Operational Analysis of Time-Optimal Maneuvering for Imaging Spacecraft

DTIC Science & Technology

2013-03-01

imaging spacecraft. The analysis is facilitated through the use of AGI’s Systems Tool Kit ( STK ) software. An Analytic Hierarchy Process (AHP)-based...the Singapore-developed X-SAT imaging spacecraft. The analysis is facilitated through the use of AGI’s Systems Tool Kit ( STK ) software. An Analytic...89  B.  FUTURE WORK................................................................................. 90  APPENDIX A. STK DATA AND BENEFIT

Updates in metabolomics tools and resources: 2014-2015.

PubMed

Misra, Biswapriya B; van der Hooft, Justin J J

2016-01-01

Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources--in the form of tools, software, and databases--is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deriving Earth Science Data Analytics Requirements

NASA Technical Reports Server (NTRS)

Kempler, Steven J.

2015-01-01

Data Analytics applications have made successful strides in the business world where co-analyzing extremely large sets of independent variables have proven profitable. Today, most data analytics tools and techniques, sometimes applicable to Earth science, have targeted the business industry. In fact, the literature is nearly absent of discussion about Earth science data analytics. Earth science data analytics (ESDA) is the process of examining large amounts of data from a variety of sources to uncover hidden patterns, unknown correlations, and other useful information. ESDA is most often applied to data preparation, data reduction, and data analysis. Co-analysis of increasing number and volume of Earth science data has become more prevalent ushered by the plethora of Earth science data sources generated by US programs, international programs, field experiments, ground stations, and citizen scientists.Through work associated with the Earth Science Information Partners (ESIP) Federation, ESDA types have been defined in terms of data analytics end goals. Goals of which are very different than those in business, requiring different tools and techniques. A sampling of use cases have been collected and analyzed in terms of data analytics end goal types, volume, specialized processing, and other attributes. The goal of collecting these use cases is to be able to better understand and specify requirements for data analytics tools and techniques yet to be implemented. This presentation will describe the attributes and preliminary findings of ESDA use cases, as well as provide early analysis of data analytics toolstechniques requirements that would support specific ESDA type goals. Representative existing data analytics toolstechniques relevant to ESDA will also be addressed.

DE-CERTS: A Decision Support System for a Comparative Evaluation Method for Risk Management Methodologies and Tools

DTIC Science & Technology

1991-09-01

iv III. THE ANALYTIC HIERARCHY PROCESS ..... ........ 15 A. INTRODUCTION ...... ................. 15 B. THE AHP PROCESS ...... ................ 16 C...INTRODUCTION ...... ................. 26 B. IMPLEMENTATION OF CERTS USING AHP ........ .. 27 1. Consistency ...... ................ 29 2. User Interface...the proposed technique into a Decision Support System. Expert Choice implements the Analytic Hierarchy Process ( AHP ), an approach to multi- criteria

Development and in-line validation of a Process Analytical Technology to facilitate the scale up of coating processes.

PubMed

Wirges, M; Funke, A; Serno, P; Knop, K; Kleinebudde, P

2013-05-05

Incorporation of an active pharmaceutical ingredient (API) into the coating layer of film-coated tablets is a method mainly used to formulate fixed-dose combinations. Uniform and precise spray-coating of an API represents a substantial challenge, which could be overcome by applying Raman spectroscopy as process analytical tool. In pharmaceutical industry, Raman spectroscopy is still mainly used as a bench top laboratory analytical method and usually not implemented in the production process. Concerning the application in the production process, a lot of scientific approaches stop at the level of feasibility studies and do not manage the step to production scale and process applications. The present work puts the scale up of an active coating process into focus, which is a step of highest importance during the pharmaceutical development. Active coating experiments were performed at lab and production scale. Using partial least squares (PLS), a multivariate model was constructed by correlating in-line measured Raman spectral data with the coated amount of API. By transferring this model, being implemented for a lab scale process, to a production scale process, the robustness of this analytical method and thus its applicability as a Process Analytical Technology (PAT) tool for the correct endpoint determination in pharmaceutical manufacturing could be shown. Finally, this method was validated according to the European Medicine Agency (EMA) guideline with respect to the special requirements of the applied in-line model development strategy. Copyright © 2013 Elsevier B.V. All rights reserved.

