基于MDL原理的快速在线信号分选算法

研究了一种基于最小描述长度(MDL)原理的快速在线雷达脉冲信号聚类分选算法,该方法利用幅度或相位差异特征,实现对雷达脉冲数据向量的聚类分选处理。设计了基于MDL原理的在线信号分选算法流程,在每接收到一定数量雷达脉冲信号后,执行一次聚类分选处理;对算法流程中的每个处理模块进行了完备的运算量分析,为工程设计提供有效的理论指导;并对比分析了离线和在线算法的性能。仿真结果表明:在线算法的信号分选正确率与离线方法基本一致,具有很强的工程应用前景。     

一种改进的K-Modes聚类算法

传统的K-Modes算法采用0-1简单匹配方法计算对象与类中心(Modes)之间的距离,并将每个对象分配到离它最近的类中去。采用基于频率方法重新计算各类的类中心(Modes)、定义目标函数,然而,对象的归类方法和目标函数的定义没有充分考虑分类数据的特点。对此,提出一种改进的K-Modes算法,采用期望熵最小的衡量方法进行归类,并且采用期望熵作为新的目标函数。通过实验将该算法与传统的K-Modes算法进行比较,表明该算法是更有效的。     

Rivality index neighbourhood algorithm with density and distances weighted schemes for the building of robust QSAR classification models with high reliable applicability domain

The rivality index (RI) is a normalized distance measurement between a molecule and their first nearest neighbours providing a robust prediction of the activity of a molecule based on the known activity of their nearest neighbours. Negative values of the RI describe molecules that would be correctly classified by a statistic algorithm and, vice versa, positive values of this index describe those molecules detected as outliers by the classification algorithms. In this paper, we have described a classification algorithm based on the RI and we have proposed four weighted schemes (kernels) for its calculation based on the measuring of different characteristics of the neighbourhood of molecules for each molecule of the dataset at established values of the threshold of neighbours. The results obtained have demonstrated that the proposed classification algorithm, based on the RI, generates more reliable and robust classification models than many of the more used and well-known machine learning algorithms. These results have been validated and corroborated by using 20 balanced and unbalanced benchmark datasets of different sizes and modelability. The classification models generated provide valuable information about the molecules of the dataset, the applicability domain of the models and the reliability of the predictions.     

Handling uncertainties in toxicity modelling using a fuzzy filter

A fundamental concern in the Quantitative Structure-Activity Relationship approach to toxicity evaluation is the generalization of the model over a wide range of compounds. The data driven modelling of toxicity, due to the complex and ill-defined nature of eco-toxicological systems, is an uncertain process. The development of a toxicity predicting model without considering uncertainties may produce a model with a low generalization performance. This study presents a novel approach to toxicity modelling that handles the involved uncertainties using a fuzzy filter, and thus improves the generalization capability of the model. The method is illustrated by considering a data set dealing with the fathead minnow (Pimephales promelas) toxicity of 568 organic compounds.     

Assessing Solvation Effects on Chemical Reactions with Globally Optimized Solvent Clusters

We have examined the influence of water solvent on the Menshutkin reaction of methyl chloride with ammonia by performing static, quantum chemical calculations. We have employed large, explicit, and globally structure‐optimized water clusters around the reaction center, in a mixed explicit/implicit solvent model. This approach deliberately deviates from attempts to capture the most likely solvent‐molecule distribution around a reaction center. Instead, it explores extremes on the scale of rearrangement speed in terms of the surrounding solvent cluster, relative to the reaction progress itself. A comparison to traditional theoretical and experimental results enables us to quantify the energy penalty that is induced by the inability of the water cluster to instantaneously and completely follow the reaction progress. In addition, the influence of water clusters on the reaction energy profile can be much larger than merely changing it somewhat. Certain clusters can completely annihilate the sizeable activation barrier of 23.5 kcal mol^?1.     

黄渤海近岸海域酚类内分泌干扰物分布特征及其来源解析

在黄渤海近岸海域采集了34个水体样品,利用HPLC-MS/MS分析了双酚A、辛基酚、壬基酚、2,4-二氯酚、对叔丁基苯酚和对特辛基苯酚等6种酚类内分泌干扰物的含量,并探讨了其分布特征及来源.结果表明,中国北部近岸海域6种酚类内分泌干扰物的含量范围在5.25～1351.20ng/mL之间.结合因子分析和层次聚类分析结果,说明渤海、黄海近岸海域中酚类化合物主要以辛基酚、壬基酚、2,4-二氯酚为主,局部海域伴有双酚A的高残留;从整个海域范围看,黄渤海近岸海域水体中酚类化合物污染状况具有区域特征,整体呈现出南高北低的特点,且酚类物质分布具有明显的地区特性,一定程度上具有聚集性;来源解析结果表明黄渤海近岸海域中酚类内分泌干扰物主要来源为生活污水和工业废水.     

A fast parallel clustering algorithm for molecular simulation trajectories

We implemented a GPU‐powered parallel k‐centers algorithm to perform clustering on the conformations of molecular dynamics (MD) simulations. The algorithm is up to two orders of magnitude faster than the CPU implementation. We tested our algorithm on four protein MD simulation datasets ranging from the small Alanine Dipeptide to a 370‐residue Maltose Binding Protein (MBP). It is capable of grouping 250,000 conformations of the MBP into 4000 clusters within 40 seconds. To achieve this, we effectively parallelized the code on the GPU and utilize the triangle inequality of metric spaces. Furthermore, the algorithm's running time is linear with respect to the number of cluster centers. In addition, we found the triangle inequality to be less effective in higher dimensions and provide a mathematical rationale. Finally, using Alanine Dipeptide as an example, we show a strong correlation between cluster populations resulting from the k‐centers algorithm and the underlying density. © 2012 Wiley Periodicals, Inc.     

回归的能源有效网络大数据流汇聚算法研究

为了降低传感器网络数据流汇聚时的能源消耗,提出了一种基于回归的能源有效数据流汇聚算法。首先,将传感器节点分为活跃节点和能源有效节点。然后,以活跃节点为中心点将所有节点进行聚类,并应用回归方法通过活跃节点的数据流对能源有效节点的数据进行预测。接下来,通过节点预测值的累积误差不断修正活跃节点集。最后,应用活跃节点的数据流信息对能源有效节点的数据进行预测。实验表明,本文提出的算法与其它相关算法相比具有更好的预测准确性。