sTools - a data reduction pipeline for the GREGOR Fabry-Pérot Interferometer and the High-resolution Fast Imager at the GREGOR solar telescope

Science.gov (United States)

Kuckein, C.; Denker, C.; Verma, M.; Balthasar, H.; González Manrique, S. J.; Louis, R. E.; Diercke, A.

2017-10-01

A huge amount of data has been acquired with the GREGOR Fabry-Pérot Interferometer (GFPI), large-format facility cameras, and since 2016 with the High-resolution Fast Imager (HiFI). These data are processed in standardized procedures with the aim of providing science-ready data for the solar physics community. For this purpose, we have developed a user-friendly data reduction pipeline called ``sTools'' based on the Interactive Data Language (IDL) and licensed under creative commons license. The pipeline delivers reduced and image-reconstructed data with a minimum of user interaction. Furthermore, quick-look data are generated as well as a webpage with an overview of the observations and their statistics. All the processed data are stored online at the GREGOR GFPI and HiFI data archive of the Leibniz Institute for Astrophysics Potsdam (AIP). The principles of the pipeline are presented together with selected high-resolution spectral scans and images processed with sTools.

ESO Reflex: a graphical workflow engine for data reduction

Science.gov (United States)

Hook, Richard; Ullgrén, Marko; Romaniello, Martino; Maisala, Sami; Oittinen, Tero; Solin, Otto; Savolainen, Ville; Järveläinen, Pekka; Tyynelä, Jani; Péron, Michèle; Ballester, Pascal; Gabasch, Armin; Izzo, Carlo

ESO Reflex is a prototype software tool that provides a novel approach to astronomical data reduction by integrating a modern graphical workflow system (Taverna) with existing legacy data reduction algorithms. Most of the raw data produced by instruments at the ESO Very Large Telescope (VLT) in Chile are reduced using recipes. These are compiled C applications following an ESO standard and utilising routines provided by the Common Pipeline Library (CPL). Currently these are run in batch mode as part of the data flow system to generate the input to the ESO/VLT quality control process and are also exported for use offline. ESO Reflex can invoke CPL-based recipes in a flexible way through a general purpose graphical interface. ESO Reflex is based on the Taverna system that was originally developed within the UK life-sciences community. Workflows have been created so far for three VLT/VLTI instruments, and the GUI allows the user to make changes to these or create workflows of their own. Python scripts or IDL procedures can be easily brought into workflows and a variety of visualisation and display options, including custom product inspection and validation steps, are available. Taverna is intended for use with web services and experiments using ESO Reflex to access Virtual Observatory web services have been successfully performed. ESO Reflex is the main product developed by Sampo, a project led by ESO and conducted by a software development team from Finland as an in-kind contribution to joining ESO. The goal was to look into the needs of the ESO community in the area of data reduction environments and to create pilot software products that illustrate critical steps along the road to a new system. Sampo concluded early in 2008. This contribution will describe ESO Reflex and show several examples of its use both locally and using Virtual Observatory remote web services. ESO Reflex is expected to be released to the community in early 2009.

Automating OSIRIS Data Reduction for the Keck Observatory Archive

Science.gov (United States)

Holt, J.; Tran, H. D.; Goodrich, R.; Berriman, G. B.; Gelino, C. R.; KOA Team

2014-05-01

By the end of 2013, the Keck Observatory Archive (KOA) will serve data from all active instruments on the Keck Telescopes. OSIRIS (OH-Suppressing Infra-Red Imaging Spectrograph), the last active instrument to be archived in KOA, has been in use behind the (AO) system at Keck since February 2005. It uses an array of tiny lenslets to simultaneously produce spectra at up to 4096 locations. Due to the complicated nature of the OSIRIS raw data, the OSIRIS team developed a comprehensive data reduction program. This data reduction system has an online mode for quick real-time reductions, which are used primarily for basic data visualization and quality assessment done at the telescope while observing. The offline version of the data reduction system includes an expanded reduction method list, does more iterations for a better construction of the data cubes, and is used to produce publication-quality products. It can also use reconstruction matrices that are developed after the observations were taken, and are more refined. The KOA team is currently utilizing the standard offline reduction mode to produce quick-look browse products for the raw data. Users of the offline data reduction system generally use a graphical user interface to manually setup the reduction parameters. However, in order to reduce and serve the 200,000 science files on disk, all of the reduction parameters and steps need to be fully automated. This pipeline will also be used to automatically produce quick-look browse products for future OSIRIS data after each night's observations. Here we discuss the complexities of OSIRIS data, the reduction system in place, methods for automating the system, performance using virtualization, and progress made to date in generating the KOA products.

Reduction of inequalities in health: assessing evidence-based tools

Directory of Open Access Journals (Sweden)

Shea Beverley

2006-09-01

Full Text Available Abstract Background The reduction of health inequalities is a focus of many national and international health organisations. The need for pragmatic evidence-based approaches has led to the development of a number of evidence-based equity initiatives. This paper describes a new program that focuses upon evidence- based tools, which are useful for policy initiatives that reduce inequities. Methods This paper is based on a presentation that was given at the "Regional Consultation on Policy Tools: Equity in Population Health Reports," held in Toronto, Canada in June 2002. Results Five assessment tools were presented. 1. A database of systematic reviews on the effects of educational, legal, social, and health interventions to reduce unfair inequalities is being established through the Cochrane and Campbell Collaborations. 2 Decision aids and shared decision making can be facilitated in disadvantaged groups by 'health coaches' to help people become better decision makers, negotiators, and navigators of the health system; a pilot study in Chile has provided proof of this concept. 3. The CIET Cycle: Combining adapted cluster survey techniques with qualitative methods, CIET's population based applications support evidence-based decision making at local and national levels. The CIET map generates maps directly from survey or routine institutional data, to be used as evidence-based decisions aids. Complex data can be displayed attractively, providing an important tool for studying and comparing health indicators among and between different populations. 4. The Ottawa Equity Gauge is applying the Global Equity Gauge Alliance framework to an industrialised country setting. 5 The Needs-Based Health Assessment Toolkit, established to assemble information on which clinical and health policy decisions can be based, is being expanded to ensure a focus on distribution and average health indicators. Conclusion Evidence-based planning tools have much to offer the

THELI: CONVENIENT REDUCTION OF OPTICAL, NEAR-INFRARED, AND MID-INFRARED IMAGING DATA

International Nuclear Information System (INIS)

Schirmer, M.

2013-01-01

The last 15 years have seen a surge of new multi-chip optical and near-IR imagers. While some of them are accompanied by specific reduction pipelines, user-friendly and generic reduction tools are uncommon. In this paper I introduce THELI, an easy-to-use graphical interface driving an end-to-end pipeline for the reduction of any optical, near-IR, and mid-IR imaging data. The advantages of THELI when compared to other approaches are highlighted. Combining a multitude of processing algorithms and third party software, THELI provides researchers with a single, homogeneous tool. A short learning curve ensures quick success for new and more experienced observers alike. All tasks are largely automated, while at the same time a high level of flexibility and alternative reduction schemes ensure that widely different scientific requirements can be met. Over 90 optical and infrared instruments at observatories world-wide are pre-configured, while more can be added by the user. The Appendices contain three walk-through examples using public data (optical, near-IR, and mid-IR). Additional extensive documentation for training and troubleshooting is available online

U.S. Geological Survey community for data integration: data upload, registry, and access tool

Science.gov (United States)

,

2012-01-01

As a leading science and information agency and in fulfillment of its mission to provide reliable scientific information to describe and understand the Earth, the U.S. Geological Survey (USGS) ensures that all scientific data are effectively hosted, adequately described, and appropriately accessible to scientists, collaborators, and the general public. To succeed in this task, the USGS established the Community for Data Integration (CDI) to address data and information management issues affecting the proficiency of earth science research. Through the CDI, the USGS is providing data and metadata management tools, cyber infrastructure, collaboration tools, and training in support of scientists and technology specialists throughout the project life cycle. One of the significant tools recently created to contribute to this mission is the Uploader tool. This tool allows scientists with limited data management resources to address many of the key aspects of the data life cycle: the ability to protect, preserve, publish and share data. By implementing this application inside ScienceBase, scientists also can take advantage of other collaboration capabilities provided by the ScienceBase platform.

Training generalized improvisation of tools by preschool children1

Science.gov (United States)

Parsonson, Barry S.; Baer, Donald M.

1978-01-01

The development of new, “creative” behaviors was examined in a problem-solving context. One form of problem solving, improvisation, was defined as finding a substitute to replace the specifically designated, but currently unavailable, tool ordinarily used to solve the problem. The study examined whether preschool children spontaneously displayed generalized improvisation skills, and if not, whether they could be trained to do so within different classes of tools. Generalization across different tool classes was monitored but not specifically trained. Five preschool children participated in individual sessions that first probed their skill at improvising tools, and later trained and probed generalized improvisation in one or more of three tool classes (Hammers, Containers, and Shoelaces), using a multiple-baseline design. All five children were trained with Hammers, two were trained in two classes, and two were trained in all three tool classes. Four of the five children improvised little in Baseline. During Training, all five showed increased generalized improvisation within the trained class, but none across classes. Tools fabricated by item combinations were rare in Baseline, but common in Training. Followup probes showed that the training effects were durable. PMID:16795596

Randomized Comparison of Mobile and Web-Tools to Provide Dementia Risk Reduction Education: Use, Engagement and Participant Satisfaction.

Science.gov (United States)

O'Connor, Elodie; Farrow, Maree; Hatherly, Chris

2014-01-01

Encouraging middle-aged adults to maintain their physical and cognitive health may have a significant impact on reducing the prevalence of dementia in the future. Mobile phone apps and interactive websites may be one effective way to target this age group. However, to date there has been little research investigating the user experience of dementia risk reduction tools delivered in this way. The aim of this study was to explore participant engagement and evaluations of three different targeted smartphone and Web-based dementia risk reduction tools following a four-week intervention. Participants completed a Web-based screening questionnaire to collect eligibility information. Eligible participants were asked to complete a Web-based baseline questionnaire and were then randomly assigned to use one of the three dementia risk reduction tools for a period of four weeks: (1) a mobile phone application; (2) an information-based website; and (3) an interactive website. User evaluations were obtained via a Web-based follow-up questionnaire after completion of the intervention. Of 415 eligible participants, 370 (89.16%) completed the baseline questionnaire and were assigned to an intervention group; 200 (54.05%) completed the post-intervention questionnaire. The average age of participants was 52 years, and 149 (75%) were female. Findings indicated that participants from all three intervention groups reported a generally positive impression of the tools across a range of domains. Participants using the information-based website reported higher ratings of their overall impression of the tool, F2,191=4.12, P=.02; how interesting the information was, F2,189=3.53, P=.03; how helpful the information was, F2,192=4.15, P=.02; and how much they learned, F2,188=3.86, P=.02. Group differences were significant between the mobile phone app and information-based website users, but not between the interactive website users and the other two groups. Additionally, participants using the

Randomized Comparison of Mobile and Web-Tools to Provide Dementia Risk Reduction Education: Use, Engagement and Participant Satisfaction

Science.gov (United States)

O'Connor, Elodie; Hatherly, Chris

2014-01-01

Background Encouraging middle-aged adults to maintain their physical and cognitive health may have a significant impact on reducing the prevalence of dementia in the future. Mobile phone apps and interactive websites may be one effective way to target this age group. However, to date there has been little research investigating the user experience of dementia risk reduction tools delivered in this way. Objective The aim of this study was to explore participant engagement and evaluations of three different targeted smartphone and Web-based dementia risk reduction tools following a four-week intervention. Methods Participants completed a Web-based screening questionnaire to collect eligibility information. Eligible participants were asked to complete a Web-based baseline questionnaire and were then randomly assigned to use one of the three dementia risk reduction tools for a period of four weeks: (1) a mobile phone application; (2) an information-based website; and (3) an interactive website. User evaluations were obtained via a Web-based follow-up questionnaire after completion of the intervention. Results Of 415 eligible participants, 370 (89.16%) completed the baseline questionnaire and were assigned to an intervention group; 200 (54.05%) completed the post-intervention questionnaire. The average age of participants was 52 years, and 149 (75%) were female. Findings indicated that participants from all three intervention groups reported a generally positive impression of the tools across a range of domains. Participants using the information-based website reported higher ratings of their overall impression of the tool, F2,191=4.12, P=.02; how interesting the information was, F2,189=3.53, P=.03; how helpful the information was, F2,192=4.15, P=.02; and how much they learned, F2,188=3.86, P=.02. Group differences were significant between the mobile phone app and information-based website users, but not between the interactive website users and the other two groups

Consequent use of IT tools as a driver for cost reduction and quality improvements

Science.gov (United States)

Hein, Stefan; Rapp, Roberto; Feustel, Andreas

2013-10-01

The semiconductor industry drives a lot of efforts in the field of cost reductions and quality improvements. The consequent use of IT tools is one possibility to support these goals. With the extensions of its 150mm Fab to 200mm Robert Bosch increased the systematic use of data analysis and Advanced Process Control (APC).

MURMoT. Design and Application of Microbial Uranium Reduction Monitoring Tools

Energy Technology Data Exchange (ETDEWEB)

Loeffler, Frank E. [Univ. of Tennessee, Knoxville, TN (United States)

2014-12-31

Uranium (U) contamination in the subsurface is a major remediation challenge at many DOE sites. Traditional site remedies present enormous costs to DOE; hence, enhanced bioremediation technologies (i.e., biostimulation and bioaugmentation) combined with monitoring efforts are being considered as cost-effective corrective actions to address subsurface contamination. This research effort improved understanding of the microbial U reduction process and developed new tools for monitoring microbial activities. Application of these tools will promote science-based site management decisions that achieve contaminant detoxification, plume control, and long-term stewardship in the most efficient manner. The overarching hypothesis was that the design, validation and application of a suite of new molecular and biogeochemical tools advance process understanding, and improve environmental monitoring regimes to assess and predict in situ U immobilization. Accomplishments: This project (i) advanced nucleic acid-based approaches to elucidate the presence, abundance, dynamics, spatial distribution, and activity of metal- and radionuclide-detoxifying bacteria; (ii) developed proteomics workflows for detection of metal reduction biomarker proteins in laboratory cultures and contaminated site groundwater; (iii) developed and demonstrated the utility of U isotopic fractionation using high precision mass spectrometry to quantify U(VI) reduction for a range of reduction mechanisms and environmental conditions; and (iv) validated the new tools using field samples from U-contaminated IFRC sites, and demonstrated their prognostic and diagnostic capabilities in guiding decision making for environmental remediation and long-term site stewardship.

Simulated dose reduction by adding artificial noise to measured raw data: A validation study

International Nuclear Information System (INIS)

Soederberg, M.; Gunnarsson, M.; Nilsson, M.

2010-01-01

The purpose of this study was to verify and validate a noise simulation tool called Dose Tutor (VAMP GmbH) in terms of level and texture of the simulated noise. By adding artificial noise to measured computed tomography (CT) raw data, a scan acquired with a lower dose (mAs) than the actual one can be simulated. A homogeneous polyethylene phantom and an anthropomorphic chest phantom were scanned for different mAs levels, tube voltages, slice thicknesses and reconstruction kernels. The simulated noise levels were compared with the noise levels in real transverse slice images actually acquired with corresponding mAs values. In general, the noise comparisons showed acceptable agreement in magnitude (<20% deviation in pixel standard deviation). Also, the calculated noise power spectra were similar, which indicates that the noise texture is correctly reproduced. In conclusion, this study establishes that the Dose Tutor might be a useful tool for estimating the dose reduction potential for CT protocols. (authors)

Generalized data management systems and scientific information

International Nuclear Information System (INIS)

Anon.

1978-01-01

This report aims to stimulate scientists of all disciplines to consider the advantages of using a generalized data management system (GDMS) for storage, manipulation and retrieval of the data they collect and often need to share. It should also be of interest to managers and programmers who need to make decisions on the management of scientific (numeric or non-numeric) data. Another goal of this report is to expose the features that a GDMS should have which are specifically necessary to support scientific data, such as data types and special manipulation functions. A GDMS is a system that provides generalized tools for the purpose of defining a database structure, for loading the data, for modification of the data, and for organizing the database for efficient retrieval and formatted output. A data management system is 'generalized' when it provides a user-oriented language for the different functions, so that it is possible to define any new database, its internal organization, and to retrieve and modify the data without the need to develop special purpose software (program) for each new database

Data Mining and Optimization Tools for Developing Engine Parameters Tools

Science.gov (United States)

Dhawan, Atam P.

1998-01-01

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

SIMONE: Tool for Data Analysis and Simulation

International Nuclear Information System (INIS)

Chudoba, V.; Hnatio, B.; Sharov, P.; Papka, Paul

2013-06-01

SIMONE is a software tool based on the ROOT Data Analysis Framework and developed in collaboration of FLNR JINR and iThemba LABS. It is intended for physicists planning experiments and analysing experimental data. The goal of the SIMONE framework is to provide a flexible system, user friendly, efficient and well documented. It is intended for simulation of a wide range of Nuclear Physics experiments. The most significant conditions and physical processes can be taken into account during simulation of the experiment. The user can create his own experimental setup through the access of predefined detector geometries. Simulated data is made available in the same format as for the real experiment for identical analysis of both experimental and simulated data. Significant time reduction is expected during experiment planning and data analysis. (authors)

Principal Components as a Data Reduction and Noise Reduction Technique

Science.gov (United States)

Imhoff, M. L.; Campbell, W. J.

1982-01-01

The potential of principal components as a pipeline data reduction technique for thematic mapper data was assessed and principal components analysis and its transformation as a noise reduction technique was examined. Two primary factors were considered: (1) how might data reduction and noise reduction using the principal components transformation affect the extraction of accurate spectral classifications; and (2) what are the real savings in terms of computer processing and storage costs of using reduced data over the full 7-band TM complement. An area in central Pennsylvania was chosen for a study area. The image data for the project were collected using the Earth Resources Laboratory's thematic mapper simulator (TMS) instrument.

The Lives Saved Tool (LiST) as a model for diarrhea mortality reduction

Science.gov (United States)

2014-01-01

Background Diarrhea is a leading cause of morbidity and mortality among children under five years of age. The Lives Saved Tool (LiST) is a model used to calculate deaths averted or lives saved by past interventions and for the purposes of program planning when costly and time consuming impact studies are not possible. Discussion LiST models the relationship between coverage of interventions and outputs, such as stunting, diarrhea incidence and diarrhea mortality. Each intervention directly prevents a proportion of diarrhea deaths such that the effect size of the intervention is multiplied by coverage to calculate lives saved. That is, the maximum effect size could be achieved at 100% coverage, but at 50% coverage only 50% of possible deaths are prevented. Diarrhea mortality is one of the most complex causes of death to be modeled. The complexity is driven by the combination of direct prevention and treatment interventions as well as interventions that operate indirectly via the reduction in risk factors, such as stunting and wasting. Published evidence is used to quantify the effect sizes for each direct and indirect relationship. Several studies have compared measured changes in mortality to LiST estimates of mortality change looking at different sets of interventions in different countries. While comparison work has generally found good agreement between the LiST estimates and measured mortality reduction, where data availability is weak, the model is less likely to produce accurate results. LiST can be used as a component of program evaluation, but should be coupled with more complete information on inputs, processes and outputs, not just outcomes and impact. Summary LiST is an effective tool for modeling diarrhea mortality and can be a useful alternative to large and expensive mortality impact studies. Predicting the impact of interventions or comparing the impact of more than one intervention without having to wait for the results of large and expensive

Radwaste volume reduction and solidification by General Electric

International Nuclear Information System (INIS)

Green, T.A.; Weech, M.E.; Miller, G.P.; Eberle, J.W.

1982-01-01

Since 1978 General Electric has been actively engaged in developing a volume reduction and solidifcation system or treatment of radwaste generated in commercial nuclear power plants. The studies have been aimed at defining an integrated system that would be directly responsive to the rapid evolving needs of the industry for the volume reduction and solidification of low-level radwaste. The resulting General Electric Volume Reduction System (GEVRS) is an integrated system based on two processes: the first uses azeotropic distillation technology and is called AZTECH, and the second is controlled-air incineration...called INCA. The AZTECH process serves to remove water from concentrated salt solutions, ion exchange resins and filter sludge slurries and then encapsulates the dried solids into a dense plastic product. The INCA unit serves to reduce combustible wastes to ashes suitable for encapsulation into the same plastic product produced by AZTECH

Survey of Object-Based Data Reduction Techniques in Observational Astronomy

Directory of Open Access Journals (Sweden)

Łukasik Szymon

2016-01-01

Full Text Available Dealing with astronomical observations represents one of the most challenging areas of big data analytics. Besides huge variety of data types, dynamics related to continuous data flow from multiple sources, handling enormous volumes of data is essential. This paper provides an overview of methods aimed at reducing both the number of features/attributes as well as data instances. It concentrates on data mining approaches not related to instruments and observation tools instead working on processed object-based data. The main goal of this article is to describe existing datasets on which algorithms are frequently tested, to characterize and classify available data reduction algorithms and identify promising solutions capable of addressing present and future challenges in astronomy.

Robust methods for data reduction

CERN Document Server

Farcomeni, Alessio

2015-01-01

Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy

Data reduction in cascade impactor and sedimentation battery

International Nuclear Information System (INIS)

Boulaud, Denis; Diouri, Mohamed.

1982-07-01

The determination of the mass distribution of an aerosol from data collected by a cascade impactor or a sedimentation battery implies the size characterization of each impactor stage or each battery length. In the case of the impactor four data reduction methods were compared. Preinning and Picknett's methods, a simulation method and the wellknown effective cut off size method. A theoretical simulation showed that both the simulation and Picknett's methods were the best adapted to restituting a mass distribution with an uncertainty not exceeding 5% for the mass median diameter and 10% for the standard deviation. In the case of the sedimentation battery a new method was developed allowing data reduction when the analytical shape of the size distribution is known. A theoretical simulation was carried out in order to test our method. The test showed that this method was also adapted to restituting the distribution shape, however the size range covered by the sedimentation battery was generally smaller than that of the impactor [fr

Quantitative Risk reduction estimation Tool For Control Systems, Suggested Approach and Research Needs

Energy Technology Data Exchange (ETDEWEB)

Miles McQueen; Wayne Boyer; Mark Flynn; Sam Alessi

2006-03-01

For the past year we have applied a variety of risk assessment technologies to evaluate the risk to critical infrastructure from cyber attacks on control systems. More recently, we identified the need for a stand alone control system risk reduction estimation tool to provide owners and operators of control systems with a more useable, reliable, and credible method for managing the risks from cyber attack. Risk is defined as the probability of a successful attack times the value of the resulting loss, typically measured in lives and dollars. Qualitative and ad hoc techniques for measuring risk do not provide sufficient support for cost benefit analyses associated with cyber security mitigation actions. To address the need for better quantitative risk reduction models we surveyed previous quantitative risk assessment research; evaluated currently available tools; developed new quantitative techniques [17] [18]; implemented a prototype analysis tool to demonstrate how such a tool might be used; used the prototype to test a variety of underlying risk calculational engines (e.g. attack tree, attack graph); and identified technical and research needs. We concluded that significant gaps still exist and difficult research problems remain for quantitatively assessing the risk to control system components and networks, but that a useable quantitative risk reduction estimation tool is not beyond reach.

LOFT data reduction

International Nuclear Information System (INIS)

Norman, N.L.

1975-08-01

The Loss-of-Fluid Test (LOFT) Facility is an experimental facility built around a ''scaled'' version of a large pressurized water reactor (LPWR). LOFT will be used to run loss-of-coolant experiments (LOCEs) and to acquire the necessary data required ''to evaluate the adequacy and improve the analytical methods currently used to predict the loss-of-coolant accident (LOCA) response of LPWRs'' and ''to identify and investigate any unexpected event(s) or threshold(s) in the response of either the plant or the engineered safety features and develop analytical techniques that adequately describe and account for the unexpected behavior(s)''. During the LOCE this required data will be acquired and recorded in both analog and digital modes. Subsequent to the test the analog data will also be converted to the raw digital mode. This raw digital data will be converted to the desired engineering units using the LOFT Data Reduction System. This system is implemented on the IBM 360/75 and is a part of a commercially available data processing program called MAC/RAN III. The theory of reducing LOFT data to engineering units and the application of the MAC/ RAN III system to accomplish this reduction is given. (auth)

Simrank: Rapid and sensitive general-purpose k-mer search tool

Energy Technology Data Exchange (ETDEWEB)

DeSantis, T.Z.; Keller, K.; Karaoz, U.; Alekseyenko, A.V; Singh, N.N.S.; Brodie, E.L; Pei, Z.; Andersen, G.L; Larsen, N.

2011-04-01

Terabyte-scale collections of string-encoded data are expected from consortia efforts such as the Human Microbiome Project (http://nihroadmap.nih.gov/hmp). Intra- and inter-project data similarity searches are enabled by rapid k-mer matching strategies. Software applications for sequence database partitioning, guide tree estimation, molecular classification and alignment acceleration have benefited from embedded k-mer searches as sub-routines. However, a rapid, general-purpose, open-source, flexible, stand-alone k-mer tool has not been available. Here we present a stand-alone utility, Simrank, which allows users to rapidly identify database strings the most similar to query strings. Performance testing of Simrank and related tools against DNA, RNA, protein and human-languages found Simrank 10X to 928X faster depending on the dataset. Simrank provides molecular ecologists with a high-throughput, open source choice for comparing large sequence sets to find similarity.

Statistical and Visualization Data Mining Tools for Foundry Production

Directory of Open Access Journals (Sweden)

M. Perzyk

2007-07-01

Full Text Available In recent years a rapid development of a new, interdisciplinary knowledge area, called data mining, is observed. Its main task is extracting useful information from previously collected large amount of data. The main possibilities and potential applications of data mining in manufacturing industry are characterized. The main types of data mining techniques are briefly discussed, including statistical, artificial intelligence, data base and visualization tools. The statistical methods and visualization methods are presented in more detail, showing their general possibilities, advantages as well as characteristic examples of applications in foundry production. Results of the author’s research are presented, aimed at validation of selected statistical tools which can be easily and effectively used in manufacturing industry. A performance analysis of ANOVA and contingency tables based methods, dedicated for determination of the most significant process parameters as well as for detection of possible interactions among them, has been made. Several numerical tests have been performed using simulated data sets, with assumed hidden relationships as well some real data, related to the strength of ductile cast iron, collected in a foundry. It is concluded that the statistical methods offer relatively easy and fairly reliable tools for extraction of that type of knowledge about foundry manufacturing processes. However, further research is needed, aimed at explanation of some imperfections of the investigated tools as well assessment of their validity for more complex tasks.

The VIDA Framework as an Education Tool: Leveraging Volcanology Data for Educational Purposes

Science.gov (United States)

Faied, D.; Sanchez, A.

2009-04-01

The VIDA Framework as an Education Tool: Leveraging Volcanology Data for Educational Purposes Dohy Faied, Aurora Sanchez (on behalf of SSP08 VAPOR Project Team) While numerous global initiatives exist to address the potential hazards posed by volcanic eruption events and assess impacts from a civil security viewpoint, there does not yet exist a single, unified, international system of early warning and hazard tracking for eruptions. Numerous gaps exist in the risk reduction cycle, from data collection, to data processing, and finally dissemination of salient information to relevant parties. As part of the 2008 International Space University's Space Studies Program, a detailed gap analysis of the state of volcano disaster risk reduction was undertaken, and this paper presents the principal results. This gap analysis considered current sensor technologies, data processing algorithms, and utilization of data products by various international organizations. Recommendations for strategies to minimize or eliminate certain gaps are also provided. In the effort to address the gaps, a framework evolved at system level. This framework, known as VIDA, is a tool to develop user requirements for civil security in hazardous contexts, and a candidate system concept for a detailed design phase. While the basic intention of VIDA is to support disaster risk reduction efforts, there are several methods of leveraging raw science data to support education across a wide demographic. Basic geophysical data could be used to educate school children about the characteristics of volcanoes, satellite mappings could support informed growth and development of societies in at-risk areas, and raw sensor data could contribute to a wide range of university-level research projects. Satellite maps, basic geophysical data, and raw sensor data are combined and accessible in a way that allows the relationships between these data types to be explored and used in a training environment. Such a resource

Data Mining Tools in Science Education

OpenAIRE

Premysl Zaskodny

2012-01-01

The main principle of paper is Data Mining in Science Education (DMSE) as Problem Solving. The main goal of paper is consisting in Delimitation of Complex Data Mining Tool and Partial Data Mining Tool of DMSE. The procedure of paper is consisting of Data Preprocessing in Science Education, Data Processing in Science Education, Description of Curricular Process as Complex Data Mining Tool (CP-DMSE), Description of Analytical Synthetic Modeling as Partial Data Mining Tool (ASM-DMSE) and finally...

ORAC-DR: A generic data reduction pipeline infrastructure

Science.gov (United States)

Jenness, Tim; Economou, Frossie

2015-03-01

ORAC-DR is a general purpose data reduction pipeline system designed to be instrument and observatory agnostic. The pipeline works with instruments as varied as infrared integral field units, imaging arrays and spectrographs, and sub-millimeter heterodyne arrays and continuum cameras. This paper describes the architecture of the pipeline system and the implementation of the core infrastructure. We finish by discussing the lessons learned since the initial deployment of the pipeline system in the late 1990s.

Cancer Data and Statistics Tools

Science.gov (United States)

... Educational Campaigns Initiatives Stay Informed Cancer Data and Statistics Tools Recommend on Facebook Tweet Share Compartir Cancer Statistics Tools United States Cancer Statistics: Data Visualizations The ...

SNP_tools: A compact tool package for analysis and conversion of genotype data for MS-Excel.

Science.gov (United States)

Chen, Bowang; Wilkening, Stefan; Drechsel, Marion; Hemminki, Kari

2009-10-23

Single nucleotide polymorphism (SNP) genotyping is a major activity in biomedical research. Scientists prefer to have a facile access to the results which may require conversions between data formats. First hand SNP data is often entered in or saved in the MS-Excel format, but this software lacks genetic and epidemiological related functions. A general tool to do basic genetic and epidemiological analysis and data conversion for MS-Excel is needed. The SNP_tools package is prepared as an add-in for MS-Excel. The code is written in Visual Basic for Application, embedded in the Microsoft Office package. This add-in is an easy to use tool for users with basic computer knowledge (and requirements for basic statistical analysis). Our implementation for Microsoft Excel 2000-2007 in Microsoft Windows 2000, XP, Vista and Windows 7 beta can handle files in different formats and converts them into other formats. It is a free software.

Dunajski–Tod equation and reductions of the generalized dispersionless 2DTL hierarchy

Energy Technology Data Exchange (ETDEWEB)

Bogdanov, L.V., E-mail: leonid@landau.ac.ru [L.D. Landau ITP RAS, Moscow (Russian Federation)

2012-10-01

We transfer the scheme for constructing differential reductions recently developed for the Manakov–Santini hierarchy to the case of the two-component generalization of dispersionless 2DTL hierarchy. We demonstrate that the equation arising as a result of the simplest reduction is equivalent (up to a Legendre type transformation) to the Dunajski–Tod equation, locally describing general ASD vacuum metric with conformal symmetry. We consider higher reductions and corresponding reduced hierarchies also. -- Highlights: ► We introduce a differential reduction for the two-component d2DTL equation. ► We demonstrate that it is connected with ASD vacuum metric with conformal symmetry. ► We construct higher reductions and the reduced hierarchies.

MAGMA: generalized gene-set analysis of GWAS data.

Science.gov (United States)

de Leeuw, Christiaan A; Mooij, Joris M; Heskes, Tom; Posthuma, Danielle

2015-04-01

By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn's Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn's Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn's Disease data was found to be considerably faster as well.

EPR design tools. Integrated data processing tools

International Nuclear Information System (INIS)

Kern, R.

1997-01-01

In all technical areas, planning and design have been supported by electronic data processing for many years. New data processing tools had to be developed for the European Pressurized Water Reactor (EPR). The work to be performed was split between KWU and Framatome and laid down in the Basic Design contract. The entire plant was reduced to a logical data structure; the circuit diagrams and flowsheets of the systems were drafted, the central data pool was established, the outlines of building structures were defined, the layout of plant components was planned, and the electrical systems were documented. Also building construction engineering was supported by data processing. The tasks laid down in the Basic Design were completed as so-called milestones. Additional data processing tools also based on the central data pool are required for the phases following after the Basic Design phase, i.e Basic Design Optimization; Detailed Design; Management; Construction, and Commissioning. (orig.) [de

Parallel Enhancements of the General Mission Analysis Tool, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The General Mission Analysis Tool (GMAT) is a state of the art spacecraft mission design tool under active development at NASA's Goddard Space Flight Center (GSFC)....

Acquisition and reduction of data obtained from Tank 101-SY in-situ ball rheometer

International Nuclear Information System (INIS)

Shepard, C.L.; Chieda, M.A.; Kirihara, L.J.

1994-12-01

Development of the ball rheometer to measure rheological properties and density of the waste in Hanford Tank 241-SY-101 will be completed around September 1994. Since the ball rheometer project began, a mixer pump has been installed in this tank, and by all accounts this pump has been very successful at mitigating the flammable gas problem associated with Tank 101-SY. Present plans now call for the use of mixer pumps in several other tanks. The ball rheometer will serve as a diagnostic tool for judging the effectiveness of mixing in Tank 101-SY and others and will be one of few in-situ probes available for diagnostic measurements. The in-situ data collection strategy and the methods of data analysis and reduction are presented in this final report concerning this instrument. It is believed that a generalized Bingham fluid model (Herschel-Bulkley fluid model) may be useful for describing at least some of the waste contained in Tank 101-SY, and data obtained in the tank will initially be reduced using this fluid model. The single largest uncertainty in the determination of the drag force on the ball is the drag force which will be experienced by the cable attached to the ball. This drag can be a substantial fraction of the total drag when the ball is deep within the tank. Careful accounting of the cable drag will be important in the reduction of the data. The data collection strategy allows the determination of the waste fluid rheology both in the undisturbed state and after it has been disturbed by the ball. Fluid density will be measured at regular intervals

Uranium tetrafluoride reduction closed bomb. Part I: Reduction process general conditions

International Nuclear Information System (INIS)

Anca Abati, R.; Lopez Rodriguez, M.

1961-01-01

General conditions about the metallo thermic reduction in small bombs (250 and 800 gr. of uranium) has been investigated. Factors such as kind and granulometry of the magnesium used, magnesium excess and preheating temperature, which affect yields and metal quality have been considered. magnesium excess increased yields in a 15% in the small bomb, about the preheating temperature, there is a range between which yields and metal quality does not change. All tests have been made with graphite linings. (Author) 18 refs

Data-Driven Model Reduction and Transfer Operator Approximation

Science.gov (United States)

Klus, Stefan; Nüske, Feliks; Koltai, Péter; Wu, Hao; Kevrekidis, Ioannis; Schütte, Christof; Noé, Frank

2018-06-01

In this review paper, we will present different data-driven dimension reduction techniques for dynamical systems that are based on transfer operator theory as well as methods to approximate transfer operators and their eigenvalues, eigenfunctions, and eigenmodes. The goal is to point out similarities and differences between methods developed independently by the dynamical systems, fluid dynamics, and molecular dynamics communities such as time-lagged independent component analysis, dynamic mode decomposition, and their respective generalizations. As a result, extensions and best practices developed for one particular method can be carried over to other related methods.

Data Tools and Apps

Science.gov (United States)

Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My ). Business Dynamics Statistics This tool shows tabulations on establishments, firms, and employment with

New data libraries and physics data management tools

International Nuclear Information System (INIS)

Han, M; Kim, C H; Seo, H; Pia, M G; Saracco, P; Augelli, M; Hauf, S; Kuster, M; Moneta, L; Quintieri, L

2011-01-01

A number of physics data libraries for Monte Carlo simulation are reviewed. The development of a package for the management of physics data is described: its design, implementation and computational benchmarks. This package improves the data management tools originally developed for Geant4 electromagnetic physics models based on data libraries. The implementation exploits recent evolutions of the C++ libraries appearing in the C++0x draft, which are intended for inclusion in the next C++ ISO Standard. The new tools improve the computational performance of physics data management.

Historic Landslide Data Combined with Sentinel Satellite Data to Improve Modelling for Disaster Risk Reduction

Science.gov (United States)

Bye, B. L.; Kontoes, C.; Catarino, N.; De Lathouwer, B.; Concalves, P.; Meyer-Arnek, J.; Mueller, A.; Kraft, C.; Grosso, N.; Goor, E.; Voidrot, M. F.; Trypitsidis, A.

2017-12-01

Landslides are geohazards potentially resulting in disasters. Landslides both vary enormously in their distribution in space and time. The surface deformation varies considerably from one type of instability to another. Individual ground instabilities may have a common trigger (extreme rainfall, earthquake), and therefore occur alongside many equivalent occurrences over a large area. This means that they can have a significant regional impact demanding national and international disaster risk reduction strategies. Regional impacts require collaboration across boarders as reflected in The Sendai Framework for Disaster Risk Reduction (2015-2030). The data demands related to the SDGs are unprecedented, another factor that will require coordinated efforts at the global, regional and national levels. Data of good quality are vital for governments, international organizations, civil society, the private sector and the general public in order to make informed decisions, included for disaster risk reduction. The NextGEOSS project evolves the European vision of a user driven GEOSS data exploitation for innovation and business, relying on 3 main pillars; engaging communities of practice, delivering technological advancements, and advocating the use of GEOSS. These 3 pillars support the creation and deployment of Earth observation based innovative research activities and commercial services. In this presentation we will explain how one of the 10 NextGEOSS pilots, Disaster Risk Reduction (DRR), plan to provide an enhanced multi-hazard risk assessment framework based on statistical analysis of long time series of data. Landslide events monitoring and landslides susceptibility estimation will be emphazised. Workflows will be based on models developed in the context of the Copernicus Emergency Management Service. Data envisaged to be used are: Radar SAR data; Yearly ground deformation/velocities; Historic landslide inventory; data related to topographic, geological, hydrological

Automated data reduction for optical interferometric data

International Nuclear Information System (INIS)

Boyd, R.D.; Miller, D.J.; Ghiglia, D.C.

1983-01-01

The potential for significant progress in understanding many transport processes exists through the use of a rapid and automated data reduction process of optical interferometric data. An example involving natural convection in a horizontal annulus is used to demonstrate that the accuracy possible in automated techniques is better than 99.0%

Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

Science.gov (United States)

Sumner, Jeremy G

2017-03-01

We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

Big Data Visualization Tools

OpenAIRE

Bikakis, Nikos

2018-01-01

Data visualization is the presentation of data in a pictorial or graphical format, and a data visualization tool is the software that generates this presentation. Data visualization provides users with intuitive means to interactively explore and analyze data, enabling them to effectively identify interesting patterns, infer correlations and causalities, and supports sense-making activities.

LDRD report nonlinear model reduction

Energy Technology Data Exchange (ETDEWEB)

Segalman, D.; Heinstein, M.

1997-09-01

The very general problem of model reduction of nonlinear systems was made tractable by focusing on the very large subclass consisting of linear subsystems connected by nonlinear interfaces. Such problems constitute a large part of the nonlinear structural problems encountered in addressing the Sandia missions. A synthesis approach to this class of problems was developed consisting of: detailed modeling of the interface mechanics; collapsing the interface simulation results into simple nonlinear interface models; constructing system models by assembling model approximations of the linear subsystems and the nonlinear interface models. These system models, though nonlinear, would have very few degrees of freedom. A paradigm problem, that of machine tool vibration, was selected for application of the reduction approach outlined above. Research results achieved along the way as well as the overall modeling of a specific machine tool have been very encouraging. In order to confirm the interface models resulting from simulation, it was necessary to develop techniques to deduce interface mechanics from experimental data collected from the overall nonlinear structure. A program to develop such techniques was also pursued with good success.

Generalized Nuclear Data: A New Structure (with Supporting Infrastructure) for Handling Nuclear Data

International Nuclear Information System (INIS)

Mattoon, C.M.; Beck, B.R.; Patel, N.R.; Summers, N.C.; Hedstrom, G.W.; Brown, D.A.