76 FR 70517 - Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-14

... requested. These systems generally also provide analytics, spreadsheets, and other tools designed to enable funds to analyze the data presented, as well as communication tools to process fund instructions...

Ultramicroelectrode Array Based Sensors: A Promising Analytical Tool for Environmental Monitoring

PubMed Central

Orozco, Jahir; Fernández-Sánchez, César; Jiménez-Jorquera, Cecilia

2010-01-01

The particular analytical performance of ultramicroelectrode arrays (UMEAs) has attracted a high interest by the research community and has led to the development of a variety of electroanalytical applications. UMEA-based approaches have demonstrated to be powerful, simple, rapid and cost-effective analytical tools for environmental analysis compared to available conventional electrodes and standardised analytical techniques. An overview of the fabrication processes of UMEAs, their characterization and applications carried out by the Spanish scientific community is presented. A brief explanation of theoretical aspects that highlight their electrochemical behavior is also given. Finally, the applications of this transducer platform in the environmental field are discussed. PMID:22315551

Haze Gray Paint and the U.S. Navy: A Procurement Process Review

DTIC Science & Technology

2017-12-01

support of the fleet. The research encompasses both qualitative and quantitative analytical tools utilizing historical demand data for Silicone Alkyd...inventory level of 1K Polysiloxane in support of the fleet. The research encompasses both qualitative and quantitative analytical tools utilizing...Chapter I. C. CONCLUSIONS As discussed in the Summary section, this research used a qualitative and a quantitative approach to analyze the Polysiloxane

Dynamic Vision for Control

DTIC Science & Technology

2006-07-27

unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The goal of this project was to develop analytical and computational tools to make vision a Viable sensor for...vision.ucla. edu July 27, 2006 Abstract The goal of this project was to develop analytical and computational tools to make vision a viable sensor for the ... sensors . We have proposed the framework of stereoscopic segmentation where multiple images of the same obejcts were jointly processed to extract geometry

Accelerated bridge construction (ABC) decision making and economic modeling tool.

DOT National Transportation Integrated Search

2011-12-01

In this FHWA-sponsored pool funded study, a set of decision making tools, based on the Analytic Hierarchy Process (AHP) was developed. This tool set is prepared for transportation specialists and decision-makers to determine if ABC is more effective ...

Rapid process development of chromatographic process using direct analysis in real time mass spectrometry as a process analytical technology tool.

PubMed

Yan, Binjun; Chen, Teng; Xu, Zhilin; Qu, Haibin

2014-06-01

The concept of quality by design (QbD) is widely applied in the process development of pharmaceuticals. However, the additional cost and time have caused some resistance about QbD implementation. To show a possible solution, this work proposed a rapid process development method, which used direct analysis in real time mass spectrometry (DART-MS) as a process analytical technology (PAT) tool for studying the chromatographic process of Ginkgo biloba L., as an example. The breakthrough curves were fast determined by DART-MS at-line. A high correlation coefficient of 0.9520 was found between the concentrations of ginkgolide A determined by DART-MS and HPLC. Based on the PAT tool, the impacts of process parameters on the adsorption capacity were discovered rapidly, which showed a decreased adsorption capacity with the increase of the flow rate. This work has shown the feasibility and advantages of integrating PAT into QbD implementation for rapid process development. Copyright © 2014 Elsevier B.V. All rights reserved.

Bio-TDS: bioscience query tool discovery system.

