Efficient Data Organization Research Articles

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping.

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays 'Fernandez') plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable.

A Service-Oriented Spatio-Temporal Data Model of the Marine Environment

On the basis of analyzing of the marine environment spatio-temporal data characteristics and the existing data model, proposes a conceptual model for marine environment data based on the feature and field to achieve integration of description and expression of feature, field, time, space and semantic domains. Designs and implements the service-oriented marine environment data organization and storage using Geography Markup Language (GML). Efficient data organization and management is crucial to marine environment visual services.

Rules Generation for Multimedia Data Classifying using Rough Sets Theory

An efficient multimedia data management process is very important in multimedia system application. Huge size of multimedia data that distributed in multi locations makes multimedia data management more complicated. Rapid development of multimedia applications created a vast volume of multimedia data and it is exponentially incremented from time to time. This situation requires for efficient data classification and organization technique for providing effective multimedia data manipulation process. Using rough sets theory and web services technology, this paper proposed a new rules generation for multimedia data classifying in collaborative environment. ROSETTA tool is applied to verify the reliability of the generated results. The experiments show that the rough sets theory based for multimedia data classifying is suitable to be executed in web services environment.

Application of Improved B+-Trees Algorithm in Embedded Database

B+-trees algorithm is a high efficient and common-used data organization algorithm in database system. But B+-trees algorithm has a disadvantage of low storage utilization. This disadvantage has a bad effect especially on embedded database systems, which have limit storage. To overcome this drawback, this paper presents an improved B+-trees algorithm, and applies it to an embedded database-Berkeley DB. Experimental results show that the improved B+-trees algorithm can attain higher storage utilization at the expense of more execution time than the conventional B+-trees algorithm.

A hierarchical organization approach of multi-dimensional remote sensing data for lightweight Web Map Services

With the rapid development of the World Wide Web, remote sensing (RS) data have become available to a wider range of public/professional users than ever before. Web Map Services (WMSs) provide a simple Web interface for requesting RS data from distributed geospatial databases. RS data providers typically expect to provide lightweight WMSs. They have a low construction cost, and can be easily managed and deployed on standard hardware/software platforms. However, existing systems for WMSs are often heavyweight and inherently hard to manage, due to their improper usage of databases or data storage. That is, they are not suitable for public data services on the Web. In addition, RS data are moving toward the multi-dimensional paradigm, which is characterized by multi-sensor, multi-spectral, multi-temporal and high resolution. Therefore, an efficient organization and storage approach of multi-dimensional RS data is needed for lightweight WMSs, and the efficient WMSs must support multi-dimensional Web browsing. In this paper, we propose a Global Remote Sensing Data Hierarchical Model (GRHM) based on the image pyramid and tiling techniques. GRHM is a logical model that is independent upon physical storage. To support lightweight WMSs, we propose a physical storage structure, and deploy multi-dimensional RS data on Web servers. To further improve the performance of WMSs, a data declustering method based on Hilbert space-filling curve is adopted for the distributed storage. We also provide an Open Geospatial Consortium (OGC) WMS and a Web map system in Web browsers. Experiments conducted on real RS datasets show promising performance of the proposed lightweight WMSs.

Integration of Environmental Fluid Dynamics Code (EFDC) Model with Geographical Information System (GIS) Platform and Its Applications

Data management and analysis are important for the application of water quality modeling in water environmental protection. The integration of the Environmental Fluid Dynamics Code (EFDC) model with Geographical Information Systems (GIS) is discussed in this paper. The data management and analysis ability of this widely used water quality model was enhanced by the integration. Database methods are used to integrate the different types of modeling data into a GIS platform. The spatial data modeling and analysis capacity of GIS is used in the pre-processing and post-processing of EFDC. The integration application is demonstrated by a case study of the Lower Charles River Basin water quality model, which was built with EFDC and has 56 varying-size curvilinear horizontal grids and 8 vertical layers. The case study shows that the integrated system significantly improved the application of EFDC with more efficient data processing, organization and analysis, and can be used as a powerful tool for water environmental management and decision making.