2012-01-01

The Evaluated Nuclear Data File (ENDF) format was designed in the 1960s to accommodate neutron reaction data to support nuclear engineering applications in power, national security and criticality safety. Over the years, the scope of the format has been extended to handle many other kinds of data including charged particle, decay, atomic, photo-nuclear and thermal neutron scattering. Although ENDF has wide acceptance and support for many data types, its limited support for correlated particle emission, limited numeric precision, and general lack of extensibility mean that the nuclear data community cannot take advantage of many emerging opportunities. More generally, the ENDF format provides an unfriendly environment that makes it difficult for new data evaluators and users to create and access nuclear data. The Cross Section Evaluation Working Group (CSEWG) has begun the design of a new Generalized Nuclear Data (or 'GND') structure, meant to replace older formats with a hierarchy that mirrors the underlying physics, and is aligned with modern coding and database practices. In support of this new structure, Lawrence Livermore National Laboratory (LLNL) has updated its nuclear data/reactions management package Fudge to handle GND structured nuclear data. Fudge provides tools for converting both the latest ENDF format (ENDF-6) and the LLNL Evaluated Nuclear Data Library (ENDL) format to and from GND, as well as for visualizing, modifying and processing (i.e., converting evaluated nuclear data into a form more suitable to transport codes) GND structured nuclear data. GND defines the structure needed for storing nuclear data evaluations and the type of data that needs to be stored. But unlike ENDF and ENDL, GND does not define how the data are to be stored in a file. Currently, Fudge writes the structured GND data to a file using the eXtensible Markup Language (XML), as it is ASCII based and can be viewed with any text editor. XML is a meta-language, meaning that it

Generalized Nuclear Data: A New Structure (with Supporting Infrastructure) for Handling Nuclear Data

Energy Technology Data Exchange (ETDEWEB)

Mattoon, C.M. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore CA (United States); Beck, B.R.; Patel, N.R.; Summers, N.C.; Hedstrom, G.W. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore CA (United States); Brown, D.A. [National Nuclear Data Center, Upton NY (United States)

2012-12-15

The Evaluated Nuclear Data File (ENDF) format was designed in the 1960s to accommodate neutron reaction data to support nuclear engineering applications in power, national security and criticality safety. Over the years, the scope of the format has been extended to handle many other kinds of data including charged particle, decay, atomic, photo-nuclear and thermal neutron scattering. Although ENDF has wide acceptance and support for many data types, its limited support for correlated particle emission, limited numeric precision, and general lack of extensibility mean that the nuclear data community cannot take advantage of many emerging opportunities. More generally, the ENDF format provides an unfriendly environment that makes it difficult for new data evaluators and users to create and access nuclear data. The Cross Section Evaluation Working Group (CSEWG) has begun the design of a new Generalized Nuclear Data (or 'GND') structure, meant to replace older formats with a hierarchy that mirrors the underlying physics, and is aligned with modern coding and database practices. In support of this new structure, Lawrence Livermore National Laboratory (LLNL) has updated its nuclear data/reactions management package Fudge to handle GND structured nuclear data. Fudge provides tools for converting both the latest ENDF format (ENDF-6) and the LLNL Evaluated Nuclear Data Library (ENDL) format to and from GND, as well as for visualizing, modifying and processing (i.e., converting evaluated nuclear data into a form more suitable to transport codes) GND structured nuclear data. GND defines the structure needed for storing nuclear data evaluations and the type of data that needs to be stored. But unlike ENDF and ENDL, GND does not define how the data are to be stored in a file. Currently, Fudge writes the structured GND data to a file using the eXtensible Markup Language (XML), as it is ASCII based and can be viewed with any text editor. XML is a meta-language, meaning that it

Present status of the 4-m ILMT data reduction pipeline: application to space debris detection and characterization

Science.gov (United States)

Pradhan, Bikram; Delchambre, Ludovic; Hickson, Paul; Akhunov, Talat; Bartczak, Przemyslaw; Kumar, Brajesh; Surdej, Jean

2018-04-01

The 4-m International Liquid Mirror Telescope (ILMT) located at the ARIES Observatory (Devasthal, India) has been designed to scan at a latitude of +29° 22' 26" a band of sky having a width of about half a degree in the Time Delayed Integration (TDI) mode. Therefore, a special data-reduction and analysis pipeline to process online the large amount of optical data being produced has been dedicated to it. This requirement has led to the development of the 4-m ILMT data reduction pipeline, a new software package built with Python in order to simplify a large number of tasks aimed at the reduction of the acquired TDI images. This software provides astronomers with specially designed data reduction functions, astrometry and photometry calibration tools. In this paper we discuss the various reduction and calibration steps followed to reduce TDI images obtained in May 2015 with the Devasthal 1.3m telescope. We report here the detection and characterization of nine space debris present in the TDI frames.

Mathematical tools for data mining set theory, partial orders, combinatorics

CERN Document Server

Simovici, Dan A

2014-01-01

Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. Topics include partially ordered sets, combinatorics, general topology, metric spaces, linear spaces, graph theory. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc. The book is intended as a reference for researchers and graduate students. The current edition is a significant expansion of the firs

Data-base tools for enhanced analysis of TMX-U data

International Nuclear Information System (INIS)

Stewart, M.E.; Carter, M.R.; Casper, T.A.; Meyer, W.H.; Perkins, D.E.; Whitney, D.M.

1986-01-01

The authors use a commercial data-base software package to create several data-base products that enhance the ability of experimental physicists to analyze data from the TMX-U experiment. This software resides on a Dec-20 computer in M-Divisions's user service center (USC), where data can be analyzed separately from the main acquisition computers. When these data-base tools are combined with interactive data analysis programs, physicists can perform automated (batch-style) processing or interactive data analysis on the computers in the USC or on the supercomputers of the NMFECC, in addition to the normal processing done on the acquisition system. One data-base tool provides highly reduced data for searching and correlation analysis of several diagnostic signals for a single shot or many shots. A second data-base tool provides retrieval and storage of unreduced data for detailed analysis of one or more diagnostic signals. The authors report how these data-base tools form the core of an evolving off-line data-analysis environment on the USC computers

Rubin's CMS reduction method for general state-space models

NARCIS (Netherlands)

Kraker, de A.; Campen, van D.H.

1996-01-01

In this paper the Rubin CMS procedure for the reduction and successive coupling of undamped structural subsystems with symmetric system matrices will be modified for the case of general damping. The final coordinate transformation is based on the use of complex (residual) flexibility modes,

Python tools for rapid development, calibration, and analysis of generalized groundwater-flow models

Science.gov (United States)

Starn, J. J.; Belitz, K.

2014-12-01

National-scale water-quality data sets for the United States have been available for several decades; however, groundwater models to interpret these data are available for only a small percentage of the country. Generalized models may be adequate to explain and project groundwater-quality trends at the national scale by using regional scale models (defined as watersheds at or between the HUC-6 and HUC-8 levels). Coast-to-coast data such as the National Hydrologic Dataset Plus (NHD+) make it possible to extract the basic building blocks for a model anywhere in the country. IPython notebooks have been developed to automate the creation of generalized groundwater-flow models from the NHD+. The notebook format allows rapid testing of methods for model creation, calibration, and analysis. Capabilities within the Python ecosystem greatly speed up the development and testing of algorithms. GeoPandas is used for very efficient geospatial processing. Raster processing includes the Geospatial Data Abstraction Library and image processing tools. Model creation is made possible through Flopy, a versatile input and output writer for several MODFLOW-based flow and transport model codes. Interpolation, integration, and map plotting included in the standard Python tool stack also are used, making the notebook a comprehensive platform within on to build and evaluate general models. Models with alternative boundary conditions, number of layers, and cell spacing can be tested against one another and evaluated by using water-quality data. Novel calibration criteria were developed by comparing modeled heads to land-surface and surface-water elevations. Information, such as predicted age distributions, can be extracted from general models and tested for its ability to explain water-quality trends. Groundwater ages then can be correlated with horizontal and vertical hydrologic position, a relation that can be used for statistical assessment of likely groundwater-quality conditions

Methods and tools for big data visualization

OpenAIRE

Zubova, Jelena; Kurasova, Olga

2015-01-01

In this paper, methods and tools for big data visualization have been investigated. Challenges faced by the big data analysis and visualization have been identified. Technologies for big data analysis have been discussed. A review of methods and tools for big data visualization has been done. Functionalities of the tools have been demonstrated by examples in order to highlight their advantages and disadvantages.

Reduction Mammoplasty: A Comparison Between Operations Performed by Plastic Surgery and General Surgery.

Science.gov (United States)

Kordahi, Anthony M; Hoppe, Ian C; Lee, Edward S

2015-01-01

Reduction mammoplasty is an often-performed procedure by plastic surgeons and increasingly by general surgeons. The question has been posed in both general surgical literature and plastic surgical literature as to whether this procedure should remain the domain of surgical specialists. Some general surgeons are trained in breast reductions, whereas all plastic surgeons receive training in this procedure. The National Surgical Quality Improvement Project provides a unique opportunity to compare the 2 surgical specialties in an unbiased manner in terms of preoperative comorbidities and 30-day postoperative complications. The National Surgical Quality Improvement Project database was queried for the years 2005-2012. Patients were identified as having undergone a reduction mammoplasty by Current Procedural Terminology codes. RESULTS were refined to include only females with an International Classification of Diseases, Ninth Revision, code of 611.1 (hypertrophy of breasts). Information was collected regarding age, surgical specialty performing procedure, body mass index, and other preoperative variables. The outcomes utilized were presence of superficial surgical site infection, presence of deep surgical site infection, presence of wound dehiscence, postoperative respiratory compromise, pulmonary embolism, deep vein thrombosis, perioperative transfusion, operative time, reintubation, reoperation, and length of hospital stay. During this time period, there were 6239 reduction mammaplasties performed within the National Surgical Quality Improvement Project database: 339 by general surgery and 5900 by plastic surgery. No statistical differences were detected between the 2 groups with regard to superficial wound infections, deep wound infections, organ space infections, or wound dehiscence. There were no significant differences noted between within groups with regard to systemic postoperative complications. Patients undergoing a procedure by general surgery were more likely

Review of ATLAS Open Data 8 TeV datasets, tools and activities

CERN Document Server

The ATLAS collaboration

2018-01-01

The ATLAS Collaboration has released two 8 TeV datasets and relevant simulated samples to the public for educational use. A number of groups within ATLAS have used these ATLAS Open Data 8 TeV datasets, developing tools and educational material to promote particle physics. The general aim of these activities is to provide simple and user-friendly interactive interfaces to simulate the procedures used by high-energy physics researchers. International Masterclasses introduce particle physics to high school students and have been studying 8 TeV ATLAS Open Data since 2015. Inspired by this success, a new ATLAS Open Data initiative was launched in 2016 for university students. A comprehensive educational platform was thus developed featuring a second 8 TeV dataset and a new set of educational tools. The 8 TeV datasets and associated tools are presented and discussed here, as well as a selection of activities studying the ATLAS Open Data 8 TeV datasets.

Digitalising the General Data Protection Regulation with Dynamic Condition Response Graphs

DEFF Research Database (Denmark)

Heuck, Emil; Hildebrandt, Thomas; Kiærulff Lerche, Rasmus

2017-01-01

We describe how the declarative Dynamic Condition Response (DCR) Graphs proces notation can be used to digitalise the General Data Protection Regulation (GDPR) and make a first evaluation to what extend the formalisation and associated tool for end-user modelling and simulation can be used to cla...

Visualization of scientific data for high energy physics: PAW, a general-purpose portable software tool for data analysis and presentation

International Nuclear Information System (INIS)

Brun, R.; Couet, O.; Vandoni, C.E.; Zanarini, P.

1990-01-01

Visualization of scientific data although a fashionable word in the world of computer graphics, is not a new invention, but it is hundreds years old. With the advent of computer graphics the visualization of Scientific Data has now become a well understood and widely used technology, with hundreds of applications in the most different fields, ranging from media applications to real scientific ones. In the present paper, we shall discuss the design concepts of the Visualization of Scientific Data systems in particular in the specific field of High Energy Physics. During the last twenty years, CERN has played a leading role as the focus for development of packages and software libraries to solve problems related to High Energy Physics (HEP). The results of the integration of resources from many different Laboratories can be expressed in several million lines of code written at CERN during this period of time, used at CERN and distributed to collaborating laboratories. Nowadays, this role of software developer is considered very important by the entire HEP community. In this paper a large software package, where man-machine interaction and graphics play a key role (PAW-Physics Analysis Workstation), is described. PAW is essentially an interactive system which includes many different software tools, strongly oriented towards data analysis and data presentation. Some of these tools have been available in different forms and with different human interfaces for several years. 6 figs

UniPOPS: Unified data reduction suite

Science.gov (United States)

Maddalena, Ronald J.; Garwood, Robert W.; Salter, Christopher J.; Stobie, Elizabeth B.; Cram, Thomas R.; Morgan, Lorrie; Vance, Bob; Hudson, Jerome

2015-03-01

UniPOPS, a suite of programs and utilities developed at the National Radio Astronomy Observatory (NRAO), reduced data from the observatory's single-dish telescopes: the Tucson 12-m, the Green Bank 140-ft, and archived data from the Green Bank 300-ft. The primary reduction programs, 'line' (for spectral-line reduction) and 'condar' (for continuum reduction), used the People-Oriented Parsing Service (POPS) as the command line interpreter. UniPOPS unified previous analysis packages and provided new capabilities; development of UniPOPS continued within the NRAO until 2004 when the 12-m was turned over to the Arizona Radio Observatory (ARO). The submitted code is version 3.5 from 2004, the last supported by the NRAO.

Musite, a tool for global prediction of general and kinase-specific phosphorylation sites.

Science.gov (United States)

Gao, Jianjiong; Thelen, Jay J; Dunker, A Keith; Xu, Dong

2010-12-01

Reversible protein phosphorylation is one of the most pervasive post-translational modifications, regulating diverse cellular processes in various organisms. High throughput experimental studies using mass spectrometry have identified many phosphorylation sites, primarily from eukaryotes. However, the vast majority of phosphorylation sites remain undiscovered, even in well studied systems. Because mass spectrometry-based experimental approaches for identifying phosphorylation events are costly, time-consuming, and biased toward abundant proteins and proteotypic peptides, in silico prediction of phosphorylation sites is potentially a useful alternative strategy for whole proteome annotation. Because of various limitations, current phosphorylation site prediction tools were not well designed for comprehensive assessment of proteomes. Here, we present a novel software tool, Musite, specifically designed for large scale predictions of both general and kinase-specific phosphorylation sites. We collected phosphoproteomics data in multiple organisms from several reliable sources and used them to train prediction models by a comprehensive machine-learning approach that integrates local sequence similarities to known phosphorylation sites, protein disorder scores, and amino acid frequencies. Application of Musite on several proteomes yielded tens of thousands of phosphorylation site predictions at a high stringency level. Cross-validation tests show that Musite achieves some improvement over existing tools in predicting general phosphorylation sites, and it is at least comparable with those for predicting kinase-specific phosphorylation sites. In Musite V1.0, we have trained general prediction models for six organisms and kinase-specific prediction models for 13 kinases or kinase families. Although the current pretrained models were not correlated with any particular cellular conditions, Musite provides a unique functionality for training customized prediction models

Data Integration Tool: From Permafrost Data Translation Research Tool to A Robust Research Application

Science.gov (United States)

Wilcox, H.; Schaefer, K. M.; Jafarov, E. E.; Strawhacker, C.; Pulsifer, P. L.; Thurmes, N.

2016-12-01

The United States National Science Foundation funded PermaData project led by the National Snow and Ice Data Center (NSIDC) with a team from the Global Terrestrial Network for Permafrost (GTN-P) aimed to improve permafrost data access and discovery. We developed a Data Integration Tool (DIT) to significantly speed up the time of manual processing needed to translate inconsistent, scattered historical permafrost data into files ready to ingest directly into the GTN-P. We leverage this data to support science research and policy decisions. DIT is a workflow manager that divides data preparation and analysis into a series of steps or operations called widgets. Each widget does a specific operation, such as read, multiply by a constant, sort, plot, and write data. DIT allows the user to select and order the widgets as desired to meet their specific needs. Originally it was written to capture a scientist's personal, iterative, data manipulation and quality control process of visually and programmatically iterating through inconsistent input data, examining it to find problems, adding operations to address the problems, and rerunning until the data could be translated into the GTN-P standard format. Iterative development of this tool led to a Fortran/Python hybrid then, with consideration of users, licensing, version control, packaging, and workflow, to a publically available, robust, usable application. Transitioning to Python allowed the use of open source frameworks for the workflow core and integration with a javascript graphical workflow interface. DIT is targeted to automatically handle 90% of the data processing for field scientists, modelers, and non-discipline scientists. It is available as an open source tool in GitHub packaged for a subset of Mac, Windows, and UNIX systems as a desktop application with a graphical workflow manager. DIT was used to completely translate one dataset (133 sites) that was successfully added to GTN-P, nearly translate three datasets

TeraTools: Multiparameter data acquisition software for the Windows 95/NT OS

International Nuclear Information System (INIS)

Piercey, R.B.

1997-01-01

TeraTools, a general purpose, multiparameter, data acquisition application for Windows 95NT is described. It is based on the Kmax architecture which has been used since 1986 on the Macintosh computer at numerous industrial, education, and research sites world-wide. TeraTools includes high-level support for industry-standard modular instrumentation; a built-in scripting language; drivers for commercially available interfaces; hooks for external code extensions; event file sorting and replay; and a full set of histogramming and display tools. The environment is scalable and may be applied to problems involving a few parameters or many parameters

Data Integration Tool: Permafrost Data Debugging

Science.gov (United States)

Wilcox, H.; Schaefer, K. M.; Jafarov, E. E.; Pulsifer, P. L.; Strawhacker, C.; Yarmey, L.; Basak, R.

2017-12-01

We developed a Data Integration Tool (DIT) to significantly speed up the time of manual processing needed to translate inconsistent, scattered historical permafrost data into files ready to ingest directly into the Global Terrestrial Network-Permafrost (GTN-P). The United States National Science Foundation funded this project through the National Snow and Ice Data Center (NSIDC) with the GTN-P to improve permafrost data access and discovery. We leverage this data to support science research and policy decisions. DIT is a workflow manager that divides data preparation and analysis into a series of steps or operations called widgets (https://github.com/PermaData/DIT). Each widget does a specific operation, such as read, multiply by a constant, sort, plot, and write data. DIT allows the user to select and order the widgets as desired to meet their specific needs, incrementally interact with and evolve the widget workflows, and save those workflows for reproducibility. Taking ideas from visual programming found in the art and design domain, debugging and iterative design principles from software engineering, and the scientific data processing and analysis power of Fortran and Python it was written for interactive, iterative data manipulation, quality control, processing, and analysis of inconsistent data in an easily installable application. DIT was used to completely translate one dataset (133 sites) that was successfully added to GTN-P, nearly translate three datasets (270 sites), and is scheduled to translate 10 more datasets ( 1000 sites) from the legacy inactive site data holdings of the Frozen Ground Data Center (FGDC). Iterative development has provided the permafrost and wider scientific community with an extendable tool designed specifically for the iterative process of translating unruly data.

ESO Reflex: A Graphical Workflow Engine for Data Reduction

Science.gov (United States)

Hook, R.; Romaniello, M.; Péron, M.; Ballester, P.; Gabasch, A.; Izzo, C.; Ullgrén, M.; Maisala, S.; Oittinen, T.; Solin, O.; Savolainen, V.; Järveläinen, P.; Tyynelä, J.

2008-08-01

Sampo {http://www.eso.org/sampo} (Hook et al. 2005) is a project led by ESO and conducted by a software development team from Finland as an in-kind contribution to joining ESO. The goal is to assess the needs of the ESO community in the area of data reduction environments and to create pilot software products that illustrate critical steps along the road to a new system. Those prototypes will not only be used to validate concepts and understand requirements but will also be tools of immediate value for the community. Most of the raw data produced by ESO instruments can be reduced using CPL {http://www.eso.org/cpl} recipes: compiled C programs following an ESO standard and utilizing routines provided by the Common Pipeline Library. Currently reduction recipes are run in batch mode as part of the data flow system to generate the input to the ESO VLT/VLTI quality control process and are also made public for external users. Sampo has developed a prototype application called ESO Reflex {http://www.eso.org/sampo/reflex/} that integrates a graphical user interface and existing data reduction algorithms. ESO Reflex can invoke CPL-based recipes in a flexible way through a dedicated interface. ESO Reflex is based on the graphical workflow engine Taverna {http://taverna.sourceforge.net} that was originally developed by the UK eScience community, mostly for work in the life sciences. Workflows have been created so far for three VLT/VLTI instrument modes ( VIMOS/IFU {http://www.eso.org/instruments/vimos/}, FORS spectroscopy {http://www.eso.org/instruments/fors/} and AMBER {http://www.eso.org/instruments/amber/}), and the easy-to-use GUI allows the user to make changes to these or create workflows of their own. Python scripts and IDL procedures can be easily brought into workflows and a variety of visualisation and display options, including custom product inspection and validation steps, are available.

An Integrable Discrete Generalized Nonlinear Schrödinger Equation and Its Reductions

International Nuclear Information System (INIS)

Li Hong-Min; Li Yu-Qi; Chen Yong

2014-01-01

An integrable discrete system obtained by the algebraization of the difference operator is studied. The system is named discrete generalized nonlinear Schrödinger (GNLS) equation, which can be reduced to classical discrete nonlinear Schrödinger (NLS) equation. Furthermore, all of the linear reductions for the discrete GNLS equation are given through the theory of circulant matrices and the discrete NLS equation is obtained by one of the reductions. At the same time, the recursion operator and symmetries of continuous GNLS equation are successfully recovered by its corresponding discrete ones. (general)

Science data, tools and services available from NSIDC

Science.gov (United States)

Gergely, K.; Sheffield, E.

2011-12-01

While the name may be narrow in focus, the National Snow and Ice Data Center archives, distributes and supports data from many scientific disciplines. It is true that the majority of our holdings are on snow, sea ice, glaciers, ice sheets, and other cryospheric parameters. These are complimented by holdings on soil moisture, ocean data, global altimeter data, and human observations of environmental change, among other data. We facilitate access and use of our data through various tools, subsetters, and visualizing interfaces, and complete the package with a staff of hands-on user support specialists, available by email or phone to assist users with questions about our data and services. Based on user questions about general cryospheric physical processes over the past 35 years, we created a suite of online educational information on our areas of research, including snow, glaciers, sea ice, frozen ground, and others material of interest to the citizen scientist. Our excellent customer service has been noted on a widely distributed annual user survey.

Data governance tools evaluation criteria, big data governance, and alignment with enterprise data management

CERN Document Server

Soares, Sunil

2015-01-01

Data governance programs often start off using programs such as Microsoft Excel and Microsoft SharePoint to document and share data governance artifacts. But these tools often lack critical functionality. Meanwhile, vendors have matured their data governance offerings to the extent that today's organizations need to consider tools as a critical component of their data governance programs. In this book, data governance expert Sunil Soares reviews the Enterprise Data Management (EDM) reference architecture and discusses key data governance tasks that can be automated by tools for business glossa

The Influence of Tool Texture on Friction and Lubrication in Strip Reduction Testing

DEFF Research Database (Denmark)

Sulaiman, Mohd Hafis Bin; Christiansen, Peter; Bay, Niels Oluf

2017-01-01

While texturing of workpiece surfaces to promote lubrication in metal forming has beenapplied for several decades, tool surface texturing is rather new. In the present paper, tool texturing is studied as a method to prevent galling. A strip reduction test was conducted with tools provided...... with shallow, longitudinal pockets oriented perpendicular to the sliding direction. The pockets had small angles to the workpiece surface and the distance between them were varied. The experiments reveal that the distance between pockets should be larger than the pocket width, thereby creating a topography...... similar to flat table mountains to avoid mechanical interlocking in the valleys; otherwise, an increase in drawing load and pick-up on the tools are observed. The textured tool surface lowers friction and improves lubrication performance, provided that the distance between pockets is 2–4 times larger than...

Application of the GEM Inventory Data Capture Tools for Dynamic Vulnerability Assessment and Recovery Modelling

Science.gov (United States)

Verrucci, Enrica; Bevington, John; Vicini, Alessandro

2014-05-01

A set of open-source tools to create building exposure datasets for seismic risk assessment was developed from 2010-13 by the Inventory Data Capture Tools (IDCT) Risk Global Component of the Global Earthquake Model (GEM). The tools were designed to integrate data derived from remotely-sensed imagery, statistically-sampled in-situ field data of buildings to generate per-building and regional exposure data. A number of software tools were created to aid the development of these data, including mobile data capture tools for in-field structural assessment, and the Spatial Inventory Data Developer (SIDD) for creating "mapping schemes" - statistically-inferred distributions of building stock applied to areas of homogeneous urban land use. These tools were made publically available in January 2014. Exemplar implementations in Europe and Central Asia during the IDCT project highlighted several potential application areas beyond the original scope of the project. These are investigated here. We describe and demonstrate how the GEM-IDCT suite can be used extensively within the framework proposed by the EC-FP7 project SENSUM (Framework to integrate Space-based and in-situ sENSing for dynamic vUlnerability and recovery Monitoring). Specifically, applications in the areas of 1) dynamic vulnerability assessment (pre-event), and 2) recovery monitoring and evaluation (post-event) are discussed. Strategies for using the IDC Tools for these purposes are discussed. The results demonstrate the benefits of using advanced technology tools for data capture, especially in a systematic fashion using the taxonomic standards set by GEM. Originally designed for seismic risk assessment, it is clear the IDCT tools have relevance for multi-hazard risk assessment. When combined with a suitable sampling framework and applied to multi-temporal recovery monitoring, data generated from the tools can reveal spatio-temporal patterns in the quality of recovery activities and resilience trends can be

Peak Wind Tool for General Forecasting

Science.gov (United States)

Barrett, Joe H., III

2010-01-01

The expected peak wind speed of the day is an important forecast element in the 45th Weather Squadron's (45 WS) daily 24-Hour and Weekly Planning Forecasts. The forecasts are used for ground and space launch operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45 WS also issues wind advisories for KSC/CCAFS when they expect wind gusts to meet or exceed 25 kt, 35 kt and 50 kt thresholds at any level from the surface to 300 ft. The 45 WS forecasters have indicated peak wind speeds are challenging to forecast, particularly in the cool season months of October - April. In Phase I of this task, the Applied Meteorology Unit (AMU) developed a tool to help the 45 WS forecast non-convective winds at KSC/CCAFS for the 24-hour period of 0800 to 0800 local time. The tool was delivered as a Microsoft Excel graphical user interface (GUI). The GUI displayed the forecast of peak wind speed, 5-minute average wind speed at the time of the peak wind, timing of the peak wind and probability the peak speed would meet or exceed 25 kt, 35 kt and 50 kt. For the current task (Phase II ), the 45 WS requested additional observations be used for the creation of the forecast equations by expanding the period of record (POR). Additional parameters were evaluated as predictors, including wind speeds between 500 ft and 3000 ft, static stability classification, Bulk Richardson Number, mixing depth, vertical wind shear, temperature inversion strength and depth and wind direction. Using a verification data set, the AMU compared the performance of the Phase I and II prediction methods. Just as in Phase I, the tool was delivered as a Microsoft Excel GUI. The 45 WS requested the tool also be available in the Meteorological Interactive Data Display System (MIDDS). The AMU first expanded the POR by two years by adding tower observations, surface observations and CCAFS (XMR) soundings for the cool season months of March 2007 to April 2009. The POR was expanded

Developing Healthcare Data Analytics APPs with Open Data Science Tools.

Science.gov (United States)

Hao, Bibo; Sun, Wen; Yu, Yiqin; Xie, Guotong

2017-01-01

Recent advances in big data analytics provide more flexible, efficient, and open tools for researchers to gain insight from healthcare data. Whilst many tools require researchers to develop programs with programming languages like Python, R and so on, which is not a skill set grasped by many researchers in the healthcare data analytics area. To make data science more approachable, we explored existing tools and developed a practice that can help data scientists convert existing analytics pipelines to user-friendly analytics APPs with rich interactions and features of real-time analysis. With this practice, data scientists can develop customized analytics pipelines as APPs in Jupyter Notebook and disseminate them to other researchers easily, and researchers can benefit from the shared notebook to perform analysis tasks or reproduce research results much more easily.

Collaborative Data Mining Tool for Education

Science.gov (United States)

Garcia, Enrique; Romero, Cristobal; Ventura, Sebastian; Gea, Miguel; de Castro, Carlos

2009-01-01

This paper describes a collaborative educational data mining tool based on association rule mining for the continuous improvement of e-learning courses allowing teachers with similar course's profile sharing and scoring the discovered information. This mining tool is oriented to be used by instructors non experts in data mining such that, its…

Application of Statistical Tools for Data Analysis and Interpretation in Rice Plant Pathology

Directory of Open Access Journals (Sweden)

Parsuram Nayak

2018-01-01

Full Text Available There has been a significant advancement in the application of statistical tools in plant pathology during the past four decades. These tools include multivariate analysis of disease dynamics involving principal component analysis, cluster analysis, factor analysis, pattern analysis, discriminant analysis, multivariate analysis of variance, correspondence analysis, canonical correlation analysis, redundancy analysis, genetic diversity analysis, and stability analysis, which involve in joint regression, additive main effects and multiplicative interactions, and genotype-by-environment interaction biplot analysis. The advanced statistical tools, such as non-parametric analysis of disease association, meta-analysis, Bayesian analysis, and decision theory, take an important place in analysis of disease dynamics. Disease forecasting methods by simulation models for plant diseases have a great potentiality in practical disease control strategies. Common mathematical tools such as monomolecular, exponential, logistic, Gompertz and linked differential equations take an important place in growth curve analysis of disease epidemics. The highly informative means of displaying a range of numerical data through construction of box and whisker plots has been suggested. The probable applications of recent advanced tools of linear and non-linear mixed models like the linear mixed model, generalized linear model, and generalized linear mixed models have been presented. The most recent technologies such as micro-array analysis, though cost effective, provide estimates of gene expressions for thousands of genes simultaneously and need attention by the molecular biologists. Some of these advanced tools can be well applied in different branches of rice research, including crop improvement, crop production, crop protection, social sciences as well as agricultural engineering. The rice research scientists should take advantage of these new opportunities adequately in

Integrated Data Visualization and Virtual Reality Tool

Science.gov (United States)

Dryer, David A.

1998-01-01

The Integrated Data Visualization and Virtual Reality Tool (IDVVRT) Phase II effort was for the design and development of an innovative Data Visualization Environment Tool (DVET) for NASA engineers and scientists, enabling them to visualize complex multidimensional and multivariate data in a virtual environment. The objectives of the project were to: (1) demonstrate the transfer and manipulation of standard engineering data in a virtual world; (2) demonstrate the effects of design and changes using finite element analysis tools; and (3) determine the training and engineering design and analysis effectiveness of the visualization system.

Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) Final Report

Energy Technology Data Exchange (ETDEWEB)

Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2014-05-19

A partnership across government, academic, and private sectors has created a novel system that enables climate researchers to solve current and emerging data analysis and visualization challenges. The Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) software project utilizes the Python application programming interface (API) combined with C/C++/Fortran implementations for performance-critical software that offers the best compromise between "scalability" and “ease-of-use.” The UV-CDAT system is highly extensible and customizable for high-performance interactive and batch visualization and analysis for climate science and other disciplines of geosciences. For complex, climate data-intensive computing, UV-CDAT’s inclusive framework supports Message Passing Interface (MPI) parallelism as well as taskfarming and other forms of parallelism. More specifically, the UV-CDAT framework supports the execution of Python scripts running in parallel using the MPI executable commands and leverages Department of Energy (DOE)-funded general-purpose, scalable parallel visualization tools such as ParaView and VisIt. This is the first system to be successfully designed in this way and with these features. The climate community leverages these tools and others, in support of a parallel client-server paradigm, allowing extreme-scale, server-side computing for maximum possible speed-up.

General Guidelines on Criteria for Adoption or Rejection of Evaluated Libraries and Data by the Nuclear Data Team

Energy Technology Data Exchange (ETDEWEB)

Neudecker, Denise [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Conlin, Jeremy Lloyd [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Gray, Mark Girard [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); McCartney, Austin Paul [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Parsons, Donald Kent [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); White, Morgan Curtis [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-04-12

This memo contains general guidelines on what documentation and tools need to be in place as well as format and data testing requirements such that evaluated nuclear data sets or entire libraries can be adopted by the nuclear data team. Additional requirements beyond this memo might apply for specific nuclear data observables. These guidelines were established based on discussions between J.L. Conlin, M.G. Gray, A.P. McCartney, D. Neudecker, D.K. Parsons and M.C. White.

Final Report for Geometric Analysis for Data Reduction and Structure Discovery DE-FG02-10ER25983, STRIPES award # DE-SC0004096

Energy Technology Data Exchange (ETDEWEB)

Vixie, Kevin R. [Washington State Univ., Pullman, WA (United States)

2014-11-27

This is the final report for the project "Geometric Analysis for Data Reduction and Structure Discovery" in which insights and tools from geometric analysis were developed and exploited for their potential to large scale data challenges.

Analysis of logging data from nuclear borehole tools

International Nuclear Information System (INIS)

Hovgaard, J.; Oelgaard, P.L.

1989-12-01

The processing procedure for logging data from a borehole of the Stenlille project of Dansk Naturgas A/S has been analysed. The tools considered in the analysis were an integral, natural-gamma tool, a neutron porosity tool, a gamma density tool and a caliper tool. It is believed that in most cases the processing procedure used by the logging company in the interpretation of the raw data is fully understood. An exception is the epithermal part of the neutron porosity tool where all data needed for an interpretation were not available. The analysis has shown that some parts of the interpretation procedure may not be consistent with the physical principle of the tools. (author)

An intelligent tool for activity data collection.

Science.gov (United States)

Sarkar, A M Jehad

2011-01-01

Activity recognition systems using simple and ubiquitous sensors require a large variety of real-world sensor data for not only evaluating their performance but also training the systems for better functioning. However, a tremendous amount of effort is required to setup an environment for collecting such data. For example, expertise and resources are needed to design and install the sensors, controllers, network components, and middleware just to perform basic data collections. It is therefore desirable to have a data collection method that is inexpensive, flexible, user-friendly, and capable of providing large and diverse activity datasets. In this paper, we propose an intelligent activity data collection tool which has the ability to provide such datasets inexpensively without physically deploying the testbeds. It can be used as an inexpensive and alternative technique to collect human activity data. The tool provides a set of web interfaces to create a web-based activity data collection environment. It also provides a web-based experience sampling tool to take the user's activity input. The tool generates an activity log using its activity knowledge and the user-given inputs. The activity knowledge is mined from the web. We have performed two experiments to validate the tool's performance in producing reliable datasets.

Horizontal decomposition of data table for finding one reduct

Science.gov (United States)

Hońko, Piotr

2018-04-01

Attribute reduction, being one of the most essential tasks in rough set theory, is a challenge for data that does not fit in the available memory. This paper proposes new definitions of attribute reduction using horizontal data decomposition. Algorithms for computing superreduct and subsequently exact reducts of a data table are developed and experimentally verified. In the proposed approach, the size of subtables obtained during the decomposition can be arbitrarily small. Reducts of the subtables are computed independently from one another using any heuristic method for finding one reduct. Compared with standard attribute reduction methods, the proposed approach can produce superreducts that usually inconsiderably differ from an exact reduct. The approach needs comparable time and much less memory to reduce the attribute set. The method proposed for removing unnecessary attributes from superreducts executes relatively fast for bigger databases.

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

DEFF Research Database (Denmark)

Tan, Qihua; Thomassen, Mads; Burton, Mark

2017-01-01

the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

Python data science handbook essential tools for working with data

CERN Document Server

VanderPlas, Jake

2016-01-01

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues.

Post-Flight Data Analysis Tool

Science.gov (United States)

George, Marina

2018-01-01

A software tool that facilitates the retrieval and analysis of post-flight data. This allows our team and other teams to effectively and efficiently analyze and evaluate post-flight data in order to certify commercial providers.

Data in the Classroom: New Tools for Engaging Students with Data

Science.gov (United States)

Dean, A.; Pisut, D.

2017-12-01

The ability to understand and analyze data effectively can increase students ability to understand current and historical global change. Since 2009, NOAA Data in the Classroom Project has been offering formal education resources and tools aimed at helping teachers to build data and environmental literacy in their classrooms. Currently, NOAA is modernizing its Data in the Classroom resources using a web application within Esri's web-based GIS platform, Story Maps. Story Maps have been used for a wide variety of purposes, including teaching and instruction, for more than a decade. This technology can help to engage students in a story, like El Niño, while harnessing the power of data - using maps, data visualizations and data query tools. The aim is to create an effective education tool that allows students access to user-friendly, relevant data sets from NOAA, ultimately providing the opportunity to explore dynamic Earth processes and understand the impact of environmental events on a regional or global scale. This presentation will include demonstrations of the recently launched web-based curricular modules, highlighting the Esri web technology used to build and distribute each module and the interactive data tools that are unique to this project.

Evaluation of Oracle Big Data Integration Tools

OpenAIRE

Urhan, Harun; Baranowski, Zbigniew

2015-01-01

Abstract The project’s objective is evaluating Oracle’s Big Data Integration Tools. The project covers evaluation of two of Oracle’s tools, Oracle Data Integrator: Application Adapters for Hadoop to load data from Oracle Database to Hadoop and Oracle SQL Connectors for HDFS to query data stored on a Hadoop file system by using SQL statements executed on an Oracle Database.

Tools for Local and Distributed Climate Data Access

Science.gov (United States)

Schweitzer, R.; O'Brien, K.; Burger, E. F.; Smith, K. M.; Manke, A. B.; Radhakrishnan, A.; Balaji, V.

2017-12-01

Last year we reported on our efforts to adapt existing tools to facilitate model development. During the lifecycle of a Climate Model Intercomparison Project (CMIP), data must be quality controlled before it can be published and studied. Like previous efforts, the next CMIP6 will produce an unprecedented volume of data. For an institution, modelling group or modeller the volume of data is unmanageable without tools that organize and automate as many processes as possible. Even if a modelling group has tools for data and metadata management, it often falls on individuals to do the initial quality assessment for a model run with bespoke tools. Using individually crafted tools can lead to interruptions when project personnel change and may result in inconsistencies and duplication of effort across groups. This talk will expand on our experiences using available tools (Ferret/PyFerret, the Live Access Server, the GFDL Curator, the GFDL Model Development Database Interface and the THREDDS Data Server) to seamlessly automate the data assembly process to give users "one-click" access to a rich suite of Web-based analysis and comparison tools. On the surface, it appears that this collection of tools is well suited to the task, but our experience of the last year taught us that the data volume and distributed storage adds a number of challenges in adapting the tools for this task. Quality control and initial evaluation add their own set of challenges. We will discuss how we addressed the needs of QC researchers by expanding standard tools to include specialized plots and leveraged the configurability of the tools to add specific user defined analysis operations so they are available to everyone using the system. We also report on our efforts to overcome some of the technical barriers for wide adoption of the tools by providing pre-built containers that are easily deployed in virtual machine and cloud environments. Finally, we will offer some suggestions for added features

Generalized kinetic model of reduction of molecular oxidant by metal containing redox

International Nuclear Information System (INIS)

Kravchenko, T.A.

1986-01-01

Present work is devoted to kinetics of reduction of molecular oxidant by metal containing redox. Constructed generalized kinetic model of redox process in the system solid redox - reagent solution allows to perform the general theoretical approach to research and to obtain new results on kinetics and mechanism of interaction of redox with oxidants.

Measuring general surgery residents' communication skills from the patient's perspective using the Communication Assessment Tool (CAT).

Science.gov (United States)

Stausmire, Julie M; Cashen, Constance P; Myerholtz, Linda; Buderer, Nancy

2015-01-01

The Communication Assessment Tool (CAT) has been used and validated to assess Family and Emergency Medicine resident communication skills from the patient's perspective. However, it has not been previously reported as an outcome measure for general surgery residents. The purpose of this study is to establish initial benchmarking data for the use of the CAT as an evaluation tool in an osteopathic general surgery residency program. Results are analyzed quarterly and used by the program director to provide meaningful feedback and targeted goal setting for residents to demonstrate progressive achievement of interpersonal and communication skills with patients. The 14-item paper version of the CAT (developed by Makoul et al. for residency programs) asks patients to anonymously rate surgery residents on discrete communication skills using a 5-point rating scale immediately after the clinical encounter. Results are reported as the percentage of items rated as "excellent" (5) by the patient. The setting is a hospital-affiliated ambulatory urban surgery office staffed by the residency program. Participants are representative of adult patients of both sexes across all ages with diverse ethnic backgrounds. They include preoperative and postoperative patients, as well as those needing diagnostic testing and follow-up. Data have been collected on 17 general surgery residents from a single residency program representing 5 postgraduate year levels and 448 patient encounters since March 2012. The reliability (Cronbach α) of the tool for surgery residents was 0.98. The overall mean percentage of items rated as excellent was 70% (standard deviations = 42%), with a median of 100%. The CAT is a useful tool for measuring 1 facet of resident communication skills-the patient's perception of the physician-patient encounter. The tool provides a unique and personalized outcome measure for identifying communication strengths and improvement opportunities, allowing residents to receive

General Purpose Data-Driven Online System Health Monitoring with Applications to Space Operations

Science.gov (United States)

Iverson, David L.; Spirkovska, Lilly; Schwabacher, Mark

2010-01-01

Modern space transportation and ground support system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional parameter limit checking, or model-based or rule-based methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults, failures, or precursors of significant failures. The Inductive Monitoring System (IMS) is a general purpose, data-driven system health monitoring software tool that has been successfully applied to several aerospace applications and is under evaluation for anomaly detection in vehicle and ground equipment for next generation launch systems. After an introduction to IMS application development, we discuss these NASA online monitoring applications, including the integration of IMS with complementary model-based and rule-based methods. Although the examples presented in this paper are from space operations applications, IMS is a general-purpose health-monitoring tool that is also applicable to power generation and transmission system monitoring.

Data Mining Tools for Malware Detection

CERN Document Server

Masud, Mehedy; Thuraisingham, Bhavani; Andreasson, Kim J

2011-01-01

Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware detection. Integrating theory with practical techniques and experimental results, it focuses on malware detection applications for email worms, malicious code, remote exploits, and botnets. The authors describe the systems they have designed and devel

Applying open source data visualization tools to standard based medical data.

Science.gov (United States)

Kopanitsa, Georgy; Taranik, Maxim

2014-01-01

Presentation of medical data in personal health records (PHRs) requires flexible platform independent tools to ensure easy access to the information. Different backgrounds of the patients, especially elder people require simple graphical presentation of the data. Data in PHRs can be collected from heterogeneous sources. Application of standard based medical data allows development of generic visualization methods. Focusing on the deployment of Open Source Tools, in this paper we applied Java Script libraries to create data presentations for standard based medical data.