PubMed

Gnimpieba, Etienne Z; VanDiermen, Menno S; Gustafson, Shayla M; Conn, Bill; Lushbough, Carol M

2017-01-04

Bioinformatics and computational biology play a critical role in bioscience and biomedical research. As researchers design their experimental projects, one major challenge is to find the most relevant bioinformatics toolkits that will lead to new knowledge discovery from their data. The Bio-TDS (Bioscience Query Tool Discovery Systems, http://biotds.org/) has been developed to assist researchers in retrieving the most applicable analytic tools by allowing them to formulate their questions as free text. The Bio-TDS is a flexible retrieval system that affords users from multiple bioscience domains (e.g. genomic, proteomic, bio-imaging) the ability to query over 12 000 analytic tool descriptions integrated from well-established, community repositories. One of the primary components of the Bio-TDS is the ontology and natural language processing workflow for annotation, curation, query processing, and evaluation. The Bio-TDS's scientific impact was evaluated using sample questions posed by researchers retrieved from Biostars, a site focusing on BIOLOGICAL DATA ANALYSIS: The Bio-TDS was compared to five similar bioscience analytic tool retrieval systems with the Bio-TDS outperforming the others in terms of relevance and completeness. The Bio-TDS offers researchers the capacity to associate their bioscience question with the most relevant computational toolsets required for the data analysis in their knowledge discovery process. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Sigma metrics as a tool for evaluating the performance of internal quality control in a clinical chemistry laboratory

PubMed Central

Kumar, B. Vinodh; Mohan, Thuthi

2018-01-01

OBJECTIVE: Six Sigma is one of the most popular quality management system tools employed for process improvement. The Six Sigma methods are usually applied when the outcome of the process can be measured. This study was done to assess the performance of individual biochemical parameters on a Sigma Scale by calculating the sigma metrics for individual parameters and to follow the Westgard guidelines for appropriate Westgard rules and levels of internal quality control (IQC) that needs to be processed to improve target analyte performance based on the sigma metrics. MATERIALS AND METHODS: This is a retrospective study, and data required for the study were extracted between July 2015 and June 2016 from a Secondary Care Government Hospital, Chennai. The data obtained for the study are IQC - coefficient of variation percentage and External Quality Assurance Scheme (EQAS) - Bias% for 16 biochemical parameters. RESULTS: For the level 1 IQC, four analytes (alkaline phosphatase, magnesium, triglyceride, and high-density lipoprotein-cholesterol) showed an ideal performance of ≥6 sigma level, five analytes (urea, total bilirubin, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level and for level 2 IQCs, same four analytes of level 1 showed a performance of ≥6 sigma level, and four analytes (urea, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level. For all analytes <6 sigma level, the quality goal index (QGI) was <0.8 indicating the area requiring improvement to be imprecision except cholesterol whose QGI >1.2 indicated inaccuracy. CONCLUSION: This study shows that sigma metrics is a good quality tool to assess the analytical performance of a clinical chemistry laboratory. Thus, sigma metric analysis provides a benchmark for the laboratory to design a protocol for IQC, address poor assay performance, and assess the efficiency of existing laboratory processes. PMID:29692587

[Construction of NIRS-based process analytical system for production of salvianolic acid for injection and relative discussion].

PubMed

Zhang, Lei; Yue, Hong-Shui; Ju, Ai-Chun; Ye, Zheng-Liang

2016-10-01

Currently, near infrared spectroscopy (NIRS) has been considered as an efficient tool for achieving process analytical technology(PAT) in the manufacture of traditional Chinese medicine (TCM) products. In this article, the NIRS based process analytical system for the production of salvianolic acid for injection was introduced. The design of the process analytical system was described in detail, including the selection of monitored processes and testing mode, and potential risks that should be avoided. Moreover, the development of relative technologies was also presented, which contained the establishment of the monitoring methods for the elution of polyamide resin and macroporous resin chromatography processes, as well as the rapid analysis method for finished products. Based on author's experience of research and work, several issues in the application of NIRS to the process monitoring and control in TCM production were then raised, and some potential solutions were also discussed. The issues include building the technical team for process analytical system, the design of the process analytical system in the manufacture of TCM products, standardization of the NIRS-based analytical methods, and improving the management of process analytical system. Finally, the prospect for the application of NIRS in the TCM industry was put forward. Copyright© by the Chinese Pharmaceutical Association.

