Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

离心泵并联运行工况点的数值求解

建立了求解多台不同型号离心泵并联运行工况点的数学模型,给出了用数值计算中的“二分法”求解该模型的方法,并附有用Exce l计算的实例。     

纤维在沥青混合料中的应用研究

选用工程中常用的几种纤维,结合工程应用要求,试验分析了纤维的吸湿性、耐热性,并通过网篮析漏试验、动态剪切试验和沉锥试验,讨论了纤维对沥青的稳定和吸附作用,以及纤维对沥青混合料“加筋”效果和作用机理。研究表明有的纤维“吸附、稳定”性能好,而有的纤维“加筋、桥接”效果好,在应用纤维时,应根据纤维的主要特点以及沥青混合料的使用要求来选用。     

裂解炉炉管基于风险的检验

管式裂解炉炉管受炉内高温及管内介质压力的共同作用,易发生蠕变等现象,因此,对裂解炉炉管进行风险评价尤为重要。应用API 581基于风险的检验规范对炉管的失效可能性及失效后果分别进行定量计算,并由此得到裂解炉炉管的定量风险结果和基于风险的检验周期,为裂解炉的风险控制与管理提供依据。     

实验室的质量监督(上)

质量监督是实验室保持人员能力,进行自我完善,日常渐进的重要手段,是持续改进的重要组成部分,也是实验室管理工作的难点,本文给出质量监督的目的、对象、方法、记录等.     

Profile-Driven Component Placement for Cluster-Based Online Services

The growth of the Internet and of various intranets has spawned a wealth of online services, most of which are implemented on local-area clusters using remote invocation (for example, remote procedure call/remote method invocation) among manually placed application components. Component placement can be a significant challenge for large-scale services, particularly when application resource needs are workload dependent. Automatic component placement has the potential to maximize overall system throughput. The key idea is to construct (offline) a mapping between input workload and individual-component resource consumption. Such mappings, called component profiles, then support high-performance placement. Preliminary results on an online auction benchmark based on J2EE (Java 2 Platform, Enterprise Edition) suggest that profile-driven tools can identify placements that achieve near-optimal overall throughput.     

电磁超声流量计的研制

基于电磁声换能器的原理，研制了一种新型的电磁超声流量计，并讨论提高测量精度的措施。     

基于电源、地桥的电源网络布线后优化

随着集成电路规模的不断增大,电源网络的重要性日趋显著,电源网络的分布直接影响芯片的电压降(IR-drop)。一种布线后通过在空闲处插入电源桥和地桥的方法,可以在不增加芯片面积的情况下,改善IR-drop效应。实验结果表明在芯片布局利用率不高的情况下(70~75%),该方法可以使IR-drop得到明显的优化。