Competitive kinetics as a tool to determine rate constants for reduction of ferrylmyoglobin by food components

DEFF Research Database (Denmark)

Jongberg, Sisse; Lund, Marianne Nissen; Pattison, David I.

2016-01-01

Competitive kinetics were applied as a tool to determine apparent rate constants for the reduction of hypervalent haem pigment ferrylmyoglobin (MbFe(IV)=O) by proteins and phenols in aqueous solution of pH 7.4 and I = 1.0 at 25 °C. Reduction of MbFe(IV)=O by a myofibrillar protein isolate (MPI) f...

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

Science.gov (United States)

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

A sparse grid based method for generative dimensionality reduction of high-dimensional data

Science.gov (United States)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

Open-source tools for data mining.

Science.gov (United States)

Zupan, Blaz; Demsar, Janez

2008-03-01

With a growing volume of biomedical databases and repositories, the need to develop a set of tools to address their analysis and support knowledge discovery is becoming acute. The data mining community has developed a substantial set of techniques for computational treatment of these data. In this article, we discuss the evolution of open-source toolboxes that data mining researchers and enthusiasts have developed over the span of a few decades and review several currently available open-source data mining suites. The approaches we review are diverse in data mining methods and user interfaces and also demonstrate that the field and its tools are ready to be fully exploited in biomedical research.

The Simultaneous Medicina-Planck Experiment: data acquisition, reduction and first results

Science.gov (United States)

Procopio, P.; Massardi, M.; Righini, S.; Zanichelli, A.; Ricciardi, S.; Libardi, P.; Burigana, C.; Cuttaia, F.; Mack, K.-H.; Terenzi, L.; Villa, F.; Bonavera, L.; Morgante, G.; Trigilio, C.; Trombetti, T.; Umana, G.

2011-10-01

The Simultaneous Medicina-Planck Experiment (SiMPlE) is aimed at observing a selected sample of 263 extragalactic and Galactic sources with the Medicina 32-m single-dish radio telescope in the same epoch as the Planck satellite observations. The data, acquired with a frequency coverage down to 5 GHz and combined with Planck at frequencies above 30 GHz, will constitute a useful reference catalogue of bright sources over the whole Northern hemisphere. Furthermore, source observations performed in different epochs and comparisons with other catalogues will allow the investigation of source variabilities on different time-scales. In this work, we describe the sample selection, the ongoing data acquisition campaign, the data reduction procedures, the developed tools and the comparison with other data sets. We present 5 and 8.3 GHz data for the SiMPlE Northern sample, consisting of 79 sources with δ≥ 45° selected from our catalogue and observed during the first 6 months of the project. A first analysis of their spectral behaviour and long-term variability is also presented.

Large Data Visualization with Open-Source Tools

CERN Multimedia

CERN. Geneva

2015-01-01

Visualization and post-processing of large data have become increasingly challenging and require more and more tools to support the diversity of data to process. In this seminar, we will present a suite of open-source tools supported and developed by Kitware to perform large-scale data visualization and analysis. In particular, we will present ParaView, an open-source tool for parallel visualization of massive datasets, the Visualization Toolkit (VTK), an open-source toolkit for scientific visualization, and Tangelohub, a suite of tools for large data analytics. About the speaker Julien Jomier is directing Kitware's European subsidiary in Lyon, France, where he focuses on European business development. Julien works on a variety of projects in the areas of parallel and distributed computing, mobile computing, image processing, and visualization. He is one of the developers of the Insight Toolkit (ITK), the Visualization Toolkit (VTK), and ParaView. Julien is also leading the CDash project, an open-source co...

The Planetary Data System (PDS) Data Dictionary Tool (LDDTool)

Science.gov (United States)

Raugh, Anne C.; Hughes, John S.

2017-10-01

One of the major design goals of the PDS4 development effort was to provide an avenue for discipline specialists and large data preparers such as mission archivists to extend the core PDS4 Information Model (IM) to include metadata definitions specific to their own contexts. This capability is critical for the Planetary Data System - an archive that deals with a data collection that is diverse along virtually every conceivable axis. Amid such diversity, it is in the best interests of the PDS archive and its users that all extensions to the core IM follow the same design techniques, conventions, and restrictions as the core implementation itself. Notwithstanding, expecting all mission and discipline archivist seeking to define metadata for a new context to acquire expertise in information modeling, model-driven design, ontology, schema formulation, and PDS4 design conventions and philosophy is unrealistic, to say the least.To bridge that expertise gap, the PDS Engineering Node has developed the data dictionary creation tool known as “LDDTool”. This tool incorporates the same software used to maintain and extend the core IM, packaged with an interface that enables a developer to create his contextual information model using the same, open standards-based metadata framework PDS itself uses. Through this interface, the novice dictionary developer has immediate access to the common set of data types and unit classes for defining attributes, and a straight-forward method for constructing classes. The more experienced developer, using the same tool, has access to more sophisticated modeling methods like abstraction and extension, and can define very sophisticated validation rules.We present the key features of the PDS Local Data Dictionary Tool, which both supports the development of extensions to the PDS4 IM, and ensures their compatibility with the IM.

Collaboratively Conceived, Designed and Implemented: Matching Visualization Tools with Geoscience Data Collections and Geoscience Data Collections with Visualization Tools via the ToolMatch Service.

Science.gov (United States)

Hoebelheinrich, N. J.; Lynnes, C.; West, P.; Ferritto, M.

2014-12-01

Two problems common to many geoscience domains are the difficulties in finding tools to work with a given dataset collection, and conversely, the difficulties in finding data for a known tool. A collaborative team from the Earth Science Information Partnership (ESIP) has gotten together to design and create a web service, called ToolMatch, to address these problems. The team began their efforts by defining an initial, relatively simple conceptual model that addressed the two uses cases briefly described above. The conceptual model is expressed as an ontology using OWL (Web Ontology Language) and DCterms (Dublin Core Terms), and utilizing standard ontologies such as DOAP (Description of a Project), FOAF (Friend of a Friend), SKOS (Simple Knowledge Organization System) and DCAT (Data Catalog Vocabulary). The ToolMatch service will be taking advantage of various Semantic Web and Web standards, such as OpenSearch, RESTful web services, SWRL (Semantic Web Rule Language) and SPARQL (Simple Protocol and RDF Query Language). The first version of the ToolMatch service was deployed in early fall 2014. While more complete testing is required, a number of communities besides ESIP member organizations have expressed interest in collaborating to create, test and use the service and incorporate it into their own web pages, tools and / or services including the USGS Data Catalog service, DataONE, the Deep Carbon Observatory, Virtual Solar Terrestrial Observatory (VSTO), and the U.S. Global Change Research Program. In this session, presenters will discuss the inception and development of the ToolMatch service, the collaborative process used to design, refine, and test the service, and future plans for the service.

Social Data Analytics Tool

DEFF Research Database (Denmark)

Hussain, Abid; Vatrapu, Ravi

2014-01-01

This paper presents the design, development and demonstrative case studies of the Social Data Analytics Tool, SODATO. Adopting Action Design Framework [1], the objective of SODATO [2] is to collect, store, analyze, and report big social data emanating from the social media engagement of and social...... media conversations about organizations. We report and discuss results from two demonstrative case studies that were conducted using SODATO and conclude with implications and future work....

The DEEP-South: Scheduling and Data Reduction Software System

Science.gov (United States)

Yim, Hong-Suh; Kim, Myung-Jin; Bae, Youngho; Moon, Hong-Kyu; Choi, Young-Jun; Roh, Dong-Goo; the DEEP-South Team

2015-08-01

The DEep Ecliptic Patrol of the Southern sky (DEEP-South), started in October 2012, is currently in test runs with the first Korea Microlensing Telescope Network (KMTNet) 1.6 m wide-field telescope located at CTIO in Chile. While the primary objective for the DEEP-South is physical characterization of small bodies in the Solar System, it is expected to discover a large number of such bodies, many of them previously unknown.An automatic observation planning and data reduction software subsystem called "The DEEP-South Scheduling and Data reduction System" (the DEEP-South SDS) is currently being designed and implemented for observation planning, data reduction and analysis of huge amount of data with minimum human interaction. The DEEP-South SDS consists of three software subsystems: the DEEP-South Scheduling System (DSS), the Local Data Reduction System (LDR), and the Main Data Reduction System (MDR). The DSS manages observation targets, makes decision on target priority and observation methods, schedules nightly observations, and archive data using the Database Management System (DBMS). The LDR is designed to detect moving objects from CCD images, while the MDR conducts photometry and reconstructs lightcurves. Based on analysis made at the LDR and the MDR, the DSS schedules follow-up observation to be conducted at other KMTNet stations. In the end of 2015, we expect the DEEP-South SDS to achieve a stable operation. We also have a plan to improve the SDS to accomplish finely tuned observation strategy and more efficient data reduction in 2016.

An Intelligent Tool for Activity Data Collection

Directory of Open Access Journals (Sweden)

A. M. Jehad Sarkar

2011-04-01

Full Text Available Activity recognition systems using simple and ubiquitous sensors require a large variety of real-world sensor data for not only evaluating their performance but also training the systems for better functioning. However, a tremendous amount of effort is required to setup an environment for collecting such data. For example, expertise and resources are needed to design and install the sensors, controllers, network components, and middleware just to perform basic data collections. It is therefore desirable to have a data collection method that is inexpensive, flexible, user-friendly, and capable of providing large and diverse activity datasets. In this paper, we propose an intelligent activity data collection tool which has the ability to provide such datasets inexpensively without physically deploying the testbeds. It can be used as an inexpensive and alternative technique to collect human activity data. The tool provides a set of web interfaces to create a web-based activity data collection environment. It also provides a web-based experience sampling tool to take the user’s activity input. The tool generates an activity log using its activity knowledge and the user-given inputs. The activity knowledge is mined from the web. We have performed two experiments to validate the tool’s performance in producing reliable datasets.

Assessment of Tools and Data for System-Level Dynamic Analyses

International Nuclear Information System (INIS)

Piet, Steven J.; Soelberg, Nick R.

2011-01-01

The only fuel cycle for which dynamic analyses and assessments are not needed is the null fuel cycle - no nuclear power. For every other concept, dynamic analyses are needed and can influence relative desirability of options. Dynamic analyses show how a fuel cycle might work during transitions from today's partial fuel cycle to something more complete, impact of technology deployments, location of choke points, the key time lags, when benefits can manifest, and how well parts of fuel cycles work together. This report summarizes the readiness of existing Fuel Cycle Technology (FCT) tools and data for conducting dynamic analyses on the range of options. VISION is the primary dynamic analysis tool. Not only does it model mass flows, as do other dynamic system analysis models, but it allows users to explore various potential constraints. The only fuel cycle for which constraints are not important are those in concept advocates PowerPoint presentations; in contrast, comparative analyses of fuel cycles must address what constraints exist and how they could impact performance. The most immediate tool need is extending VISION to the thorium/U233 fuel cycle. Depending on further clarification of waste management strategies in general and for specific fuel cycle candidates, waste management sub-models in VISION may need enhancement, e.g., more on 'co-flows' of non-fuel materials, constraints in waste streams, or automatic classification of waste streams on the basis of user-specified rules. VISION originally had an economic sub-model. The economic calculations were deemed unnecessary in later versions so it was retired. Eventually, the program will need to restore and improve the economics sub-model of VISION to at least the cash flow stage and possibly to incorporating cost constraints and feedbacks. There are multiple sources of data that dynamic analyses can draw on. In this report, 'data' means experimental data, data from more detailed theoretical or empirical

Assessment of Tools and Data for System-Level Dynamic Analyses

Energy Technology Data Exchange (ETDEWEB)

Steven J. Piet; Nick R. Soelberg

2011-06-01

The only fuel cycle for which dynamic analyses and assessments are not needed is the null fuel cycle - no nuclear power. For every other concept, dynamic analyses are needed and can influence relative desirability of options. Dynamic analyses show how a fuel cycle might work during transitions from today's partial fuel cycle to something more complete, impact of technology deployments, location of choke points, the key time lags, when benefits can manifest, and how well parts of fuel cycles work together. This report summarizes the readiness of existing Fuel Cycle Technology (FCT) tools and data for conducting dynamic analyses on the range of options. VISION is the primary dynamic analysis tool. Not only does it model mass flows, as do other dynamic system analysis models, but it allows users to explore various potential constraints. The only fuel cycle for which constraints are not important are those in concept advocates PowerPoint presentations; in contrast, comparative analyses of fuel cycles must address what constraints exist and how they could impact performance. The most immediate tool need is extending VISION to the thorium/U233 fuel cycle. Depending on further clarification of waste management strategies in general and for specific fuel cycle candidates, waste management sub-models in VISION may need enhancement, e.g., more on 'co-flows' of non-fuel materials, constraints in waste streams, or automatic classification of waste streams on the basis of user-specified rules. VISION originally had an economic sub-model. The economic calculations were deemed unnecessary in later versions so it was retired. Eventually, the program will need to restore and improve the economics sub-model of VISION to at least the cash flow stage and possibly to incorporating cost constraints and feedbacks. There are multiple sources of data that dynamic analyses can draw on. In this report, 'data' means experimental data, data from more detailed

Data poverty: A global evaluation for 2009 to 2013 - implications for sustainable development and disaster risk reduction

Science.gov (United States)

Leidig, Mathias; Teeuw, Richard M.; Gibson, Andrew D.

2016-08-01

The article presents a time series (2009-2013) analysis for a new version of the ;Digital Divide; concept that developed in the 1990s. Digital information technologies, such as the Internet, mobile phones and social media, provide vast amounts of data for decision-making and resource management. The Data Poverty Index (DPI) provides an open-source means of annually evaluating global access to data and information. The DPI can be used to monitor aspects of data and information availability at global and national levels, with potential application at local (district) levels. Access to data and information is a major factor in disaster risk reduction, increased resilience to disaster and improved adaptation to climate change. In that context, the DPI could be a useful tool for monitoring the Sustainable Development Goals of the Sendai Framework for Disaster Risk Reduction (2015-2030). The effects of severe data poverty, particularly limited access to geoinformatic data, free software and online training materials, are discussed in the context of sustainable development and disaster risk reduction. Unlike many other indices, the DPI is underpinned by datasets that are consistently provided annually for almost all the countries of the world and can be downloaded without restriction or cost.

Reduction of radiation exposure and image quality using dose reduction tool on computed tomography fluoroscopy

International Nuclear Information System (INIS)

Sakabe, Daisuke; Tochihara, Syuichi; Ono, Michiaki; Tokuda, Masaki; Kai, Noriyuki; Nakato, Kengo; Hashida, Masahiro; Funama, Yoshinori; Murazaki, Hiroo

2012-01-01

The purpose of our study was to measure the reduction rate of radiation dose and variability of image noise using the angular beam modulation (ABM) on computed tomography (CT) fluoroscopy. The Alderson-Rando phantom and the homemade phantom were used in our study. These phantoms were scanned at on-center and off-center positions at -12 cm along y-axis with and without ABM technique. Regarding the technique, the x-ray tube is turned off in a 100-degree angle sector at the center of 12 o'clock, 10 o'clock, and 2 o'clock positions during CT fluoroscopy. CT fluoroscopic images were obtained with tube voltages, 120 kV; tube current-time product per reconstructed image, 30 mAs; rotation time, 0.5 s/rot; slice thickness, 4.8 mm; and reconstruction kernel B30s in each scanning. After CT scanning, radiation exposure and image noise were measured and the image artifacts were evaluated with and without the technique. The reduction rate for radiation exposure was 75-80% with and without the technique at on-center position regardless of each angle position. In the case of the off-center position at -12 cm, the reduction rate was 50% with and without the technique. In contrast, image noise remained constant with and without the technique. Visual inspection for image artifacts almost have the same scores with and without the technique and no statistical significance was found in both techniques (p>0.05). ABM is an appropriate tool for reducing radiation exposure and maintaining image-noise and artifacts during CT fluoroscopy. (author)

Dimension reduction methods for microarray data: a review

Directory of Open Access Journals (Sweden)

Rabia Aziz

2017-03-01

Full Text Available Dimension reduction has become inevitable for pre-processing of high dimensional data. “Gene expression microarray data” is an instance of such high dimensional data. Gene expression microarray data displays the maximum number of genes (features simultaneously at a molecular level with a very small number of samples. The copious numbers of genes are usually provided to a learning algorithm for producing a complete characterization of the classification task. However, most of the times the majority of the genes are irrelevant or redundant to the learning task. It will deteriorate the learning accuracy and training speed as well as lead to the problem of overfitting. Thus, dimension reduction of microarray data is a crucial preprocessing step for prediction and classification of disease. Various feature selection and feature extraction techniques have been proposed in the literature to identify the genes, that have direct impact on the various machine learning algorithms for classification and eliminate the remaining ones. This paper describes the taxonomy of dimension reduction methods with their characteristics, evaluation criteria, advantages and disadvantages. It also presents a review of numerous dimension reduction approaches for microarray data, mainly those methods that have been proposed over the past few years.

TSCA Inventory Data Extraction Tool

Data.gov (United States)

U.S. Environmental Protection Agency — This data extraction tool contains the non confidential identities of chemical substances submitted under the Toxic Substances Control Act (TSCA). TSCA was enacted...

A simple tool for neuroimaging data sharing

Directory of Open Access Journals (Sweden)

Christian eHaselgrove

2014-05-01

Full Text Available Data sharing is becoming increasingly common, but despite encouragement and facilitation by funding agencies, journals, and some research efforts, most neuroimaging data acquired today is still not shared due to political, financial, social, and technical barriers to sharing data that remain. In particular, technical solutions are few for researchers that are not a part of larger efforts with dedicated sharing infrastructures, and social barriers such as the time commitment required to share can keep data from becoming publicly available.We present a system for sharing neuroimaging data, designed to be simple to use and to provide benefit to the data provider. The system consists of a server at the International Neuroinformatics Coordinating Facility (INCF and user tools for uploading data to the server. The primary design principle for the user tools is ease of use: the user identifies a directory containing DICOM data, provides their INCF Portal authentication, and provides identifiers for the subject and imaging session. The user tool anonymizes the data and sends it to the server. The server then runs quality control routines on the data, and the data and the quality control reports are made public. The user retains control of the data and may change the sharing policy as they need. The result is that in a few minutes of the user’s time, DICOM data can be anonymized and made publicly available, and an initial quality control assessment can be performed on the data. The system is currently functional, and user tools and access to the public image database are available at http://xnat.incf.org/.

An Automated Data Analysis Tool for Livestock Market Data

Science.gov (United States)

Williams, Galen S.; Raper, Kellie Curry

2011-01-01

This article describes an automated data analysis tool that allows Oklahoma Cooperative Extension Service educators to disseminate results in a timely manner. Primary data collected at Oklahoma Quality Beef Network (OQBN) certified calf auctions across the state results in a large amount of data per sale site. Sale summaries for an individual sale…

A general transform for variance reduction in Monte Carlo simulations

International Nuclear Information System (INIS)

Becker, T.L.; Larsen, E.W.

2011-01-01

This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)

Validation of an explanatory tool for data-fused displays for high-technology future aircraft

Science.gov (United States)

Fletcher, Georgina C. L.; Shanks, Craig R.; Selcon, Stephen J.

1996-05-01

As the number of sensor and data sources in the military cockpit increases, pilots will suffer high levels of workload which could result in reduced performance and the loss of situational awareness. A DRA research program has been investigating the use of data-fused displays in decision support and has developed and laboratory-tested an explanatory tool for displaying information in air combat scenarios. The tool has been designed to provide pictorial explanations of data that maintain situational awareness by involving the pilot in the hostile aircraft threat assessment task. This paper reports a study carried out to validate the success of the explanatory tool in a realistic flight simulation facility. Aircrew were asked to perform a threat assessment task, either with or without the explanatory tool providing information in the form of missile launch success zone envelopes, while concurrently flying a waypoint course within set flight parameters. The results showed that there was a significant improvement (p less than 0.01) in threat assessment accuracy of 30% when using the explanatory tool. This threat assessment performance advantage was achieved without a trade-off with flying task performance. Situational awareness measures showed no general differences between the explanatory and control conditions, but significant learning effects suggested that the explanatory tool makes the task initially more intuitive and hence less demanding on the pilots' attentional resources. The paper concludes that DRA's data-fused explanatory tool is successful at improving threat assessment accuracy in a realistic simulated flying environment, and briefly discusses the requirements for further research in the area.

New Tools for Sea Ice Data Analysis and Visualization: NSIDC's Arctic Sea Ice News and Analysis

Science.gov (United States)

Vizcarra, N.; Stroeve, J.; Beam, K.; Beitler, J.; Brandt, M.; Kovarik, J.; Savoie, M. H.; Skaug, M.; Stafford, T.

2017-12-01

Arctic sea ice has long been recognized as a sensitive climate indicator and has undergone a dramatic decline over the past thirty years. Antarctic sea ice continues to be an intriguing and active field of research. The National Snow and Ice Data Center's Arctic Sea Ice News & Analysis (ASINA) offers researchers and the public a transparent view of sea ice data and analysis. We have released a new set of tools for sea ice analysis and visualization. In addition to Charctic, our interactive sea ice extent graph, the new Sea Ice Data and Analysis Tools page provides access to Arctic and Antarctic sea ice data organized in seven different data workbooks, updated daily or monthly. An interactive tool lets scientists, or the public, quickly compare changes in ice extent and location. Another tool allows users to map trends, anomalies, and means for user-defined time periods. Animations of September Arctic and Antarctic monthly average sea ice extent and concentration may also be accessed from this page. Our tools help the NSIDC scientists monitor and understand sea ice conditions in near real time. They also allow the public to easily interact with and explore sea ice data. Technical innovations in our data center helped NSIDC quickly build these tools and more easily maintain them. The tools were made publicly accessible to meet the desire from the public and members of the media to access the numbers and calculations that power our visualizations and analysis. This poster explores these tools and how other researchers, the media, and the general public are using them.

SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.

Science.gov (United States)

Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin

2018-05-25

Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.

The neutron porosity tool

International Nuclear Information System (INIS)

Oelgaard, P.L.

1988-01-01

The report contains a review of available information on neutron porosity tools with the emphasis on dual thermal-neutron-detector porosity tools and epithermal-neutron-detector porosity tools. The general principle of such tools is discussed and theoretical models are very briefly reviewed. Available data on tool designs are summarized with special regard to the source-detector distance. Tool operational data, porosity determination and correction of measurements are briefly discussed. (author) 15 refs

Greenhouse Gas Data Publication Tool

Data.gov (United States)

U.S. Environmental Protection Agency — This tool to gives you access to greenhouse gas data reported to EPA by large facilities and suppliers in the United States through EPA's Greenhouse Gas Reporting...

A Linked Data Approach for the Discovery of Educational ICT Tools in the Web of Data

Science.gov (United States)

Ruiz-Calleja, Adolfo; Vega-Gorgojo, Guillermo; Asensio-Perez, Juan I.; Bote-Lorenzo, Miguel L.; Gomez-Sanchez, Eduardo; Alario-Hoyos, Carlos

2012-01-01

The use of Information and Communication Technologies (ICT) tools to support learning activities is nowadays generalized. Several educational registries provide information about ICT tools in order to help educators in their discovery and selection. These registries are typically isolated and require much effort to keep tool information up to…

[General principles of database storage operations with emphasis on OLAP reports].

Science.gov (United States)

Borkowski, Włodzimierz; Mielniczuk, Hanna

2004-01-01

In article general principles and features of data warehouse were presented in particular of OLAP reports. The data warehouse was built using Oracle tools. The repository was filled with death records from Central Office of Statistics. Various features adequate for epidemiological analyses have been discussed and illustrated like pivoting and rotating dimension, drilling on hierarchical data, reduction of dimensions. The possibility of specific for epidemiology indicators creation was shown. The need of implementation of data warehouses and OLAP reports in Polish healthcare was discussed. In comparison with traditional manner of analysis and presentation epidemiological facts OLAP reports give new perspectives.

Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics

KAUST Repository

Efendiev, Yalchin R.; Presho, Michael

2015-01-01

In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.

Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics

KAUST Repository

Efendiev, Yalchin R.

2015-09-02

In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems. In the current chapter, we consider some of these applications and outline the basic methodological concepts.

RISK REDUCTION WITH A FUZZY EXPERT EXPLORATION TOOL

Energy Technology Data Exchange (ETDEWEB)

William W. Weiss

2000-06-30

Incomplete or sparse information on geologic or formation characteristics introduces a high level of risk for oil exploration and development projects. Expert systems have been developed and used in several disciplines and industries, including medical diagnostics, with favorable results. A state-of-the-art exploration ''expert'' tool, relying on a computerized data base and computer maps generated by neural networks, is proposed through the use of ''fuzzy'' logic, a relatively new mathematical treatment of imprecise or non-explicit parameters and values. This project will develop an Artificial Intelligence system that will draw upon a wide variety of information to provide realistic estimates of risk. ''Fuzzy logic,'' a system of integrating large amounts of inexact, incomplete information with modern computational methods to derive usable conclusions, has been demonstrated as a cost-effective computational technology in many industrial applications. During project year 1, 90% of geologic, geophysical, production and price data were assimilated for installation into the database. Logs provided geologic data consisting of formation tops of the Brushy Canyon, Lower Brushy Canyon, and Bone Springs zones of 700 wells used to construct regional cross sections. Regional structure and isopach maps were constructed using kriging to interpolate between the measured points. One of the structure derivative maps (azimuth of curvature) visually correlates with Brushy Canyon fields on the maximum change contours. Derivatives of the regional geophysical data also visually correlate with the location of the fields. The azimuth of maximum dip approximately locates fields on the maximum change contours. In a similar manner the second derivative in the x-direction of the gravity map visually correlates with the alignment of the known fields. The visual correlations strongly suggest that neural network architectures will be

Data Grid tools: enabling science on big distributed data

Energy Technology Data Exchange (ETDEWEB)

Allcock, Bill [Mathematics and Computer Science, Argonne National Laboratory, Argonne, IL 60439 (United States); Chervenak, Ann [Information Sciences Institute, University of Southern California, Marina del Rey, CA 90291 (United States); Foster, Ian [Mathematics and Computer Science, Argonne National Laboratory, Argonne, IL 60439 (United States); Department of Computer Science, University of Chicago, Chicago, IL 60615 (United States); Kesselman, Carl [Information Sciences Institute, University of Southern California, Marina del Rey, CA 90291 (United States); Livny, Miron [Department of Computer Science, University of Wisconsin, Madison, WI 53705 (United States)

2005-01-01

A particularly demanding and important challenge that we face as we attempt to construct the distributed computing machinery required to support SciDAC goals is the efficient, high-performance, reliable, secure, and policy-aware management of large-scale data movement. This problem is fundamental to diverse application domains including experimental physics (high energy physics, nuclear physics, light sources), simulation science (climate, computational chemistry, fusion, astrophysics), and large-scale collaboration. In each case, highly distributed user communities require high-speed access to valuable data, whether for visualization or analysis. The quantities of data involved (terabytes to petabytes), the scale of the demand (hundreds or thousands of users, data-intensive analyses, real-time constraints), and the complexity of the infrastructure that must be managed (networks, tertiary storage systems, network caches, computers, visualization systems) make the problem extremely challenging. Data management tools developed under the auspices of the SciDAC Data Grid Middleware project have become the de facto standard for data management in projects worldwide. Day in and day out, these tools provide the 'plumbing' that allows scientists to do more science on an unprecedented scale in production environments.

Data Grid tools: enabling science on big distributed data

International Nuclear Information System (INIS)

Allcock, Bill; Chervenak, Ann; Foster, Ian; Kesselman, Carl; Livny, Miron

2005-01-01

A particularly demanding and important challenge that we face as we attempt to construct the distributed computing machinery required to support SciDAC goals is the efficient, high-performance, reliable, secure, and policy-aware management of large-scale data movement. This problem is fundamental to diverse application domains including experimental physics (high energy physics, nuclear physics, light sources), simulation science (climate, computational chemistry, fusion, astrophysics), and large-scale collaboration. In each case, highly distributed user communities require high-speed access to valuable data, whether for visualization or analysis. The quantities of data involved (terabytes to petabytes), the scale of the demand (hundreds or thousands of users, data-intensive analyses, real-time constraints), and the complexity of the infrastructure that must be managed (networks, tertiary storage systems, network caches, computers, visualization systems) make the problem extremely challenging. Data management tools developed under the auspices of the SciDAC Data Grid Middleware project have become the de facto standard for data management in projects worldwide. Day in and day out, these tools provide the 'plumbing' that allows scientists to do more science on an unprecedented scale in production environments

Molecular data and radiative transfer tools for ALMA

NARCIS (Netherlands)

Tak, F F S van der; ; Hogerheijde, M

2007-01-01

Abstract: This paper presents an overview of several modeling tools for analyzing molecular line observations at submillimeter wavelengths. These tools are already proving to be very valuable for the interpretation of data from current telescopes, and will be indispensable for data obtained with

The GNAT: A new tool for processing NMR data.

Science.gov (United States)

Castañar, Laura; Poggetto, Guilherme Dal; Colbourne, Adam A; Morris, Gareth A; Nilsson, Mathias

2018-06-01

The GNAT (General NMR Analysis Toolbox) is a free and open-source software package for processing, visualising, and analysing NMR data. It supersedes the popular DOSY Toolbox, which has a narrower focus on diffusion NMR. Data import of most common formats from the major NMR platforms is supported, as well as a GNAT generic format. Key basic processing of NMR data (e.g., Fourier transformation, baseline correction, and phasing) is catered for within the program, as well as more advanced techniques (e.g., reference deconvolution and pure shift FID reconstruction). Analysis tools include DOSY and SCORE for diffusion data, ROSY T 1 /T 2 estimation for relaxation data, and PARAFAC for multilinear analysis. The GNAT is written for the MATLAB® language and comes with a user-friendly graphical user interface. The standard version is intended to run with a MATLAB installation, but completely free-standing compiled versions for Windows, Mac, and Linux are also freely available. © 2018 The Authors Magnetic Resonance in Chemistry Published by John Wiley & Sons Ltd.

Comparisons of receive array interference reduction techniques under erroneous generalized transmit beamforming

KAUST Repository

Radaydeh, Redha Mahmoud

2014-02-01

This paper studies generalized single-stream transmit beamforming employing receive array co-channel interference reduction algorithms under slow and flat fading multiuser wireless systems. The impact of imperfect prediction of channel state information for the desired user spatially uncorrelated transmit channels on the effectiveness of transmit beamforming for different interference reduction techniques is investigated. The case of over-loaded receive array with closely-spaced elements is considered, wherein it can be configured to specified interfering sources. Both dominant interference reduction and adaptive interference reduction techniques for statistically ordered and unordered interferers powers, respectively, are thoroughly studied. The effect of outdated statistical ordering of the interferers powers on the efficiency of dominant interference reduction is studied and then compared against the adaptive interference reduction. For the system models described above, new analytical formulations for the statistics of combined signal-to-interference-plus-noise ratio are presented, from which results for conventional maximum ratio transmission and single-antenna best transmit selection can be directly deduced as limiting cases. These results are then utilized to obtain quantitative measures for various performance metrics. They are also used to compare the achieved performance of various configuration models under consideration. © 1972-2012 IEEE.

Generalized massive optimal data compression

Science.gov (United States)

Alsing, Justin; Wandelt, Benjamin

2018-05-01

In this paper, we provide a general procedure for optimally compressing N data down to n summary statistics, where n is equal to the number of parameters of interest. We show that compression to the score function - the gradient of the log-likelihood with respect to the parameters - yields n compressed statistics that are optimal in the sense that they preserve the Fisher information content of the data. Our method generalizes earlier work on linear Karhunen-Loéve compression for Gaussian data whilst recovering both lossless linear compression and quadratic estimation as special cases when they are optimal. We give a unified treatment that also includes the general non-Gaussian case as long as mild regularity conditions are satisfied, producing optimal non-linear summary statistics when appropriate. As a worked example, we derive explicitly the n optimal compressed statistics for Gaussian data in the general case where both the mean and covariance depend on the parameters.

QUICKSILVER - A general tool for electromagnetic PIC simulation

International Nuclear Information System (INIS)

Seidel, David B.; Coats, Rebecca S.; Johnson, William A.; Kiefer, Mark L.; Mix, L. Paul; Pasik, Michael F.; Pointon, Timothy D.; Quintenz, Jeffrey P.; Riley, Douglas J.; Turner, C. David

1997-01-01

The dramatic increase in computational capability that has occurred over the last ten years has allowed fully electromagnetic simulations of large, complex, three-dimensional systems to move progressively from impractical, to expensive, and recently, to routine and widespread. This is particularly true for systems that require the motion of free charge to be self-consistently treated. The QUICKSILVER electromagnetic Particle-In-Cell (EM-PIC) code has been developed at Sandia National Laboratories to provide a general tool to simulate a wide variety of such systems. This tool has found widespread use for many diverse applications, including high-current electron and ion diodes, magnetically insulated power transmission systems, high-power microwave oscillators, high-frequency digital and analog integrated circuit packages, microwave integrated circuit components, antenna systems, radar cross-section applications, and electromagnetic interaction with biological material. This paper will give a brief overview of QUICKSILVER and provide some thoughts on its future development

Software tool for data mining and its applications

Science.gov (United States)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

The PDS4 Data Dictionary Tool - Metadata Design for Data Preparers

Science.gov (United States)

Raugh, A.; Hughes, J. S.

2017-12-01

One of the major design goals of the PDS4 development effort was to create an extendable Information Model (IM) for the archive, and to allow mission data designers/preparers to create extensions for metadata definitions specific to their own contexts. This capability is critical for the Planetary Data System - an archive that deals with a data collection that is diverse along virtually every conceivable axis. Amid such diversity in the data itself, it is in the best interests of the PDS archive and its users that all extensions to the IM follow the same design techniques, conventions, and restrictions as the core implementation itself. But it is unrealistic to expect mission data designers to acquire expertise in information modeling, model-driven design, ontology, schema formulation, and PDS4 design conventions and philosophy in order to define their own metadata. To bridge that expertise gap and bring the power of information modeling to the data label designer, the PDS Engineering Node has developed the data dictionary creation tool known as "LDDTool". This tool incorporates the same software used to maintain and extend the core IM, packaged with an interface that enables a developer to create his extension to the IM using the same, standards-based metadata framework PDS itself uses. Through this interface, the novice dictionary developer has immediate access to the common set of data types and unit classes for defining attributes, and a straight-forward method for constructing classes. The more experienced developer, using the same tool, has access to more sophisticated modeling methods like abstraction and extension, and can define context-specific validation rules. We present the key features of the PDS Local Data Dictionary Tool, which both supports the development of extensions to the PDS4 IM, and ensures their compatibility with the IM.

Mobile task management tool that improves workflow of an acute general surgical service.

Science.gov (United States)

Foo, Elizabeth; McDonald, Rod; Savage, Earle; Floyd, Richard; Butler, Anthony; Rumball-Smith, Alistair; Connor, Saxon

2015-10-01

Understanding and being able to measure constraints within a health system is crucial if outcomes are to be improved. Current systems lack the ability to capture decision making with regard to tasks performed within a patient journey. The aim of this study was to assess the impact of a mobile task management tool on clinical workflow within an acute general surgical service by analysing data capture and usability of the application tool. The Cortex iOS application was developed to digitize patient flow and provide real-time visibility over clinical decision making and task performance. Study outcomes measured were workflow data capture for patient and staff events. Usability was assessed using an electronic survey. There were 449 unique patient journeys tracked with a total of 3072 patient events recorded. The results repository was accessed 7792 times. The participants reported that the application sped up decision making, reduced redundancy of work and improved team communication. The mode of the estimated time the application saved participants was 5-9 min/h of work. Of the 14 respondents, nine discarded their analogue methods of tracking tasks by the end of the study period. The introduction of a mobile task management system improved the working efficiency of junior clinical staff. The application allowed capture of data not previously available to hospital systems. In the future, such data will contribute to the accurate mapping of patient journeys through the health system. © 2015 Royal Australasian College of Surgeons.

Database tools for enhanced analysis of TMX-U data

International Nuclear Information System (INIS)

Stewart, M.E.; Carter, M.R.; Casper, T.A.; Meyer, W.H.; Perkins, D.E.; Whitney, D.M.

1986-01-01

A commercial database software package has been used to create several databases and tools that assist and enhance the ability of experimental physicists to analyze data from the Tandem Mirror Experiment-Upgrade (TMX-U) experiment. This software runs on a DEC-20 computer in M-Divisions's User Service Center at Lawrence Livermore National Laboratory (LLNL), where data can be analyzed off line from the main TMX-U acquisition computers. When combined with interactive data analysis programs, these tools provide the capability to do batch-style processing or interactive data analysis on the computers in the USC or the supercomputers of the National Magnetic Fusion Energy Computer Center (NMFECC) in addition to the normal processing done by the TMX-U acquisition system. One database tool provides highly reduced data for searching and correlation analysis of several diagnostic signals within a single shot or over many shots. A second database tool provides retrieval and storage of unreduced data for use in detailed analysis of one or more diagnostic signals. We will show how these database tools form the core of an evolving off-line data analysis environment on the USC computers

Database tools for enhanced analysis of TMX-U data

International Nuclear Information System (INIS)

Stewart, M.E.; Carter, M.R.; Casper, T.A.; Meyer, W.H.; Perkins, D.E.; Whitney, D.M.

1986-01-01

A commercial database software package has been used to create several databases and tools that assist and enhance the ability of experimental physicists to analyze data from the Tandem Mirror Experiment-Upgrade (TMX-U) experiment. This software runs on a DEC-20 computer in M-Division's User Service Center at Lawrence Livermore National Laboratory (LLNL), where data can be analyzed offline from the main TMX-U acquisition computers. When combined with interactive data analysis programs, these tools provide the capability to do batch-style processing or interactive data analysis on the computers in the USC or the supercomputers of the National Magnetic Fusion Energy Computer Center (NMFECC) in addition to the normal processing done by the TMX-U acquisition system. One database tool provides highly reduced data for searching and correlation analysis of several diagnostic signals within a single shot or over many shots. A second database tool provides retrieval and storage of unreduced data for use in detailed analysis of one or more diagnostic signals. We will show how these database tools form the core of an evolving offline data analysis environment on the USC computers

Tools and data services registry

DEFF Research Database (Denmark)

Ison, Jon; Rapacki, Kristoffer; Ménager, Hervé

2016-01-01

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a...

An interactive visualization tool for multi-channel confocal microscopy data in neurobiology research

KAUST Repository

Yong Wan,

2009-11-01

Confocal microscopy is widely used in neurobiology for studying the three-dimensional structure of the nervous system. Confocal image data are often multi-channel, with each channel resulting from a different fluorescent dye or fluorescent protein; one channel may have dense data, while another has sparse; and there are often structures at several spatial scales: subneuronal domains, neurons, and large groups of neurons (brain regions). Even qualitative analysis can therefore require visualization using techniques and parameters fine-tuned to a particular dataset. Despite the plethora of volume rendering techniques that have been available for many years, the techniques standardly used in neurobiological research are somewhat rudimentary, such as looking at image slices or maximal intensity projections. Thus there is a real demand from neurobiologists, and biologists in general, for a flexible visualization tool that allows interactive visualization of multi-channel confocal data, with rapid fine-tuning of parameters to reveal the three-dimensional relationships of structures of interest. Together with neurobiologists, we have designed such a tool, choosing visualization methods to suit the characteristics of confocal data and a typical biologist\\'s workflow. We use interactive volume rendering with intuitive settings for multidimensional transfer functions, multiple render modes and multi-views for multi-channel volume data, and embedding of polygon data into volume data for rendering and editing. As an example, we apply this tool to visualize confocal microscopy datasets of the developing zebrafish visual system.

A Generalized Correlation Plot Package for the CEBAF Control System

International Nuclear Information System (INIS)

D. Wu; W. Akers; S. Schaffner; H. Shoaee; W. A. Watson; D. Wetherholt

1996-01-01

The Correlation Package is a general facility for data acquisition and analysis serving as an online environment for performing a wide variety of machine physics experiments and engineering diagnostics. Typical correlation experiments consist of an initial set of actions followed by stepping one or two accelerator parameters while measuring up to several hundred control system parameters. The package utilizes the CDEV [1] device API to access accelerator systems. A variety of analysis and graphics tools are included through integration with the Matlab math modeling package. A post- acquisition script capability is available to automate the data reduction process. A callable interface allows this facility to serve as the data acquisition and analysis engine for high level applications. A planned interface to archived accelerator data will allow the same analysis and graphics tools to be used for viewing and correlating history data. The object oriented design and C++ implementation details as well as the current status of the Correlation Package will be presented

Big Data, Biostatistics and Complexity Reduction

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2018-01-01

Roč. 14, č. 2 (2018), s. 24-32 ISSN 1801-5603 R&D Projects: GA MZd(CZ) NV15-29835A Institutional support: RVO:67985807 Keywords : Biostatistics * Big data * Multivariate statistics * Dimensionality * Variable selection Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) https://www.ejbi.org/scholarly-articles/big-data-biostatistics-and-complexity-reduction.pdf

Big Data as a Revolutionary Tool in Finance

Directory of Open Access Journals (Sweden)

Aureliano Angel Bressan

2015-08-01

Full Text Available A data driven culture is arising as a research field and analytic tool in Finance and Management since the advent of structured, semi-structured and unstructured socio-economic and demographic information from social media, mobile devices, blogs and product reviews from consumers. Big Data, the expression that encompasses this revolution, involves the usage of new tools for financial professionals and academic researchers due to the size of data involved, which require more powerful manipulation tools. In this sense, Machine Learning techniques can allow more effective ways to model complex relationships that arise from the interaction of different types of data, regarding issues such as Operational and Reputational Risk, Portfolio Management, Business Intelligence and Predictive Analytics. The following books can be a good start for those interested in this new field.

