Online phenotype discovery based on minimum classification error model

Identifying and validating novel phenotypes from images inputting online is a major challenge against high-content RNA interference (RNAi) screening. Newly discovered phenotypes should be visually distinct from existing ones and make biological sense. An online phenotype discovery method featuring adaptive phenotype modeling and iterative cluster merging using improved gap statistics is proposed. Clustering results based on compactness criteria and Gaussian mixture models (GMM) for existing phenotypes iteratively modify each other by multiple hypothesis test and model optimization based on minimum classification error (MCE). The method works well on discovering new phenotypes adaptively when applied to both of synthetic datasets and RNAi high content screen (HCS) images with ground truth labels.     

Ordinal Optimization and Quantification of Heuristic Designs

This paper focuses on the performance evaluation of complex man-made systems, such as assembly lines, electric power grid, traffic systems, and various paper processing bureaucracies, etc. For such problems, applying the traditional optimization tool of mathematical programming and gradient descent procedures of continuous variables optimization are often inappropriate or infeasible, as the design variables are usually discrete and the accurate evaluation of the system performance via a simulation model can take too much calculation. General search type and heuristic methods are the only two methods to tackle the problems. However, the “goodness” of heuristic methods is generally difficult to quantify while search methods often involve extensive evaluation of systems at many design choices in a large search space using a simulation model resulting in an infeasible computation burden. The purpose of this paper is to address these difficulties simultaneously by extending the recently developed methodology of Ordinal Optimization (OO). Uniform samples are taken out from the whole search space and evaluated with a crude but computationally easy model when applying OO. And, we argue, after ordering via the crude performance estimates, that the lined-up uniform samples can be seen as an approximate ruler. By comparing the heuristic design with such a ruler, we can quantify the heuristic design, just as we measure the length of an object with a ruler. In a previous paper we showed how to quantify a heuristic design for a special case but we did not have the OO ruler idea at that time. In this paper we propose the OO ruler idea and extend the quantifying method to the general case and the multiple independent results case. Experimental results of applying the ruler are also given to illustrate the utility of this approach.

Improved statistics of sub-mesoscale eddies in the Baltic Sea retrieved from SAR imagery

In the present article the spatio-temporal distribution of sub-mesoscale eddies seen in Envisat Advanced Synthetic Aperture Radar (ASAR) imagery of the Baltic Sea is discussed. A total of 1250 ASAR images acquired between 2009 and 2011 form the basis of our studies and show imprints of almost 7000 sub-mesoscale eddies. Since the visibility of vortical structures in synthetic aperture radar (SAR) imagery significantly depends on the near-surface wind speed, wind data from a numerical model of the Baltic Sea were additionally used to obtain improved eddy statistics. Seasonally averaged fields of near-surface wind speed, surface currents, sea surface temperature (SST), and SST gradient were also analysed in order to reveal the role of these hydrophysical parameters in the observed spatial and temporal variation of sub-mesoscale eddies.     

基于区块链项目开发语言选型的初探

区块链技术及持续发展的各种开源区块链项目,正吸引着越来越多开发者的目光. 而繁多的主流编程语言及特色各异的区块链项目,使得开发者在开发基于区块链的系统与应用时,在技术选型上难免会有所困惑. 为此,对12个较知名的开源区块链项目,使用了源码统计工具Cloc统计其源代码,并进一步通过阅读相关代码及文档,分析和比较了其开发语言的构成. 同时,以图表的形式呈现其体量和关注度,从而为区块链开发者在选型上提供参考信息和建议.     

国民体质监测系统

随着经济社会的发展,人们不仅追求更高的物质生活,也更加关注体质健康和监测自身体质信息.本文介绍了国民体质监测系统,用于集中监测用户个人信息、健康数据和基础运动数据,为健康管理和慢性病干预提供了完整的一站式服务解决方案.本系统包含基于.NET MVC的数据统计分析子系统、基于Windows服务的数据同步服务与汇总服务以及基于Zabbix的系统监控程序等功能模块,能同时提供Web和移动终端两种访问形式.其中数据统计分析子系统用于统计用户数据,并利用数据挖掘技术给出统计分析结果和科学健身指导方案.数据同步服务用于准备数据,保证系统的数据完整性和一致性.数据汇总服务把省数据中心的地面站数据库数据汇总到中心数据库,中心数据库与数据统计分析子系统进行数据交互.系统监控程序监控服务器联网情况、IIS状态、数据库状态以及系统运行过程中可能发生的错误,并通过短信或邮件给出告警信息.本文设计开发完成的国民体质监测系统,提供了高效的国民体质监测和科学健身指导方案,有利于用户改善自己的身体机能.     

