基于小波多分辨率分析的指横纹定位新算法

针对指横纹感兴趣区域(ROI)难以准确定位的问题,在明确提出指横纹ROI定义的前提下,提出利用小波多分辨率分析进行指横纹ROI自动检测定位的新算法.该方法利用纹理相似性原理,在高频子图采用基于特征向量和区域生长法产生指横纹的候选子区域集合,然后利用低频子图Radon投影得到的指横纹的区域特征对候选子区域进行验证,最后结合直线拟合手指轮廓得到指横纹在原图的有效位置,最终实现指横纹ROI的精准定位.实验证明该算法不仅能有效克服噪声以及手形姿态变化的影响,并且对多种情况有很强的鲁棒性.     

Group interaction analysis in dynamic context.

Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.     

多级故障诊断系统

介绍了为提高故障诊断的正确率,将一混合故障诊断专家系统中的基于BP神经网络诊断模块、基于自组织神经网络诊断模块和基于小波分析诊断模块设计成多级诊断系统。对多级诊断系统的性能进行了分析,给出了多级诊断系统的拒绝输出策略。     

梯形波脉冲筛板萃取柱传质性能

本文以UO_2(NO_3)_2—30％TBP(KO)为实验体系,进行了梯形波脉冲筛板柱传质性能的研究。实验中测量了两组分的两相稳态浓度剖面共13组,以扩散模型为基础,求得了梯形波脉冲柱的“真实”传质单元高度HTU_(ox),分散单元高度HDU及表观传质单元高度HTU_(oxp)。通过对实验结果进行分析,选择出了适于本实验体系的较好的操作条件。     

计算机维修模拟训练系统的设计与实现

探索了一种在多媒体环境下进行计算机及外部设备维修教学、训练的新方法 ,介绍了计算机维修模拟训练系统的设计与实现 ,给出了主要的设计思想、总体结构及关键技术。     

中药知母有效组分——知母皂甙元“滋阴”作用的研究

本工作以~(123)I-心得静结合分析法及环核苷酸RIA法观察了知母中提取得到的知母皂甙元对甲亢模型(模拟“阴虚”)βAR-cAMP系统的作和,结果表现,知母皂甙元明显降低甲亢小鼠脑β受体的RT值,显著降低甲亢小鼠β受体-cAMP系统的反应性,重现了知母水煎剂的下调作用。体外竞争抑制实验表明,知母皂甙元和知母皂甙元半琥珀酸都不能抑制~(125)I-心得静与β受体的结合。     

水利对粮食生产贡献率的认识与思考

针对目前很多人对农业科技进步贡献率和水利对粮食生产贡献率的不同认识,从发展历程、概念内涵、测算思路方法等方面,剖析了二者差异,认为二者在测算范围上存在大口径与小口径的差异,在测算对象上存在增量与总量的差异,在测算指标上存在产值与产量的差异,在测算方法上存在余值法与有无对比法的差异,为正确认识这两个指标提供了参考。     

Acoustic emission from gas-filled coal under triaxial compression

Acoustic emission (AE) experiments have been performed on gas-saturated coal specimens under conventional triaxial compression. The AE characteristics were investigated for a methane gas flow through the coal specimen. One AE parameter, AE count, when normalized by the total count number was used to represent the damage evolution in the gassy coal. It is shown that this AE parameter is a reasonable indicator for damage occurring within the coal specimen since its envelope has almost the same shape as the complete stress–strain curve, except for a short time delay. In addition, the change in AE count is highly consistent with the change in coal permeability. Test results also show that methane containing coal emits a small number of AE events before entering the yield stage. AE activity gradually increases during the yield process up to the peak stress. The lowest permeability corresponds to the highest AE activity, implying failure will soon occur. An AE based constitutive model was constructed and the theoretical results agree well with those of experiments.     

Robust and efficient ridge-based palmprint matching

During the past decade, many efforts have been made to use palmprints as a biometric modality. However, most of the existing palmprint recognition systems are based on encoding and matching creases, which are not as reliable as ridges. This affects the use of palmprints in large-scale person identification applications where the biometric modality needs to be distinctive as well as insensitive to changes in age and skin conditions. Recently, several ridge-based palmprint matching algorithms have been proposed to fill the gap. Major contributions of these systems include reliable orientation field estimation in the presence of creases and the use of multiple features in matching, while the matching algorithms adopted in these systems simply follow the matching algorithms for fingerprints. However, palmprints differ from fingerprints in several aspects: 1) Palmprints are much larger and thus contain a large number of minutiae, 2) palms are more deformable than fingertips, and 3) the quality and discrimination power of different regions in palmprints vary significantly. As a result, these matchers are unable to appropriately handle the distortion and noise, despite heavy computational cost. Motivated by the matching strategies of human palmprint experts, we developed a novel palmprint recognition system. The main contributions are as follows: 1) Statistics of major features in palmprints are quantitatively studied, 2) a segment-based matching and fusion algorithm is proposed to deal with the skin distortion and the varying discrimination power of different palmprint regions, and 3) to reduce the computational complexity, an orientation field-based registration algorithm is designed for registering the palmprints into the same coordinate system before matching and a cascade filter is built to reject the nonmated gallery palmprints in early stage. The proposed matcher is tested by matching 840 query palmprints against a gallery set of 13,736 palmprints. Experimental results show that the proposed matcher outperforms the existing matchers a lot both in matching accuracy and speed.     

Identification of Breast Cancer Prognosis Markers via Integrative Analysis

In breast cancer research, it is of great interest to identify genomic markers associated with prognosis. Multiple gene profiling studies have been conducted for such a purpose. Genomic markers identified from the analysis of single datasets often do not have satisfactory reproducibility. Among the multiple possible reasons, the most important one is the small sample sizes of individual studies. A cost-effective solution is to pool data from multiple comparable studies and conduct integrative analysis. In this study, we collect four breast cancer prognosis studies with gene expression measurements. We describe the relationship between prognosis and gene expressions using the accelerated failure time (AFT) models. We adopt a 2-norm group bridge penalization approach for marker identification. This integrative analysis approach can effectively identify markers with consistent effects across multiple datasets and naturally accommodate the heterogeneity among studies. Statistical and simulation studies demonstrate satisfactory performance of this approach. Breast cancer prognosis markers identified using this approach have sound biological implications and satisfactory prediction performance.