Real time 3D simulation for nose surgery and automatic individual prosthesis design

This paper presents an intuitive nose surgery planning and simulation system, using 3D laser scan image and lateral X-ray image, to provide high quality prediction of the postoperative appearance, and design the patient specific prosthesis model automatically. After initial registration, the internal surface of soft tissue at the nose region was generated by the statistical data for soft tissue thickness adapted by the individual thickness information from the X-ray image. Then, the sketch contour of the 3D scan data on the lateral X-ray image was modified manually or adjusted automatically according to some aesthetic statistical data, to drive the simulation in real time by the state-of-the-art Laplacian surface deformation method. When satisfied with the 3D postoperative appearance, the deformation was mapped to the internal surface of soft tissue, and the change before and after simulation was utilized to generate the patient specific prosthesis model automatically. The surgeons who used the system confirmed that this planning system is attractive and has potential for daily clinical practice.     

B/S模式应用系统的一种新型结构及其实现

由于目前Ｂ／Ｓ模式应用系统的缺陷,提出了一种新型的系统结构并从原理上阐述了它的合理性,最后从模块间的通信。处理线程和数据库操作程间的同步和互斥以及系统等方面讲述系统的实现。     

化学因子分析法测定液体推进剂A

基于测定推进剂Ａ现有分析方法准确度低,神经网络法对仪器要求高等不足,提出了的一种新的分析方法。该方法利用已知酸的电位滴定数据建立多元线性回归数学模型,利用化学因子分解该模型,对未知样进行浓度测定。实际测定结果表明本方法的最大分析误差不超过０．１７％,标准偏差不超过１．９％,满足样品分析要求。     

健壮性学习算法

使用统计方法可以对汉英机器翻译的词性标注和句法语义分析阶段产生的歧义进行消歧,在估计过程中往往使用最大可能方法,但是并不是在所有的情况下取最大值都是正确的。为了从所有候选结果中取到正确的结果,本文使用健壮性学习算法。使用这个算法,当正确的候选结果评分不是最高时,仍能通过健壮性算法来调整正确结果的评分,使之最大,并且降低不正确候选的评分。而且,由于训练集与测试集存在不同,使训练集中的错误率最小不能保证测试集中的错误率也最小。因此当考虑训练语料库和测试语料库存在统计变化时,应该使用健壮性学习算法。     

平面内一组线段的可见性

给定平面内一组互不相交的线段,本文讨论其相对于某点的可见性,给出了时间复杂性为O(mlogm)的算法,并证明了这一算法在时间上是最优的.     

Performance evaluation of a dental handpiece in simulation of clinical finishing using a novel 2DOF in vitro apparatus

This paper reports on the performance evaluation of a dental handpiece in simulation of clinical finishing using a novel two-degrees-of-freedom (2DOF) in vitro apparatus. The instrumented apparatus consisted of a two-dimensional computer-controlled coordinate worktable carrying a dental handpiece, a piezoelectric force dynamometer, and a high-speed data acquisition and signal conditioning system for simulating the clinical operations and monitoring the dental finishing processes. The performance of the dental handpiece was experimentally evaluated with respect to rotational speed, torque, and specific finishing energy under the applied clinical finishing conditions. The results show that the rotational speeds of the dental handpiece decreased by increasing either the depth of cut or the feed rate at a constant clinically applied air pressure and water flowrate. They also decreased when increasing both the tangential and normal finishing forces. The specific finishing energy decreased with an increase in either depth of cut or feed rate, while the finishing torque increased as either the depth of cut or the feed rate was increased. Implications of these results were to provide guidance for proper applications of dental handpieces in clinical practice.     

动态地构建和维护基于小波的直方图*

利用小波变换的数学理论和方法,对基本的数据分布进行小波分解,在此基础上采用一种新的方法来动态地构建和维护基于小波的直方图,并给出相应的算法。实验证明基于这种方法的小波直方图能提供好的选择性估算和近似技术。     

1000BASE—T—在5类铜缆上实现千兆传输

１０００ＢＡＳＥ－Ｔ是一种在５类铜缆上传输１０００Ｍｂｐｓ速度的以太网解决方案。本文介绍了１０００ＢＡＳＥ－Ｔ的基本特性、关键性能参数及其设计。     

Generalized Adjusted Rand Indices for cluster ensembles

In this paper, Adjusted Rand Index (ARI) is generalized to two new measures based on matrix comparison: (i) Adjusted Rand Index between a similarity matrix and a cluster partition (ARImp), to evaluate the consistency of a set of clustering solutions with their corresponding consensus matrix in a cluster ensemble, and (ii) Adjusted Rand Index between similarity matrices (ARImm), to evaluate the consistency between two similarity matrices. Desirable properties of ARI are preserved in the two new measures, and new properties are discussed. These properties include: (i) detection of uncorrelatedness; (ii) computation of ARImp/ARImm in a distributed environment; and (iii) characterization of the degree of uncertainty of a consensus matrix. All of these properties are investigated from both the perspectives of theoretical analysis and experimental validation. We have also performed a number of experiments to show the usefulness and effectiveness of the two proposed measures in practical applications.     

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.