Differential reduction of generalized hypergeometric functions from Feynman diagrams. One-variable case

Energy Technology Data Exchange (ETDEWEB)

Bytev, Vladimir V.; Kalmykov, Mikhail Yu.; Kniehl, Bernd A. [Hamburg Univ. (Germany). II. Inst. fuer Theoretische Physik

2010-03-15

The differential-reduction algorithm, which allows one to express generalized hypergeometric functions with parameters of arbitrary values in terms of such functions with parameters whose values differ from the original ones by integers, is discussed in the context of evaluating Feynman diagrams. Where this is possible, we compare our results with those obtained using standard techniques. It is shown that the criterion of reducibility of multiloop Feynman integrals can be reformulated in terms of the criterion of reducibility of hypergeometric functions. The relation between the numbers of master integrals obtained by differential reduction and integration by parts is discussed. (orig.)

Accounting for Natural Reduction of Nitrogen

DEFF Research Database (Denmark)

Højberg, A L; Refsgaard, J. C.; Hansen, A.L.

the same restriction for all areas independent on drainage schemes, hydrogeochemical conditions in the subsurface and retention in surface waters. Although significant reductions have been achieved this way, general measures are not cost-effective, as nitrogen retention (primarily as denitrification...... degradation at a sufficient small scale with adequate certainty. The development of a national model to describe nitrogen leaching, transport and degradation as well as related uncertainty revealed that a national approach, based on existing data and knowledge, would be associated with significant...... Scales” (www.nitrate.dk), aims at advancing the understanding of these processes and quantify their impact on nitrate transport and transformation. The project combines detailed field studies and model simulations and develops methodologies and tools to: i) detect drain pipe location and quantify...

Time varying, multivariate volume data reduction

Energy Technology Data Exchange (ETDEWEB)

Ahrens, James P [Los Alamos National Laboratory; Fout, Nathaniel [UC DAVIS; Ma, Kwan - Liu [UC DAVIS

2010-01-01

Large-scale supercomputing is revolutionizing the way science is conducted. A growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. The data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. Transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. Although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering. In this paper we present our study of multivariate compression, which exploits correlations among related variables, for volume rendering. Two configurations for multidimensional compression based on vector quantization are examined. We emphasize quality reconstruction and interactive rendering, which leads us to a solution using graphics hardware to perform on-the-fly decompression during rendering. In this paper we present a solution which addresses the need for data reduction in large supercomputing environments where data resulting from simulations occupies tremendous amounts of storage. Our solution employs a lossy encoding scheme to acrueve data reduction with several options in terms of rate-distortion behavior. We focus on encoding of multiple variables together, with optional compression in space and time. The compressed volumes can be rendered directly with commodity graphics cards at interactive frame rates and rendering quality similar to that of static volume renderers. Compression results using a multivariate time-varying data set indicate that encoding multiple variables results in acceptable performance in the case of spatial and temporal encoding as compared to independent compression of variables. The relative performance of spatial vs. temporal compression is data dependent, although temporal compression has the

Implementation of on-line data reduction algorithms in the CMS Endcap Preshower Data Concentrator Cards

CERN Document Server

Barney, D; Kokkas, P; Manthos, N; Sidiropoulos, G; Reynaud, S; Vichoudis, P

2007-01-01

The CMS Endcap Preshower (ES) sub-detector comprises 4288 silicon sensors, each containing 32 strips. The data are transferred from the detector to the counting room via 1208 optical fibres running at 800Mbps. Each fibre carries data from two, three or four sensors. For the readout of the Preshower, a VME-based system, the Endcap Preshower Data Concentrator Card (ES-DCC), is currently under development. The main objective of each readout board is to acquire on-detector data from up to 36 optical links, perform on-line data reduction via zero suppression and pass the concentrated data to the CMS event builder. This document presents the conceptual design of the Reduction Algorithms as well as their implementation in the ES-DCC FPGAs. These algorithms, as implemented in the ES-DCC, result in a data-reduction factor of 20.

SECIMTools: a suite of metabolomics data analysis tools.

Science.gov (United States)

Kirpich, Alexander S; Ibarra, Miguel; Moskalenko, Oleksandr; Fear, Justin M; Gerken, Joseph; Mi, Xinlei; Ashrafi, Ali; Morse, Alison M; McIntyre, Lauren M

2018-04-20

Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists. SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net). SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

CUAHSI Data Services: Tools and Cyberinfrastructure for Water Data Discovery, Research and Collaboration

Science.gov (United States)

Seul, M.; Brazil, L.; Castronova, A. M.

2017-12-01

CUAHSI Data Services: Tools and Cyberinfrastructure for Water Data Discovery, Research and CollaborationEnabling research surrounding interdisciplinary topics often requires a combination of finding, managing, and analyzing large data sets and models from multiple sources. This challenge has led the National Science Foundation to make strategic investments in developing community data tools and cyberinfrastructure that focus on water data, as it is central need for many of these research topics. CUAHSI (The Consortium of Universities for the Advancement of Hydrologic Science, Inc.) is a non-profit organization funded by the National Science Foundation to aid students, researchers, and educators in using and managing data and models to support research and education in the water sciences. This presentation will focus on open-source CUAHSI-supported tools that enable enhanced data discovery online using advanced searching capabilities and computational analysis run in virtual environments pre-designed for educators and scientists so they can focus their efforts on data analysis rather than IT set-up.

Abstract interfaces for data analysis - component architecture for data analysis tools

International Nuclear Information System (INIS)

Barrand, G.; Binko, P.; Doenszelmann, M.; Pfeiffer, A.; Johnson, A.

2001-01-01

The fast turnover of software technologies, in particular in the domain of interactivity (covering user interface and visualisation), makes it difficult for a small group of people to produce complete and polished software-tools before the underlying technologies make them obsolete. At the HepVis'99 workshop, a working group has been formed to improve the production of software tools for data analysis in HENP. Beside promoting a distributed development organisation, one goal of the group is to systematically design a set of abstract interfaces based on using modern OO analysis and OO design techniques. An initial domain analysis has come up with several categories (components) found in typical data analysis tools: Histograms, Ntuples, Functions, Vectors, Fitter, Plotter, analyzer and Controller. Special emphasis was put on reducing the couplings between the categories to a minimum, thus optimising re-use and maintainability of any component individually. The interfaces have been defined in Java and C++ and implementations exist in the form of libraries and tools using C++ (Anaphe/Lizard, OpenScientist) and Java (Java Analysis Studio). A special implementation aims at accessing the Java libraries (through their Abstract Interfaces) from C++. The authors give an overview of the architecture and design of the various components for data analysis as discussed in AIDA

Environmental Remediation Data Management Tools

International Nuclear Information System (INIS)

Wierowski, J. V.; Henry, L. G.; Dooley, D. A.

2002-01-01

Computer software tools for data management can improve site characterization, planning and execution of remediation projects. This paper discusses the use of two such products that have primarily been used within the nuclear power industry to enhance the capabilities of radiation protection department operations. Advances in digital imaging, web application development and programming technologies have made development of these tools possible. The Interactive Visual Tour System (IVTS) allows the user to easily create and maintain a comprehensive catalog containing digital pictures of the remediation site. Pictures can be cataloged in groups (termed ''tours'') that can be organized either chronologically or spatially. Spatial organization enables the user to ''walk around'' the site and view desired areas or components instantly. Each photo is linked to a map (floor plan, topographical map, elevation drawing, etc.) with graphics displaying the location on the map and any available tour/component links. Chronological organization enables the user to view the physical results of the remediation efforts over time. Local and remote management teams can view these pictures at any time and from any location. The Visual Survey Data System (VSDS) allows users to record survey and sample data directly on photos and/or maps of areas and/or components. As survey information is collected for each area, survey data trends can be reviewed for any repetitively measured location or component. All data is stored in a Quality Assurance (Q/A) records database with reference to its physical sampling point on the site as well as other information to support the final closeout report for the site. The ease of use of these web-based products has allowed nuclear power plant clients to plan outage work from their desktop and realize significant savings with respect to dose and cost. These same tools are invaluable for remediation and decommissioning planning of any scale and for recording

Data Mining Practical Machine Learning Tools and Techniques

CERN Document Server

Witten, Ian H; Hall, Mark A

2011-01-01

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place

Implementation of On-Line Data Reduction Algorithms in the CMS Endcap Preshower Data Concentrator Card

CERN Document Server

Barney, David; Kokkas, Panagiotis; Manthos, Nikolaos; Reynaud, Serge; Sidiropoulos, Georgios; Vichoudis, Paschalis

2006-01-01

The CMS Endcap Preshower (ES) sub-detector comprises 4288 silicon sensors, each containing 32 strips. The data are transferred from the detector to the counting room via 1208 optical fibres running at 800Mbps. Each fibre carries data from 2, 3 or 4 sensors. For the readout of the Preshower, a VME-based system - the Endcap Preshower Data Concentrator Card (ES-DCC) is currently under development. The main objective of each readout board is to acquire on-detector data from up to 36 optical links, perform on-line data reduction (zero suppression) and pass the concentrated data to the CMS event builder. This document presents the conceptual design of the Reduction Algorithms as well as their implementation into the ES-DCC FPGAs. The algorithms implemented into the ES-DCC resulted in a reduction factor of ~20.

HAEMATOMA BLOCK- AN EFFECTIVE ALTERNATIVE TO GENERAL ANAESTHESIA FOR REDUCTION OF DISTAL RADIUS FRACTURES

Directory of Open Access Journals (Sweden)

Prabhati Rani Mishra

2016-12-01

Full Text Available BACKGROUND Most common fracture in elderly patients is distal radius fracture. The most common method of management is closed reduction and immobilisation. The aim of the study is to compare the analgesic effects of haematoma block and general anaesthesia for closed reduction of distal fracture of radius. MATERIALS AND METHODS A prospective randomised controlled study was carried out among 100 patients of age group between 15-70 years of either sex who had fracture distal radius between 2015-2016. The patients having multiple fractures, pathological fractures or suffering from any organic diseases were excluded from the study. After taking informed written consent, the patients were randomised into two equal groups. In group A, reduction of fracture was done following administration of IV propofol and in group B after infiltration with 2% lignocaine into fracture haematoma site. Pain score was compared by VAS before, during and after manipulation in both the groups. Time taken from presentation at emergency department to reduction and discharge from hospital was also compared. Statistical analysis was done by applying SPSS software. RESULTS 100 patients of mean age 42.5 years, male: female 43:57 with fracture distal radius were studied. Mean time from admission to fracture reduction in group A was 2.64±0.93 hours and in group B 0.90±0.45 hours (P=0.0001. Discharge time from hospital after reduction of fracture in group A was 4.24±0.94 hours and in group B 0.75±0.2 hours (P=0.0001. VAS during reduction in group A was 0 and in group B 0.98±0.8 (P=0.0001. 10 minutes after reduction VAS in group A was 2.28±0.24 and group B 0.72±0.45 (P=0.0001. CONCLUSION For closed reduction of distal radius fracture, haematoma block with lignocaine is safe and effective alternative to intravenous general anaesthesia with propofol.

Hurricane Data Analysis Tool

Science.gov (United States)

Liu, Zhong; Ostrenga, Dana; Leptoukh, Gregory

2011-01-01

In order to facilitate Earth science data access, the NASA Goddard Earth Sciences Data Information Services Center (GES DISC) has developed a web prototype, the Hurricane Data Analysis Tool (HDAT; URL: http://disc.gsfc.nasa.gov/HDAT), to allow users to conduct online visualization and analysis of several remote sensing and model datasets for educational activities and studies of tropical cyclones and other weather phenomena. With a web browser and few mouse clicks, users can have a full access to terabytes of data and generate 2-D or time-series plots and animation without downloading any software and data. HDAT includes data from the NASA Tropical Rainfall Measuring Mission (TRMM), the NASA Quick Scatterometer(QuikSCAT) and NECP Reanalysis, and the NCEP/CPC half-hourly, 4-km Global (60 N - 60 S) IR Dataset. The GES DISC archives TRMM data. The daily global rainfall product derived from the 3-hourly multi-satellite precipitation product (3B42 V6) is available in HDAT. The TRMM Microwave Imager (TMI) sea surface temperature from the Remote Sensing Systems is in HDAT as well. The NASA QuikSCAT ocean surface wind and the NCEP Reanalysis provide ocean surface and atmospheric conditions, respectively. The global merged IR product, also known as, the NCEP/CPC half-hourly, 4-km Global (60 N -60 S) IR Dataset, is one of TRMM ancillary datasets. They are globally-merged pixel-resolution IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 & GMS). The GES DISC has collected over 10 years of the data beginning from February of 2000. This high temporal resolution (every 30 minutes) dataset not only provides additional background information to TRMM and other satellite missions, but also allows observing a wide range of meteorological phenomena from space, such as, hurricanes, typhoons, tropical cyclones, mesoscale convection system, etc. Basic functions include selection of area of

History plotting tool for Data Quality Monitoring

International Nuclear Information System (INIS)

Giordano, D.; Le Bihan, A.-C.; Pierro, A.; De Mattia, M.

2010-01-01

The size and complexity of the CMS detector makes the Data Quality Monitoring (DQM) system very challenging. Given the high granularity of the CMS sub-detectors, several approaches and tools have been developed to monitor the detector performance closely. We describe here the History DQM, a tool allowing the detector performance monitoring over time.

Generalized G-theory

International Nuclear Information System (INIS)

Sladkowski, J.

1991-01-01

Various attempts to formulate the fundamental physical interactions in the framework of unified geometric theories have recently gained considerable success (Kaluza, 1921; Klein, 1926; Trautmann, 1970; Cho, 1975). Symmetries of the spacetime and so-called internal spaces seem to play a key role in investigating both the fundamental interactions and the abundance of elementary particles. The author presents a category-theoretic description of a generalization of the G-theory concept and its application to geometric compactification and dimensional reduction. The main reasons for using categories and functors as tools are the clearness and the level of generalization one can obtain

NTL Data Management Planning "Greenout" Bingo Self Assessment Tool

Science.gov (United States)

2016-08-11

This tool is designed to help assess your current data management practices. Pick a dataset or research project, sit down with your data collection team, and discuss each prompt below. This tool can guide DMP improvement by revealing best practices t...

Data from mobile phone operators: A tool for smarter cities?

NARCIS (Netherlands)

Steenbruggen, J.; Tranos, E.; Nijkamp, P.

2015-01-01

Abstract The use of mobile phone data provides new spatio-temporal tools for improving urban planning, and for reducing inefficiencies in present-day urban systems. Data from mobile phones, originally intended as a communication tool, are increasingly used as innovative tools in geography and social

GBTIDL: Reduction and Analysis of GBT Spectral Line Data

Science.gov (United States)

Marganian, P.; Garwood, R. W.; Braatz, J. A.; Radziwill, N. M.; Maddalena, R. J.

2013-03-01

GBTIDL is an interactive package for reduction and analysis of spectral line data taken with the Robert C. Byrd Green Bank Telescope (GBT). The package, written entirely in IDL, consists of straightforward yet flexible calibration, averaging, and analysis procedures (the "GUIDE layer") modeled after the UniPOPS and CLASS data reduction philosophies, a customized plotter with many built-in visualization features, and Data I/O and toolbox functionality that can be used for more advanced tasks. GBTIDL makes use of data structures which can also be used to store intermediate results. The package consumes and produces data in GBT SDFITS format. GBTIDL can be run online and have access to the most recent data coming off the telescope, or can be run offline on preprocessed SDFITS files.

Tools for Educational Data Mining: A Review

Science.gov (United States)

Slater, Stefan; Joksimovic, Srecko; Kovanovic, Vitomir; Baker, Ryan S.; Gasevic, Dragan

2017-01-01

In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will…

Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets

DEFF Research Database (Denmark)

Pereira, Ivo F.; Sousa, Tiago; Praca, Isabel

2014-01-01

of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge to define realistic scenarios, which are essential for understanding and forecast electricity markets behavior. The development of tools able to extract, transform, store and dynamically update data......, is of great importance to go a step further into the comprehension of electricity markets and of the behaviour of the involved entities. In this paper an adaptable tool capable of downloading, parsing and storing data from market operators’ websites is presented, assuring constant updating and reliability...... of the stored data....

Orbiter data reduction complex data processing requirements for the OFT mission evaluation team (level C)

Science.gov (United States)

1979-01-01

This document addresses requirements for post-test data reduction in support of the Orbital Flight Tests (OFT) mission evaluation team, specifically those which are planned to be implemented in the ODRC (Orbiter Data Reduction Complex). Only those requirements which have been previously baselined by the Data Systems and Analysis Directorate configuration control board are included. This document serves as the control document between Institutional Data Systems Division and the Integration Division for OFT mission evaluation data processing requirements, and shall be the basis for detailed design of ODRC data processing systems.

Accounting and Financial Data Analysis Data Mining Tools

Directory of Open Access Journals (Sweden)

Diana Elena Codreanu

2011-05-01

Full Text Available Computerized accounting systems in recent years have seen an increase in complexity due to thecompetitive economic environment but with the help of data analysis solutions such as OLAP and DataMining can be a multidimensional data analysis, can detect the fraud and can discover knowledge hidden indata, ensuring such information is useful for decision making within the organization. In the literature thereare many definitions for data mining but all boils down to same idea: the process takes place to extract newinformation from large data collections, information without the aid of data mining tools would be verydifficult to obtain. Information obtained by data mining process has the advantage that only respond to thequestion of what happens but at the same time argue and show why certain things are happening. In this paperwe wish to present advanced techniques for analysis and exploitation of data stored in a multidimensionaldatabase.

Building the evidence base for stigma and discrimination-reduction programming in Thailand: development of tools to measure healthcare stigma and discrimination

Directory of Open Access Journals (Sweden)

Kriengkrai Srithanaviboonchai

2017-03-01

Full Text Available Abstract Background HIV-related stigma and discrimination (S&D are recognized as key impediments to controlling the HIV epidemic. S&D are particularly detrimental within health care settings because people who are at risk of HIV and people living with HIV (PLHIV must seek services from health care facilities. Standardized tools and monitoring systems are needed to inform S&D reduction efforts, measure progress, and monitor trends. This article describes the processes followed to adapt and refine a standardized global health facility staff S&D questionnaire for the context of Thailand and develop a similar questionnaire measuring health facility stigma experienced by PLHIV. Both questionnaires are currently being used for the routine monitoring of HIV-related S&D in the Thai healthcare system. Methods The questionnaires were adapted through a series of consultative meetings, pre-testing, and revision. The revised questionnaires then underwent field testing, and the data and field experiences were analyzed. Results Two brief questionnaires were finalized and are now being used by the Department of Disease Control to collect national routine data for monitoring health facility S&D: 1 a health facility staff questionnaire that collects data on key drivers of S&D in health facilities (i.e., fear of HIV infection, attitudes toward PLHIV and key populations, and health facility policy and environment and observed enacted stigma and 2 a brief PLHIV questionnaire that captures data on experienced discriminatory practices at health care facilities. Conclusions This effort provides an example of how a country can adapt global S&D measurement tools to a local context for use in national routine monitoring. Such data helps to strengthen the national response to HIV through the provision of evidence to shape S&D-reduction programming.

Reducing catheter-related thrombosis using a risk reduction tool centered on catheter to vessel ratio.

Science.gov (United States)

Spencer, Timothy R; Mahoney, Keegan J

2017-11-01

In vascular access practices, the internal vessel size is considered important, and a catheter to vessel ratio (CVR) is recommended to assist clinicians in selecting the most appropriate-sized device for the vessel. In 2016, new practice recommendations stated that the CVR can increase from 33 to 45% of the vessels diameter. There has been evidence on larger diameter catheters and increased thrombosis risk in recent literature, while insufficient information established on what relationship to vessel size is appropriate for any intra-vascular device. Earlier references to clinical standards and guidelines did not clearly address vessel size in relation to the area consumed or external catheter diameter. The aim of this manuscript is to present catheter-related thrombosis evidence and develop a standardized process of ultrasound-guided vessel assessment, integrating CVR, Virchow's triad phenomenon and vessel health and preservation strategies, empowering an evidence-based approach to device placement. Through review, calculation and assessment on the areas of the 33 and 45% rule, a preliminary clinical tool was developed to assist clinicians make cognizant decisions when placing intravascular devices relating to target vessel size, focusing on potential reduction in catheter-related thrombosis. Increasing the understanding and utilization of CVRs will lead to a safer, more consistent approach to device placement, with potential thrombosis reduction strategies. The future of evidence-based data relies on the clinician to capture accurate vessel measurements and device-related outcomes. This will lead to a more dependable data pool, driving the relationship of catheter-related thrombosis and vascular assessment.

Interactive Data Visualization for HIV Cohorts: Leveraging Data Exchange Standards to Share and Reuse Research Tools.

Directory of Open Access Journals (Sweden)

Meridith Blevins

Full Text Available To develop and disseminate tools for interactive visualization of HIV cohort data.If a picture is worth a thousand words, then an interactive video, composed of a long string of pictures, can produce an even richer presentation of HIV population dynamics. We developed an HIV cohort data visualization tool using open-source software (R statistical language. The tool requires that the data structure conform to the HIV Cohort Data Exchange Protocol (HICDEP, and our implementation utilized Caribbean, Central and South America network (CCASAnet data.This tool currently presents patient-level data in three classes of plots: (1 Longitudinal plots showing changes in measurements viewed alongside event probability curves allowing for simultaneous inspection of outcomes by relevant patient classes. (2 Bubble plots showing changes in indicators over time allowing for observation of group level dynamics. (3 Heat maps of levels of indicators changing over time allowing for observation of spatial-temporal dynamics. Examples of each class of plot are given using CCASAnet data investigating trends in CD4 count and AIDS at antiretroviral therapy (ART initiation, CD4 trajectories after ART initiation, and mortality.We invite researchers interested in this data visualization effort to use these tools and to suggest new classes of data visualization. We aim to contribute additional shareable tools in the spirit of open scientific collaboration and hope that these tools further the participation in open data standards like HICDEP by the HIV research community.

Tools and data for meeting America's conservation challenges

Science.gov (United States)

Gergely, Kevin J.; McKerrow, Alexa

2013-01-01

The Gap Analysis Program (GAP) produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The GAP is managed by the U.S. Geological Survey, Department of the Interior. GAP supports a wide range of national, State, and local agencies as well as nongovernmental organizations and businesses with scientific tools and data. GAP uses a collaborative approach to do research, analysis, and data development, resulting in a history of cooperation with more than 500 agencies and organizations nationally.

A "Carbon Reduction Challenge" as tool for undergraduate engagement on climate change

Science.gov (United States)

Cobb, K. M.; Toktay, B.

2017-12-01

Challenge represents a solutions-oriented, hands-on, project-based learning tool that has achieved significant pedagogical benefits while delivering real-world carbon reductions and cost savings to community stakeholders.

Tools for educational access to seismic data

Science.gov (United States)

Taber, J. J.; Welti, R.; Bravo, T. K.; Hubenthal, M.; Frechette, K.

2017-12-01

Student engagement can be increased both by providing easy access to real data, and by addressing newsworthy events such as recent large earthquakes. IRIS EPO has a suite of access and visualization tools that can be used for such engagement, including a set of three tools that allow students to explore global seismicity, use seismic data to determine Earth structure, and view and analyze near-real-time ground motion data in the classroom. These tools are linked to online lessons that are designed for use in middle school through introductory undergraduate classes. The IRIS Earthquake Browser allows discovery of key aspects of plate tectonics, earthquake locations (in pseudo 3D) and seismicity rates and patterns. IEB quickly displays up to 20,000 seismic events over up to 30 years, making it one of the most responsive, practical ways to visualize historical seismicity in a browser. Maps are bookmarkable and preserve state, meaning IEB map links can be shared or worked into a lesson plan. The Global Seismogram Plotter automatically creates visually clear seismic record sections from selected large earthquakes that are tablet-friendly and can also to be printed for use in a classroom without computers. The plots are designed to be appropriate for use with no parameters to set, but users can also modify the plots, such as including a recording station near a chosen location. A guided exercise is provided where students use the record section to discover the diameter of Earth's outer core. Students can pick and compare phase arrival times onscreen which is key to performing the exercise. A companion station map shows station locations and further information and is linked to the record section. jAmaSeis displays seismic data in real-time from either a local instrument and/or from remote seismic stations that stream data using standard seismic data protocols, and can be used in the classroom or as a public display. Users can filter data, fit a seismogram to travel time

Gender and poverty reduction strategy processes in Latin America

OpenAIRE

Dijkstra, Geske

2007-01-01

textabstractIn 1999, countries that wished to qualify for the Enhanced Initiative for the Heavily Indebted Poor Countries (HIPC initiative) had to elaborate Poverty Reduction Strategy Papers (PRSP) and had to do so with participation of civil society. Since then, the elaboration and subsequent implementation of PRSs (Poverty Reduction Strategies)have been seen as a tool for the international donor community to guarantee that not only debt relief, but also aid in general would be spent well. T...

Individual and social learning processes involved in the acquisition and generalization of tool use in macaques

Science.gov (United States)

Macellini, S.; Maranesi, M.; Bonini, L.; Simone, L.; Rozzi, S.; Ferrari, P. F.; Fogassi, L.

2012-01-01

Macaques can efficiently use several tools, but their capacity to discriminate the relevant physical features of a tool and the social factors contributing to their acquisition are still poorly explored. In a series of studies, we investigated macaques' ability to generalize the use of a stick as a tool to new objects having different physical features (study 1), or to new contexts, requiring them to adapt the previously learned motor strategy (study 2). We then assessed whether the observation of a skilled model might facilitate tool-use learning by naive observer monkeys (study 3). Results of study 1 and study 2 showed that monkeys trained to use a tool generalize this ability to tools of different shape and length, and learn to adapt their motor strategy to a new task. Study 3 demonstrated that observing a skilled model increases the observers' manipulations of a stick, thus facilitating the individual discovery of the relevant properties of this object as a tool. These findings support the view that in macaques, the motor system can be modified through tool use and that it has a limited capacity to adjust the learnt motor skills to a new context. Social factors, although important to facilitate the interaction with tools, are not crucial for tool-use learning. PMID:22106424

Swift UVOT Grism Observations of Nearby Type Ia Supernovae - I. Observations and Data Reduction

Science.gov (United States)

Pan, Y.-C.; Foley, R. J.; Filippenko, A. V.; Kuin, N. P. M.

2018-05-01

Ultraviolet (UV) observations of Type Ia supernovae (SNe Ia) are useful tools for understanding progenitor systems and explosion physics. In particular, UV spectra of SNe Ia, which probe the outermost layers, are strongly affected by the progenitor metallicity. In this work, we present 120 Neil Gehrels Swift Observatory UV spectra of 39 nearby SNe Ia. This sample is the largest UV (λ Ia to date, doubling the number of UV spectra and tripling the number of SNe with UV spectra. The sample spans nearly the full range of SN Ia light-curve shapes (Δm15(B) ≈ 0.6-1.8 mag). The fast turnaround of Swift allows us to obtain UV spectra at very early times, with 13 out of 39 SNe having their first spectra observed ≳ 1 week before peak brightness and the earliest epoch being 16.5 days before peak brightness. The slitless design of the Swift UV grism complicates the data reduction, which requires separating SN light from underlying host-galaxy light and occasional overlapping stellar light. We present a new data-reduction procedure to mitigate these issues, producing spectra that are significantly improved over those of standard methods. For a subset of the spectra we have nearly simultaneous Hubble Space Telescope UV spectra; the Swift spectra are consistent with these comparison data.

User's manual for the UNDERDOG [Underground Nuclear Depository Evaluation, Reduction, and Detailed Output Generator] data reduction software

International Nuclear Information System (INIS)

Ball, J.R.; Shepard, L.K.

1987-12-01

UNDERDOG is a computer program that aids experimentalists in the process of data reduction. This software allows a user to reduce, extract, and generate displays of data collected at the WIPP site. UNDERDOG contains three major functional components: a Data Reduction package, a Data Analysis interface, and a Publication-Quality Output generator. It also maintains audit trails of all actions performed for quality assurance purposes and provides mechanisms which control an individual's access to the data. UNDERDOG was designed to run on a Digital Equipment Corporation VAX computer using the VMS operating system. 8 refs., 24 figs., 2 tabs

The value of statistical tools to detect data fabrication

NARCIS (Netherlands)

Hartgerink, C.H.J.; Wicherts, J.M.; van Assen, M.A.L.M.

2016-01-01

We aim to investigate how statistical tools can help detect potential data fabrication in the social- and medical sciences. In this proposal we outline three projects to assess the value of such statistical tools to detect potential data fabrication and make the first steps in order to apply them

The RACER (risk analysis, communication, evaluation, and reduction) stakeholder environmental data transparency project for Los Alamos National Laboratory

International Nuclear Information System (INIS)

Echohawk, John Chris; Dorries, Alison M.; Eberhart, Craig F.; Werdel, Nancy

2008-01-01

The RACER (Risk Analysis, Communication, Evaluation, and Reduction) project was created in 2003, as an effort to enhance the Los Alamos National Laboratory's ability to effectively communicate the data and processes used to evaluate environmental risks to the public and the environment. The RACER project staff consists of members of Risk Assessment Corporation, Los Alamos National Laboratory (LANL), and the New Mexico Environment Department (NMED). RACER staff worked closely with members of the community, tribal governments, and others within NMED and LANL to create innovative tools and a process that could provide information to regulators, LANL and the community about the sources of public health risk and ecological impact from LAN L operations. The RACER Data Analysis Tool (DA T) provides the public with webbased access to environmental measurement data collected in and around the LANL site. Its purpose is to provide a 'transparent' view to the public of all data collected by LANL and NMED regarding the LANL site. The DAT is available to the public at 'www.racernm.com'.

ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data.

Directory of Open Access Journals (Sweden)

Yuttachon Promworn

Full Text Available Biochemical methods are available for enriching 5' ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5' ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance.We present Transformation of Nucleotide Enrichment Ratios (ToNER, a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5' ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5' ends than TSSAR. In general, the transcript 5' ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR.ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5'ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a.biotec.or.th/GI/tools

ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data.

Science.gov (United States)

Promworn, Yuttachon; Kaewprommal, Pavita; Shaw, Philip J; Intarapanich, Apichart; Tongsima, Sissades; Piriyapongsa, Jittima

2017-01-01

Biochemical methods are available for enriching 5' ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq) and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5' ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance. We present Transformation of Nucleotide Enrichment Ratios (ToNER), a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5' ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5' ends than TSSAR. In general, the transcript 5' ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR. ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5'ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a.biotec.or.th/GI/tools/toner) and Git

Dynamical reduction models with general gaussian noises

International Nuclear Information System (INIS)

Bassi, Angelo; Ghirardi, GianCarlo

2002-02-01

We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the statevector, white noise stochastic processes with non white ones. We prove that such a modification can be consistently performed without altering the most interesting features of the previous models. One of the reasons to discuss this matter derives from the desire of being allowed to deal with physical stochastic fields, such as the gravitational one, which cannot give rise to white noises. From our point of view the most relevant motivation for the approach we propose here derives from the fact that in relativistic models the occurrence of white noises is the main responsible for the appearance of untractable divergences. Therefore, one can hope that resorting to non white noises one can overcome such a difficulty. We investigate stochastic equations with non white noises, we discuss their reduction properties and their physical implications. Our analysis has a precise interest not only for the above mentioned subject but also for the general study of dissipative systems and decoherence. (author)

Dynamical reduction models with general Gaussian noises

International Nuclear Information System (INIS)

Bassi, Angelo; Ghirardi, GianCarlo

2002-01-01

We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the state vector, white-noise stochastic processes with nonwhite ones. We prove that such a modification can be consistently performed without altering the most interesting features of the previous models. One of the reasons to discuss this matter derives from the desire of being allowed to deal with physical stochastic fields, such as the gravitational one, which cannot give rise to white noises. From our point of view, the most relevant motivation for the approach we propose here derives from the fact that in relativistic models intractable divergences appear as a consequence of the white nature of the noises. Therefore, one can hope that resorting to nonwhite noises, one can overcome such a difficulty. We investigate stochastic equations with nonwhite noises, we discuss their reduction properties and their physical implications. Our analysis has a precise interest not only for the above-mentioned subject but also for the general study of dissipative systems and decoherence

Hipparcos, the new reduction of the raw data

CERN Document Server

van Leeuwen, Floor

2007-01-01

The new reduction of the Hipparcos data presents a very significant improvement in the overall reliability of the astrometric catalogue derived from this mission. Improvements by up to a factor 4 in the accuracies for in particular brighter stars have been obtained. This has been achieved mainly through careful study of the satellite dynamics, and incorporating results from these studies in the attitude modelling. Data correlations, caused by attitude-modelling errors in the original catalogue, have all but disappeared. This book provides overviews of the new reduction as well as on the use of the Hipparcos data in a variety of astrophysical implementations. A range of new results, like cluster distances and luminosity calibrations, is presented. The Hipparcos data provide a unique opportunity for the study of satellite dynamics. The orbit covered a wide range of altitudes, showing in detail the different torques acting on the satellite. One part of the book details these studies and their impact on the new r...

Exposure Assessment Tools by Lifestages and Populations - General Population

Science.gov (United States)

EPA ExpoBox is a toolbox for exposure assessors. Its purpose is to provide a compendium of exposure assessment and risk characterization tools that will present comprehensive step-by-step guidance and links to relevant exposure assessment data bases

Automated multispectra alpha spectrometer and data reduction system

International Nuclear Information System (INIS)

Hochel, R.C.

1975-12-01

A complete hardware and software package for the accumulation and rapid analysis of multiple alpha pulse height spectra has been developed. The system utilizes a 4096-channel analyzer capable of accepting up to sixteen inputs from solid-state surface barrier detectors via mixer-router modules. The analyzer is interfaced to a desk-top programmable calculator and thermal line printer. A chained software package including spectrum printout, peak analysis, plutonium-238 and plutonium-239 data reduction, and automatic energy calibration routines was written. With the chained program a complete printout, peak analysis, and plutonium data reduction of a 512-channel alpha spectrum are obtained in about three minutes with an accuracy within five percent of hand analyses

Abstract Interfaces for Data Analysis Component Architecture for Data Analysis Tools

CERN Document Server

Barrand, G; Dönszelmann, M; Johnson, A; Pfeiffer, A

2001-01-01

The fast turnover of software technologies, in particular in the domain of interactivity (covering user interface and visualisation), makes it difficult for a small group of people to produce complete and polished software-tools before the underlying technologies make them obsolete. At the HepVis '99 workshop, a working group has been formed to improve the production of software tools for data analysis in HENP. Beside promoting a distributed development organisation, one goal of the group is to systematically design a set of abstract interfaces based on using modern OO analysis and OO design techniques. An initial domain analysis has come up with several categories (components) found in typical data analysis tools: Histograms, Ntuples, Functions, Vectors, Fitter, Plotter, Analyzer and Controller. Special emphasis was put on reducing the couplings between the categories to a minimum, thus optimising re-use and maintainability of any component individually. The interfaces have been defined in Java and C++ and i...

Reduction Of Gravimetric Data Using An Integrated Computer ...

African Journals Online (AJOL)

The rigour of gravimetric data collection, and the non-availability of comprehensive data reduction software that takes care of local peculiarities, have always constituted hindrance to the application of the gravity method of geophysical studies. However, in recent time, the importance of the gravity method in mineral ...

Quack: A quality assurance tool for high throughput sequence data.

Science.gov (United States)

Thrash, Adam; Arick, Mark; Peterson, Daniel G

2018-05-01

The quality of data generated by high-throughput DNA sequencing tools must be rapidly assessed in order to determine how useful the data may be in making biological discoveries; higher quality data leads to more confident results and conclusions. Due to the ever-increasing size of data sets and the importance of rapid quality assessment, tools that analyze sequencing data should quickly produce easily interpretable graphics. Quack addresses these issues by generating information-dense visualizations from FASTQ files at a speed far surpassing other publicly available quality assurance tools in a manner independent of sequencing technology. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

CyBy(2): a structure-based data management tool for chemical and biological data.

Science.gov (United States)

Höck, Stefan; Riedl, Rainer

2012-01-01

We report the development of a powerful data management tool for chemical and biological data: CyBy(2). CyBy(2) is a structure-based information management tool used to store and visualize structural data alongside additional information such as project assignment, physical information, spectroscopic data, biological activity, functional data and synthetic procedures. The application consists of a database, an application server, used to query and update the database, and a client application with a rich graphical user interface (GUI) used to interact with the server.

The Panchromatic High-Resolution Spectroscopic Survey of Local Group Star Clusters. I. General data reduction procedures for the VLT/X-shooter UVB and VIS arm

Science.gov (United States)

Schönebeck, Frederik; Puzia, Thomas H.; Pasquali, Anna; Grebel, Eva K.; Kissler-Patig, Markus; Kuntschner, Harald; Lyubenova, Mariya; Perina, Sibilla

2014-12-01

Aims: Our dataset contains spectroscopic observations of 29 globular clusters in the Magellanic Clouds and the Milky Way performed with VLT/X-shooter over eight full nights. To derive robust results instrument and pipeline systematics have to be well understood and properly modeled. We aim at a consistent data reduction procedure with an accurate understanding of the measurement accuracy limitations. Here we present detailed data reduction procedures for the VLT/X-shooter UVB and VIS arm. These are not restricted to our particular dataset, but are generally applicable to different kinds of X-shooter data without major limitation on the astronomical object of interest. Methods: ESO's X-shooter pipeline (v1.5.0) performs well and reliably for the wavelength calibration and the associated rectification procedure, yet we find several weaknesses in the reduction cascade that are addressed with additional calibration steps, such as bad pixel interpolation, flat fielding, and slit illumination corrections. Furthermore, the instrumental PSF is analytically modeled and used to reconstruct flux losses at slit transit. This also forms the basis for an optimal extraction of point sources out of the two-dimensional pipeline product. Regular observations of spectrophotometric standard stars obtained from the X-shooter archive allow us to detect instrumental variability, which needs to be understood if a reliable absolute flux calibration is desired. Results: A cascade of additional custom calibration steps is presented that allows for an absolute flux calibration uncertainty of ≲10% under virtually every observational setup, provided that the signal-to-noise ratio is sufficiently high. The optimal extraction increases the signal-to-noise ratio typically by a factor of 1.5, while simultaneously correcting for resulting flux losses. The wavelength calibration is found to be accurate to an uncertainty level of Δλ ≃ 0.02 Å. Conclusions: We find that most of the X

Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data

KAUST Repository

Cheng, Guang

2014-02-01

We consider efficient estimation of the Euclidean parameters in a generalized partially linear additive models for longitudinal/clustered data when multiple covariates need to be modeled nonparametrically, and propose an estimation procedure based on a spline approximation of the nonparametric part of the model and the generalized estimating equations (GEE). Although the model in consideration is natural and useful in many practical applications, the literature on this model is very limited because of challenges in dealing with dependent data for nonparametric additive models. We show that the proposed estimators are consistent and asymptotically normal even if the covariance structure is misspecified. An explicit consistent estimate of the asymptotic variance is also provided. Moreover, we derive the semiparametric efficiency score and information bound under general moment conditions. By showing that our estimators achieve the semiparametric information bound, we effectively establish their efficiency in a stronger sense than what is typically considered for GEE. The derivation of our asymptotic results relies heavily on the empirical processes tools that we develop for the longitudinal/clustered data. Numerical results are used to illustrate the finite sample performance of the proposed estimators. © 2014 ISI/BS.

Comparative genomics using data mining tools

Indian Academy of Sciences (India)

We have analysed the genomes of representatives of three kingdoms of life, namely, archaea, eubacteria and eukaryota using data mining tools based on compositional analyses of the protein sequences. The representatives chosen in this analysis were Methanococcus jannaschii, Haemophilus influenzae and ...

Development of a climate data analysis tool (CDAT)

Energy Technology Data Exchange (ETDEWEB)

Marlais, S.M.

1997-09-01

The Climate Data Analysis Tool (CDAT) is designed to provide the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at Lawrence Livermore National Laboratory, California, with the capabilities needed to analyze model data with little effort on the part of the scientist, while performing complex mathematical calculations, and graphically displaying the results. This computer software will meet the demanding need of climate scientists by providing the necessary tools to diagnose, validate, and intercompare large observational and global climate model datasets.

Automated data extraction from general practice records in an Australian setting: trends in influenza-like illness in sentinel general practices and emergency departments.

Science.gov (United States)

Liljeqvist, Gösta T H; Staff, Michael; Puech, Michele; Blom, Hans; Torvaldsen, Siranda

2011-06-06

Influenza intelligence in New South Wales (NSW), Australia is derived mainly from emergency department (ED) presentations and hospital and intensive care admissions, which represent only a portion of influenza-like illness (ILI) in the population. A substantial amount of the remaining data lies hidden in general practice (GP) records. Previous attempts in Australia to gather ILI data from GPs have given them extra work. We explored the possibility of applying automated data extraction from GP records in sentinel surveillance in an Australian setting.The two research questions asked in designing the study were: Can syndromic ILI data be extracted automatically from routine GP data? How do ILI trends in sentinel general practice compare with ILI trends in EDs? We adapted a software program already capable of automated data extraction to identify records of patients with ILI in routine electronic GP records in two of the most commonly used commercial programs. This tool was applied in sentinel sites to gather retrospective data for May-October 2007-2009 and in real-time for the same interval in 2010. The data were compared with that provided by the Public Health Real-time Emergency Department Surveillance System (PHREDSS) and with ED data for the same periods. The GP surveillance tool identified seasonal trends in ILI both retrospectively and in near real-time. The curve of seasonal ILI was more responsive and less volatile than that of PHREDSS on a local area level. The number of weekly ILI presentations ranged from 8 to 128 at GP sites and from 0 to 18 in EDs in non-pandemic years. Automated data extraction from routine GP records offers a means to gather data without introducing any additional work for the practitioner. Adding this method to current surveillance programs will enhance their ability to monitor ILI and to detect early warning signals of new ILI events.