The Rat Genome Database curation tool suite: a set of optimized software tools enabling efficient acquisition, organization, and presentation of biological data

The Rat Genome Database (RGD) is the premier repository of rat genomic and genetic data and currently houses over 40 000 rat gene records as well as human and mouse orthologs, 1771 rat and 1911 human quantitative trait loci (QTLs) and 2209 rat strains. Biological information curated for these data objects includes disease associations, phenotypes, pathways, molecular functions, biological processes and cellular components. A suite of tools has been developed to aid curators in acquiring and validating data objects, assigning nomenclature, attaching biological information to objects and making connections among data types. The software used to assign nomenclature, to create and edit objects and to make annotations to the data objects has been specifically designed to make the curation process as fast and efficient as possible. The user interfaces have been adapted to the work routines of the curators, creating a suite of tools that is intuitive and powerful.Database URL: http://rgd.mcw.edu

The Study on Framework and Functions of Integrated Design Environments for Preliminary Design

For complex product design, many software and tools are used, and large scale intermediate data with heterogeneous formats and complex relationships are produced in preliminary design. Efficient organization and management of data are very difficult. The integrated design environments(IDE) are useful to solve this problem. This paper gives an overview on IDE and some correlative key technologies. According to characteristics of preliminary design stage, a framework of IDE is put forward in this paper and the system function components are analyzed. The framework includes some innovative methodologies, such as task-drove design by workflow management, design tools and software seamless integration, and design knowledge templates. The realization of IDE is presented to illustrate the applicability of the new framework.

Mayday - integrative analytics for expression data

BackgroundDNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmer's access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Mayday's functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files.ResultsWe have rewritten large parts of Mayday's core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved.ConclusionsWe present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at http://microarray-analysis.org.

The Schema of the European EPILEPSIAE database for seizure prediction

The Schema of the European EPILEPSIAE database for seizure prediction

Search Location-Dependent Data In Broadcasting Environment

Abstract Location-based services (LBSs) provide the information based on location information as specified in a query. Queries that support LBS are called Location-Dependent Queries (LDQ). LDQ contain: range query, nearest neighbor (NN) query, k-nearest neighbor (KNN) query and reverse nearest neighbor (RNN) query. Examples of mobile LBSs include location-dependent information access (e.g., traffic reports and attractions) and nearest neighbor queries (e.g. fmding the nearest restaurant). While LDQ is well studied in the traditional wired, disk-based client-server environment, it has not yet been tackled in relation to a wireless broadcasting environrent. In this paper, the issues involved with organizing location-dependent data and answering LDQ queries on the air, aze investigated. The lineaz property of wireless broadcasting media and the power conservation requirement of mobile devices make the problem particularly interesting and challenging. An efficient data organization, called Jump Rdnn-Tree, and...

Integrated data management in complex product collaborative design

Scientific computing in complex product engineering design process has the characteristics of being tentative and iterative, which produces large scale intermediate data with heterogeneous formats and complex relationships, and the efficient organization and management of data becomes a bottleneck of product design performance. The concept of business component is introduced in this paper based on the modular analysis of the engineering process, and an integrated data management and storage framework is proposed for efficient heterogeneous design data management, in which XML schema, relational database and design files are synthesized. A network version management model is designed to enhance the design process and design object data management, which can describe both the individual object's evolution process and the inheritance relationships among multiple objects. Furthermore, key operations of version merge, submission and visualization are discussed. Finally the methods and technologies are implemented in an integrated management system for aerodynamic design of aero turbine engines (IMS-DATE).

Applications of SQL for informetric frequency distribution processing

Many informetric data types lend themselves to ready adaptation to relational DBMS environments for storage and processing. SQL, the standard language used for constructing and querying relational databases, provides useful tools for processing informetric data. The author demonstrates the applications and some limitations of SQL for efficient organization and tabulation of raw informetric data.

Adaptive zero-tree structure for curved wavelet image coding

We investigate the issue of efficient data organization and representation of the curved wavelet coefficients [curved wavelet transform (WT)]. We present an adaptive zero-tree structure that exploits the cross-subband similarity of the curved wavelet transform. In the embedded zero-tree wavelet (EZW) and the set partitioning in hierarchical trees (SPIHT), the parent-child relationship is defined in such a way that a parent has four children, restricted to a square of 2×2 pixels, the parent-child relationship in the adaptive zero-tree structure varies according to the curves along which the curved WT is performed. Five child patterns were determined based on different combinations of curve orientation. A new image coder was then developed based on this adaptive zero-tree structure and the set-partitioning technique. Experimental results using synthetic and natural images showed the effectiveness of the proposed adaptive zero-tree structure for encoding of the curved wavelet coefficients. The coding gain of the proposed coder can be up to 1.2 dB in terms of peak SNR (PSNR) compared to the SPIHT coder. Subjective evaluation shows that the proposed coder preserves lines and edges better than the SPIHT coder.

