A call for mtDNA data quality control in forensic science

There is increasing evidence that many of the mitochondrial DNA (mtDNA) databases published in the fields of forensic science and molecular anthropology are flawed. An a posteriori phylogenetic analysis of the sequences could help to eliminate most of the errors and thus greatly improve data quality. However, previously published caveats and recommendations along these lines were not yet picked up by all researchers. Here we call for stringent quality control of mtDNA data by haplogroup-directed database comparisons. We take some problematic databases of East Asian mtDNAs, published in the Journal of Forensic Sciences and Forensic Science International, as examples to demonstrate the process of pinpointing obvious errors. Our results show that data sets are not only notoriously plagued by base shifts and artificial recombination but also by lab-specific phantom mutations, especially in the second hypervariable region (HVR-II). (C) 2003 Elsevier Ireland Ltd. All rights reserved.

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

胜利勘探数据中心及勘探辅助决策系统研究

In the paper through extensive study and design, the technical plan for establishing the exploration database center is made to combine imported and self developed techniques. By research and repeated experiment a modern database center has been set up with its hardware and network having advanced performance, its system well configured, its data store and management complete, and its data support being fast and direct. Through study on the theory, method and model of decision an exploration decision assistant schema is designed with one decision plan of well location decision support system being evaluated and put into action. 1. Study on the establishment of Shengli exploration database center Research is made on the hardware configuration of the database center including its workstations and all connected hardware and system. The hardware of the database center is formed by connecting workstations, microcomputer workstations, disk arrays, and those equipments used for seismic processing and interpretation. Research on the data store and management includes the analysis of the contents to be managed, data flow, data standard, data QC, data backup and restore policy, optimization of database system. A reasonable data management regulation and workflow is made and the scientific exploration data management system is created. Data load is done by working out a schedule firstly and at last 200 more projects of seismic surveys has been loaded amount to 25TB. 2. Exploration work support system and its application Seismic data processing system support has the following features, automatic extraction of seismic attributes, GIS navigation, data order, extraction of any sized data cube, pseudo huge capacity disk array, standard output exchange format etc. The prestack data can be accessed by the processing system or data can be transferred to other processing system through standard exchange format. For supporting seismic interpretation system the following features exist such as auto scan and store of interpretation result, internal data quality control etc. the interpretation system is connected directly with database center to get real time support of seismic data, formation data and well data. Comprehensive geological study support is done through intranet with the ability to query or display data graphically on the navigation system under some geological constraints. Production management support system is mainly used to collect, analyze and display production data with its core technology on the controlled data collection and creation of multiple standard forms. 3. exploration decision support system design By classification of workflow and data flow of all the exploration stages and study on decision theory and method, target of each decision step, decision model and requirement, three concept models has been formed for the Shengli exploration decision support system including the exploration distribution support system, the well location support system and production management support system. the well location decision support system has passed evaluation and been put into action. 4. Technical advance Hardware and software match with high performance for the database center. By combining parallel computer system, database server, huge capacity ATL, disk array, network and firewall together to create the first exploration database center in China with reasonable configuration, high performance and able to manage the whole data sets of exploration. Huge exploration data management technology is formed where exploration data standards and management regulations are made to guarantee data quality, safety and security. Multifunction query and support system for comprehensive exploration information support. It includes support system for geological study, seismic processing and interpretation and production management. In the system a lot of new database and computer technology have been used to provide real time information support for exploration work. Finally is the design of Shengli exploration decision support system. 5. Application and benefit Data storage has reached the amount of 25TB with thousand of users in Shengli oil field to access data to improve work efficiency multiple times. The technology has also been applied by many other units of SINOPEC. Its application of providing data to a project named Exploration achievements and Evaluation of Favorable Targets in Hekou Area shortened the data preparation period from 30 days to 2 days, enriching data abundance 15 percent and getting information support from the database center perfectly. Its application to provide former processed result for a project named Pre-stack depth migration in Guxi fracture zone reduced the amount of repeated process and shortened work period of one month and improved processing precision and quality, saving capital investment of data processing of 30 million yuan. It application by providing project database automatically in project named Geological and seismic study of southern slope zone of Dongying Sag shortened data preparation time so that researchers have more time to do research, thus to improve interpretation precision and quality.