Visualizing data mining results with the Brede tools

Directory of Open Access Journals (Sweden)

Finn A Nielsen

2009-07-01

Full Text Available A few neuroinformatics databases now exist that record results from neuroimaging studies in the form of brain coordinates in stereotaxic space. The Brede Toolbox was originally developed to extract, analyze and visualize data from one of them --- the BrainMap database. Since then the Brede Toolbox has expanded and now includes its own database with coordinates along with ontologies for brain regions and functions: The Brede Database. With Brede Toolbox and Database combined we setup automated workflows for extraction of data, mass meta-analytic data mining and visualizations. Most of the Web presence of the Brede Database is established by a single script executing a workflow involving these steps together with a final generation of Web pages with embedded visualizations and links to interactive three-dimensional models in the Virtual Reality Modeling Language. Apart from the Brede tools I briefly review alternate visualization tools and methods for Internet-based visualization and information visualization as well as portals for visualization tools.

Improvements in Spectrum's fit to program data tool.

Science.gov (United States)

Mahiane, Severin G; Marsh, Kimberly; Grantham, Kelsey; Crichlow, Shawna; Caceres, Karen; Stover, John

2017-04-01

The Joint United Nations Program on HIV/AIDS-supported Spectrum software package (Glastonbury, Connecticut, USA) is used by most countries worldwide to monitor the HIV epidemic. In Spectrum, HIV incidence trends among adults (aged 15-49 years) are derived by either fitting to seroprevalence surveillance and survey data or generating curves consistent with program and vital registration data, such as historical trends in the number of newly diagnosed infections or people living with HIV and AIDS related deaths. This article describes development and application of the fit to program data (FPD) tool in Joint United Nations Program on HIV/AIDS' 2016 estimates round. In the FPD tool, HIV incidence trends are described as a simple or double logistic function. Function parameters are estimated from historical program data on newly reported HIV cases, people living with HIV or AIDS-related deaths. Inputs can be adjusted for proportions undiagnosed or misclassified deaths. Maximum likelihood estimation or minimum chi-squared distance methods are used to identify the best fitting curve. Asymptotic properties of the estimators from these fits are used to estimate uncertainty. The FPD tool was used to fit incidence for 62 countries in 2016. Maximum likelihood and minimum chi-squared distance methods gave similar results. A double logistic curve adequately described observed trends in all but four countries where a simple logistic curve performed better. Robust HIV-related program and vital registration data are routinely available in many middle-income and high-income countries, whereas HIV seroprevalence surveillance and survey data may be scarce. In these countries, the FPD tool offers a simpler, improved approach to estimating HIV incidence trends.

Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks

Science.gov (United States)

Kanevski, Mikhail

2015-04-01

The research deals with an adaptation and application of Adaptive General Regression Neural Networks (GRNN) to high dimensional environmental data. GRNN [1,2,3] are efficient modelling tools both for spatial and temporal data and are based on nonparametric kernel methods closely related to classical Nadaraya-Watson estimator. Adaptive GRNN, using anisotropic kernels, can be also applied for features selection tasks when working with high dimensional data [1,3]. In the present research Adaptive GRNN are used to study geospatial data predictability and relevant feature selection using both simulated and real data case studies. The original raw data were either three dimensional monthly precipitation data or monthly wind speeds embedded into 13 dimensional space constructed by geographical coordinates and geo-features calculated from digital elevation model. GRNN were applied in two different ways: 1) adaptive GRNN with the resulting list of features ordered according to their relevancy; and 2) adaptive GRNN applied to evaluate all possible models N [in case of wind fields N=(2^13 -1)=8191] and rank them according to the cross-validation error. In both cases training were carried out applying leave-one-out procedure. An important result of the study is that the set of the most relevant features depends on the month (strong seasonal effect) and year. The predictabilities of precipitation and wind field patterns, estimated using the cross-validation and testing errors of raw and shuffled data, were studied in detail. The results of both approaches were qualitatively and quantitatively compared. In conclusion, Adaptive GRNN with their ability to select features and efficient modelling of complex high dimensional data can be widely used in automatic/on-line mapping and as an integrated part of environmental decision support systems. 1. Kanevski M., Pozdnoukhov A., Timonin V. Machine Learning for Spatial Environmental Data. Theory, applications and software. EPFL Press

Fault-Tolerant NDE Data Reduction Framework, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — A distributed fault tolerant nondestructive evaluation (NDE) data reduction framework is proposed in which large NDE datasets are mapped to thousands to millions of...

Benefits, Challenges and Tools of Big Data Management

Directory of Open Access Journals (Sweden)

Fernando L. F. Almeida

2017-10-01

Full Text Available Big Data is one of the most predominant field of knowledge and research that has generated high repercussion in the process of digital transformation of organizations in recent years. The Big Data's main goal is to improve work processes through analysis and interpretation of large amounts of data. Knowing how Big Data works, its benefits, challenges and tools, are essential elements for business success. Our study performs a systematic review on Big Data field adopting a mind map approach, which allows us to easily and visually identify its main elements and dependencies. The findings identified and mapped a total of 12 main branches of benefits, challenges and tools, and also a total of 52 sub branches in each of the main areas of the model.

DataUp: A tool to help researchers describe and share tabular data.

Science.gov (United States)

Strasser, Carly; Kunze, John; Abrams, Stephen; Cruse, Patricia

2014-01-01

Scientific datasets have immeasurable value, but they lose their value over time without proper documentation, long-term storage, and easy discovery and access. Across disciplines as diverse as astronomy, demography, archeology, and ecology, large numbers of small heterogeneous datasets (i.e., the long tail of data) are especially at risk unless they are properly documented, saved, and shared. One unifying factor for many of these at-risk datasets is that they reside in spreadsheets. In response to this need, the California Digital Library (CDL) partnered with Microsoft Research Connections and the Gordon and Betty Moore Foundation to create the DataUp data management tool for Microsoft Excel. Many researchers creating these small, heterogeneous datasets use Excel at some point in their data collection and analysis workflow, so we were interested in developing a data management tool that fits easily into those work flows and minimizes the learning curve for researchers. The DataUp project began in August 2011. We first formally assessed the needs of researchers by conducting surveys and interviews of our target research groups: earth, environmental, and ecological scientists. We found that, on average, researchers had very poor data management practices, were not aware of data centers or metadata standards, and did not understand the benefits of data management or sharing. Based on our survey results, we composed a list of desirable components and requirements and solicited feedback from the community to prioritize potential features of the DataUp tool. These requirements were then relayed to the software developers, and DataUp was successfully launched in October 2012.

Decommissioned Data Tools and Web Applications

Science.gov (United States)

Employment and Payroll Survey of Business Owners Work from Home Our statistics highlight trends in household statistics from multiple surveys. Data Tools & Apps Main American FactFinder Census Business Builder My small business owners selected Census Bureau & other statistics to guide their research for opening

Efficient Data Generation and Publication as a Test Tool

Science.gov (United States)

Einstein, Craig Jakob

2017-01-01

A tool to facilitate the generation and publication of test data was created to test the individual components of a command and control system designed to launch spacecraft. Specifically, this tool was built to ensure messages are properly passed between system components. The tool can also be used to test whether the appropriate groups have access (read/write privileges) to the correct messages. The messages passed between system components take the form of unique identifiers with associated values. These identifiers are alphanumeric strings that identify the type of message and the additional parameters that are contained within the message. The values that are passed with the message depend on the identifier. The data generation tool allows for the efficient creation and publication of these messages. A configuration file can be used to set the parameters of the tool and also specify which messages to pass.

Statistical near-real-time accountancy procedures applied to AGNS [Allied General Nuclear Services] minirun data using PROSA

International Nuclear Information System (INIS)

Beedgen, R.

1988-03-01

The computer program PROSA (PROgram for Statistical Analysis of near-real-time accountancy data) was developed as a tool to apply statistical test procedures to a sequence of materials balance results for detecting losses of material. First applications of PROSA to model facility data and real plant data showed that PROSA is also usable as a tool for process or measurement control. To deepen the experience for the application of PROSA to real data of bulk-handling facilities, we applied it to uranium data of the Allied General Nuclear Services miniruns, where accountancy data were collected on a near-real-time basis. Minirun 6 especially was considered, and the pulsed columns were chosen as materials balance area. The structure of the measurement models for flow sheet data and actual operation data are compared, and methods are studied to reduce the error for inventory measurements of the columns

Basic Radar Altimetry Toolbox: Tools and Tutorial to Use Cryosat Data

Science.gov (United States)

Benveniste, J.; Bronner, E.; Dinardo, S.; Lucas, B. M.; Rosmorduc, V.; Earith, D.; Niemeijer, S.

2011-12-01

Radar altimetry is very much a technique expanding its applications. Even If quite a lot of effort has been invested for oceanography users, the use of Altimetry data for cryosphere application, especially with the new ESA CryoSat-2 mission data is still somehow tedious for new Altimetry data products users. ESA and CNES therfore developed the Basic Radar Altimetry Toolbox a few years ago, and are improving and upgrading it to fit new missions and the growing number of altimetry uses. The Basic Radar Altimetry Toolbox is an "all-altimeter" collection of tools, tutorials and documents designed to facilitate the use of radar altimetry data. The software is able: - to read most distributed radar altimetry data, from ERS-1 & 2, Topex/Poseidon, Geosat Follow-on, Jason-1, Envisat, Jason- 2, CryoSat, the future Saral missions and is ready for adaptation to Sentinel-3 products - to perform some processing, data editing and statistic, - and to visualize the results. It can be used at several levels/several ways: - as a data reading tool, with APIs for C, Fortran, Matlab and IDL - as processing/extraction routines, through the on-line command mode - as an educational and a quick-look tool, with the graphical user interface As part of the Toolbox, a Radar Altimetry Tutorial gives general information about altimetry, the technique involved and its applications, as well as an overview of past, present and future missions, including information on how to access data and additional software and documentation. It also presents a series of data use cases, covering all uses of altimetry over ocean, cryosphere and land, showing the basic methods for some of the most frequent manners of using altimetry data. It is an opportunity to teach remote sensing with practical training. It has been available since April 2007, and had been demonstrated during training courses and scientific meetings. About 2000 people downloaded it (Summer 2011), with many "newcomers" to altimetry among them

Micro-Arcsec mission: implications of the monitoring, diagnostic and calibration of the instrument response in the data reduction chain. .

Science.gov (United States)

Busonero, D.; Gai, M.

The goals of 21st century high angular precision experiments rely on the limiting performance associated to the selected instrumental configuration and observational strategy. Both global and narrow angle micro-arcsec space astrometry require that the instrument contributions to the overall error budget has to be less than the desired micro-arcsec level precision. Appropriate modelling of the astrometric response is required for optimal definition of the data reduction and calibration algorithms, in order to ensure high sensitivity to the astrophysical source parameters and in general high accuracy. We will refer to the framework of the SIM-Lite and the Gaia mission, the most challenging space missions of the next decade in the narrow angle and global astrometry field, respectively. We will focus our dissertation on the Gaia data reduction issues and instrument calibration implications. We describe selected topics in the framework of the Astrometric Instrument Modelling for the Gaia mission, evidencing their role in the data reduction chain and we give a brief overview of the Astrometric Instrument Model Data Analysis Software System, a Java-based pipeline under development by our team.

FOSS Tools for Research Data Management

Science.gov (United States)

Stender, Vivien; Jankowski, Cedric; Hammitzsch, Martin; Wächter, Joachim

2017-04-01

Established initiatives and organizations, e.g. the Initiative for Scientific Cyberinfrastructures (NSF, 2007) or the European Strategy Forum on Research Infrastructures (ESFRI, 2008), promote and foster the development of sustainable research infrastructures. These infrastructures aim the provision of services supporting scientists to search, visualize and access data, to collaborate and exchange information, as well as to publish data and other results. In this regard, Research Data Management (RDM) gains importance and thus requires the support by appropriate tools integrated in these infrastructures. Different projects provide arbitrary solutions to manage research data. However, within two projects - SUMARIO for land and water management and TERENO for environmental monitoring - solutions to manage research data have been developed based on Free and Open Source Software (FOSS) components. The resulting framework provides essential components for harvesting, storing and documenting research data, as well as for discovering, visualizing and downloading these data on the basis of standardized services stimulated considerably by enhanced data management approaches of Spatial Data Infrastructures (SDI). In order to fully exploit the potentials of these developments for enhancing data management in Geosciences the publication of software components, e.g. via GitHub, is not sufficient. We will use our experience to move these solutions into the cloud e.g. as PaaS or SaaS offerings. Our contribution will present data management solutions for the Geosciences developed in two projects. A sort of construction kit with FOSS components build the backbone for the assembly and implementation of projects specific platforms. Furthermore, an approach is presented to stimulate the reuse of FOSS RDM solutions with cloud concepts. In further projects specific RDM platforms can be set-up much faster, customized to the individual needs and tools can be added during the run-time.

Data Basin: Expanding Access to Conservation Data, Tools, and People

Science.gov (United States)

Comendant, T.; Strittholt, J.; Frost, P.; Ward, B. C.; Bachelet, D. M.; Osborne-Gowey, J.

2009-12-01

Mapping and spatial analysis are a fundamental part of problem solving in conservation science, yet spatial data are widely scattered, difficult to locate, and often unavailable. Valuable time and resources are wasted locating and gaining access to important biological, cultural, and economic datasets, scientific analysis, and experts. As conservation problems become more serious and the demand to solve them grows more urgent, a new way to connect science and practice is needed. To meet this need, an open-access, web tool called Data Basin (www.databasin.org) has been created by the Conservation Biology Institute in partnership with ESRI and the Wilburforce Foundation. Users of Data Basin can gain quick access to datasets, experts, groups, and tools to help solve real-world problems. Individuals and organizations can perform essential tasks such as exploring and downloading from a vast library of conservation datasets, uploading existing datasets, connecting to other external data sources, create groups, and produce customized maps that can be easily shared. Data Basin encourages sharing and publishing, but also provides privacy and security for sensitive information when needed. Users can publish projects within Data Basin to tell more complete and rich stories of discovery and solutions. Projects are an ideal way to publish collections of datasets, maps and other information on the internet to reach wider audiences. Data Basin also houses individual centers that provide direct access to data, maps, and experts focused on specific geographic areas or conservation topics. Current centers being developed include the Boreal Information Centre, the Data Basin Climate Center, and proposed Aquatic and Forest Conservation Centers.

A Tool for Evaluating Strategies for Grouping of Biological Data

OpenAIRE

Jakoniene, Vaida; Lambrix, Patrick

2007-01-01

During the last decade an enormous amount of biological data has been generated and techniques and tools to analyze this data have been developed. Many of these tools use some form of grouping and are used in, for instance, data integration, data cleaning, prediction of protein functionality, and correlation of genes based on microarray data. A number of aspects influence the quality of the grouping results: the data sources, the grouping attributes and the algorithms implementing the groupin...

GAViT: Genome Assembly Visualization Tool for Short Read Data

Energy Technology Data Exchange (ETDEWEB)

Syed, Aijazuddin; Shapiro, Harris; Tu, Hank; Pangilinan, Jasmyn; Trong, Stephan

2008-03-14

It is a challenging job for genome analysts to accurately debug, troubleshoot, and validate genome assembly results. Genome analysts rely on visualization tools to help validate and troubleshoot assembly results, including such problems as mis-assemblies, low-quality regions, and repeats. Short read data adds further complexity and makes it extremely challenging for the visualization tools to scale and to view all needed assembly information. As a result, there is a need for a visualization tool that can scale to display assembly data from the new sequencing technologies. We present Genome Assembly Visualization Tool (GAViT), a highly scalable and interactive assembly visualization tool developed at the DOE Joint Genome Institute (JGI).

A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets

Directory of Open Access Journals (Sweden)

Sandeep R Panta

2016-03-01

Full Text Available In this paper we propose a web-based approach for quick visualization of big data from brain magnetic resonance imaging (MRI scans using a combination of an automated image capture and processing system, nonlinear embedding, and interactive data visualization tools. We draw upon thousands of MRI scans captured via the COllaborative Imaging and Neuroinformatics Suite (COINS. We then interface the output of several analysis pipelines based on structural and functional data to a t-distributed stochastic neighbor embedding (t-SNE algorithm which reduces the number of dimensions for each scan in the input data set to two dimensions while preserving the local structure of data sets. Finally, we interactively display the output of this approach via a web-page, based on data driven documents (D3 JavaScript library. Two distinct approaches were used to visualize the data. In the first approach, we computed multiple quality control (QC values from pre-processed data, which were used as inputs to the t-SNE algorithm. This approach helps in assessing the quality of each data set relative to others. In the second case, computed variables of interest (e.g. brain volume or voxel values from segmented gray matter images were used as inputs to the t-SNE algorithm. This approach helps in identifying interesting patterns in the data sets. We demonstrate these approaches using multiple examples including 1 quality control measures calculated from phantom data over time, 2 quality control data from human functional MRI data across various studies, scanners, sites, 3 volumetric and density measures from human structural MRI data across various studies, scanners and sites. Results from (1 and (2 show the potential of our approach to combine t-SNE data reduction with interactive color coding of variables of interest to quickly identify visually unique clusters of data (i.e. data sets with poor QC, clustering of data by site quickly. Results from (3 demonstrate

Twitter as a Potential Disaster Risk Reduction Tool. Part II: Descriptive Analysis of Identified Twitter Activity during the 2013 Hattiesburg F4 Tornado.

Science.gov (United States)

Cooper, Guy Paul; Yeager, Violet; Burkle, Frederick M; Subbarao, Italo

2015-06-29

This article describes a novel triangulation methodological approach for identifying twitter activity of regional active twitter users during the 2013 Hattiesburg EF-4 Tornado. A data extraction and geographically centered filtration approach was utilized to generate Twitter data for 48 hrs pre- and post-Tornado. The data was further validated using six sigma approach utilizing GPS data. The regional analysis revealed a total of 81,441 tweets, 10,646 Twitter users, 27,309 retweets and 2637 tweets with GPS coordinates. Twitter tweet activity increased 5 fold during the response to the Hattiesburg Tornado.  Retweeting activity increased 2.2 fold. Tweets with a hashtag increased 1.4 fold. Twitter was an effective disaster risk reduction tool for the Hattiesburg EF-4 Tornado 2013.

TACO: a general-purpose tool for predicting cell-type-specific transcription factor dimers.

Science.gov (United States)

Jankowski, Aleksander; Prabhakar, Shyam; Tiuryn, Jerzy

2014-03-19

Cooperative binding of transcription factor (TF) dimers to DNA is increasingly recognized as a major contributor to binding specificity. However, it is likely that the set of known TF dimers is highly incomplete, given that they were discovered using ad hoc approaches, or through computational analyses of limited datasets. Here, we present TACO (Transcription factor Association from Complex Overrepresentation), a general-purpose standalone software tool that takes as input any genome-wide set of regulatory elements and predicts cell-type-specific TF dimers based on enrichment of motif complexes. TACO is the first tool that can accommodate motif complexes composed of overlapping motifs, a characteristic feature of many known TF dimers. Our method comprehensively outperforms existing tools when benchmarked on a reference set of 29 known dimers. We demonstrate the utility and consistency of TACO by applying it to 152 DNase-seq datasets and 94 ChIP-seq datasets. Based on these results, we uncover a general principle governing the structure of TF-TF-DNA ternary complexes, namely that the flexibility of the complex is correlated with, and most likely a consequence of, inter-motif spacing.

Big Data Tools as Applied to ATLAS Event Data

Science.gov (United States)

Vukotic, I.; Gardner, R. W.; Bryant, L. A.

2017-10-01

Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Logfiles, database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and associated analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data. Such modes would simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning environments and tools like Spark, Jupyter, R, SciPy, Caffe, TensorFlow, etc. Machine learning challenges such as the Higgs Boson Machine Learning Challenge, the Tracking challenge, Event viewers (VP1, ATLANTIS, ATLASrift), and still to be developed educational and outreach tools would be able to access the data through a simple REST API. In this preliminary investigation we focus on derived xAOD data sets. These are much smaller than the primary xAODs having containers, variables, and events of interest to a particular analysis. Being encouraged with the performance of Elasticsearch for the ADC analytics platform, we developed an algorithm for indexing derived xAOD event data. We have made an appropriate document mapping and have imported a full set of standard model W/Z datasets. We compare the disk space efficiency of this approach to that of standard ROOT files, the performance in simple cut flow type of data analysis, and will present preliminary results on its scaling

The DataTools Professional Development Program: Sustainability via a University Partnership

Science.gov (United States)

Haddad, N.; Ledley, T. S.; McAuliffe, C. A.; Reider, D.

2009-12-01

development for teachers in the geographic region of UMD, the course can also serve as a science course for undergraduate students to fulfill general education requirements. This tremendously enlarges the number of students potentially served by the course. Nevertheless, after almost two years and a trial program that was hailed as a success by the participants, the work of transforming the DataTools program into a standard course is ongoing. In this session we will share details of our efforts, past and present, to sustain the operation of the DataTools program.

Northwestern University Schizophrenia Data and Software Tool (NUSDAST

Directory of Open Access Journals (Sweden)

Lei eWang

2013-11-01

Full Text Available The schizophrenia research community has invested substantial resources on collecting, managing and sharing large neuroimaging datasets. As part of this effort, our group has collected high resolution magnetic resonance (MR datasets from individuals with schizophrenia, their non-psychotic siblings, healthy controls and their siblings. This effort has resulted in a growing resource, the Northwestern University Schizophrenia Data and Software Tool (NUSDAST, an NIH-funded data sharing project to stimulate new research. This resource resides on XNAT Central, and it contains neuroimaging (MR scans, landmarks and surface maps for deep subcortical structures, and FreeSurfer cortical parcellation and measurement data, cognitive (cognitive domain scores for crystallized intelligence, working memory, episodic memory, and executive function, clinical (demographic, sibling relationship, SAPS and SANS psychopathology, and genetic (20 polymorphisms data, collected from more than 450 subjects, most with 2-year longitudinal follow-up. A neuroimaging mapping, analysis and visualization software tool, CAWorks, is also part of this resource. Moreover, in making our existing neuroimaging data along with the associated meta-data and computational tools publically accessible, we have established a web-based information retrieval portal that allows the user to efficiently search the collection. This research-ready dataset meaningfully combines neuroimaging data with other relevant information, and it can be used to help facilitate advancing neuroimaging research. It is our hope that this effort will help to overcome some of the commonly recognized technical barriers in advancing neuroimaging research such as lack of local organization and standard descriptions.

Application of advanced data reduction methods to gas turbine dynamic analysis

International Nuclear Information System (INIS)

Juhl, P.B.

1978-01-01

This paper discusses the application of advanced data reduction methods to the evaluation of dynamic data from gas turbines and turbine components. The use of the Fast Fourier Transform and of real-time spectrum analyzers is discussed. The use of power spectral density and probability density functions for analyzing random data is discussed. Examples of the application of these modern techniques to gas turbine testing are presented. The use of the computer to automate the data reduction procedures is discussed. (orig.) [de

Popularity Prediction Tool for ATLAS Distributed Data Management

CERN Document Server

Beermann, T; The ATLAS collaboration; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

2013-01-01

This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distri...

Popularity Prediction Tool for ATLAS Distributed Data Management

CERN Document Server

Beermann, T; The ATLAS collaboration; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

2014-01-01

This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distri...

'tomo_display' and 'vol_tools': IDL VM Packages for Tomography Data Reconstruction, Processing, and Visualization

Science.gov (United States)

Rivers, M. L.; Gualda, G. A.

2009-05-01

One of the challenges in tomography is the availability of suitable software for image processing and analysis in 3D. We present here 'tomo_display' and 'vol_tools', two packages created in IDL that enable reconstruction, processing, and visualization of tomographic data. They complement in many ways the capabilities offered by Blob3D (Ketcham 2005 - Geosphere, 1: 32-41, DOI: 10.1130/GES00001.1) and, in combination, allow users without programming knowledge to perform all steps necessary to obtain qualitative and quantitative information using tomographic data. The package 'tomo_display' was created and is maintained by Mark Rivers. It allows the user to: (1) preprocess and reconstruct parallel beam tomographic data, including removal of anomalous pixels, ring artifact reduction, and automated determination of the rotation center, (2) visualization of both raw and reconstructed data, either as individual frames, or as a series of sequential frames. The package 'vol_tools' consists of a series of small programs created and maintained by Guilherme Gualda to perform specific tasks not included in other packages. Existing modules include simple tools for cropping volumes, generating histograms of intensity, sample volume measurement (useful for porous samples like pumice), and computation of volume differences (for differential absorption tomography). The module 'vol_animate' can be used to generate 3D animations using rendered isosurfaces around objects. Both packages use the same NetCDF format '.volume' files created using code written by Mark Rivers. Currently, only 16-bit integer volumes are created and read by the packages, but floating point and 8-bit data can easily be stored in the NetCDF format as well. A simple GUI to convert sequences of tiffs into '.volume' files is available within 'vol_tools'. Both 'tomo_display' and 'vol_tools' include options to (1) generate onscreen output that allows for dynamic visualization in 3D, (2) save sequences of tiffs to disk

Database tools for enhanced analysis of TMX-U data. Revision 1

International Nuclear Information System (INIS)

Stewart, M.E.; Carter, M.R.; Casper, T.A.; Meyer, W.H.; Perkins, D.E.; Whitney, D.M.

1986-01-01

A commercial database software package has been used to create several databases and tools that assist and enhance the ability of experimental physicists to analyze data from the Tandem Mirror Experiment-Upgrade (TMX-U) experiment. This software runs on a DEC-20 computer in M-Division's User Service Center at Lawrence Livermore National Laboratory (LLNL), where data can be analyzed offline from the main TMX-U acquisition computers. When combined with interactive data analysis programs, these tools provide the capability to do batch-style processing or interactive data analysis on the computers in the USC or the supercomputers of the National Magnetic Fusion Energy Computer Center (NMFECC) in addition to the normal processing done by the TMX-U acquisition system. One database tool provides highly reduced data for searching and correlation analysis of several diagnostic signals within a single shot or over many shots. A second database tool provides retrieval and storage of unreduced data for use in detailed analysis of one or more diagnostic signals. We will show how these database tools form the core of an evolving offline data analysis environment on the USC computers

Legal assessment tool (LAT): an interactive tool to address privacy and data protection issues for data sharing.

Science.gov (United States)

Kuchinke, Wolfgang; Krauth, Christian; Bergmann, René; Karakoyun, Töresin; Woollard, Astrid; Schluender, Irene; Braasch, Benjamin; Eckert, Martin; Ohmann, Christian

2016-07-07

In an unprecedented rate data in the life sciences is generated and stored in many different databases. An ever increasing part of this data is human health data and therefore falls under data protected by legal regulations. As part of the BioMedBridges project, which created infrastructures that connect more than 10 ESFRI research infrastructures (RI), the legal and ethical prerequisites of data sharing were examined employing a novel and pragmatic approach. We employed concepts from computer science to create legal requirement clusters that enable legal interoperability between databases for the areas of data protection, data security, Intellectual Property (IP) and security of biosample data. We analysed and extracted access rules and constraints from all data providers (databases) involved in the building of data bridges covering many of Europe's most important databases. These requirement clusters were applied to five usage scenarios representing the data flow in different data bridges: Image bridge, Phenotype data bridge, Personalised medicine data bridge, Structural data bridge, and Biosample data bridge. A matrix was built to relate the important concepts from data protection regulations (e.g. pseudonymisation, identifyability, access control, consent management) with the results of the requirement clusters. An interactive user interface for querying the matrix for requirements necessary for compliant data sharing was created. To guide researchers without the need for legal expert knowledge through legal requirements, an interactive tool, the Legal Assessment Tool (LAT), was developed. LAT provides researchers interactively with a selection process to characterise the involved types of data and databases and provides suitable requirements and recommendations for concrete data access and sharing situations. The results provided by LAT are based on an analysis of the data access and sharing conditions for different kinds of data of major databases in Europe

THE EFFELSBERG-BONN H I SURVEY: DATA REDUCTION

International Nuclear Information System (INIS)

Winkel, B.; Kalberla, P. M. W.; Kerp, J.; Floeer, L.

2010-01-01

Starting in winter 2008/2009 an L-band seven-feed-array receiver is used for a 21 cm line survey performed with the 100 m telescope, the Effelsberg-Bonn H I survey (EBHIS). The EBHIS will cover the whole northern hemisphere for decl. > - 5 0 comprising both the galactic and extragalactic sky out to a distance of about 230 Mpc. Using state-of-the-art FPGA-based digital fast Fourier transform spectrometers, superior in dynamic range and temporal resolution to conventional correlators, allows us to apply sophisticated radio frequency interference (RFI) mitigation schemes. In this paper, the EBHIS data reduction package and first results are presented. The reduction software consists of RFI detection schemes, flux and gain-curve calibration, stray-radiation removal, baseline fitting, and finally the gridding to produce data cubes. The whole software chain is successfully tested using multi-feed data toward many smaller test fields (1-100 deg 2 ) and recently applied for the first time to data of two large sky areas, each covering about 2000 deg 2 . The first large area is toward the northern galactic pole and the second one toward the northern tip of the Magellanic Leading Arm. Here, we demonstrate the data quality of EBHIS Milky Way data and give a first impression on the first data release in 2011.

Development and application of a decision support tool for reduction of product losses in the food-processing industry

NARCIS (Netherlands)

Akkerman, Renzo; van Donk, Dirk Pieter

2008-01-01

In food-processing industries, reduction of product losses is important for improving profitability and sustainability. This paper presents a decision support tool for analyzing the effects of planning decisions on the amount of product losses in the food-processing industry. We created a research

General pathologist-helper: The new medical app about general pathology.

Science.gov (United States)

Fernández-Vega, Iván

2015-01-01

Smartphone applications (apps) have become increasingly prevalent in medicine. Due to most pathologists, pathology trainees, technicians, and medical students use smartphones; apps can be a different way for general pathology education. "General pathologist-helper (GP-HELPER)" is a novel app developed as a reference tool in general pathology and especially for general pathologists, developed for Android and iOS platforms. "GP-HELPER," was created using Mobincube website platform. This tool also integrates "FORUM GP-HELPER," an external website created using Miarroba website (http://forum-gp-helper.mboards.com) and "COMMUNITY GP-HELPER" a multichannel chat created using Chatango website platform. The application was released in July 2015, and it is been periodically updated since then. The app has permanent information (offline data) about different pathology protocols (TNM latest edition, protocols regarding management of tumors of unknown primary origin, and flowcharts for some of the most difficult tumors to diagnose) and a database with more than 5000 immunohistochemistry results from different tumors. Online data have links to more than 1100 reference pathology video lectures, 250 antibodies information, more than 70 pathology association websites, 46 pathology providers, and 78 outstanding pathology journal websites. Besides this information, the app has two interactive places such as "FORUM GP-HELPER" and "COMMUNITY GP-HELPER" that let users to stay in touch everywhere and every time. Expert consult section is also available. "GP-HELPER" pretends to integrate offline and online data about pathology with two interactive external places in order to represent a reference tool for general pathologists and associate members.

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl

2013-01-01

Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng

2013-11-05

Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

8 CFR 273.5 - General criteria used for reduction, refund, or waiver of fines.

Science.gov (United States)

2010-01-01

... 8 Aliens and Nationality 1 2010-01-01 2010-01-01 false General criteria used for reduction, refund, or waiver of fines. 273.5 Section 273.5 Aliens and Nationality DEPARTMENT OF HOMELAND SECURITY..., liquidated damages, and user fee payment records; and, (3) The existence of any extenuating circumstances. ...

Visual Data Comm: A Tool for Visualizing Data Communication in the Multi Sector Planner Study

Science.gov (United States)

Lee, Hwasoo Eric

2010-01-01

Data comm is a new technology proposed in future air transport system as a potential tool to provide comprehensive data connectivity. It is a key enabler to manage 4D trajectory digitally, potentially resulting in improved flight times and increased throughput. Future concepts with data comm integration have been tested in a number of human-in-the-loop studies but analyzing the results has proven to be particularly challenging because future traffic environment in which data comm is fully enabled has assumed high traffic density, resulting in data set with large amount of information. This paper describes the motivation, design, current and potential future application of Visual Data Comm (VDC), a tool for visualizing data developed in Java using Processing library which is a tool package designed for interactive visualization programming. This paper includes an example of an application of VDC on data pertaining to the most recent Multi Sector Planner study, conducted at NASA s Airspace Operations Laboratory in 2009, in which VDC was used to visualize and interpret data comm activities

Modeling with data tools and techniques for scientific computing

CERN Document Server

Klemens, Ben

2009-01-01

Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods

Chronic Care Team Profile: a brief tool to measure the structure and function of chronic care teams in general practice.

Science.gov (United States)

Proudfoot, Judith G; Bubner, Tanya; Amoroso, Cheryl; Swan, Edward; Holton, Christine; Winstanley, Julie; Beilby, Justin; Harris, Mark F

2009-08-01

At a time when workforce shortages in general practices are leading to greater role substitution and skill-mix diversification, and the demand on general practices for chronic disease care is increasing, the structure and function of the general practice team is taking on heightened importance. To assist general practices and the organizations supporting them to assess the effectiveness of their chronic care teamworking, we developed an interview tool, the Chronic Care Team Profile (CCTP), to measure the structure and function of teams in general practice. This paper describes its properties and potential use. An initial pool of items was derived from guidelines of best-practice for chronic disease care and performance standards for general practices. The items covered staffing, skill-mix, job descriptions and roles, training, protocols and procedures within the practice. The 41-item pool was factor analysed, retained items were measured for internal consistency and the reduced instrument's face, content and construct validity were evaluated. A three-factor solution corresponding to non-general practitioner staff roles in chronic care, administrative functions and management structures provided the best fit to the data and explained 45% of the variance in the CCTP. Further analyses suggested that the CCTP is reliable, valid and has some utility. The CCTP measures aspects of the structure and function of general practices which are independent of team processes. It is associated with the job satisfaction of general practice staff and the quality of care provided to patients with chronic illnesses. As such, the CCTP offers a simple and useful tool for general practices to assess their teamworking in chronic disease care.

New software for neutron data reduction and visualization

International Nuclear Information System (INIS)

Worlton, T.; Chatterjee, A.; Hammonds, J.; Chen, D.; Loong, C.K.; Mikkelson, D.; Mikkelson, R.

2001-01-01

Development of advanced neutron sources and instruments has necessitated corresponding advances in software for neutron scattering data reduction and visualization. New sources produce datasets more rapidly, and new instruments produce large numbers of spectra. Because of the shorter collection times, users are able to make more measurements on a given sample. This rapid production of datasets requires that users be able to reduce and analyze data quickly to prevent a data bottleneck. In addition, the new sources and instruments are accommodating more users with less neutron-scattering specific expertise, which requires software that is easy to use and freely available. We have developed an Integrated Spectral Analysis Workbench (ISAW) software package to permit the rapid reduction and visualization of neutron data. It can handle large numbers of spectra and merge data from separate measurements. The data can be sorted according to any attribute and transformed in numerous ways. ISAW provides several views of the data that enable users to compare spectra and observe trends in the data. A command interpreter, which is now part of ISAW, allows scientists to easily set up a series of instrument-specific operations to reduce and visualize data automatically. ISAW is written entirely in Java to permit portability to different computer platforms and easy distribution of the software. The software was constructed using modern computer design methods to allow easy customization and improvement. ISAW currently only reads data from IPNS 'run' files, but work is underway to provide input of NeXus files. (author)

New software for neutron data reduction and visualization

Energy Technology Data Exchange (ETDEWEB)

Worlton, T.; Chatterjee, A.; Hammonds, J.; Chen, D.; Loong, C.K. [Argonne National Laboratory, Argonne, IL (United States); Mikkelson, D.; Mikkelson, R. [Univ. of Wisconsin-Stout, Menomonie, WI (United States)

2001-03-01

Development of advanced neutron sources and instruments has necessitated corresponding advances in software for neutron scattering data reduction and visualization. New sources produce datasets more rapidly, and new instruments produce large numbers of spectra. Because of the shorter collection times, users are able to make more measurements on a given sample. This rapid production of datasets requires that users be able to reduce and analyze data quickly to prevent a data bottleneck. In addition, the new sources and instruments are accommodating more users with less neutron-scattering specific expertise, which requires software that is easy to use and freely available. We have developed an Integrated Spectral Analysis Workbench (ISAW) software package to permit the rapid reduction and visualization of neutron data. It can handle large numbers of spectra and merge data from separate measurements. The data can be sorted according to any attribute and transformed in numerous ways. ISAW provides several views of the data that enable users to compare spectra and observe trends in the data. A command interpreter, which is now part of ISAW, allows scientists to easily set up a series of instrument-specific operations to reduce and visualize data automatically. ISAW is written entirely in Java to permit portability to different computer platforms and easy distribution of the software. The software was constructed using modern computer design methods to allow easy customization and improvement. ISAW currently only reads data from IPNS 'run' files, but work is underway to provide input of NeXus files. (author)

Interactive and Approachable Web-Based Tools for Exploring Global Geophysical Data Records

Science.gov (United States)

Croteau, M. J.; Nerem, R. S.; Merrifield, M. A.; Thompson, P. R.; Loomis, B. D.; Wiese, D. N.; Zlotnicki, V.; Larson, J.; Talpe, M.; Hardy, R. A.

2017-12-01

Making global and regional data accessible and understandable for non-experts can be both challenging and hazardous. While data products are often developed with end users in mind, the ease of use of these data can vary greatly. Scientists must take care to provide detailed guides for how to use data products to ensure users are not incorrectly applying data to their problem. For example, terrestrial water storage data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission is notoriously difficult for non-experts to access and correctly use. However, allowing these data to be easily accessible to scientists outside the GRACE community is desirable because this would allow that data to see much wider-spread use. We have developed a web-based interactive mapping and plotting tool that provides easy access to geophysical data. This work presents an intuitive method for making such data widely accessible to experts and non-experts alike, making the data approachable and ensuring proper use of the data. This tool has proven helpful to experts by providing fast and detailed access to the data. Simultaneously, the tool allows non-experts to gain familiarity with the information contained in the data and access to that information for both scientific studies and public use. In this presentation, we discuss the development of this tool and application to both GRACE and ocean altimetry satellite missions, and demonstrate the capabilities of the tool. Focusing on the data visualization aspects of the tool, we showcase our integrations of the Mapbox API and the D3.js data-driven web document framework. We then explore the potential of these tools in other web-based visualization projects, and how incorporation of such tools into science can improve the presentation of research results. We demonstrate how the development of an interactive and exploratory resource can enable further layers of exploratory and scientific discovery.

Data reduction for neutron scattering from plutonium samples. Final report

International Nuclear Information System (INIS)

Seeger, P.A.

1997-01-01

An experiment performed in August, 1993, on the Low-Q Diffractometer (LQD) at the Manual Lujan Jr. Neutron Scattering Center (MLNSC) was designed to study the formation and annealing of He bubbles in aged 239 Pu metal. Significant complications arise in the reduction of the data because of the very high total neutron cross section of 239 Pu, and also because the sample are difficult to make uniform and to characterize. This report gives the details of the data and the data reduction procedures, presents the resulting scattering patterns in terms of macroscopic cross section as a function of momentum transfer, and suggests improvements for future experiments

Reduction procedures for accurate analysis of MSX surveillance experiment data

Science.gov (United States)

Gaposchkin, E. Mike; Lane, Mark T.; Abbot, Rick I.

1994-01-01

Technical challenges of the Midcourse Space Experiment (MSX) science instruments require careful characterization and calibration of these sensors for analysis of surveillance experiment data. Procedures for reduction of Resident Space Object (RSO) detections will be presented which include refinement and calibration of the metric and radiometric (and photometric) data and calculation of a precise MSX ephemeris. Examples will be given which support the reduction, and these are taken from ground-test data similar in characteristics to the MSX sensors and from the IRAS satellite RSO detections. Examples to demonstrate the calculation of a precise ephemeris will be provided from satellites in similar orbits which are equipped with S-band transponders.

A SOFTWARE TOOL TO COMPARE MEASURED AND SIMULATED BUILDING ENERGY PERFORMANCE DATA

Energy Technology Data Exchange (ETDEWEB)

Maile, Tobias; Bazjanac, Vladimir; O' Donnell, James; Garr, Matthew

2011-11-01

Building energy performance is often inadequate when compared to design goals. To link design goals to actual operation one can compare measured with simulated energy performance data. Our previously developed comparison approach is the Energy Performance Comparison Methodology (EPCM), which enables the identification of performance problems based on a comparison of measured and simulated performance data. In context of this method, we developed a software tool that provides graphing and data processing capabilities of the two performance data sets. The software tool called SEE IT (Stanford Energy Efficiency Information Tool) eliminates the need for manual generation of data plots and data reformatting. SEE IT makes the generation of time series, scatter and carpet plots independent of the source of data (measured or simulated) and provides a valuable tool for comparing measurements with simulation results. SEE IT also allows assigning data points on a predefined building object hierarchy and supports different versions of simulated performance data. This paper briefly introduces the EPCM, describes the SEE IT tool and illustrates its use in the context of a building case study.