SQL执行计划与直方图关系研究

sql语句调优是数据库性能调优的重要方面.要达到同样的执行结果,sql语句有多种写法,不同的写法其性能差别很大.即使同一个sql语句,oracle也有多种途径去执行,即有多个执行计划.oracle比较这多个执行计划的性能优劣,耗费资源多少,来选择最优的执行计划.oracle在评估各个执行计划的性能时,需要借助sql语句执行的环境,即统计信息,来计算出每个执行计划耗费资源的多少.因此,尽可能收集准确的统计信息,对于oracle能否选择最优的执行计划,至关重要.其中,直方图的收集与否起着很重要的作用.本文通过实验来验证直方图对sql执行计划的影响,从而明确何种情况下需要收集直方图.     

药物信息服务实践应用的信度与效度分析

为建立科学的药物信息服务评价体系,我们采用问卷调查法对新疆医科大学第四附属医院药房及患者信息进行系统性调查,利用Excel和SPSSStatistics进行数据整理分析,采用Cronbach＇sAlpha系数、因子分析等方法对问卷做了信度和效度评价分析,初步提出了医院药物信息服务的要素．结果,本次研究的过程和方法为他人在药物信息乃至其它信息分析中提供重要的参考依据．     

增量统计方法在二代身份证系统中的应用

报表统计在二代身份证系统中非常重要,而且要求以天为单位按行政区划统计。当数据量比较小时,可以实时统计,但是当数据量比较大时,实践表明如果采用常规的统计方法,性能较差。因此,针对这种情况,提出了一种基于ORACLE的新统计方法—增量统计法,提高系统性能,来满足省、地市、区县、派出所各级公安机关工作人员的统计需求。     

Extreme value analysis of streamflow time series in Poyang Lake Basin, China

Extreme meteorological and hydrological events may cause major disasters and heavy social and economic losses.Therefore,more and more studies have focused on extreme hydro-meteorological events in various climates and geographic regions.Based on nearly 50 years of observed records of the Poyang Lake Basin,the occurrence and changing trends of extreme streamflow indices,including the annual maximum flow,annual peak-over-threshold flows,and low flows,were analyzed for ten hydrological stations.The results indicate that most annual maximum flows occurred from April to July,highly attributed to the Southeast Asian summer monsoons,whereas the annual minimum flows were concentrated between January and February.As for the low flow indices (the annual minimum flow,annual minimum 7-d flow,and annual minimum 30-d flow),a significant increasing trend was detected in most parts of the Poyang Lake Basin.The trends illustrate the potential effects of climate change and human activities on the hydrological cycle over the Poyang Lake Basin.     

Estimating inter-group interaction radius for point processes with nested spatial structures

A statistical procedure is proposed in order to estimate the interaction radius between points of a non-stationary point process when the process can present local aggregated and regular patterns. The model under consideration is a hierarchical process with two levels, points and clusters of points. Points will represent individuals, clusters will represent groups of individuals. Points or clusters do not interact as soon as they are located beyond a given interaction radius, and are assumed to interact if their distance is less than this interaction radius. Interaction radius estimation is performed in the following way. For a given distance, observations are split into several clusters whose in-between distances are larger than this distance. For each cluster, a neighbourhood and an area in which this cluster is randomly located is defined under the assumption that the distance between the cluster and its neighbourhood is larger than the interaction radius. The p-value of a test of this assumption is then computed for each cluster. Modelling the expectation of this p-value as a function of the distance leads to an estimate of the interaction radius by a least-square method. This approach is shown to be robust against non-stationarity. Unlike most classical approaches, this method makes no assumption on the point spatial distribution inside the clusters. Two applications are presented in animal and plant ecology.