

Meshfree simulations of spall fracture

Shock wave induced spall fracture is a complex multiscale phenomenon, and it is a challenge to build a constitutive and computational model that can capture essential features of the spall fracture. In this work, we present a computational micro-mechanics model to simulate spall fracture by utilizing the multiscale micro-mechanics theory proposed by Wright and Ramesh [36] and a RKPM meshfree method. The focus of this work is to develop and demonstrate a simulation tool that is capable of simulations of spall fracture in engineering application. First, based on a well-known empirical formula, we relate the macroscale spall strength to the kinematics of micro void growth in a Representative Volume Element (RVE). The connection between micro void growth and overall kinematics of the RVE is made through the conservation of mass in the micro to macro transition process. Second, we develop a set of meshfree void growth algorithms that is tailored to represent kinematics of void nucleation, growth and coalescence, and these algorithms retain the conservation of mass, momentum, and energy during simulations of ductile spall fracture. Third, based on the Johnson–Cook model, we developed a meshfree computational formulation, and we have carried out simulations of the spall fracture of a Ti–6Al plate under impact loads to validate the model. From the simulation, we find that the interaction between the first two inelastic wave pulses plays an important role in the mechanism of spall fracture. The numerical results show that the proposed method can capture some features of the spall fracture, and it may be used to simulate the spall fracture in engineering applications.     

Online gesture spotting from visual hull data

This paper presents a robust framework for online full-body gesture spotting from visual hull data. Using view-invariant pose features as observations, hidden Markov models (HMMs) are trained for gesture spotting from continuous movement data streams. Two major contributions of this paper are 1) view-invariant pose feature extraction from visual hulls, and 2) a systematic approach to automatically detecting and modeling specific nongesture movement patterns and using their HMMs for outlier rejection in gesture spotting. The experimental results have shown the view-invariance property of the proposed pose features for both training poses and new poses unseen in training, as well as the efficacy of using specific nongesture models for outlier rejection. Using the IXMAS gesture data set, the proposed framework has been extensively tested and the gesture spotting results are superior to those reported on the same data set obtained using existing state-of-the-art gesture spotting methods.     

Optimal software pricing in the presence of piracy and word-of-mouth effect

We develop an analytical model that embeds empirical findings on software diffusion to examine optimal pricing strategies for a spreadsheet software product under coalescing effects of piracy and word-of-mouth through its entire life cycle. We find that the demand of the innovators has the most significant impact on the firm's pricing decision. Our research recommends market skimming pricing strategy if innovators' demand is high and the market penetration pricing strategy is preferred otherwise. Surprisingly, the increase of conversion rate of imitators to buyers never significantly alters the pricing strategy pre-determined by the demand of innovators. Most interestingly, the optimal profit from instituting a two prices policy for a software product with five years lifespan outperforms that from a one price policy by no more than 4%, a finding that corroborates the common one price policy observed in reality.     

Using capture-recapture data and hybrid Monte Carlo sampling to estimate an animal population affected by an environmental catastrophe

We propose a dynamic model for the evolution of an open animal population that is subject to an environmental catastrophe. The model incorporates a capture-recapture experiment often conducted for studying wildlife population, and enables inferences on the population size and possible effect of the catastrophe. A Bayesian approach is used to model unobserved quantities in the problem as latent variables and Markov chain Monte Carlo (MCMC) is used for posterior computation. Because the particular interrelationship between observed and latent variables negates the feasibility of standard MCMC methods, we propose a hybrid Monte Carlo approach that integrates a Gibbs sampler with the strategies of sequential importance sampling (SIS) and acceptance-rejection (AR) sampling for model estimation. We develop results on how to construct effective proposal densities for the SIS scheme. The approach is illustrated through a simulation study, and is applied to data from a mountain pygmy possum (Burramys Parvus) population that was affected by a bushfire.     

基于Xilinx System Generator的PID算法快速硬件实现

介绍了利用Xilinx System Generator平台构建模型化数字PID控制算法,并通过FPGA将数字PID算法结合传感器与实际硬件控制对象快速建立控制模型,构成完整的闭环控制。通过对控制效果的实验验证,证明了其控制方法的可行性。     

基于iFIX高速公路隧道监控系统的设计与实现

高速公路及隧道监控系统中,没有现成可用的I/O驱动,无法直接通过组态软件的I/O驱动获取数据。只能通过用户编写大量复杂的通信程序与之进行数据交换。为降低开发难度、提高开发效率,提出在组态软件脚本语言环境下运用API函数实现系统的通信设计。该系统以iFIX组态软件为平台,开发上位机监控系统软件,系统硬件部分搭建了以光纤作为传输介质的PLC冗余环网。运行结果表明,该系统占用资源小、维护方便、通信稳定且数据传输率高。