AnnGIS: Integration of GIS and a Continuous Simulation Model for Non‐Point Source Pollution Assessment

Non‐Point Source (NPS) models and monitoring data are often used to evaluate management practices and develop NPS pollution control plans. Application of a dynamic NPS model requires efficient input data acquisition, storage, organization, reduction, and analysis accompanied by manipulation, interpretation, reporting, and display of model outputs. A Geographic Information System (GIS) helps extract, store, and organize input data as well as manipulate and display model outputs. This paper illustrates the development of an integrated GIS system for a continuous simulation, pollutant‐loading model, AnnAGNPS (Annualized AGricultural Non‐Point Source Pollution). The integrated system, called AnnGIS, was developed using the ArcView GIS and related program extensions. Using AnnGIS, modeling studies and management plans can be efficiently and easily developed. AnnGIS helps store, organize, and manipulate spatial and tabular data, extract spatial input parameters, develop analysis scenarios, and visualize input and output data in spatial, tabular, and graphical forms. AnnGIS is generic in nature (not limited to a particular geographic location) and can be successfully used in regions for which AnnAGNPS is designed. AnnGIS's powerful graphical user interface and reference data sets facilitate efficient and informed decision‐making concerning agricultural non‐point pollution control and management.

Supporting Temporal Views in a ManagementInformation Base

In many network management applications, like post-mortem fault analysis or performance trends profiling, it is advantageous to have the ability to view the state of the network as it was at some time in the past. To support such Temporal Views an efficient data organization, or access method, is needed for storing and updating network related data (as the network evolves over time) and for retrieving requested past network states. For applications where the network manager is not interested in the full (and maybe too large) snapshot of a past network state it is useful if partial state snapshots can be extracted quickly. It is thus of particular interest to construct an access method that can efficiently support Partial Temporal Views. Efficiency implies that a requested partial temporal view should be constructed directly, without first computing the elaborate full temporal view. In this paper we present a new access method (called the Neighbor History Index) for this problem. One of the advantages of this method is that the update processing is independent of the evolution size (the total number of changes in the evolution). In addition, our method uses a small disk space overhead. We then present a general framework for organizing time-evolving network data. Our framework distinguishes between flat and hierarchical evolutions and subsequently between flat and hierarchical temporal views. We also provide a way to efficiently construct temporal views on hierarchical evolutions. This paper shows that supporting temporal views on flat or hierarchical evolutions is not expensive: our solutions use small space overhead, have small updating and compute temporal views fast.

Parallel Processing for Terrain Analysis in GIS: Visibility as a Case Study

The application of parallel processing to computationally intensive GIS problems has been advocated and illustrated by many researchers over the last twenty years. Despite this, GIS users have been slow to capitalize on the potential which the technology offers. Whilst today’s processors are adequate for the majority of GIS uses, some applications are too processor-intensive to be deemed viable for serial machines. This is particularly true of many digital terrain modelling applications, which has been the primary focus of parallel processing in GIS to date. This paper considers the problem of parallelizing line-of-sight (LOS) calculations in determining the visibility indices of entities such as elevation vertices in a digital terrain model (DTM). This is a requirement of site selection for a particular development, especially if visibility, or more specifically, visual intrusion is likely to be a key factor in gaining planning approval. To demonstrate the simplicity and applicability of parallelizing such GIS problems, this paper presents some parallel approaches in an efficient data organization, framework using a Transputer network. Speed-up performance can be increased by a factor of twelve using a simple network of twenty Transputers. As vast quantities of spatial data become available, particularly DTMs at larger scales and denser resolution, the demands for parallel processing will inevitably increase. It is hoped that the continued experiences of today’s researchers at applying parallel processing to well-defined problems will benefit the GIS users of tomorrow.

A fast implementation of two-dimensional convolution algorithm for image-processing applications

An implementation of the two-dimensional convolution algorithm that is suitable for image-processing applications is presented. The execution time of the algorithm is shown to be reduced due to an efficient data organization and by taking into account the fact that the pixel values in an image assume a fixed number of discrete levels.

Computerization of a Large Relay Setting File

An existing highly functional relay settings card file containing a vast amount of technical data for a large variety of relaying terminals was computerized. The primary goal was to retain the transparency of the existing manual file while benefiting from computerization's handling capabilities. The computer's limited ability to use preprinted output forms was overcome by programming it to create its own forms. Efficient programming and data organization resulted in the computer displaying and printing forms similar to those used in the manual file. This made the new file as convenient as the old and compatible with it over the 2 year transition period. The programming provides fast, interactive access to all records in the file and allows displaying and printing of a large variety of card forms and useful reports.