Management and display of four-dimensional environmental data sets using McIDAS
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Over the past four years, great strides have been made in the areas of data management and display of 4-D meteorological data sets. A survey was conducted of available and planned 4-D meteorological data sources. The data types were evaluated for their impact on the data management and display system. The requirements were analyzed for data base management generated by the 4-D data display system. The suitability of the existing data base management procedures and file structure were evaluated in light of the new requirements. Where needed, new data base management tools and file procedures were designed and implemented. The quality of the basic 4-D data sets was assured. The interpolation and extrapolation techniques of the 4-D data were investigated. The 4-D data from various sources were combined to make a uniform and consistent data set for display purposes. Data display software was designed to create abstract line graphic 3-D displays. Realistic shaded 3-D displays were created. Animation routines for these displays were developed in order to produce a dynamic 4-D presentation. A prototype dynamic color stereo workstation was implemented. A computer functional design specification was produced based on interactive studies and user feedback.Keywords:
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This report documents a data collection where we recorded redundant range image data from multiple views of a simple scene, and recorded accurate survey measurements of the same scene. Collecting these data was a focus of the research project Automated Geometric Model Builder Using Range Image Sensor Data (96-0384), supported by Sandia's Laboratory-Directed Research and Development (LDRD) Program during fiscal years 1996, 1997, and 1998. The data described here are available from the authors on CDROM, or electronically over the Internet. Included in this data distribution are Computer-Aided Design (CAD) models we constructed from the survey measurements. The CAD models are compatible with the SolidWorks 98 Plus system, the modern Computer-Aided Design software system that is central to Sandia's DeskTop Engineering Project (DTEP). Integration of our measurements (as built) with the constructive geometry process of the CAD system (as designed) delivers on a vision of the research project. This report on our final data collection will also serve as a final report on the project.
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The paper is on technological parameters data processing and analysis for further input signal significance estimation. In the paper the data retrieving from distributed control system software and hardware complex historical database is described and the algorithm of data formatting and processing is presented along with the examples. The problem of input signal impact on thermal power plant technical-and-economic indices is addressed in the research. The chosen data analysis tools are described and the plots and diagrams used to illustrate the data are presented. The novel parameter and group of parameters visualization approach is introduced. The possible ways of automating the database interaction and data analysis are proposed.
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The vast adoption of machine learning techniques in developing smart solutions increases the need of training and testing data. This data can be either collected from physical systems or created using simulation tools. In this regard, this paper presents a set of data collected using a digital twin known as the FASTory Simulator. The data contains more than 100 K events which are collected during a simulated assembly process. The FASTory simulator is a replica of a real assembly line with web-based industrial controllers. The data have been collected using specific-developed orchestrator. During the simulated process, the orchestrator was able to record all the events that occurred in the system. The provided data contains raw JavaScript Object Notation (JSON) formatted data and filtered Comma Separated Values (CSV) formatted data. This data can be exploited in machine learning for modelling the behaviour of the production systems or as testing data for optimization solution for the production system. Finally, this data has been utilized in a research for comparing different data analysis approaches including Knowledge-based systems and data-based systems.
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All along, the traditional comprehensive month report forms of the grid enterprise are mainly achieved by artificial, so that there are numerous shortcomings, such as low work efficiency, labor costs higher and so on. In order to adapt to the modern grid enterprises, especially the smart grid construction requirements, the grid enterprises developed Comprehensive Statistics Analysis and Data Acquisition System(CSAADA) to solve the problems. Compared with the report, visualization graphics display provides more intuitive data display and analyzes more efficient, so the system uses it for statistics and analysis of the collected data. In this paper, based on the indicators of grid enterprises and conforming the indicators architecture of the graphics display, we use Extjs charts control and the related technology to design and implement relevant graphics display of CSAADA.
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The system design and analysis processes involved in collecting data from a mobile laboratory to a finished analysis are presented. This involves real-time data collection on a small mobile cart, an intermediate analysis station in a nearby mobile van, and the final analysis performed through a minicomputer network of facilities. An iterative approach to data collection and review was established to provide timely analysis and verification of incoming data. This requires a highly interactive user-oriented environment in the field. After the data have been collected and preliminary analysis has been completed, the results can be integrated into a larger analysis system through a minicomputer network. This procedure also allows for utilization of high-cost equipment that cannot be placed in the field. A single hardware interface, BATNET (Battelle Network), is used to perform all data transfers via either radio (cart-to-van) or external network connections (van-to-computer network). The key software components described are a self-describing data base system utilizing simple relational data base concepts, a simple command language allowing analysis and investigation in the field, and a simple preview system for intensity-modulated data. 2 figures.