Popularity Prediction Tool for ATLAS Distributed Data Management

Science.gov (United States)

Beermann, T.; Maettig, P.; Stewart, G.; Lassnig, M.; Garonne, V.; Barisits, M.; Vigne, R.; Serfon, C.; Goossens, L.; Nairz, A.; Molfetas, A.; Atlas Collaboration

2014-06-01

This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

Popularity prediction tool for ATLAS distributed data management

International Nuclear Information System (INIS)

Beermann, T; Maettig, P; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

2014-01-01

This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

Data Center IT Equipment Energy Assessment Tools: Current State of Commercial Tools, Proposal for a Future Set of Assessment Tools

Energy Technology Data Exchange (ETDEWEB)

Radhakrishnan, Ben D. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); National Univ., San Diego, CA (United States). School of Engineering

2012-06-30

This research project, which was conducted during the Summer and Fall of 2011, investigated some commercially available assessment tools with a focus on IT equipment to see if such tools could round out the DC Pro tool suite. In this research, the assessment capabilities of the various tools were compiled to help make “non-biased” information available to the public. This research should not be considered to be exhaustive on all existing vendor tools although a number of vendors were contacted. Large IT equipment OEM’s like IBM and Dell provide their proprietary internal automated software which does not work on any other IT equipment. However, found two companies with products that showed promise in performing automated assessments for IT equipment from different OEM vendors. This report documents the research and provides a list of software products reviewed, contacts and websites, product details, discussions with specific companies, a set of recommendations, and next steps. As a result of this research, a simple 3-level approach to an IT assessment tool is proposed along with an example of an assessment using a simple IT equipment data collection tool (Level 1, spreadsheet). The tool has been reviewed with the Green Grid and LBNL staff. The initial feedback has been positive although further refinement to the tool will be necessary. Proposed next steps include a field trial of at least two vendors’ software in two different data centers with an objective to prove the concept, ascertain the extent of energy and computational assessment, ease of installation and opportunities for continuous improvement. Based on the discussions, field trials (or case studies) are proposed with two vendors – JouleX (expected to be completed in 2012) and Sentilla.

Mapping data through concept maps: an auxiliary tool for decision making regarding institutional projects

International Nuclear Information System (INIS)

D’Avila, Adriana L.

2017-01-01

This paper reports a data mapping construction aimed to subsidize the decision making process regarding institutional projects, at different levels of responsibility, at the Instituto de Engenharia Nuclear. The conception models a systemic and adaptive tool which is based on the concept mapping theory developed by Novak. The Instituto de Engenharia Nuclear (IEN) is a research center of the Comissão de Energia Nuclear (CNEN), an autarchy attached to Ministério da Ciência, Tecnologia, Inovações e Comunicações. The main focus of IEN is research and development of nuclear science and technology. The developed tool creates a more effective and accessible way of sharing information. However, beyond project data integration into a specific instrument, it also has the intent to compensate the consequences of the continued reduction of the number of workers at IEN over recent years. The recent CNEN management report, published in 2016, showed the problematic situation caused by the loss of workers, stressing the high number of pensions granted and to be granted in the near future. The loss of labor force, besides exposing the urgent need for optimizing knowledge management efforts, also sheds light into another problem: the need for grouping responsibilities among the remaining workers. In this respect, the tool developed helps to face this challenge, enhancing autonomy at different levels but preserving the institutional guidelines. To conclude the report, and in order to exemplify the method, the paper also describes the map construction relative an innovative project proposal in a joint development towards the nuclear area. (author)

Mapping data through concept maps: an auxiliary tool for decision making regarding institutional projects

Energy Technology Data Exchange (ETDEWEB)

D’Avila, Adriana L., E-mail: adriana@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil). Divisão de Engenharia Nuclear

2017-11-01

This paper reports a data mapping construction aimed to subsidize the decision making process regarding institutional projects, at different levels of responsibility, at the Instituto de Engenharia Nuclear. The conception models a systemic and adaptive tool which is based on the concept mapping theory developed by Novak. The Instituto de Engenharia Nuclear (IEN) is a research center of the Comissão de Energia Nuclear (CNEN), an autarchy attached to Ministério da Ciência, Tecnologia, Inovações e Comunicações. The main focus of IEN is research and development of nuclear science and technology. The developed tool creates a more effective and accessible way of sharing information. However, beyond project data integration into a specific instrument, it also has the intent to compensate the consequences of the continued reduction of the number of workers at IEN over recent years. The recent CNEN management report, published in 2016, showed the problematic situation caused by the loss of workers, stressing the high number of pensions granted and to be granted in the near future. The loss of labor force, besides exposing the urgent need for optimizing knowledge management efforts, also sheds light into another problem: the need for grouping responsibilities among the remaining workers. In this respect, the tool developed helps to face this challenge, enhancing autonomy at different levels but preserving the institutional guidelines. To conclude the report, and in order to exemplify the method, the paper also describes the map construction relative an innovative project proposal in a joint development towards the nuclear area. (author)

Data Mining and Knowledge Discovery tools for exploiting big Earth-Observation data

Science.gov (United States)

Espinoza Molina, D.; Datcu, M.

2015-04-01

The continuous increase in the size of the archives and in the variety and complexity of Earth-Observation (EO) sensors require new methodologies and tools that allow the end-user to access a large image repository, to extract and to infer knowledge about the patterns hidden in the images, to retrieve dynamically a collection of relevant images, and to support the creation of emerging applications (e.g.: change detection, global monitoring, disaster and risk management, image time series, etc.). In this context, we are concerned with providing a platform for data mining and knowledge discovery content from EO archives. The platform's goal is to implement a communication channel between Payload Ground Segments and the end-user who receives the content of the data coded in an understandable format associated with semantics that is ready for immediate exploitation. It will provide the user with automated tools to explore and understand the content of highly complex images archives. The challenge lies in the extraction of meaningful information and understanding observations of large extended areas, over long periods of time, with a broad variety of EO imaging sensors in synergy with other related measurements and data. The platform is composed of several components such as 1.) ingestion of EO images and related data providing basic features for image analysis, 2.) query engine based on metadata, semantics and image content, 3.) data mining and knowledge discovery tools for supporting the interpretation and understanding of image content, 4.) semantic definition of the image content via machine learning methods. All these components are integrated and supported by a relational database management system, ensuring the integrity and consistency of Terabytes of Earth Observation data.

CMS Analysis and Data Reduction with Apache Spark

OpenAIRE

Gutsche, Oliver; Canali, Luca; Cremer, Illia; Cremonesi, Matteo; Elmer, Peter; Fisk, Ian; Girone, Maria; Jayatilaka, Bo; Kowalkowski, Jim; Khristenko, Viktor; Motesnitsalis, Evangelos; Pivarski, Jim; Sehrish, Saba; Surdy, Kacper; Svyatkovskiy, Alexey

2017-01-01

Experimental Particle Physics has been at the forefront of analyzing the world's largest datasets for decades. The HEP community was among the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems for distributed data processing, collectively called "Big Data" technologies have emerged from industry and open source projects to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HE...

Scaling up close-range surveys, a challenge for the generalization of as-built data in industrial applications

Directory of Open Access Journals (Sweden)

J.-F. Hullo

2014-06-01

Full Text Available As-built CAD data reconstructed from Terrestrial Laser Scanner (TLS data are used for more than two decades by Electricité de France (EDF to prepare maintenance operations in its facilities. But today, the big picture is renewed: "as-built virtual reality" must address a huge scale-up to provide data to an increasing number of applications. In this paper, we first present a wide multi-sensor multi-purpose scanning campaign performed in a 10 floor building of a power plant in 2013: 1083 TLS stations (about 40.109 3D points referenced under a 2 cm tolerance and 1025 RGB panoramic images (340.106 pixels per point of view. As expected, this very large survey of high precision measurements in a complex environment stressed sensors and tools that were developed for more favourable conditions and smaller data sets. The whole survey process (tools and methods used from acquisition and processing to CAD reconstruction underwent a detailed follow-up in order to state on the locks to a possible generalization to other buildings. Based on these recent feedbacks, we have highlighted some of these current bottlenecks in this paper: sensors denoising, automation in processes, data validation tools improvements, standardization of formats and (meta- data structures.

Scaling up close-range surveys, a challenge for the generalization of as-built data in industrial applications

Science.gov (United States)

Hullo, J.-F.; Thibault, G.

2014-06-01

As-built CAD data reconstructed from Terrestrial Laser Scanner (TLS) data are used for more than two decades by Electricité de France (EDF) to prepare maintenance operations in its facilities. But today, the big picture is renewed: "as-built virtual reality" must address a huge scale-up to provide data to an increasing number of applications. In this paper, we first present a wide multi-sensor multi-purpose scanning campaign performed in a 10 floor building of a power plant in 2013: 1083 TLS stations (about 40.109 3D points referenced under a 2 cm tolerance) and 1025 RGB panoramic images (340.106 pixels per point of view). As expected, this very large survey of high precision measurements in a complex environment stressed sensors and tools that were developed for more favourable conditions and smaller data sets. The whole survey process (tools and methods used from acquisition and processing to CAD reconstruction) underwent a detailed follow-up in order to state on the locks to a possible generalization to other buildings. Based on these recent feedbacks, we have highlighted some of these current bottlenecks in this paper: sensors denoising, automation in processes, data validation tools improvements, standardization of formats and (meta-) data structures.

General pathologist-helper: The new medical app about general pathology

Directory of Open Access Journals (Sweden)

Iván Fernandez-Vega

2015-01-01

Full Text Available Introduction: Smartphone applications (apps have become increasingly prevalent in medicine. Due to most pathologists, pathology trainees, technicians, and medical students use smartphones; apps can be a different way for general pathology education. “General pathologist-helper (GP-HELPER” is a novel app developed as a reference tool in general pathology and especially for general pathologists, developed for Android and iOS platforms. Materials and Methods: “GP-HELPER,” was created using Mobincube website platform. This tool also integrates “FORUM GP-HELPER,” an external website created using Miarroba website (http://forum-gp-helper.mboards.com and “COMMUNITY GP-HELPER” a multichannel chat created using Chatango website platform. Results: The application was released in July 2015, and it is been periodically updated since then. The app has permanent information (offline data about different pathology protocols (TNM latest edition, protocols regarding management of tumors of unknown primary origin, and flowcharts for some of the most difficult tumors to diagnose and a database with more than 5000 immunohistochemistry results from different tumors. Online data have links to more than 1100 reference pathology video lectures, 250 antibodies information, more than 70 pathology association websites, 46 pathology providers, and 78 outstanding pathology journal websites. Besides this information, the app has two interactive places such as “FORUM GP-HELPER” and “COMMUNITY GP-HELPER” that let users to stay in touch everywhere and every time. Expert consult section is also available. Conclusions: “GP-HELPER” pretends to integrate offline and online data about pathology with two interactive external places in order to represent a reference tool for general pathologists and associate members.

MTpy - Python Tools for Magnetotelluric Data Processing and Analysis

Science.gov (United States)

Krieger, Lars; Peacock, Jared; Thiel, Stephan; Inverarity, Kent; Kirkby, Alison; Robertson, Kate; Soeffky, Paul; Didana, Yohannes

2014-05-01

We present the Python package MTpy, which provides functions for the processing, analysis, and handling of magnetotelluric (MT) data sets. MT is a relatively immature and not widely applied geophysical method in comparison to other geophysical techniques such as seismology. As a result, the data processing within the academic MT community is not thoroughly standardised and is often based on a loose collection of software, adapted to the respective local specifications. We have developed MTpy to overcome problems that arise from missing standards, and to provide a simplification of the general handling of MT data. MTpy is written in Python, and the open-source code is freely available from a GitHub repository. The setup follows the modular approach of successful geoscience software packages such as GMT or Obspy. It contains sub-packages and modules for the various tasks within the standard work-flow of MT data processing and interpretation. In order to allow the inclusion of already existing and well established software, MTpy does not only provide pure Python classes and functions, but also wrapping command-line scripts to run standalone tools, e.g. modelling and inversion codes. Our aim is to provide a flexible framework, which is open for future dynamic extensions. MTpy has the potential to promote the standardisation of processing procedures and at same time be a versatile supplement for existing algorithms. Here, we introduce the concept and structure of MTpy, and we illustrate the workflow of MT data processing, interpretation, and visualisation utilising MTpy on example data sets collected over different regions of Australia and the USA.

A business intelligence approach using web search tools and online data reduction techniques to examine the value of product-enabled services

DEFF Research Database (Denmark)

Tanev, Stoyan; Liotta, Giacomo; Kleismantas, Andrius

2015-01-01

in Canada and Europe. It adopts an innovative methodology based on online textual data that could be implemented in advanced business intelligence tools aiming at the facilitation of innovation, marketing and business decision making. Combinations of keywords referring to different aspects of service value......-service innovation as a competitive advantage on the marketplace. On the other hand, the focus of EU firms on innovative hybrid offerings is not explicitly related to business differentiation and competitiveness....

A survey of tools for the analysis of quantitative PCR (qPCR data

Directory of Open Access Journals (Sweden)

Stephan Pabinger

2014-09-01

Our comprehensive survey showed that most tools use their own file format and only a fraction of the currently existing tools support the standardized data exchange format RDML. To allow a more streamlined and comparable analysis of qPCR data, more vendors and tools need to adapt the standardized format to encourage the exchange of data between instrument software, analysis tools, and researchers.

Evaluation of Linked Data tools for Learning Analytics

NARCIS (Netherlands)

Drachsler, Hendrik; Herder, Eelco; d'Aquin, Mathieu; Dietze, Stefan

2013-01-01

Drachsler, H., Herder, E., d'Aquin, M., & Dietze, S. (2013, 8-12 April). Evaluation of Linked Data tools for Learning Analytics. Presentation given in the tutorial on 'Using Linked Data for Learning Analytics' at LAK2013, the Third Conference on Learning Analytics and Knowledge, Leuven, Belgium.

Selected constants oxydo-reduction potentials tables of constants and numerical data affiliated to the International Union of Pure and Applied Chemistry, v.8

CERN Document Server

Charlot, G

1958-01-01

Selected Constants: Oxydo-Reduction Potentials contains Tables of the most probable value of the normal oxidation-reduction potential, or of the formal or apparent potential, of a given oxidation-reduction system. This book is prepared under the sponsorship of the Commission on Electrochemical Data of the Section of Analytical Chemistry of the International Union of Pure and Applied Chemistry. It is included in a general program of the Section of Analytical Chemistry. Entry items are classified in alphabetical order. This book will be of value to specialized and non-specialized chemists, teach

Customer Data Analysis Model using Business Intelligence Tools in Telecommunication Companies

Directory of Open Access Journals (Sweden)

Monica LIA

2015-10-01

Full Text Available This article presents a customer data analysis model in a telecommunication company and business intelligence tools for data modelling, transforming, data visualization and dynamic reports building . For a mature market, knowing the information inside the data and making forecast for strategic decision become more important in Romanian Market. Business Intelligence tools are used in business organization as support for decision making.

A new web-based tool for data visualization in MDSplus

Energy Technology Data Exchange (ETDEWEB)

Manduchi, G., E-mail: gabriele.manduchi@igi.cnr.it [Consorzio RFX, Euratom-ENEA Association, Corso Stati Uniti 4, Padova 35127 (Italy); Fredian, T.; Stillerman, J. [Massachusetts Institute of Technology, 175 Albany Street, Cambridge, MA 02139 (United States)

2014-05-15

Highlights: • The paper describes a new web-based data visualization tool for MDSplus. • It describes the experience gained with the previous data visualization tools. • It describes the used technologies for web data access and visualization. • It describes the current architecture of the tool and the new foreseen features. - Abstract: The Java tool jScope has been widely used for years to display acquired waveform in MDSplus. The choice of the Java programming language for its implementation has been successful for several reasons among which the fact that Java supports a multiplatform environment and it is well suited for graphics and the management of network communication. jScope can be used both as a local and remote application. In the latter case, data are acquired via TCP/IP communication using the mdsip protocol. Exporting data in this way however introduces several security problems due to the necessity of opening firewall holes for the user ports. For this reason, and also due to the fact that JavaScript is becoming a widely used language for web applications, a new tool written in JavaScript and called WebScope has been developed for the visualization of MDSplus data in web browsers. Data communication is now achieved via http protocol using Asynchronous JavaScript and XML (AJAX) technology. At the server side, data access is carried out by a Python module that interacts with the web server via Web Server Gateway Interface (WSGI). When a data item, described by an MDSplus expression, is requested by the web browser for visualization, it is returned as a binary message and then handled by callback JavaScript functions activated by the web browser. Scalable Vector Graphics (SVG) technology is used to handle graphics within the web browser and to carry out the same interactive data visualization provided by jScope. In addition to mouse events, touch events are supported to provide interactivity also on touch screens. In this way, waveforms can be

A new web-based tool for data visualization in MDSplus

International Nuclear Information System (INIS)

Manduchi, G.; Fredian, T.; Stillerman, J.

2014-01-01

Highlights: • The paper describes a new web-based data visualization tool for MDSplus. • It describes the experience gained with the previous data visualization tools. • It describes the used technologies for web data access and visualization. • It describes the current architecture of the tool and the new foreseen features. - Abstract: The Java tool jScope has been widely used for years to display acquired waveform in MDSplus. The choice of the Java programming language for its implementation has been successful for several reasons among which the fact that Java supports a multiplatform environment and it is well suited for graphics and the management of network communication. jScope can be used both as a local and remote application. In the latter case, data are acquired via TCP/IP communication using the mdsip protocol. Exporting data in this way however introduces several security problems due to the necessity of opening firewall holes for the user ports. For this reason, and also due to the fact that JavaScript is becoming a widely used language for web applications, a new tool written in JavaScript and called WebScope has been developed for the visualization of MDSplus data in web browsers. Data communication is now achieved via http protocol using Asynchronous JavaScript and XML (AJAX) technology. At the server side, data access is carried out by a Python module that interacts with the web server via Web Server Gateway Interface (WSGI). When a data item, described by an MDSplus expression, is requested by the web browser for visualization, it is returned as a binary message and then handled by callback JavaScript functions activated by the web browser. Scalable Vector Graphics (SVG) technology is used to handle graphics within the web browser and to carry out the same interactive data visualization provided by jScope. In addition to mouse events, touch events are supported to provide interactivity also on touch screens. In this way, waveforms can be

Automated Reduction of Data from Images and Holograms

Science.gov (United States)

Lee, G. (Editor); Trolinger, James D. (Editor); Yu, Y. H. (Editor)

1987-01-01

Laser techniques are widely used for the diagnostics of aerodynamic flow and particle fields. The storage capability of holograms has made this technique an even more powerful. Over 60 researchers in the field of holography, particle sizing and image processing convened to discuss these topics. The research program of ten government laboratories, several universities, industry and foreign countries were presented. A number of papers on holographic interferometry with applications to fluid mechanics were given. Several papers on combustion and particle sizing, speckle velocimetry and speckle interferometry were given. A session on image processing and automated fringe data reduction techniques and the type of facilities for fringe reduction was held.

Surface Operations Data Analysis and Adaptation Tool, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — This effort undertook the creation of a Surface Operations Data Analysis and Adaptation (SODAA) tool to store data relevant to airport surface research and...

Evaluation of data reduction methods for dynamic PET series based on Monte Carlo techniques and the NCAT phantom

International Nuclear Information System (INIS)

Thireou, Trias; Rubio Guivernau, Jose Luis; Atlamazoglou, Vassilis; Ledesma, Maria Jesus; Pavlopoulos, Sotiris; Santos, Andres; Kontaxakis, George

2006-01-01

A realistic dynamic positron-emission tomography (PET) thoracic study was generated, using the 4D NURBS-based (non-uniform rational B-splines) cardiac-torso (NCAT) phantom and a sophisticated model of the PET imaging process, simulating two solitary pulmonary nodules. Three data reduction and blind source separation methods were applied to the simulated data: principal component analysis, independent component analysis and similarity mapping. All methods reduced the initial amount of image data to a smaller, comprehensive and easily managed set of parametric images, where structures were separated based on their different kinetic characteristics and the lesions were readily identified. The results indicate that the above-mentioned methods can provide an accurate tool for the support of both visual inspection and subsequent detailed kinetic analysis of the dynamic series via compartmental or non-compartmental models

Noise Reduction of Measurement Data using Linear Digital Filters

Directory of Open Access Journals (Sweden)

Hitzmann B.

2007-12-01

Full Text Available In this paper Butterworth, Chebyshev (Type I and II and Elliptic digital filters are designed for signal noise reduction. On-line data measurements of substrate concentration from E. coli fed-batch cultivation process are used. Application of the designed filters leads to a successful noise reduction of on-line glucose measurements. The digital filters presented here are simple, easy to implement and effective - the used filters allow for a smart compromise between signal information and noise corruption.

Generalized Reduction Formula for Discrete Wigner Functions of Multiqubit Systems

Science.gov (United States)

Srinivasan, K.; Raghavan, G.

2018-03-01

Density matrices and Discrete Wigner Functions are equally valid representations of multiqubit quantum states. For density matrices, the partial trace operation is used to obtain the quantum state of subsystems, but an analogous prescription is not available for discrete Wigner Functions. Further, the discrete Wigner function corresponding to a density matrix is not unique but depends on the choice of the quantum net used for its reconstruction. In the present work, we derive a reduction formula for discrete Wigner functions of a general multiqubit state which works for arbitrary quantum nets. These results would be useful for the analysis and classification of entangled states and the study of decoherence purely in a discrete phase space setting and also in applications to quantum computing.

Supervised learning of tools for content-based search of image databases

Science.gov (United States)

Delanoy, Richard L.

1996-03-01

A computer environment, called the Toolkit for Image Mining (TIM), is being developed with the goal of enabling users with diverse interests and varied computer skills to create search tools for content-based image retrieval and other pattern matching tasks. Search tools are generated using a simple paradigm of supervised learning that is based on the user pointing at mistakes of classification made by the current search tool. As mistakes are identified, a learning algorithm uses the identified mistakes to build up a model of the user's intentions, construct a new search tool, apply the search tool to a test image, display the match results as feedback to the user, and accept new inputs from the user. Search tools are constructed in the form of functional templates, which are generalized matched filters capable of knowledge- based image processing. The ability of this system to learn the user's intentions from experience contrasts with other existing approaches to content-based image retrieval that base searches on the characteristics of a single input example or on a predefined and semantically- constrained textual query. Currently, TIM is capable of learning spectral and textural patterns, but should be adaptable to the learning of shapes, as well. Possible applications of TIM include not only content-based image retrieval, but also quantitative image analysis, the generation of metadata for annotating images, data prioritization or data reduction in bandwidth-limited situations, and the construction of components for larger, more complex computer vision algorithms.

Tools and data services registry

DEFF Research Database (Denmark)

Ison, Jon; Rapacki, Kristoffer; Ménager, Hervé

2016-01-01

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across...... a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task...

Single Molecule Analysis Research Tool (SMART: an integrated approach for analyzing single molecule data.

Directory of Open Access Journals (Sweden)

Max Greenfeld

Full Text Available Single molecule studies have expanded rapidly over the past decade and have the ability to provide an unprecedented level of understanding of biological systems. A common challenge upon introduction of novel, data-rich approaches is the management, processing, and analysis of the complex data sets that are generated. We provide a standardized approach for analyzing these data in the freely available software package SMART: Single Molecule Analysis Research Tool. SMART provides a format for organizing and easily accessing single molecule data, a general hidden Markov modeling algorithm for fitting an array of possible models specified by the user, a standardized data structure and graphical user interfaces to streamline the analysis and visualization of data. This approach guides experimental design, facilitating acquisition of the maximal information from single molecule experiments. SMART also provides a standardized format to allow dissemination of single molecule data and transparency in the analysis of reported data.

General-Purpose Data Containers for Science and Engineering

International Nuclear Information System (INIS)

2015-01-01

In 2012 the SG38 international committee was formed to develop a modern structure to replace the ENDF-6 format for storing evaluated nuclear reaction data on a computer system. This committee divided the project into seven tasks. One of these tasks, the design of General-Purpose Data Containers (GPDCs), is described in this article. What type of data does SG38 need to store and why is the task called General-Purpose Data Containers? The most common types of data in an evaluated nuclear reaction database are representations of physical functions in tabulated forms. There is also a need to store 1-dimensional functions using truncated Legendre or polynomial (or others) expansions. The phrase General-Purpose implies that the containers are to be designed to store generic forms of tabulated data rather than one for each physical function. Also, where possible, it would be beneficial to design containers that can store data forms not currently used in evaluated nuclear database or at least be easily extended. In addition to containers for storing physical functions as tabulated data, other types of containers are needed. There exists a desire within SG38 to support the storage of documentation at various levels within an evaluated file. Containers for storing non-functional data (e.g., a list of numbers) as well as units and labels for axes are also needed. Herein, containers for storing physical functions are called functional containers. One of the goals for the general-purpose data containers task is to design containers that will be useful to other scientific and engineering applications. To meet this goal, task members should think outside of the immediate needs of evaluated nuclear data to ensure that the containers are general- purpose rather than simply repackaged versions of existing containers. While the examples in this article may be specific to nuclear reaction data, it is hoped that the end product will be useful for other applications. To this end, some

CyNC - towards a General Tool for Performance Analysis of Complex Distributed Real Time Systems

DEFF Research Database (Denmark)

Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens F. Dalsgaard

2005-01-01

The paper addresses the current state and the ongoing activities of a tool for performance analysis of complex real time systems. The tool named CyNC is based on network calculus allowing for the computation of backlogs and delays in a system from specified lower and upper bounds of external...... workflow and computational resources. The current version of the tool implements an extension to previous work in that it allows for general workflow and resource bounds and provides optimal solutions even to systems with cyclic dependencies. Despite the virtues of the current tool, improvements...... and extensions still remain, which are in focus of ongoing activities. Improvements include accounting for phase information to improve bounds, whereas the tool awaits extension to include flow control models, which both depend on the possibility of accounting for propagation delay. Since the current version...

msBiodat analysis tool, big data analysis for high-throughput experiments.

Science.gov (United States)

Muñoz-Torres, Pau M; Rokć, Filip; Belužic, Robert; Grbeša, Ivana; Vugrek, Oliver

2016-01-01

Mass spectrometry (MS) are a group of a high-throughput techniques used to increase knowledge about biomolecules. They produce a large amount of data which is presented as a list of hundreds or thousands of proteins. Filtering those data efficiently is the first step for extracting biologically relevant information. The filtering may increase interest by merging previous data with the data obtained from public databases, resulting in an accurate list of proteins which meet the predetermined conditions. In this article we present msBiodat Analysis Tool, a web-based application thought to approach proteomics to the big data analysis. With this tool, researchers can easily select the most relevant information from their MS experiments using an easy-to-use web interface. An interesting feature of msBiodat analysis tool is the possibility of selecting proteins by its annotation on Gene Ontology using its Gene Id, ensembl or UniProt codes. The msBiodat analysis tool is a web-based application that allows researchers with any programming experience to deal with efficient database querying advantages. Its versatility and user-friendly interface makes easy to perform fast and accurate data screening by using complex queries. Once the analysis is finished, the result is delivered by e-mail. msBiodat analysis tool is freely available at http://msbiodata.irb.hr.

A survey of tools for the analysis of quantitative PCR (qPCR) data.

Science.gov (United States)

Pabinger, Stephan; Rödiger, Stefan; Kriegner, Albert; Vierlinger, Klemens; Weinhäusel, Andreas

2014-09-01

Real-time quantitative polymerase-chain-reaction (qPCR) is a standard technique in most laboratories used for various applications in basic research. Analysis of qPCR data is a crucial part of the entire experiment, which has led to the development of a plethora of methods. The released tools either cover specific parts of the workflow or provide complete analysis solutions. Here, we surveyed 27 open-access software packages and tools for the analysis of qPCR data. The survey includes 8 Microsoft Windows, 5 web-based, 9 R-based and 5 tools from other platforms. Reviewed packages and tools support the analysis of different qPCR applications, such as RNA quantification, DNA methylation, genotyping, identification of copy number variations, and digital PCR. We report an overview of the functionality, features and specific requirements of the individual software tools, such as data exchange formats, availability of a graphical user interface, included procedures for graphical data presentation, and offered statistical methods. In addition, we provide an overview about quantification strategies, and report various applications of qPCR. Our comprehensive survey showed that most tools use their own file format and only a fraction of the currently existing tools support the standardized data exchange format RDML. To allow a more streamlined and comparable analysis of qPCR data, more vendors and tools need to adapt the standardized format to encourage the exchange of data between instrument software, analysis tools, and researchers.

SNS Diagnostics Tools for Data Acquisition and Display

CERN Document Server

Sundaram, Madhan; Long, Cary D

2005-01-01

The Spallation Neutron Source (SNS) accelerator systems will deliver a 1.0 GeV, 1.4 MW proton beam to a liquid mercury target for neutron scattering research. The accelerator complex consists of a 1.0 GeV linear accelerator, an accumulator ring and associated transport lines. The SNS diagnostics platform is PC-based and will run Windows for its OS and LabVIEW as its programming language. The diagnostics platform as well as other control systems and operator consoles use the Channel Access (CA) protocol of the Experimental Physics and Industrial Control System (EPICS) to communicate. This paper describes the tools created to evaluate the diagnostic instrument using our standard programming environment, LabVIEW. The tools are based on the LabVIEW Channel Access library and can run on Windows, Linux, and Mac OS X. The data-acquisition tool uses drop and drag to select process variables organized by instrument, accelerator component, or beam parameters. The data can be viewed on-line and logged to disk for later ...

Design and Implementation of Data Reduction Pipelines for the Keck Observatory Archive

Science.gov (United States)

Gelino, C. R.; Berriman, G. B.; Kong, M.; Laity, A. C.; Swain, M. A.; Campbell, R.; Goodrich, R. W.; Holt, J.; Lyke, J.; Mader, J. A.; Tran, H. D.; Barlow, T.

2015-09-01

The Keck Observatory Archive (KOA), a collaboration between the NASA Exoplanet Science Institute and the W. M. Keck Observatory, serves science and calibration data for all active and inactive instruments from the twin Keck Telescopes located near the summit of Mauna Kea, Hawaii. In addition to the raw data, we produce and provide quick look reduced data for four instruments (HIRES, LWS, NIRC2, and OSIRIS) so that KOA users can more easily assess the scientific content and the quality of the data, which can often be difficult with raw data. The reduced products derive from both publicly available data reduction packages (when available) and KOA-created reduction scripts. The automation of publicly available data reduction packages has the benefit of providing a good quality product without the additional time and expense of creating a new reduction package, and is easily applied to bulk processing needs. The downside is that the pipeline is not always able to create an ideal product, particularly for spectra, because the processing options for one type of target (eg., point sources) may not be appropriate for other types of targets (eg., extended galaxies and nebulae). In this poster we present the design and implementation for the current pipelines used at KOA and discuss our strategies for handling data for which the nature of the targets and the observers' scientific goals and data taking procedures are unknown. We also discuss our plans for implementing automated pipelines for the remaining six instruments.

Physical activity in adolescents – Accelerometer data reduction criteria

DEFF Research Database (Denmark)

Toftager, Mette; Breum, Lars; Kristensen, Peter Lund

and PA outcomes (mean cpm). The following parameters in the data reduction analyses were fixed: 30sec epoch, 24h duration, first registration accepted after 4h, maximum value 20,000cpm, and two activity epochs permitted in blocks of non-wear. Results: Accelerometer data were obtained from a total of 1...... 1 valid day of 6h wear time using a 10min non-wear criterion. The corresponding numbers using a 90min non-wear criterion were 20.6% and 99.4%. Lengthening the non-wear period decreases PA level (mean cpm) substantially, e.g. average PA was 641 cpm (5 days of 10h) using the 10min non-wear criterion...... compared to 570 cpm using 90min non-wear. No systematic differences in PA outcomes were found when comparing the range of days and hours. Discussion: We used a systematic approach to illustrate that even small inconsistencies in accelerometer data reduction can have substantial impact on compliance and PA...

Application research on big data in energy conservation and emission reduction of transportation industry

Science.gov (United States)

Bai, Bingdong; Chen, Jing; Wang, Mei; Yao, Jingjing

2017-06-01

In the context of big data age, the energy conservation and emission reduction of transportation is a natural big data industry. The planning, management, decision-making of energy conservation and emission reduction of transportation and other aspects should be supported by the analysis and forecasting of large amounts of data. Now, with the development of information technology, such as intelligent city, sensor road and so on, information collection technology in the direction of the Internet of things gradually become popular. The 3G/4G network transmission technology develop rapidly, and a large number of energy conservation and emission reduction of transportation data is growing into a series with different ways. The government not only should be able to make good use of big data to solve the problem of energy conservation and emission reduction of transportation, but also to explore and use a large amount of data behind the hidden value. Based on the analysis of the basic characteristics and application technology of energy conservation and emission reduction of transportation data, this paper carries out its application research in energy conservation and emission reduction of transportation industry, so as to provide theoretical basis and reference value for low carbon management.

Applications of Spatial Data Using Business Analytics Tools

Directory of Open Access Journals (Sweden)

Anca Ioana ANDREESCU

2011-12-01

Full Text Available This paper addresses the possibilities of using spatial data in business analytics tools, with emphasis on SAS software. Various kinds of map data sets containing spatial data are presented and discussed. Examples of map charts illustrating macroeconomic parameters demonstrate the application of spatial data for the creation of map charts in SAS Enterprise Guise. Extended features of map charts are being exemplified by producing charts via SAS programming procedures.

Development of data analysis tool for combat system integration

Directory of Open Access Journals (Sweden)

Seung-Chun Shin

2013-03-01

Full Text Available System integration is an important element for the construction of naval combat ships. In particular, because impeccable combat system integration together with the sensors and weapons can ensure the combat capability and survivability of the ship, the integrated performance of the combat system should be verified and validated whether or not it fulfills the requirements of the end user. In order to conduct systematic verification and validation, a data analysis tool is requisite. This paper suggests the Data Extraction, Recording and Analysis Tool (DERAT for the data analysis of the integrated performance of the combat system, including the functional definition, architecture and effectiveness of the DERAT by presenting the test results.

The Global Earthquake Model and Disaster Risk Reduction

Science.gov (United States)

Smolka, A. J.

2015-12-01

Advanced, reliable and transparent tools and data to assess earthquake risk are inaccessible to most, especially in less developed regions of the world while few, if any, globally accepted standards currently allow a meaningful comparison of risk between places. The Global Earthquake Model (GEM) is a collaborative effort that aims to provide models, datasets and state-of-the-art tools for transparent assessment of earthquake hazard and risk. As part of this goal, GEM and its global network of collaborators have developed the OpenQuake engine (an open-source software for hazard and risk calculations), the OpenQuake platform (a web-based portal making GEM's resources and datasets freely available to all potential users), and a suite of tools to support modelers and other experts in the development of hazard, exposure and vulnerability models. These resources are being used extensively across the world in hazard and risk assessment, from individual practitioners to local and national institutions, and in regional projects to inform disaster risk reduction. Practical examples for how GEM is bridging the gap between science and disaster risk reduction are: - Several countries including Switzerland, Turkey, Italy, Ecuador, Papua-New Guinea and Taiwan (with more to follow) are computing national seismic hazard using the OpenQuake-engine. In some cases these results are used for the definition of actions in building codes. - Technical support, tools and data for the development of hazard, exposure, vulnerability and risk models for regional projects in South America and Sub-Saharan Africa. - Going beyond physical risk, GEM's scorecard approach evaluates local resilience by bringing together neighborhood/community leaders and the risk reduction community as a basis for designing risk reduction programs at various levels of geography. Actual case studies are Lalitpur in the Kathmandu Valley in Nepal and Quito/Ecuador. In agreement with GEM's collaborative approach, all

IT Data Mining Tool Uses in Aerospace

Science.gov (United States)

Monroe, Gilena A.; Freeman, Kenneth; Jones, Kevin L.

2012-01-01

Data mining has a broad spectrum of uses throughout the realms of aerospace and information technology. Each of these areas has useful methods for processing, distributing, and storing its corresponding data. This paper focuses on ways to leverage the data mining tools and resources used in NASA's information technology area to meet the similar data mining needs of aviation and aerospace domains. This paper details the searching, alerting, reporting, and application functionalities of the Splunk system, used by NASA's Security Operations Center (SOC), and their potential shared solutions to address aircraft and spacecraft flight and ground systems data mining requirements. This paper also touches on capacity and security requirements when addressing sizeable amounts of data across a large data infrastructure.

High-Performance Data Analysis Tools for Sun-Earth Connection Missions

Science.gov (United States)

Messmer, Peter

2011-01-01

The data analysis tool of choice for many Sun-Earth Connection missions is the Interactive Data Language (IDL) by ITT VIS. The increasing amount of data produced by these missions and the increasing complexity of image processing algorithms requires access to higher computing power. Parallel computing is a cost-effective way to increase the speed of computation, but algorithms oftentimes have to be modified to take advantage of parallel systems. Enhancing IDL to work on clusters gives scientists access to increased performance in a familiar programming environment. The goal of this project was to enable IDL applications to benefit from both computing clusters as well as graphics processing units (GPUs) for accelerating data analysis tasks. The tool suite developed in this project enables scientists now to solve demanding data analysis problems in IDL that previously required specialized software, and it allows them to be solved orders of magnitude faster than on conventional PCs. The tool suite consists of three components: (1) TaskDL, a software tool that simplifies the creation and management of task farms, collections of tasks that can be processed independently and require only small amounts of data communication; (2) mpiDL, a tool that allows IDL developers to use the Message Passing Interface (MPI) inside IDL for problems that require large amounts of data to be exchanged among multiple processors; and (3) GPULib, a tool that simplifies the use of GPUs as mathematical coprocessors from within IDL. mpiDL is unique in its support for the full MPI standard and its support of a broad range of MPI implementations. GPULib is unique in enabling users to take advantage of an inexpensive piece of hardware, possibly already installed in their computer, and achieve orders of magnitude faster execution time for numerically complex algorithms. TaskDL enables the simple setup and management of task farms on compute clusters. The products developed in this project have the

Data visualization, bar naked: A free tool for creating interactive graphics.

Science.gov (United States)

Weissgerber, Tracey L; Savic, Marko; Winham, Stacey J; Stanisavljevic, Dejana; Garovic, Vesna D; Milic, Natasa M

2017-12-15

Although bar graphs are designed for categorical data, they are routinely used to present continuous data in studies that have small sample sizes. This presentation is problematic, as many data distributions can lead to the same bar graph, and the actual data may suggest different conclusions from the summary statistics. To address this problem, many journals have implemented new policies that require authors to show the data distribution. This paper introduces a free, web-based tool for creating an interactive alternative to the bar graph (http://statistika.mfub.bg.ac.rs/interactive-dotplot/). This tool allows authors with no programming expertise to create customized interactive graphics, including univariate scatterplots, box plots, and violin plots, for comparing values of a continuous variable across different study groups. Individual data points may be overlaid on the graphs. Additional features facilitate visualization of subgroups or clusters of non-independent data. A second tool enables authors to create interactive graphics from data obtained with repeated independent experiments (http://statistika.mfub.bg.ac.rs/interactive-repeated-experiments-dotplot/). These tools are designed to encourage exploration and critical evaluation of the data behind the summary statistics and may be valuable for promoting transparency, reproducibility, and open science in basic biomedical research. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

A Data Management System for International Space Station Simulation Tools

Science.gov (United States)

Betts, Bradley J.; DelMundo, Rommel; Elcott, Sharif; McIntosh, Dawn; Niehaus, Brian; Papasin, Richard; Mah, Robert W.; Clancy, Daniel (Technical Monitor)

2002-01-01

Groups associated with the design, operational, and training aspects of the International Space Station make extensive use of modeling and simulation tools. Users of these tools often need to access and manipulate large quantities of data associated with the station, ranging from design documents to wiring diagrams. Retrieving and manipulating this data directly within the simulation and modeling environment can provide substantial benefit to users. An approach for providing these kinds of data management services, including a database schema and class structure, is presented. Implementation details are also provided as a data management system is integrated into the Intelligent Virtual Station, a modeling and simulation tool developed by the NASA Ames Smart Systems Research Laboratory. One use of the Intelligent Virtual Station is generating station-related training procedures in a virtual environment, The data management component allows users to quickly and easily retrieve information related to objects on the station, enhancing their ability to generate accurate procedures. Users can associate new information with objects and have that information stored in a database.

A Tool Supporting Collaborative Data Analytics Workflow Design and Management

Science.gov (United States)

Zhang, J.; Bao, Q.; Lee, T. J.

2016-12-01

Collaborative experiment design could significantly enhance the sharing and adoption of the data analytics algorithms and models emerged in Earth science. Existing data-oriented workflow tools, however, are not suitable to support collaborative design of such a workflow, to name a few, to support real-time co-design; to track how a workflow evolves over time based on changing designs contributed by multiple Earth scientists; and to capture and retrieve collaboration knowledge on workflow design (discussions that lead to a design). To address the aforementioned challenges, we have designed and developed a technique supporting collaborative data-oriented workflow composition and management, as a key component toward supporting big data collaboration through the Internet. Reproducibility and scalability are two major targets demanding fundamental infrastructural support. One outcome of the project os a software tool, supporting an elastic number of groups of Earth scientists to collaboratively design and compose data analytics workflows through the Internet. Instead of recreating the wheel, we have extended an existing workflow tool VisTrails into an online collaborative environment as a proof of concept.

Standalone General Purpose Data Logger Design and Implementation

African Journals Online (AJOL)

This paper describes the design of a general purpose data logger that is compatible with a variety of transducers, potentially permitting the measurement and recording of a wide range of phenomena. The recorded data can be retrieved to a PC via an RS-232 serial port. The standalone general purpose data logger ...

Data-Driven Model Order Reduction for Bayesian Inverse Problems

KAUST Repository

Cui, Tiangang; Youssef, Marzouk; Willcox, Karen

2014-01-01

One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce

Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

Science.gov (United States)

Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah

2017-02-01

Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.

A web-based data visualization tool for the MIMIC-II database.

Science.gov (United States)

Lee, Joon; Ribey, Evan; Wallace, James R

2016-02-04

Although MIMIC-II, a public intensive care database, has been recognized as an invaluable resource for many medical researchers worldwide, becoming a proficient MIMIC-II researcher requires knowledge of SQL programming and an understanding of the MIMIC-II database schema. These are challenging requirements especially for health researchers and clinicians who may have limited computer proficiency. In order to overcome this challenge, our objective was to create an interactive, web-based MIMIC-II data visualization tool that first-time MIMIC-II users can easily use to explore the database. The tool offers two main features: Explore and Compare. The Explore feature enables the user to select a patient cohort within MIMIC-II and visualize the distributions of various administrative, demographic, and clinical variables within the selected cohort. The Compare feature enables the user to select two patient cohorts and visually compare them with respect to a variety of variables. The tool is also helpful to experienced MIMIC-II researchers who can use it to substantially accelerate the cumbersome and time-consuming steps of writing SQL queries and manually visualizing extracted data. Any interested researcher can use the MIMIC-II data visualization tool for free to quickly and conveniently conduct a preliminary investigation on MIMIC-II with a few mouse clicks. Researchers can also use the tool to learn the characteristics of the MIMIC-II patients. Since it is still impossible to conduct multivariable regression inside the tool, future work includes adding analytics capabilities. Also, the next version of the tool will aim to utilize MIMIC-III which contains more data.

My Family Health Portrait, A tool from the Surgeon General | NIH MedlinePlus the Magazine

Science.gov (United States)

... of this page please turn Javascript on. My Family Health Portrait, A tool from the Surgeon General ... use Why is it important to know my family medical history? Your family medical history is a ...

Big Data Analytics Tools as Applied to ATLAS Event Data

CERN Document Server

Vukotic, Ilija; The ATLAS collaboration

2016-01-01

Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Log file data and database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data so as to simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of big data, statistical and machine learning tools...

A document centric metadata registration tool constructing earth environmental data infrastructure

Science.gov (United States)

Ichino, M.; Kinutani, H.; Ono, M.; Shimizu, T.; Yoshikawa, M.; Masuda, K.; Fukuda, K.; Kawamoto, H.

2009-12-01

DIAS (Data Integration and Analysis System) is one of GEOSS activities in Japan. It is also a leading part of the GEOSS task with the same name defined in GEOSS Ten Year Implementation Plan. The main mission of DIAS is to construct data infrastructure that can effectively integrate earth environmental data such as observation data, numerical model outputs, and socio-economic data provided from the fields of climate, water cycle, ecosystem, ocean, biodiversity and agriculture. Some of DIAS's data products are available at the following web site of http://www.jamstec.go.jp/e/medid/dias. Most of earth environmental data commonly have spatial and temporal attributes such as the covering geographic scope or the created date. The metadata standards including these common attributes are published by the geographic information technical committee (TC211) in ISO (the International Organization for Standardization) as specifications of ISO 19115:2003 and 19139:2007. Accordingly, DIAS metadata is developed with basing on ISO/TC211 metadata standards. From the viewpoint of data users, metadata is useful not only for data retrieval and analysis but also for interoperability and information sharing among experts, beginners and nonprofessionals. On the other hand, from the viewpoint of data providers, two problems were pointed out after discussions. One is that data providers prefer to minimize another tasks and spending time for creating metadata. Another is that data providers want to manage and publish documents to explain their data sets more comprehensively. Because of solving these problems, we have been developing a document centric metadata registration tool. The features of our tool are that the generated documents are available instantly and there is no extra cost for data providers to generate metadata. Also, this tool is developed as a Web application. So, this tool does not demand any software for data providers if they have a web-browser. The interface of the tool

A Visualization Tool to Analyse Usage of Web-Based Interventions: The Example of Positive Online Weight Reduction (POWeR)

Science.gov (United States)

Smith, Emily; Bradbury, Katherine; Morrison, Leanne; Dennison, Laura; Michaelides, Danius; Yardley, Lucy

2015-01-01

Background Attrition is a significant problem in Web-based interventions. Consequently, this research aims to identify the relation between Web usage and benefit from such interventions. A visualization tool has been developed that enables researchers to more easily examine large datasets on intervention usage that can be difficult to make sense of using traditional descriptive or statistical techniques alone. Objective This paper demonstrates how the visualization tool was used to explore patterns in participants’ use of a Web-based weight management intervention, termed "positive online weight reduction (POWeR)." We also demonstrate how the visualization tool can be used to perform subsequent statistical analyses of the association between usage patterns, participant characteristics, and intervention outcome. Methods The visualization tool was used to analyze data from 132 participants who had accessed at least one session of the POWeR intervention. Results There was a drop in usage of optional sessions after participants had accessed the initial, core POWeR sessions, but many users nevertheless continued to complete goal and weight reviews. The POWeR tools relating to the food diary and steps diary were reused most often. Differences in participant characteristics and usage of other intervention components were identified between participants who did and did not choose to access optional POWeR sessions (in addition to the initial core sessions) or reuse the food and steps diaries. Reuse of the steps diary and the getting support tools was associated with greater weight loss. Conclusions The visualization tool provided a quick and efficient method for exploring patterns of Web usage, which enabled further analyses of whether different usage patterns were associated with participant characteristics or differences in intervention outcome. Further usage of visualization techniques is recommended to (1) make sense of large datasets more quickly and efficiently; (2

Uranium tetrafluoride reduction closed bomb. Part I: Reduction process general conditions; Reduccion del tetrafluoruro de uranio en bomba cerrada. Part I. estudio de las variables generales del proceso de reduccion

Energy Technology Data Exchange (ETDEWEB)

Anca Abati, R; Lopez Rodriguez, M

1961-07-01

General conditions about the metallo thermic reduction in small bombs (250 and 800 gr. of uranium) has been investigated. Factors such as kind and granulometry of the magnesium used, magnesium excess and preheating temperature, which affect yields and metal quality have been considered. magnesium excess increased yields in a 15% in the small bomb, about the preheating temperature, there is a range between which yields and metal quality does not change. All tests have been made with graphite linings. (Author) 18 refs.

Watershed modeling tools and data for prognostic and diagnostic

Science.gov (United States)

Chambel-Leitao, P.; Brito, D.; Neves, R.

2009-04-01

When eutrophication is considered an important process to control it can be accomplished reducing nitrogen and phosphorus losses from both point and nonpoint sources and helping to assess the effectiveness of the pollution reduction strategy. HARP-NUT guidelines (Guidelines on Harmonized Quantification and Reporting Procedures for Nutrients) (Borgvang & Selvik, 2000) are presented by OSPAR as the best common quantification and reporting procedures for calculating the reduction of nutrient inputs. In 2000, OSPAR HARP-NUT guidelines on a trial basis. They were intended to serve as a tool for OSPAR Contracting Parties to report, in a harmonized manner, their different commitments, present or future, with regard to nutrients under the OSPAR Convention, in particular the "Strategy to Combat Eutrophication". HARP-NUT Guidelines (Borgvang and Selvik, 2000; Schoumans, 2003) were developed to quantify and report on the individual sources of nitrogen and phosphorus discharges/losses to surface waters (Source Orientated Approach). These results can be compared to nitrogen and phosphorus figures with the total riverine loads measured at downstream monitoring points (Load Orientated Approach), as load reconciliation. Nitrogen and phosphorus retention in river systems represents the connecting link between the "Source Orientated Approach" and the "Load Orientated Approach". Both approaches are necessary for verification purposes and both may be needed for providing the information required for the various commitments. Guidelines 2,3,4,5 are mainly concerned with the sources estimation. They present a set of simple calculations that allow the estimation of the origin of loads. Guideline 6 is a particular case where the application of a model is advised, in order to estimate the sources of nutrients from diffuse sources associated with land use/land cover. The model chosen for this was SWAT (Arnold & Fohrer, 2005) model because it is suggested in the guideline 6 and because it

Data Centric Sensor Stream Reduction for Real-Time Applications in Wireless Sensor Networks

Science.gov (United States)

Aquino, Andre Luiz Lins; Nakamura, Eduardo Freire

2009-01-01

This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An analytic model to estimate the ideal sample size used by data-reduction algorithms; and (iii) Two data-centric stream-based sampling algorithms to perform data reduction whenever necessary. Simulation results show that our data-centric strategies meet deadlines without loosing data representativeness. PMID:22303145

Data Mining Tools Make Flights Safer, More Efficient

Science.gov (United States)

2014-01-01

A small data mining team at Ames Research Center developed a set of algorithms ideal for combing through flight data to find anomalies. Dallas-based Southwest Airlines Co. signed a Space Act Agreement with Ames in 2011 to access the tools, helping the company refine its safety practices, improve its safety reviews, and increase flight efficiencies.

Anaphe - OO Libraries and Tools for Data Analysis

CERN Document Server

Couet, O; Molnar, Z; Moscicki, J T; Pfeiffer, A; Sang, M

2001-01-01

The Anaphe project is an ongoing effort to provide an Object Oriented software environment for data analysis in HENP experiments. A range of commercial and public domain libraries is used to cover basic functionalities; on top of these libraries a set of HENP-specific C++ class libraries for histogram management, fitting, plotting and ntuple-like data analysis has been developed. In order to comply with the user requirements for a command-line driven tool, we have chosen to use a scripting language (Python) as the front-end for a data analysis tool. The loose coupling provided by the consequent use of (AIDA compliant) Abstract Interfaces for each component in combination with the use of shared libraries for their implementation provides an easy integration of existing libraries into modern scripting languages thus allowing for rapid application development. This integration is simplified even further using a specialised toolkit (SWIG) to create "shadow classes" for the Python language, which map the definitio...

[Linked Data as a tool in the nutrition domain].

Science.gov (United States)

Míguez Pérez, R; Santos Gago, J M; Alonso Rorís, V M; Álvarez Sabucedo, L M; Mikic Fonte, F A

2012-01-01

Currently, there is a huge amount of information available on Internet that can neither be interpreted nor used by software agents. This fact poses a serious drawback to the potential of tools that deal with data on the current Web. Nevertheless, in recent times, advances in the domain of Semantic Web make possible the development of a new generation of smart applications capable of creating added-value services for the final user. This work shows the technical challenges that must be faced in the area of nutrition in order to transform one or several oldfashion sources of raw data into a web repository based on semantic technologies and linked with external and publicly available data on Internet. This approach makes possible for automatic tools to operate on the top of this information providing new functionalities highly interesting in the domain of public health, such as the automatic generation of menus for children or intelligent dietetic assistants, among others. This article explains the process to create such information support applying the guidelines of the Linked Data initiative and provides insights into the use of tools to make the most of this technology for its adoption in related use cases and environments.

Prediction With Dimension Reduction of Multiple Molecular Data Sources for Patient Survival

Directory of Open Access Journals (Sweden)

Adam Kaplan

2017-07-01

Full Text Available Predictive modeling from high-dimensional genomic data is often preceded by a dimension reduction step, such as principal component analysis (PCA. However, the application of PCA is not straightforward for multisource data, wherein multiple sources of ‘omics data measure different but related biological components. In this article, we use recent advances in the dimension reduction of multisource data for predictive modeling. In particular, we apply exploratory results from Joint and Individual Variation Explained (JIVE, an extension of PCA for multisource data, for prediction of differing response types. We conduct illustrative simulations to illustrate the practical advantages and interpretability of our approach. As an application example, we consider predicting survival for patients with glioblastoma multiforme from 3 data sources measuring messenger RNA expression, microRNA expression, and DNA methylation. We also introduce a method to estimate JIVE scores for new samples that were not used in the initial dimension reduction and study its theoretical properties; this method is implemented in the R package R.JIVE on CRAN, in the function jive.predict.

Bigger Data, Collaborative Tools and the Future of Predictive Drug Discovery

Science.gov (United States)

Clark, Alex M.; Swamidass, S. Joshua; Litterman, Nadia; Williams, Antony J.

2014-01-01

Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service (SaaS) commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas. PMID:24943138

Calculating the radiological parameters used in non-human biota dose assessment tools using ERICA Tool and site-specific data

Energy Technology Data Exchange (ETDEWEB)

Sotiropoulou, Maria [INRASTES, NCSR ' ' Demokritos' ' , Environmental Radioactivity Laboratory, Athens (Greece); Aristotle University of Thessaloniki, Atomic and Nuclear Physics Laboratory, Thessaloniki (Greece); Florou, Heleny [INRASTES, NCSR ' ' Demokritos' ' , Environmental Radioactivity Laboratory, Athens (Greece); Kitis, Georgios [Aristotle University of Thessaloniki, Atomic and Nuclear Physics Laboratory, Thessaloniki (Greece)

2017-11-15

The substantial complexity in ecosystem-radionuclide interactions is difficult to be represented in terms of radiological doses. Thus, radiological dose assessment tools use typical exposure situations for generalized organisms and ecosystems. In the present study, site-specific data and radioactivity measurements of terrestrial organisms (grass and herbivore mammals) and abiotic components (soil) are provided. The retrieved data are used in combination with the ERICA Assessment Tool for calculation of radiological parameters. The process of radionuclide transfer within ecosystem components is represented using concentration ratios (CRs), while for the calculation of dose rates the dose conversion coefficient (DCC) methodology is applied. Comparative assessments are performed between the generic and assessment-specific radiological parameters and between the resulting dose rates. Significant differences were observed between CRs calculated in this study and those reported in the literature for cesium and thorium, which can easily be explained. On the other hand, CRs calculated for radium are in very good agreement with those reported in the literature. The DCCs exhibited some small differences between the reference and the assessment-specific organism due to mass differences. The differences were observed for internal and external dose rates, but they were less pronounced for total dose rates which are typically used in the assessment of radiological impact. The results of the current work can serve as a basis for further studies of the radiological parameters in environments that have not been studied yet. (orig.)

Information Theoretic Tools for Parameter Fitting in Coarse Grained Models

KAUST Repository

Kalligiannaki, Evangelia

2015-01-07

We study the application of information theoretic tools for model reduction in the case of systems driven by stochastic dynamics out of equilibrium. The model/dimension reduction is considered by proposing parametrized coarse grained dynamics and finding the optimal parameter set for which the relative entropy rate with respect to the atomistic dynamics is minimized. The minimization problem leads to a generalization of the force matching methods to non equilibrium systems. A multiplicative noise example reveals the importance of the diffusion coefficient in the optimization problem.

Spectacle and SpecViz: New Spectral Analysis and Visualization Tools

Science.gov (United States)

Earl, Nicholas; Peeples, Molly; JDADF Developers

2018-01-01

A new era of spectroscopic exploration of our universe is being ushered in with advances in instrumentation and next-generation space telescopes. The advent of new spectroscopic instruments has highlighted a pressing need for tools scientists can use to analyze and explore these new data. We have developed Spectacle, a software package for analyzing both synthetic spectra from hydrodynamic simulations as well as real COS data with an aim of characterizing the behavior of the circumgalactic medium. It allows easy reduction of spectral data and analytic line generation capabilities. Currently, the package is focused on automatic determination of absorption regions and line identification with custom line list support, simultaneous line fitting using Voigt profiles via least-squares or MCMC methods, and multi-component modeling of blended features. Non-parametric measurements, such as equivalent widths, delta v90, and full-width half-max are available. Spectacle also provides the ability to compose compound models used to generate synthetic spectra allowing the user to define various LSF kernels, uncertainties, and to specify sampling.We also present updates to the visualization tool SpecViz, developed in conjunction with the JWST data analysis tools development team, to aid in the exploration of spectral data. SpecViz is an open source, Python-based spectral 1-D interactive visualization and analysis application built around high-performance interactive plotting. It supports handling general and instrument-specific data and includes advanced tool-sets for filtering and detrending one-dimensional data, along with the ability to isolate absorption regions using slicing and manipulate spectral features via spectral arithmetic. Multi-component modeling is also possible using a flexible model fitting tool-set that supports custom models to be used with various fitting routines. It also features robust user extensions such as custom data loaders and support for user

LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data.

Science.gov (United States)

Zhang, Wei; Zhang, Jiyang; Xu, Changming; Li, Ning; Liu, Hui; Ma, Jie; Zhu, Yunping; Xie, Hongwei

2012-12-01

Database searching based methods for label-free quantification aim to reconstruct the peptide extracted ion chromatogram based on the identification information, which can limit the search space and thus make the data processing much faster. The random effect of the MS/MS sampling can be remedied by cross-assignment among different runs. Here, we present a new label-free fast quantitative analysis tool, LFQuant, for high-resolution LC-MS/MS proteomics data based on database searching. It is designed to accept raw data in two common formats (mzXML and Thermo RAW), and database search results from mainstream tools (MASCOT, SEQUEST, and X!Tandem), as input data. LFQuant can handle large-scale label-free data with fractionation such as SDS-PAGE and 2D LC. It is easy to use and provides handy user interfaces for data loading, parameter setting, quantitative analysis, and quantitative data visualization. LFQuant was compared with two common quantification software packages, MaxQuant and IDEAL-Q, on the replication data set and the UPS1 standard data set. The results show that LFQuant performs better than them in terms of both precision and accuracy, and consumes significantly less processing time. LFQuant is freely available under the GNU General Public License v3.0 at http://sourceforge.net/projects/lfquant/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Experiences and lessons learned from creating a generalized workflow for data publication of field campaign datasets

Science.gov (United States)

Santhana Vannan, S. K.; Ramachandran, R.; Deb, D.; Beaty, T.; Wright, D.

2017-12-01

This paper summarizes the workflow challenges of curating and publishing data produced from disparate data sources and provides a generalized workflow solution to efficiently archive data generated by researchers. The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for biogeochemical dynamics and the Global Hydrology Resource Center (GHRC) DAAC have been collaborating on the development of a generalized workflow solution to efficiently manage the data publication process. The generalized workflow presented here are built on lessons learned from implementations of the workflow system. Data publication consists of the following steps: Accepting the data package from the data providers, ensuring the full integrity of the data files. Identifying and addressing data quality issues Assembling standardized, detailed metadata and documentation, including file level details, processing methodology, and characteristics of data files Setting up data access mechanisms Setup of the data in data tools and services for improved data dissemination and user experience Registering the dataset in online search and discovery catalogues Preserving the data location through Digital Object Identifiers (DOI) We will describe the steps taken to automate, and realize efficiencies to the above process. The goals of the workflow system are to reduce the time taken to publish a dataset, to increase the quality of documentation and metadata, and to track individual datasets through the data curation process. Utilities developed to achieve these goal will be described. We will also share metrics driven value of the workflow system and discuss the future steps towards creation of a common software framework.

Aggregation Tool to Create Curated Data albums to Support Disaster Recovery and Response

Science.gov (United States)

Ramachandran, Rahul; Kulkarni, Ajinkya; Maskey, Manil; Bakare, Rohan; Basyal, Sabin; Li, Xiang; Flynn, Shannon

2014-01-01

Despite advances in science and technology of prediction and simulation of natural hazards, losses incurred due to natural disasters keep growing every year. Natural disasters cause more economic losses as compared to anthropogenic disasters. Economic losses due to natural hazards are estimated to be around $6-$10 billion dollars annually for the U.S. and this number keeps increasing every year. This increase has been attributed to population growth and migration to more hazard prone locations such as coasts. As this trend continues, in concert with shifts in weather patterns caused by climate change, it is anticipated that losses associated with natural disasters will keep growing substantially. One of challenges disaster response and recovery analysts face is to quickly find, access and utilize a vast variety of relevant geospatial data collected by different federal agencies such as DoD, NASA, NOAA, EPA, USGS etc. Some examples of these data sets include high spatio-temporal resolution multi/hyperspectral satellite imagery, model prediction outputs from weather models, latest radar scans, measurements from an array of sensor networks such as Integrated Ocean Observing System etc. More often analysts may be familiar with limited, but specific datasets and are often unaware of or unfamiliar with a large quantity of other useful resources. Finding airborne or satellite data useful to a natural disaster event often requires a time consuming search through web pages and data archives. Additional information related to damages, deaths, and injuries requires extensive online searches for news reports and official report summaries. An analyst must also sift through vast amounts of potentially useful digital information captured by the general public such as geo-tagged photos, videos and real time damage updates within twitter feeds. Collecting and aggregating these information fragments can provide useful information in assessing damage in real time and help direct

A General Design Methodology for Synchronous Early-Completion-Prediction Adders in Nano-CMOS DSP Architectures

Directory of Open Access Journals (Sweden)

Mauro Olivieri

2013-01-01

Full Text Available Synchronous early-completion-prediction adders (ECPAs are used for high clock rate and high-precision DSP datapaths, as they allow a dominant amount of single-cycle operations even if the worst-case carry propagation delay is longer than the clock period. Previous works have also demonstrated ECPA advantages for average leakage reduction and NBTI effects reduction in nanoscale CMOS technologies. This paper illustrates a general systematic methodology to design ECPA units, targeting nanoscale CMOS technologies, which is not available in the current literature yet. The method is fully compatible with standard VLSI macrocell design tools and standard adder structures and includes automatic definition of critical test patterns for postlayout verification. A design example is included, reporting speed and power data superior to previous works.

Large-scale inverse model analyses employing fast randomized data reduction

Science.gov (United States)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

A Climate Statistics Tool and Data Repository

Science.gov (United States)

Wang, J.; Kotamarthi, V. R.; Kuiper, J. A.; Orr, A.

2017-12-01

Researchers at Argonne National Laboratory and collaborating organizations have generated regional scale, dynamically downscaled climate model output using Weather Research and Forecasting (WRF) version 3.3.1 at a 12km horizontal spatial resolution over much of North America. The WRF model is driven by boundary conditions obtained from three independent global scale climate models and two different future greenhouse gas emission scenarios, named representative concentration pathways (RCPs). The repository of results has a temporal resolution of three hours for all the simulations, includes more than 50 variables, is stored in Network Common Data Form (NetCDF) files, and the data volume is nearly 600Tb. A condensed 800Gb set of NetCDF files were made for selected variables most useful for climate-related planning, including daily precipitation, relative humidity, solar radiation, maximum temperature, minimum temperature, and wind. The WRF model simulations are conducted for three 10-year time periods (1995-2004, 2045-2054, and 2085-2094), and two future scenarios RCP4.5 and RCP8.5). An open-source tool was coded using Python 2.7.8 and ESRI ArcGIS 10.3.1 programming libraries to parse the NetCDF files, compute summary statistics, and output results as GIS layers. Eight sets of summary statistics were generated as examples for the contiguous U.S. states and much of Alaska, including number of days over 90°F, number of days with a heat index over 90°F, heat waves, monthly and annual precipitation, drought, extreme precipitation, multi-model averages, and model bias. This paper will provide an overview of the project to generate the main and condensed data repositories, describe the Python tool and how to use it, present the GIS results of the computed examples, and discuss some of the ways they can be used for planning. The condensed climate data, Python tool, computed GIS results, and documentation of the work are shared on the Internet.

Detection of adverse events in general surgery using the " Trigger Tool" methodology.

Science.gov (United States)

Pérez Zapata, Ana Isabel; Gutiérrez Samaniego, María; Rodríguez Cuéllar, Elías; Andrés Esteban, Eva María; Gómez de la Cámara, Agustín; Ruiz López, Pedro

2015-02-01

Surgery is one of the high-risk areas for the occurrence of adverse events (AE). The purpose of this study is to know the percentage of hospitalisation-related AE that are detected by the «Global Trigger Tool» methodology in surgical patients, their characteristics and the tool validity. Retrospective, observational study on patients admitted to a general surgery department, who underwent a surgical operation in a third level hospital during the year 2012. The identification of AE was carried out by patient record review using an adaptation of «Global Trigger Tool» methodology. Once an AE was identified, a harm category was assigned, including the grade in which the AE could have been avoided and its relation with the surgical procedure. The prevalence of AE was 36,8%. There were 0,5 AE per patient. 56,2% were deemed preventable. 69,3% were directly related to the surgical procedure. The tool had a sensitivity of 86% and a specificity of 93,6%. The positive predictive value was 89% and the negative predictive value 92%. Prevalence of AE is greater than the estimate of other studies. In most cases the AE detected were related to the surgical procedure and more than half were also preventable. The adapted «Global Trigger Tool» methodology has demonstrated to be highly effective and efficient for detecting AE in surgical patients, identifying all the serious AE with few false negative results. Copyright © 2014 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

WILBER and PyWEED: Event-based Seismic Data Request Tools

Science.gov (United States)

Falco, N.; Clark, A.; Trabant, C. M.

2017-12-01

WILBER and PyWEED are two user-friendly tools for requesting event-oriented seismic data. Both tools provide interactive maps and other controls for browsing and filtering event and station catalogs, and downloading data for selected event/station combinations, where the data window for each event/station pair may be defined relative to the arrival time of seismic waves from the event to that particular station. Both tools allow data to be previewed visually, and can download data in standard miniSEED, SAC, and other formats, complete with relevant metadata for performing instrument correction. WILBER is a web application requiring only a modern web browser. Once the user has selected an event, WILBER identifies all data available for that time period, and allows the user to select stations based on criteria such as the station's distance and orientation relative to the event. When the user has finalized their request, the data is collected and packaged on the IRIS server, and when it is ready the user is sent a link to download. PyWEED is a downloadable, cross-platform (Macintosh / Windows / Linux) application written in Python. PyWEED allows a user to select multiple events and stations, and will download data for each event/station combination selected. PyWEED is built around the ObsPy seismic toolkit, and allows direct interaction and control of the application through a Python interactive console.

New features and improved uncertainty analysis in the NEA nuclear data sensitivity tool (NDaST)

Science.gov (United States)

Dyrda, J.; Soppera, N.; Hill, I.; Bossant, M.; Gulliford, J.

2017-09-01

Following the release and initial testing period of the NEA's Nuclear Data Sensitivity Tool [1], new features have been designed and implemented in order to expand its uncertainty analysis capabilities. The aim is to provide a free online tool for integral benchmark testing, that is both efficient and comprehensive, meeting the needs of the nuclear data and benchmark testing communities. New features include access to P1 sensitivities for neutron scattering angular distribution [2] and constrained Chi sensitivities for the prompt fission neutron energy sampling. Both of these are compatible with covariance data accessed via the JANIS nuclear data software, enabling propagation of the resultant uncertainties in keff to a large series of integral experiment benchmarks. These capabilities are available using a number of different covariance libraries e.g., ENDF/B, JEFF, JENDL and TENDL, allowing comparison of the broad range of results it is possible to obtain. The IRPhE database of reactor physics measurements is now also accessible within the tool in addition to the criticality benchmarks from ICSBEP. Other improvements include the ability to determine and visualise the energy dependence of a given calculated result in order to better identify specific regions of importance or high uncertainty contribution. Sorting and statistical analysis of the selected benchmark suite is now also provided. Examples of the plots generated by the software are included to illustrate such capabilities. Finally, a number of analytical expressions, for example Maxwellian and Watt fission spectra will be included. This will allow the analyst to determine the impact of varying such distributions within the data evaluation, either through adjustment of parameters within the expressions, or by comparison to a more general probability distribution fitted to measured data. The impact of such changes is verified through calculations which are compared to a `direct' measurement found by

Patient satisfaction surveys as a market research tool for general practices.

Science.gov (United States)

Khayat, K; Salter, B

1994-05-01

Recent policy developments, embracing the notions of consumer choice, quality of care, and increased general practitioner control over practice budgets have resulted in a new competitive environment in primary care. General practitioners must now be more aware of how their patients feel about the services they receive, and patient satisfaction surveys can be an effective tool for general practices. A survey was undertaken to investigate the use of a patient satisfaction survey and whether aspects of patient satisfaction varied according to sociodemographic characteristics such as age, sex, social class, housing tenure and length of time in education. A sample of 2173 adults living in Medway District Health Authority were surveyed by postal questionnaire in September 1991 in order to elicit their views on general practice services. Levels of satisfaction varied with age, with younger people being consistently less satisfied with general practice services than older people. Women, those in social classes 1-3N, home owners and those who left school aged 17 years or older were more critical of primary care services than men, those in social classes 3M-5, tenants and those who left school before the age of 17 years. Surveys and analyses of this kind, if conducted for a single practice, can form the basis of a marketing strategy aimed at optimizing list size, list composition, and service quality. Satisfaction surveys can be readily incorporated into medical audit and financial management.

Parameter-free Network Sparsification and Data Reduction by Minimal Algorithmic Information Loss

KAUST Repository

Zenil, Hector

2018-02-16

The study of large and complex datasets, or big data, organized as networks has emerged as one of the central challenges in most areas of science and technology. Cellular and molecular networks in biology is one of the prime examples. Henceforth, a number of techniques for data dimensionality reduction, especially in the context of networks, have been developed. Yet, current techniques require a predefined metric upon which to minimize the data size. Here we introduce a family of parameter-free algorithms based on (algorithmic) information theory that are designed to minimize the loss of any (enumerable computable) property contributing to the object\\'s algorithmic content and thus important to preserve in a process of data dimension reduction when forcing the algorithm to delete first the least important features. Being independent of any particular criterion, they are universal in a fundamental mathematical sense. Using suboptimal approximations of efficient (polynomial) estimations we demonstrate how to preserve network properties outperforming other (leading) algorithms for network dimension reduction. Our method preserves all graph-theoretic indices measured, ranging from degree distribution, clustering-coefficient, edge betweenness, and degree and eigenvector centralities. We conclude and demonstrate numerically that our parameter-free, Minimal Information Loss Sparsification (MILS) method is robust, has the potential to maximize the preservation of all recursively enumerable features in data and networks, and achieves equal to significantly better results than other data reduction and network sparsification methods.

Joint carbon footprint assessment and data envelopment analysis for the reduction of greenhouse gas emissions in agriculture production.

Science.gov (United States)

Rebolledo-Leiva, Ricardo; Angulo-Meza, Lidia; Iriarte, Alfredo; González-Araya, Marcela C

2017-09-01

Operations management tools are critical in the process of evaluating and implementing action towards a low carbon production. Currently, a sustainable production implies both an efficient resource use and the obligation to meet targets for reducing greenhouse gas (GHG) emissions. The carbon footprint (CF) tool allows estimating the overall amount of GHG emissions associated with a product or activity throughout its life cycle. In this paper, we propose a four-step method for a joint use of CF assessment and Data Envelopment Analysis (DEA). Following the eco-efficiency definition, which is the delivery of goods using fewer resources and with decreasing environmental impact, we use an output oriented DEA model to maximize production and reduce CF, taking into account simultaneously the economic and ecological perspectives. In another step, we stablish targets for the contributing CF factors in order to achieve CF reduction. The proposed method was applied to assess the eco-efficiency of five organic blueberry orchards throughout three growing seasons. The results show that this method is a practical tool for determining eco-efficiency and reducing GHG emissions. Copyright © 2017 Elsevier B.V. All rights reserved.

Data reduction, radial velocities and stellar parameters from spectra in the very low signal-to-noise domain

Science.gov (United States)

Malavolta, Luca

2013-10-01

Large astronomical facilities usually provide data reduction pipeline designed to deliver ready-to-use scientific data, and too often as- tronomers are relying on this to avoid the most difficult part of an astronomer job Standard data reduction pipelines however are usu- ally designed and tested to have good performance on data with av- erage Signal to Noise Ratio (SNR) data, and the issues that are related with the reduction of data in the very low SNR domain are not taken int account properly. As a result, informations in data with low SNR are not optimally exploited. During the last decade our group has collected thousands of spec- tra using the GIRAFFE spectrograph at Very Large Telescope (Chile) of the European Southern Observatory (ESO) to determine the ge- ometrical distance and dynamical state of several Galactic Globular Clusters but ultimately the analysis has been hampered by system- atics in data reduction, calibration and radial velocity measurements. Moreover these data has never been exploited to get other informa- tions like temperature and metallicity of stars, because considered too noisy for these kind of analyses. In this thesis we focus our attention on data reduction and analysis of spectra with very low SNR. The dataset we analyze in this thesis comprises 7250 spectra for 2771 stars of the Globular Cluster M 4 (NGC 6121) in the wavelength region 5145-5360Å obtained with GIRAFFE. Stars from the upper Red Giant Branch down to the Main Sequence have been observed in very different conditions, including nights close to full moon, and reaching SNR - 10 for many spectra in the dataset. We will first review the basic steps of data reduction and spec- tral extraction, adapting techniques well tested in other field (like photometry) but still under-developed in spectroscopy. We improve the wavelength dispersion solution and the correction of radial veloc- ity shift between day-time calibrations and science observations by following a completely

Follow up: Compound data sets and software tools for chemoinformatics and medicinal chemistry applications: update and data transfer

Science.gov (United States)

Hu, Ye; Bajorath, Jürgen

2014-01-01

In 2012, we reported 30 compound data sets and/or programs developed in our laboratory in a data article and made them freely available to the scientific community to support chemoinformatics and computational medicinal chemistry applications. These data sets and computational tools were provided for download from our website. Since publication of this data article, we have generated 13 new data sets with which we further extend our collection of publicly available data and tools. Due to changes in web servers and website architectures, data accessibility has recently been limited at times. Therefore, we have also transferred our data sets and tools to a public repository to ensure full and stable accessibility. To aid in data selection, we have classified the data sets according to scientific subject areas. Herein, we describe new data sets, introduce the data organization scheme, summarize the database content and provide detailed access information in ZENODO (doi: 10.5281/zenodo.8451 and doi:10.5281/zenodo.8455). PMID:25520777

Utilization of data processing as a tool in mineral extraction

International Nuclear Information System (INIS)

Stuart, F.W.

1982-01-01

The development of a system for the reduction and utilization of gamma log data for uranium ore bodies is described. This system, available from Western Nuclear, Inc., on a source license basis, has proved to be extremely effective for the reduction of gamma log data. Highlights of a new system which is being developed by Phelps Dodge's corporate regional data center are also discussed. This new system designed to more heavily utilize geostatistical concepts and hexagonal prisms for block modeling, will also provide the necessary interface to the mine haulage equipment dispatching systems developed by Phelps Dodge. This will allow for load by load analyses of material profitability, which will significantly enhance the economic benefits of the dispatching systems

On-line data acquisition and reduction at the magnetic detector PLUTO

International Nuclear Information System (INIS)

Franke, G.; Schmitz, R.

1976-12-01

We present a method for reducing cosmic ray background in a set of cylindrical proportional wire chambers. Data taking and reduction is done by a PDP 11/45 computer. The method is applied in e + e - storage ring experiments with the superconductive solenoid magnet PLUTO. A reduction of about 50% of the incoming events is achieved. (orig.) [de

Tools help deliver CERN data to labs worldwide

CERN Multimedia

Jackson, Joab

2006-01-01

Whatever its success in the marketplace, grid has been a great success in the research community. Thanks to grid tools, data created at CERN can be distributed and then analyzed at other facilities around the world. (1 page)

Exact Solutions of Generalized Modified Boussinesq, Kuramoto-Sivashinsky, and Camassa-Holm Equations via Double Reduction Theory

Directory of Open Access Journals (Sweden)

Zulfiqar Ali

2013-01-01

Full Text Available We find exact solutions of the Generalized Modified Boussinesq (GMB equation, the Kuromoto-Sivashinsky (KS equation the and, Camassa-Holm (CH equation by utilizing the double reduction theory related to conserved vectors. The fourth order GMB equation involves the arbitrary function and mixed derivative terms in highest derivative. The partial Noether’s approach yields seven conserved vectors for GMB equation and one conserved for vector KS equation. Due to presence of mixed derivative term the conserved vectors for GMB equation derived by the Noether like theorem do not satisfy the divergence relationship. The extra terms that constitute the trivial part of conserved vectors are adjusted and the resulting conserved vectors satisfy the divergence property. The double reduction theory yields two independent solutions and one reduction for GMB equation and one solution for KS equation. For CH equation two independent solutions are obtained elsewhere by double reduction theory with the help of conserved Vectors.

Generalized formal model of Big Data

OpenAIRE

Shakhovska, N.; Veres, O.; Hirnyak, M.

2016-01-01

This article dwells on the basic characteristic features of the Big Data technologies. It is analyzed the existing definition of the “big data” term. The article proposes and describes the elements of the generalized formal model of big data. It is analyzed the peculiarities of the application of the proposed model components. It is described the fundamental differences between Big Data technology and business analytics. Big Data is supported by the distributed file system Google File System ...

Overview on How Data Mining Tools May Support Cardiovascular Disease Prediction

Directory of Open Access Journals (Sweden)

Dan-Andrei Sitar-Taut

2010-01-01

Full Text Available Terms as knowledge discovery or KnowledgeDiscovery from Databases (KDD, Data Mining (DM, ArtificialIntelligence (AI, Machine Learning (ML, Artificial Neuralnetworks (ANN, decision tables and trees, gain from day to day,an increasing significance in medical data analysis. They permitthe identification, evaluation, and quantification of some lessvisible, intuitively unpredictable, by using generally large sets ofdata. Cardiology represents an extremely vast and importantdomain, having multiple and complex social and humanimplications. These are enough reasons to promote theresearches in this area, becoming shortly not just national orEuropean priorities, but also world-level ones. The profoundand multiple interwoven relationships among the cardiovascularrisk factors and cardiovascular diseases – but still far to becompletely discovered or understood – represent a niche forapplying IT&C modern and multidisciplinary tools in order tosolve the existing knowledge gaps.This paper’s aim is to present, by emphasizing their absoluteor relative pros and cons, several opportunities of applying DMtools in cardiology, more precisely in endothelial dysfunctiondiagnostic and quantification the relationships between theseand so-called “classical” cardiovascular risk factors.

Federal metering data analysis needs and existing tools

Energy Technology Data Exchange (ETDEWEB)

Henderson, Jordan W. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Fowler, Kimberly M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2015-07-01

Agencies have been working to improve their metering data collection, management, and analysis efforts over the last decade (since EPAct 2005) and will continue to address these challenges as new requirements and data needs come into place. Unfortunately there is no “one-size-fits-all” solution. As agencies continue to expand their capabilities to use metered consumption data to reducing resource use and improve operations, the hope is that shared knowledge will empower others to follow suit. This paper discusses the Federal metering data analysis needs and some existing tools.

Development and performance analysis of a lossless data reduction algorithm for voip

International Nuclear Information System (INIS)

Misbahuddin, S.; Boulejfen, N.

2014-01-01

VoIP (Voice Over IP) is becoming an alternative way of voice communications over the Internet. To better utilize voice call bandwidth, some standard compression algorithms are applied in VoIP systems. However, these algorithms affect the voice quality with high compression ratios. This paper presents a lossless data reduction technique to improve VoIP data transfer rate over the IP network. The proposed algorithm exploits the data redundancies in digitized VFs (Voice Frames) generated by VoIP systems. Performance of proposed data reduction algorithm has been presented in terms of compression ratio. The proposed algorithm will help retain the voice quality along with the improvement in VoIP data transfer rates. (author)

Overview of laboratory data tools available in a single electronic medical record

Directory of Open Access Journals (Sweden)

Neil R Kudler

2010-01-01

Full Text Available Background: Laboratory data account for the bulk of data stored in any given electronic medical record (EMR. To best serve the user, electronic laboratory data needs to be flexible and customizable. Our aim was to determine the various ways in which laboratory data get utilized by clinicians in our health system′s EMR. Method: All electronic menus, tabs, flowsheets, notes and subsections within the EMR (Millennium v2007.13, Cerner Corporation, Kansas City, MO, US were explored to determine how clinicians utilize discrete laboratory data. Results: Laboratory data in the EMR were utilized by clinicians in five distinct ways: within flowsheets, their personal inbox (EMR messaging, with decision support tools, in the health maintenance tool, and when incorporating laboratory data into their clinical notes and letters. Conclusions : Flexible electronic laboratory data in the EMR hava many advantages. Users can view, sort, pool, and appropriately route laboratory information to better support trend analyses, clinical decision making, and clinical charting. Laboratory data in the EMR can also be utilized to develop clinical decision support tools. Pathologists need to participate in the creation of these EMR tools in order to better support the appropriate utilization of laboratory information in the EMR.

Occupational dose reduction developments and data collected at nuclear power plants

International Nuclear Information System (INIS)

Dionne, B.J.; Baum, J.W.

1984-01-01

Occupational dose reduction developments and data collected at nuclear power plants have been described. Written descriptions of repetitive high dose jobs, their collective dose equivalent ranges and list of dose reduction techniques will aid in reducing collective dose equivalents from these dose-reduction targets. Knowing which components contribute to high maintenance or repair dose will aid in reducing routine maintenance collective dose equivalents. The radwaste dose reduction improvements will aid in reducing radwaste operations collective dose equivalent and reduce the number of radwaste workers who exceed their administrative dose limits. The identification and rating of managers' and workers' ALARA incentives will provide the basis for recommendations to improve dose reduction incentives. Lastly, the identification and rating of the key components of an ALARA program will aid in the development and coordination of the nuclear station ALARA programs

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.

Science.gov (United States)

Simonyan, Vahan; Mazumder, Raja

2014-09-30

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

High-Performance Integrated Virtual Environment (HIVE Tools and Applications for Big Data Analysis

Directory of Open Access Journals (Sweden)

Vahan Simonyan

2014-09-01

Full Text Available The High-performance Integrated Virtual Environment (HIVE is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

New Tools to Document and Manage Data/Metadata: Example NGEE Arctic and ARM

Science.gov (United States)

Crow, M. C.; Devarakonda, R.; Killeffer, T.; Hook, L.; Boden, T.; Wullschleger, S.