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Abstract : The Meteorological Sensor Array (MSA) goal is to provide reliable and persistent atmospheric data resources, which allow atmospheric modelers and sensor developers to validate and compare model and sensor performance with observations at and near the surface and in close proximity to terrain of varying complexity. The MSA Phase I ( Proof of Concept ) field campaign was executed in 2014. Concurrently, a Proof of Concept data management tool was designed, created and initial tests conducted. The Data Management task was divided into 2 parts: Data Processing and Data Distribution. The Data Processing was defined as the data flow from field sensor measurements through the initial data averaging, data merging, and time-series visualization plots used to quality control the data. The Data Distribution task began once the field data were quality controlled and included the process of reconfiguring the field data files for MSA data users. An earlier report (ARL-TR-7058) describes the Data Processing, in detail. Volume 2 focuses on the subsequent 2014-Data Distribution Tool development. This Data Distribution Tool consisted of 4 functions: Data Storage, Data Extraction, Data Visualization, and Data Documentation. Each function is elaborated in this report, along with a sample of the lessons learned . Data management is a nontrivial, critical pillar of the MSA. With software technologies advancing daily, the possibilities for improved data management tools are almost open ended. With this documentation, however, a foundation for creating a successful MSA Data Management Tool has been initiated.
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To deal with a great amount of data acquired in a large structure test efficiently, a data processing system is established. The database model to store the original experimental data is abstracted according to the test of civil engineering structures and insite inspection. A database management program is designed based on the processing procedures and as the preprocessing program for the data to be used in MATLAB that has strong calculating functions. This system has the full functions of data acquisition, processing and visualization.
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Outdoor data acquisition systems (DAS) designed for long term monitoring of photovoltaic (PV) modules provide wide range of measurement conditions. Measured data contain modules' electrical parameters extracted from I-V curves and meteorological conditions occurring during measurements. Every year measurement volume of data systematically increases making analysis more complex and difficult. To cope with such large amount of data efficient database together with analytical tools is essential. This paper presents a set of analytic tools implemented with The SAS Institute Software (USA) as online analytical processing (OLAP) website. Data are available for analysis via SolarLab's website for authorized users. Software provides multidimensional data filtering, data visualization and different types of regression. Additionally, summarized data, like periodical energy gain or insolation, can be viewed and drilled down to single measurements. Efficient data integration and data warehouse tools enable efficient analysis of data measured in different laboratories. Internet web browser interface simplifies multilaboratory cooperation in data analysis and does not require any additional software to be installed
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Data set
Data Analysis
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The application of an existing image analysis system to the display and analysis of geophysical data is described, the potential for expanding the capabilities of such a system toward more advanced computer analytic and modeling functions is investigated. The major features of the IDIMS (Interactive Display and Image Manipulation System) and its applicability for image type analysis of geophysical data are described. Development of a basic geophysical data processing system to permit the image representation, coloring, interdisplay and comparison of geophysical data sets using existing IDIMS functions and to provide for the production of hard copies of processed images was described. An instruction manual and documentation for the GEOPAK subsystem was produced. A training course for personnel in the use of the IDIMS/GEOPAK was conducted. The effectiveness of the current IDIMS/GEOPAK system for geophysical data analysis was evaluated.
Representation
Data Processing
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A man-machine control system is described which is designed specifically for use with computerized data processing in operational numerical weather analysis and prognosis. The equipment configuration and organization of programs and data libraries in this system at the Melbourne World Meteorological Center is briefly described, together with an account of the computer activities and data flow needed in the weather analysis and prognosis data processing system. A manually interactive automatic control system, consisting of a data-driven real-time monitor program on the one hand and a data-driven visual display program on the other, was programmed to operate in parallel with all programmed meteorological activities. The interactive portion of the control system serves as the primary interface between the meteorologist and the computer equipment and operational program complex, allowing him facilities to select directly and modify the characteristics of both the data and programs being used. The flexibility of the system is well suited to the nature of weather data processing in the Southern Hemisphere, which, as a result of vast sparse data regions, must admit of a high degree of manual interaction for acceptable results. The implementation of the interactive control system results in a large saving of time in manual handling of programs and data, and reduces human error, at the same time adhering to, and warning of departures from, a preset time table of operations.
Table (database)
Interface (matter)
Data Processing
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Data processing system
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