2017-12-01

Tools used for documenting, archiving, cataloging, and searching data are critical pieces of informatics. This poster describes tools being used in several projects at Oak Ridge National Laboratory (ORNL), with a focus on the U.S. Department of Energy's Next Generation Ecosystem Experiment in the Arctic (NGEE Arctic) and Atmospheric Radiation Measurements (ARM) project, and their usage at different stages of the data lifecycle. The Online Metadata Editor (OME) is used for the documentation and archival stages while a Data Search tool supports indexing, cataloging, and searching. The NGEE Arctic OME Tool [1] provides a method by which researchers can upload their data and provide original metadata with each upload while adhering to standard metadata formats. The tool is built upon a Java SPRING framework to parse user input into, and from, XML output. Many aspects of the tool require use of a relational database including encrypted user-login, auto-fill functionality for predefined sites and plots, and file reference storage and sorting. The Data Search Tool conveniently displays each data record in a thumbnail containing the title, source, and date range, and features a quick view of the metadata associated with that record, as well as a direct link to the data. The search box incorporates autocomplete capabilities for search terms and sorted keyword filters are available on the side of the page, including a map for geo-searching. These tools are supported by the Mercury [2] consortium (funded by DOE, NASA, USGS, and ARM) and developed and managed at Oak Ridge National Laboratory. Mercury is a set of tools for collecting, searching, and retrieving metadata and data. Mercury collects metadata from contributing project servers, then indexes the metadata to make it searchable using Apache Solr, and provides access to retrieve it from the web page. Metadata standards that Mercury supports include: XML, Z39.50, FGDC, Dublin-Core, Darwin-Core, EML, and ISO-19115.

Visual Tools for Crowdsourcing Data Validation Within the GLOBELAND30 Geoportal

Science.gov (United States)

Chuprikova, E.; Wu, H.; Murphy, C. E.; Meng, L.

2016-06-01

This research aims to investigate the role of visualization of the user generated data that can empower the geoportal of GlobeLand30 produced by NGCC (National Geomatics Center of China). The focus is set on the development of a concept of tools that can extend the Geo-tagging functionality and make use of it for different target groups. The anticipated tools should improve the continuous data validation, updating and efficient use of the remotely-sensed data distributed within GlobeLand30.

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

Science.gov (United States)

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

Science.gov (United States)

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.

User Driven Development of Software Tools for Open Data Discovery and Exploration

Science.gov (United States)

Schlobinski, Sascha; Keppel, Frank; Dihe, Pascal; Boot, Gerben; Falkenroth, Esa

2016-04-01

The use of open data in research faces challenges not restricted to inherent properties such as data quality, resolution of open data sets. Often Open data is catalogued insufficiently or fragmented. Software tools that support the effective discovery including the assessment of the data's appropriateness for research have shortcomings such as the lack of essential functionalities like support for data provenance. We believe that one of the reasons is the neglect of real end users requirements in the development process of aforementioned software tools. In the context of the FP7 Switch-On project we have pro-actively engaged the relevant user user community to collaboratively develop a means to publish, find and bind open data relevant for hydrologic research. Implementing key concepts of data discovery and exploration we have used state of the art web technologies to provide an interactive software tool that is easy to use yet powerful enough to satisfy the data discovery and access requirements of the hydrological research community.

Total Generalized Variation for Manifold-valued Data

OpenAIRE

Bredies, K.; Holler, M.; Storath, M.; Weinmann, A.

2017-01-01

In this paper we introduce the notion of second-order total generalized variation (TGV) regularization for manifold-valued data. We provide an axiomatic approach to formalize reasonable generalizations of TGV to the manifold setting and present two possible concrete instances that fulfill the proposed axioms. We provide well-posedness results and present algorithms for a numerical realization of these generalizations to the manifold setup. Further, we provide experimental results for syntheti...

A generally applicable lightweight method for calculating a value structure for tools and services in bioinformatics infrastructure projects.

Science.gov (United States)

Mayer, Gerhard; Quast, Christian; Felden, Janine; Lange, Matthias; Prinz, Manuel; Pühler, Alfred; Lawerenz, Chris; Scholz, Uwe; Glöckner, Frank Oliver; Müller, Wolfgang; Marcus, Katrin; Eisenacher, Martin

2017-10-30

Sustainable noncommercial bioinformatics infrastructures are a prerequisite to use and take advantage of the potential of big data analysis for research and economy. Consequently, funders, universities and institutes as well as users ask for a transparent value model for the tools and services offered. In this article, a generally applicable lightweight method is described by which bioinformatics infrastructure projects can estimate the value of tools and services offered without determining exactly the total costs of ownership. Five representative scenarios for value estimation from a rough estimation to a detailed breakdown of costs are presented. To account for the diversity in bioinformatics applications and services, the notion of service-specific 'service provision units' is introduced together with the factors influencing them and the main underlying assumptions for these 'value influencing factors'. Special attention is given on how to handle personnel costs and indirect costs such as electricity. Four examples are presented for the calculation of the value of tools and services provided by the German Network for Bioinformatics Infrastructure (de.NBI): one for tool usage, one for (Web-based) database analyses, one for consulting services and one for bioinformatics training events. Finally, from the discussed values, the costs of direct funding and the costs of payment of services by funded projects are calculated and compared. © The Author 2017. Published by Oxford University Press.

πScope: Python based scientific workbench with MDSplus data visualization tool

Energy Technology Data Exchange (ETDEWEB)

Shiraiwa, S., E-mail: shiraiwa@PSFC.MIT.EDU; Fredian, T.; Hillairet, J.; Stillerman, J.

2016-11-15

Highlights: • πScope provides great enhancement in MDSplus data visualization. • πScope provides a single platform for both data browsing and complicated analysis. • πScope is scriptable and easily expandable due to its object oriented. • πScope is written in python and available from (http://piscope.psfc.mit.edu/). - Abstract: A newly developed python based scientific data analysis and visualization tool, πScope ( (http://piscope.psfc.mit.edu)), is reported. The primary motivation is 1) to provide an updated tool to browse the MDSplus data beyond existing dwscope/jScope and 2) to realize a universal foundation to construct interface tools to perform computer modeling from experimental data. To visualize MDSplus data, πScope has many features including overplotting different signals and discharges, generating various plot types (line, contour, image, etc.), performing in-panel data analysis using python scripts, and producing publication quality graphics. The logic to generate multi-panel plots is designed to be backward compatible with dwscope, enabling smooth migration for users. πScope uses multi-threading in data loading, and is easy to modify and expand due to its object-oriented design. Furthermore, A user can access the data structure both from a GUI and a script, enabling relatively complex data analysis workflow built quickly on πScope.

πScope: Python based scientific workbench with MDSplus data visualization tool

International Nuclear Information System (INIS)

Shiraiwa, S.; Fredian, T.; Hillairet, J.; Stillerman, J.

2016-01-01

Highlights: • πScope provides great enhancement in MDSplus data visualization. • πScope provides a single platform for both data browsing and complicated analysis. • πScope is scriptable and easily expandable due to its object oriented. • πScope is written in python and available from (http://piscope.psfc.mit.edu/). - Abstract: A newly developed python based scientific data analysis and visualization tool, πScope ( (http://piscope.psfc.mit.edu)), is reported. The primary motivation is 1) to provide an updated tool to browse the MDSplus data beyond existing dwscope/jScope and 2) to realize a universal foundation to construct interface tools to perform computer modeling from experimental data. To visualize MDSplus data, πScope has many features including overplotting different signals and discharges, generating various plot types (line, contour, image, etc.), performing in-panel data analysis using python scripts, and producing publication quality graphics. The logic to generate multi-panel plots is designed to be backward compatible with dwscope, enabling smooth migration for users. πScope uses multi-threading in data loading, and is easy to modify and expand due to its object-oriented design. Furthermore, A user can access the data structure both from a GUI and a script, enabling relatively complex data analysis workflow built quickly on πScope.

Data-Driven Model Order Reduction for Bayesian Inverse Problems

KAUST Repository

Cui, Tiangang

2014-01-06

One of the major challenges in using MCMC for the solution of inverse problems is the repeated evaluation of computationally expensive numerical models. We develop a data-driven projection- based model order reduction technique to reduce the computational cost of numerical PDE evaluations in this context.

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

Science.gov (United States)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

New Tools to Document and Manage Data/Metadata: Example NGEE Arctic and UrbIS

Science.gov (United States)

Crow, M. C.; Devarakonda, R.; Hook, L.; Killeffer, T.; Krassovski, M.; Boden, T.; King, A. W.; Wullschleger, S. D.

2016-12-01

Tools used for documenting, archiving, cataloging, and searching data are critical pieces of informatics. This discussion describes tools being used in two different projects at Oak Ridge National Laboratory (ORNL), but at different stages of the data lifecycle. The Metadata Entry and Data Search Tool is being used for the documentation, archival, and data discovery stages for the Next Generation Ecosystem Experiment - Arctic (NGEE Arctic) project while the Urban Information Systems (UrbIS) Data Catalog is being used to support indexing, cataloging, and searching. The NGEE Arctic Online Metadata Entry Tool [1] provides a method by which researchers can upload their data and provide original metadata with each upload. The tool is built upon a Java SPRING framework to parse user input into, and from, XML output. Many aspects of the tool require use of a relational database including encrypted user-login, auto-fill functionality for predefined sites and plots, and file reference storage and sorting. The UrbIS Data Catalog is a data discovery tool supported by the Mercury cataloging framework [2] which aims to compile urban environmental data from around the world into one location, and be searchable via a user-friendly interface. Each data record conveniently displays its title, source, and date range, and features: (1) a button for a quick view of the metadata, (2) a direct link to the data and, for some data sets, (3) a button for visualizing the data. The search box incorporates autocomplete capabilities for search terms and sorted keyword filters are available on the side of the page, including a map for searching by area. References: [1] Devarakonda, Ranjeet, et al. "Use of a metadata documentation and search tool for large data volumes: The NGEE arctic example." Big Data (Big Data), 2015 IEEE International Conference on. IEEE, 2015. [2] Devarakonda, R., Palanisamy, G., Wilson, B. E., & Green, J. M. (2010). Mercury: reusable metadata management, data discovery

A Proposal for User-defined Reductions in OpenMP

Energy Technology Data Exchange (ETDEWEB)

Duran, A; Ferrer, R; Klemm, M; de Supinski, B R; Ayguade, E

2010-03-22

Reductions are commonly used in parallel programs to produce a global result from partial results computed in parallel. Currently, OpenMP only supports reductions for primitive data types and a limited set of base language operators. This is a significant limitation for those applications that employ user-defined data types (e. g., objects). Implementing manual reduction algorithms makes software development more complex and error-prone. Additionally, an OpenMP runtime system cannot optimize a manual reduction algorithm in ways typically applied to reductions on primitive types. In this paper, we propose new mechanisms to allow the use of most pre-existing binary functions on user-defined data types as User-Defined Reduction (UDR) operators. Our measurements show that our UDR prototype implementation provides consistently good performance across a range of thread counts without increasing general runtime overheads.

VISUAL TOOLS FOR CROWDSOURCING DATA VALIDATION WITHIN THE GLOBELAND30 GEOPORTAL

Directory of Open Access Journals (Sweden)

E. Chuprikova

2016-06-01

Full Text Available This research aims to investigate the role of visualization of the user generated data that can empower the geoportal of GlobeLand30 produced by NGCC (National Geomatics Center of China. The focus is set on the development of a concept of tools that can extend the Geo-tagging functionality and make use of it for different target groups. The anticipated tools should improve the continuous data validation, updating and efficient use of the remotely-sensed data distributed within GlobeLand30.

Toolkit for data reduction to tuples for the ATLAS experiment

International Nuclear Information System (INIS)

Snyder, Scott; Krasznahorkay, Attila

2012-01-01

The final step in a HEP data-processing chain is usually to reduce the data to a ‘tuple’ form which can be efficiently read by interactive analysis tools such as ROOT. Often, this is implemented independently by each group analyzing the data, leading to duplicated effort and needless divergence in the format of the reduced data. ATLAS has implemented a common toolkit for performing this processing step. By using tools from this package, physics analysis groups can produce tuples customized for a particular analysis but which are still consistent in format and vocabulary with those produced by other physics groups. The package is designed so that almost all the code is independent of the specific form used to store the tuple. The code that does depend on this is grouped into a set of small backend packages. While the ROOT backend is the most used, backends also exist for HDF5 and for specialized databases. By now, the majority of ATLAS analyses rely on this package, and it is an important contributor to the ability of ATLAS to rapidly analyze physics data.

Next generation tools for genomic data generation, distribution, and visualization.

Science.gov (United States)

Nix, David A; Di Sera, Tonya L; Dalley, Brian K; Milash, Brett A; Cundick, Robert M; Quinn, Kevin S; Courdy, Samir J

2010-09-09

With the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the laboratory and clinic is shifting to one of effectively managing, analyzing, and sharing genomic data. Here we present three open-source, platform independent, software tools for generating, analyzing, distributing, and visualizing genomic data. These include a next generation sequencing/microarray LIMS and analysis project center (GNomEx); an application for annotating and programmatically distributing genomic data using the community vetted DAS/2 data exchange protocol (GenoPub); and a standalone Java Swing application (GWrap) that makes cutting edge command line analysis tools available to those who prefer graphical user interfaces. Both GNomEx and GenoPub use the rich client Flex/Flash web browser interface to interact with Java classes and a relational database on a remote server. Both employ a public-private user-group security model enabling controlled distribution of patient and unpublished data alongside public resources. As such, they function as genomic data repositories that can be accessed manually or programmatically through DAS/2-enabled client applications such as the Integrated Genome Browser. These tools have gained wide use in our core facilities, research laboratories and clinics and are freely available for non-profit use. See http://sourceforge.net/projects/gnomex/, http://sourceforge.net/projects/genoviz/, and http://sourceforge.net/projects/useq.

A new monitoring data tool for MINOS+

International Nuclear Information System (INIS)

Castromonte, Cesar; Gomes, Ricardo A.

2013-01-01

Full text: Monitoring the data taking process is one of the most important and critical parts of every High Energy Physics (HEP) experiment. This guarantees the reliability and good quality of the data taken. It also allows detecting and tracking down the different problems associated with the detector operations. The MINOS+ experiment is the continuation of the former MINOS neutrino experiment, which operated from August 2003 to April 2012. MINOS+ will continue exposing the two MINOS detectors (Near and Far) to the NuMI muon neutrino beam for three years starting in 2013. The medium energy setting of the NuMI beam projected for NO νA will deliver about 18 X 10 20 protons-on-target during the first three years of operation. This will allow the MINOS Far Detector to collect more than 10,000 charged current muon neutrino events in the 4-10 GeV energy range, providing an accurate test for non-standard neutrino interactions, sterile neutrinos, extra dimensions, neutrino time-of-flight, and perhaps more. In this poster we show the full MINOS+ monitoring process, how this process is done, the several tools used to perform this task, and specially, the web monitoring data tool developed and implemented by the HEP group of the Federal University of Goiania as a contribution for the MINOS+ experiment. (author)

A new monitoring data tool for MINOS+

Energy Technology Data Exchange (ETDEWEB)

Castromonte, Cesar; Gomes, Ricardo A. [Universidade Federal de Goias, Goiania (Brazil)

2013-07-01

Full text: Monitoring the data taking process is one of the most important and critical parts of every High Energy Physics (HEP) experiment. This guarantees the reliability and good quality of the data taken. It also allows detecting and tracking down the different problems associated with the detector operations. The MINOS+ experiment is the continuation of the former MINOS neutrino experiment, which operated from August 2003 to April 2012. MINOS+ will continue exposing the two MINOS detectors (Near and Far) to the NuMI muon neutrino beam for three years starting in 2013. The medium energy setting of the NuMI beam projected for NO νA will deliver about 18 X 10{sup 20} protons-on-target during the first three years of operation. This will allow the MINOS Far Detector to collect more than 10,000 charged current muon neutrino events in the 4-10 GeV energy range, providing an accurate test for non-standard neutrino interactions, sterile neutrinos, extra dimensions, neutrino time-of-flight, and perhaps more. In this poster we show the full MINOS+ monitoring process, how this process is done, the several tools used to perform this task, and specially, the web monitoring data tool developed and implemented by the HEP group of the Federal University of Goiania as a contribution for the MINOS+ experiment. (author)

Development of multi-frequency array induction logging (MAIL) tool. 3; Multi shuhasu array gata induction kenso tool (MAIL) no kaihatsu (genchi shiken data no ichijigen kaiseki). 3

Energy Technology Data Exchange (ETDEWEB)

Sato, T; Osato, K; Takasugi, S [Geothermal Energy Research and Development Co. Ltd., Tokyo (Japan); Uchida, T [New Energy and Industrial Technology Development Organization, Tokyo, (Japan)

1996-05-01

A field test was carried out in 1995 on a deep-seated geothermal investigation and reduction well WDR (in Kakkonda, Shizuku-ishi, Iwate Prefecture) by utilizing a multi-frequency array induction logging tool which is under development by NEDO. This paper reports results of analyzing the acquired data. With the WDR wells, an investigation has been conducted to a drilling depth of 330 m. Three frequencies in a range from 3 to 24 kHz provided relatively good data, but data with 42 kHz had poor quality that cannot be utilized for the analysis. Precise device calibration is difficult on data acquired from three array type vertical component magnetometers (the difficulty may be due to a signal line from a transmitter passing on the magnetometer side). Because of this difficulty, analysis using one-dimensional inversion program was performed by using ratio of the amplitude for each frequency and phase difference as input data. The analysis allowed to have derived a result that corresponds to the ground bed structure. 5 refs., 8 figs., 3 tabs.

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

Energy Technology Data Exchange (ETDEWEB)

Yoo, Wucherl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Koo, Michelle [Univ. of California, Berkeley, CA (United States); Cao, Yu [California Inst. of Technology (CalTech), Pasadena, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Nugent, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Wu, Kesheng [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2016-09-17

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

MultiSpec—a tool for multispectral hyperspectral image data analysis

Science.gov (United States)

Biehl, Larry; Landgrebe, David

2002-12-01

MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

Teaching Advanced Data Analysis Tools to High School Astronomy Students

Science.gov (United States)

Black, David V.; Herring, Julie; Hintz, Eric G.

2015-01-01

A major barrier to becoming an astronomer is learning how to analyze astronomical data, such as using photometry to compare the brightness of stars. Most fledgling astronomers learn observation, data reduction, and analysis skills through an upper division college class. If the same skills could be taught in an introductory high school astronomy class, then more students would have an opportunity to do authentic science earlier, with implications for how many choose to become astronomers. Several software tools have been developed that can analyze astronomical data ranging from fairly straightforward (AstroImageJ and DS9) to very complex (IRAF and DAOphot). During the summer of 2014, a study was undertaken at Brigham Young University through a Research Experience for Teachers (RET) program to evaluate the effectiveness and ease-of-use of these four software packages. Standard tasks tested included creating a false-color IR image using WISE data in DS9, Adobe Photoshop, and The Gimp; a multi-aperture analyses of variable stars over time using AstroImageJ; creating Spectral Energy Distributions (SEDs) of stars using photometry at multiple wavelengths in AstroImageJ and DS9; and color-magnitude and hydrogen alpha index diagrams for open star clusters using IRAF and DAOphot. Tutorials were then written and combined with screen captures to teach high school astronomy students at Walden School of Liberal Arts in Provo, UT how to perform these same tasks. They analyzed image data using the four software packages, imported it into Microsoft Excel, and created charts using images from BYU's 36-inch telescope at their West Mountain Observatory. The students' attempts to complete these tasks were observed, mentoring was provided, and the students then reported on their experience through a self-reflection essay and concept test. Results indicate that high school astronomy students can successfully complete professional-level astronomy data analyses when given detailed

Parallel Landscape Driven Data Reduction & Spatial Interpolation Algorithm for Big LiDAR Data

Directory of Open Access Journals (Sweden)

Rahil Sharma

2016-06-01

Full Text Available Airborne Light Detection and Ranging (LiDAR topographic data provide highly accurate digital terrain information, which is used widely in applications like creating flood insurance rate maps, forest and tree studies, coastal change mapping, soil and landscape classification, 3D urban modeling, river bank management, agricultural crop studies, etc. In this paper, we focus mainly on the use of LiDAR data in terrain modeling/Digital Elevation Model (DEM generation. Technological advancements in building LiDAR sensors have enabled highly accurate and highly dense LiDAR point clouds, which have made possible high resolution modeling of terrain surfaces. However, high density data result in massive data volumes, which pose computing issues. Computational time required for dissemination, processing and storage of these data is directly proportional to the volume of the data. We describe a novel technique based on the slope map of the terrain, which addresses the challenging problem in the area of spatial data analysis, of reducing this dense LiDAR data without sacrificing its accuracy. To the best of our knowledge, this is the first ever landscape-driven data reduction algorithm. We also perform an empirical study, which shows that there is no significant loss in accuracy for the DEM generated from a 52% reduced LiDAR dataset generated by our algorithm, compared to the DEM generated from an original, complete LiDAR dataset. For the accuracy of our statistical analysis, we perform Root Mean Square Error (RMSE comparing all of the grid points of the original DEM to the DEM generated by reduced data, instead of comparing a few random control points. Besides, our multi-core data reduction algorithm is highly scalable. We also describe a modified parallel Inverse Distance Weighted (IDW spatial interpolation method and show that the DEMs it generates are time-efficient and have better accuracy than the one’s generated by the traditional IDW method.

BrainCheck - a very brief tool to detect incipient cognitive decline: optimized case-finding combining patient- and informant-based data.

Science.gov (United States)

Ehrensperger, Michael M; Taylor, Kirsten I; Berres, Manfred; Foldi, Nancy S; Dellenbach, Myriam; Bopp, Irene; Gold, Gabriel; von Gunten, Armin; Inglin, Daniel; Müri, René; Rüegger, Brigitte; Kressig, Reto W; Monsch, Andreas U

2014-01-01

Optimal identification of subtle cognitive impairment in the primary care setting requires a very brief tool combining (a) patients' subjective impairments, (b) cognitive testing, and (c) information from informants. The present study developed a new, very quick and easily administered case-finding tool combining these assessments ('BrainCheck') and tested the feasibility and validity of this instrument in two independent studies. We developed a case-finding tool comprised of patient-directed (a) questions about memory and depression and (b) clock drawing, and (c) the informant-directed 7-item version of the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). Feasibility study: 52 general practitioners rated the feasibility and acceptance of the patient-directed tool. Validation study: An independent group of 288 Memory Clinic patients (mean ± SD age = 76.6 ± 7.9, education = 12.0 ± 2.6; 53.8% female) with diagnoses of mild cognitive impairment (n = 80), probable Alzheimer's disease (n = 185), or major depression (n = 23) and 126 demographically matched, cognitively healthy volunteer participants (age = 75.2 ± 8.8, education = 12.5 ± 2.7; 40% female) partook. All patient and healthy control participants were administered the patient-directed tool, and informants of 113 patient and 70 healthy control participants completed the very short IQCODE. Feasibility study: General practitioners rated the patient-directed tool as highly feasible and acceptable. Validation study: A Classification and Regression Tree analysis generated an algorithm to categorize patient-directed data which resulted in a correct classification rate (CCR) of 81.2% (sensitivity = 83.0%, specificity = 79.4%). Critically, the CCR of the combined patient- and informant-directed instruments (BrainCheck) reached nearly 90% (that is 89.4%; sensitivity = 97.4%, specificity = 81.6%). A new and very brief instrument for

INTERFACING INTERACTIVE DATA ANALYSIS TOOLS WITH THE GRID: THE PPDG CS-11 ACTIVITY

International Nuclear Information System (INIS)

Perl, Joseph

2003-01-01

For today's physicists, who work in large geographically distributed collaborations, the data grid promises significantly greater capabilities for analysis of experimental data and production of physics results than is possible with today's ''remote access'' technologies. The goal of letting scientists at their home institutions interact with and analyze data as if they were physically present at the major laboratory that houses their detector and computer center has yet to be accomplished. The Particle Physics Data Grid project (www.ppdg.net) has recently embarked on an effort to ''Interface and Integrate Interactive Data Analysis Tools with the grid and identify Common Components and Services''. The initial activities are to collect known and identify new requirements for grid services and analysis tools from a range of current and future experiments to determine if existing plans for tools and services meet these requirements. Follow-on activities will foster the interaction between grid service developers, analysis tool developers, experiment analysis framework developers and end user physicists, and will identify and carry out specific development/integration work so that interactive analysis tools utilizing grid services actually provide the capabilities that users need. This talk will summarize what we know of requirements for analysis tools and grid services, as well as describe the identified areas where more development work is needed

Open-source tool for automatic import of coded surveying data to multiple vector layers in GIS environment

Directory of Open Access Journals (Sweden)

Eva Stopková

2016-12-01

Full Text Available This paper deals with a tool that enables import of the coded data in a singletext file to more than one vector layers (including attribute tables, together withautomatic drawing of line and polygon objects and with optional conversion toCAD. Python script v.in.survey is available as an add-on for open-source softwareGRASS GIS (GRASS Development Team. The paper describes a case study basedon surveying at the archaeological mission at Tell-el Retaba (Egypt. Advantagesof the tool (e.g. significant optimization of surveying work and its limits (demandson keeping conventions for the points’ names coding are discussed here as well.Possibilities of future development are suggested (e.g. generalization of points’names coding or more complex attribute table creation.

HDAT: web-based high-throughput screening data analysis tools

International Nuclear Information System (INIS)

Liu, Rong; Hassan, Taimur; Rallo, Robert; Cohen, Yoram

2013-01-01

The increasing utilization of high-throughput screening (HTS) in toxicity studies of engineered nano-materials (ENMs) requires tools for rapid and reliable processing and analyses of large HTS datasets. In order to meet this need, a web-based platform for HTS data analyses tools (HDAT) was developed that provides statistical methods suitable for ENM toxicity data. As a publicly available computational nanoinformatics infrastructure, HDAT provides different plate normalization methods, various HTS summarization statistics, self-organizing map (SOM)-based clustering analysis, and visualization of raw and processed data using both heat map and SOM. HDAT has been successfully used in a number of HTS studies of ENM toxicity, thereby enabling analysis of toxicity mechanisms and development of structure–activity relationships for ENM toxicity. The online approach afforded by HDAT should encourage standardization of and future advances in HTS as well as facilitate convenient inter-laboratory comparisons of HTS datasets. (paper)

A low-cost multichannel analyzer with data reduction assembly for continuous air monitoring system

International Nuclear Information System (INIS)

Zoghi, B.; Lee, Y.; Nelson, D.C.

1992-01-01

This paper reports on a microcontroller-based multichannel analyzer (MCA) with a data reduction assembly (DRA) for a plutonium continuous air monitor (CAM) system. The MCA is capable of detecting the airborne alpha emitters in the presence of radon daughter products. The pulse output from the preamplifier has been stretched to allow the peak detector sufficient time to capture the pulse height. The pulse amplitude conversion, the data acquisition, and the output functions are carried out fully by software. The DRA consists of a data reduction unit (DRU) and its operator interface panel. The data reduction assembly has the ability to be networked to a single PC with up to 332 different CAM's remotely connected to it

A tool to increase information-processing capacity for consumer water meter data

Directory of Open Access Journals (Sweden)

Heinz E. Jacobs

2012-06-01

Objective: The objective of this research article was to describe the development of Swift, a locally developed software tool for analysing water meter data from an information management perspective, which engineers in the water field generally use, and to assess critically the influence of Swift on published research and industry. This article focuses on water usage and the challenge of data interchange and extraction as issues that various industries face. Method: This article presents the first detailed report on Swift. It uses a detailed knowledge review and presents and summarises the findings chronologically. Results: The water meter data flow path used to be quite simple. The risk of breaches in confidentiality was limited. Technological advances over the years have led to additional knowledge coming from the same water meter readings with subsequent research outputs. However, there are also complicated data flow paths and increased risks. Users have used Swift to analyse more than two million consumers’ water meter readings to date. Studies have culminated in 10 peer-reviewed journal articles using the data. Seven of them were in the last five years. Conclusion: Swift-based data was the basis of various research studies in the past decade. Practical guidelines in the civil engineering fraternity for estimating water use in South Africa have incorporated knowledge from these studies. Developments after 1995 have increased the information processing capacity for water meter data.

Coping with Complexity Model Reduction and Data Analysis

CERN Document Server

Gorban, Alexander N

2011-01-01

This volume contains the extended version of selected talks given at the international research workshop 'Coping with Complexity: Model Reduction and Data Analysis', Ambleside, UK, August 31 - September 4, 2009. This book is deliberately broad in scope and aims at promoting new ideas and methodological perspectives. The topics of the chapters range from theoretical analysis of complex and multiscale mathematical models to applications in e.g., fluid dynamics and chemical kinetics.

Selective data reduction in gas chromatography/infrared spectrometry

International Nuclear Information System (INIS)

Pyo, Dong Jin; Shin, Hyun Du

2001-01-01

As gas chromatography/infrared spectrometry (GC/IR) becomes routinely available, methods must be developed to deal with the large amount of data produced. We demonstrate computer methods that quickly search through a large data file, locating those spectra that display a spectral feature of interest. Based on a modified library search routine, these selective data reduction methods retrieve all or nearly all of the compounds of interest, while rejection the vast majority of unrelated compounds. To overcome the shifting problem of IR spectra, a search method of moving the average pattern was designed. In this moving pattern search, the average pattern of a particular functional group was not held stationary, but was allowed to be moved a little bit right and left

Characterizing Aerosols over Southeast Asia using the AERONET Data Synergy Tool

Science.gov (United States)

Giles, David M.; Holben, Brent N.; Eck, Thomas F.; Slutsker, Ilya; Slutsker, Ilya; Welton, Ellsworth, J.; Chin, Mian; Kucsera, Thomas; Schmaltz, Jeffery E.; Diehl, Thomas;

A Comprehensive Probabilistic Framework to Learn Air Data from Surface Pressure Measurements

Directory of Open Access Journals (Sweden)

Ankur Srivastava

2015-01-01

Full Text Available Use of probabilistic techniques has been demonstrated to learn air data parameters from surface pressure measurements. Integration of numerical models with wind tunnel data and sequential experiment design of wind tunnel runs has been demonstrated in the calibration of a flush air data sensing anemometer system. Development and implementation of a metamodeling method, Sequential Function Approximation (SFA, are presented which lies at the core of the discussed probabilistic framework. SFA is presented as a tool capable of nonlinear statistical inference, uncertainty reduction by fusion of data with physical models of variable fidelity, and sequential experiment design. This work presents the development and application of these tools in the calibration of FADS for a Runway Assisted Landing Site (RALS control tower. However, the multidisciplinary nature of this work is general in nature and is potentially applicable to a variety of mechanical and aerospace engineering problems.

Triggering and data acquisition general considerations

International Nuclear Information System (INIS)

Butler, Joel N.

2003-01-01

We provide a general introduction to trigger and data acquisition systems in High Energy Physics. We emphasize the new possibilities and new approaches that have been made possible by developments in computer technology and networking

Anaphe - OO libraries and tools for data analysis

International Nuclear Information System (INIS)

Couet, O.; Ferrero-Merlino, B.; Molnar, Z.; Moscicki, J.T.; Pfeiffer, A.; Sang, M.

2001-01-01

The Anaphe project is an ongoing effort to provide an Object Oriented software environment for data analysis in HENP experiments. A range of commercial and public domain libraries is used to cover basic functionalities; on top of these libraries a set of HENP-specific C++ class libraries for histogram management, fitting, plotting and ntuple-like data analysis has been developed. In order to comply with the user requirements for a command-line driven tool, the authors have chosen to use a scripting language (Python) as the front-end for a data analysis tool. The loose coupling provided by the consequent use of (AIDA compliant) Abstract Interfaces for each component in combination with the use of shared libraries for their implementation provides an easy integration of existing libraries into modern scripting languages thus allowing for rapid application development. This integration is simplified even further using a specialised toolkit (SWIG) to create 'shadow classes' for the Python language, which map the definitions of the Abstract Interfaces almost at a one-to-one level. The authors will give an overview of the architecture and design choices and will present the current status and future developments of the project

A general mixed boundary model reduction method for component mode synthesis

International Nuclear Information System (INIS)

Voormeeren, S N; Van der Valk, P L C; Rixen, D J

2010-01-01

A classic issue in component mode synthesis (CMS) methods is the choice for fixed or free boundary conditions at the interface degrees of freedom (DoF) and the associated vibration modes in the components reduction base. In this paper, a novel mixed boundary CMS method called the 'Mixed Craig-Bampton' method is proposed. The method is derived by dividing the substructure DoF into a set of internal DoF, free interface DoF and fixed interface DoF. To this end a simple but effective scheme is introduced that, for every pair of interface DoF, selects a free or fixed boundary condition for each DoF individually. Based on this selection a reduction basis is computed consisting of vibration modes, static constraint modes and static residual flexibility modes. In order to assemble the reduced substructures a novel mixed assembly procedure is developed. It is shown that this approach leads to relatively sparse reduced matrices, whereas other mixed boundary methods often lead to full matrices. As such, the Mixed Craig-Bampton method forms a natural generalization of the classic Craig-Bampton and more recent Dual Craig-Bampton methods. Finally, the method is applied to a finite element test model. Analysis reveals that the proposed method has comparable or better accuracy and superior versatility with respect to the existing methods.

Next generation tools for genomic data generation, distribution, and visualization

Directory of Open Access Journals (Sweden)

Nix David A

2010-09-01

Full Text Available Abstract Background With the rapidly falling cost and availability of high throughput sequencing and microarray technologies, the bottleneck for effectively using genomic analysis in the laboratory and clinic is shifting to one of effectively managing, analyzing, and sharing genomic data. Results Here we present three open-source, platform independent, software tools for generating, analyzing, distributing, and visualizing genomic data. These include a next generation sequencing/microarray LIMS and analysis project center (GNomEx; an application for annotating and programmatically distributing genomic data using the community vetted DAS/2 data exchange protocol (GenoPub; and a standalone Java Swing application (GWrap that makes cutting edge command line analysis tools available to those who prefer graphical user interfaces. Both GNomEx and GenoPub use the rich client Flex/Flash web browser interface to interact with Java classes and a relational database on a remote server. Both employ a public-private user-group security model enabling controlled distribution of patient and unpublished data alongside public resources. As such, they function as genomic data repositories that can be accessed manually or programmatically through DAS/2-enabled client applications such as the Integrated Genome Browser. Conclusions These tools have gained wide use in our core facilities, research laboratories and clinics and are freely available for non-profit use. See http://sourceforge.net/projects/gnomex/, http://sourceforge.net/projects/genoviz/, and http://sourceforge.net/projects/useq.

The electronic patient record as a meaningful audit tool - Accountability and autonomy in general practitioner work

DEFF Research Database (Denmark)

Winthereik, Brit Ross; van der Ploeg, I.; Berg, Marc

2007-01-01

Health authorities increasingly request that general practitioners (GPs) use information and communication technologies such as electronic patient records (EPR) for accountability purposes. This article deals with the use of EPRs among general practitioners in Britain. It examines two ways in which...... makes them active in finding ways that turn the EPR into a meaningful tool for them, that is, a tool that helps them provide what they see as good care. The article's main contribution is to show how accountability and autonomy are coproduced; less professional autonomy does not follow from more...... GPs use the EPR for accountability purposes. One way is to generate audit reports on the basis of the information that has been entered into the record. The other is to let the computer intervene in the clinical process through prompts. The article argues that GPs' ambivalence toward using the EPR...

The Java interface of MDSplus: towards a unified approach for local and remote data access

International Nuclear Information System (INIS)

Manduchi, G.; Taliercio, C.; Luchetta, A.

2000-01-01

The paper presents the main design concepts of the new Java interface of the MDSplus system, a data acquisition system currently in use in several fusion devices that is becoming the standard 'de facto' for data access in US fusion laboratories. The interface is currently composed of two tools, which represent the extension of the two original, X-Windows-based MDSplus interface tools. The first one, called jScope, provides interactive display of stored waveforms. The second one, called jTraverser, provides graphical support for navigation into the tree structure of the pulse files and for the set-up of experiment devices. Though both tools support network communication, remote data access has been considered as a key issue for jScope, in order to make it a general purpose tool for data display, which can be connected to a variety of experiments. Our experience in the development of these tools confirmed the widespread concept about the promising features of the Java language. In particular, the object oriented organization of the language and the rich set of support classes allowed an impressive reduction in the time required for development and testing

Enhanced STEM Learning with the GeoMapApp Data Exploration Tool

Science.gov (United States)

Goodwillie, A. M.

2014-12-01

GeoMapApp (http://www.geomapapp.org), is a free, map-based data discovery and visualisation tool developed with NSF funding at Lamont-Doherty Earth Observatory. GeoMapApp provides casual and specialist users alike with access to hundreds of built-in geoscience data sets covering geology, geophysics, geochemistry, oceanography, climatology, cryospherics, and the environment. Users can also import their own data tables, spreadsheets, shapefiles, grids and images. Simple manipulation and analysis tools combined with layering capabilities and engaging visualisations provide a powerful platform with which to explore and interrogate geoscience data in its proper geospatial context thus helping users to more easily gain insight into the meaning of the data. A global elevation base map covering the oceans as well as continents forms the backbone of GeoMapApp. The multi-resolution base map is updated regularly and includes data sources ranging from Space Shuttle elevation data for land areas to ultra-high-resolution surveys of coral reefs and seafloor hydrothermal vent fields. Examples of built-in data sets that can be layered over the elevation model include interactive earthquake and volcano data, plate tectonic velocities, hurricane tracks, land and ocean temperature, water column properties, age of the ocean floor, and deep submersible bottom photos. A versatile profiling tool provides instant access to data cross-sections. Contouring and 3-D views are also offered - the attached image shows a 3-D view of East Africa's Ngorongoro Crater as an example. Tabular data - both imported and built-in - can be displayed in a variety of ways and a lasso tool enables users to quickly select data points directly from the map. A range of STEM-based education material based upon GeoMapApp is already available, including a number of self-contained modules for school- and college-level students (http://www.geomapapp.org/education/contributed_material.html). More learning modules are

Neuro-Simulation Tool for Enhanced Oil Recovery Screening and Reservoir Performance Prediction

Directory of Open Access Journals (Sweden)

Soheil Bahrekazemi

2017-09-01

Full Text Available Assessment of the suitable enhanced oil recovery method in an oilfield is one of the decisions which are made prior to the natural drive production mechanism. In some cases, having in-depth knowledge about reservoir’s rock, fluid properties, and equipment is needed as well as economic evaluation. Both putting such data into simulation and its related consequent processes are generally very time consuming and costly.  In order to reduce study cases, an appropriate tool is required for primary screening prior to any operations being performed, to which leads reduction of time in design of ether pilot section or production under field condition. In this research, two different and useful screening tools are presented through a graphical user interface. The output of just over 900 simulations and verified screening criteria tables were employed to design the mentioned tools. Moreover, by means of gathered data and development of artificial neural networks, two dissimilar screening tools for proper assessment of suitable enhanced oil recovery method were finally introduced. The first tool is about the screening of enhanced oil recovery process based on published tables/charts and the second one which is Neuro-Simulation tool, concerns economical evaluation of miscible and immiscible injection of carbon dioxide, nitrogen and natural gas into the reservoir. Both of designed tools are provided in the form of a graphical user interface by which the user, can perceive suitable method through plot of oil recovery graph during 20 years of production, costs of gas injection per produced barrel, cumulative oil production, and finally, design the most efficient scenario.

Generalization from uncertain and imprecise data

Energy Technology Data Exchange (ETDEWEB)

Bouchon-Meunier, B.; Marsala, C.; Rifqi, M. [Universite P. et M. Curie, Paris (France); Ramdani, M. [Universite P. et M. Curie, Paris (France)]|[Faculte des Sciences et Techniques, Mohammadia (Morocco)

1996-12-31

Most of the knowledge available about a given system is imperfect, which means imprecise, uncertain, qualitative, expressed in natural language with words which are generally vague. Some pieces of knowledge are numerical, obtained by means of measurements with more or less precise devices. They can also be incomplete, with unknown values for some elements of the system. Classification of objects, decision-making according to the description of the system, are well known problems which can be approached by various ways. Methods based on a generalization process appear very efficient when a list of already solved cases is available and sufficiently representative of all the possible cases. In this paper, we focus on the case where fuzzy sets are used to represent imperfect knowledge because of the capability of fuzzy sets to help managing imprecise data, possibly submitted to some non probabilistic uncertainty such as a subjective doubt. Fuzzy sets also present the interesting property to establish an interface between numerical and symbolic data and are interesting to use when both types of data are present. We suppose that the objects of the system are described by means of attributes, the value of which can be imprecise, uncertain or undetermined. Our purpose is to find rules enabling us to attach a class to any object of the system. We focus this study on two generalization methods based on the knowledge of a training set of objects associated with their descriptions and their classes.

MYRaf: A new Approach with IRAF for Astronomical Photometric Reduction

Science.gov (United States)

Kilic, Y.; Shameoni Niaei, M.; Özeren, F. F.; Yesilyaprak, C.

2016-12-01

In this study, the design and some developments of MYRaf software for astronomical photometric reduction are presented. MYRaf software is an easy to use, reliable, and has a fast IRAF aperture photometry GUI tools. MYRaf software is an important step for the automated software process of robotic telescopes, and uses IRAF, PyRAF, matplotlib, ginga, alipy, and Sextractor with the general-purpose and high-level programming language Python and uses the QT framework.

General Purpose Data-Driven Monitoring for Space Operations