Collaborative Web-Enabled GeoAnalytics Applied to OECD Regional Data

NASA Astrophysics Data System (ADS)

Jern, Mikael

Recent advances in web-enabled graphics technologies have the potential to make a dramatic impact on developing collaborative geovisual analytics (GeoAnalytics). In this paper, tools are introduced that help establish progress initiatives at international and sub-national levels aimed at measuring and collaborating, through statistical indicators, economic, social and environmental developments and to engage both statisticians and the public in such activities. Given this global dimension of such a task, the “dream” of building a repository of progress indicators, where experts and public users can use GeoAnalytics collaborative tools to compare situations for two or more countries, regions or local communities, could be accomplished. While the benefits of GeoAnalytics tools are many, it remains a challenge to adapt these dynamic visual tools to the Internet. For example, dynamic web-enabled animation that enables statisticians to explore temporal, spatial and multivariate demographics data from multiple perspectives, discover interesting relationships, share their incremental discoveries with colleagues and finally communicate selected relevant knowledge to the public. These discoveries often emerge through the diverse backgrounds and experiences of expert domains and are precious in a creative analytics reasoning process. In this context, we introduce a demonstrator “OECD eXplorer”, a customized tool for interactively analyzing, and collaborating gained insights and discoveries based on a novel story mechanism that capture, re-use and share task-related explorative events.

Sigma Metrics Across the Total Testing Process.

PubMed

Charuruks, Navapun

2017-03-01

Laboratory quality control has been developed for several decades to ensure patients' safety, from a statistical quality control focus on the analytical phase to total laboratory processes. The sigma concept provides a convenient way to quantify the number of errors in extra-analytical and analytical phases through the defect per million and sigma metric equation. Participation in a sigma verification program can be a convenient way to monitor analytical performance continuous quality improvement. Improvement of sigma-scale performance has been shown from our data. New tools and techniques for integration are needed. Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluation Model for Applying an E-Learning System in a Course: An Analytic Hierarchy Process-Multi-Choice Goal Programming Approach

ERIC Educational Resources Information Center

Lin, Teng-Chiao; Ho, Hui-Ping; Chang, Ching-Ter

2014-01-01

With the widespread use of the Internet, adopting e-learning systems in courses has gradually become more and more important in universities in Taiwan. However, because of limitations of teachers' time, selecting suitable online IT tools has become very important. This study proposes an analytic hierarchy process (AHP)-multi-choice goal…

The Hico Image Processing System: A Web-Accessible Hyperspectral Remote Sensing Toolbox

NASA Astrophysics Data System (ADS)

Harris, A. T., III; Goodman, J.; Justice, B.

2014-12-01

As the quantity of Earth-observation data increases, the use-case for hosting analytical tools in geospatial data centers becomes increasingly attractive. To address this need, HySpeed Computing and Exelis VIS have developed the HICO Image Processing System, a prototype cloud computing system that provides online, on-demand, scalable remote sensing image processing capabilities. The system provides a mechanism for delivering sophisticated image processing analytics and data visualization tools into the hands of a global user community, who will only need a browser and internet connection to perform analysis. Functionality of the HICO Image Processing System is demonstrated using imagery from the Hyperspectral Imager for the Coastal Ocean (HICO), an imaging spectrometer located on the International Space Station (ISS) that is optimized for acquisition of aquatic targets. Example applications include a collection of coastal remote sensing algorithms that are directed at deriving critical information on water and habitat characteristics of our vulnerable coastal environment. The project leverages the ENVI Services Engine as the framework for all image processing tasks, and can readily accommodate the rapid integration of new algorithms, datasets and processing tools.

Energy geotechnics: Advances in subsurface energy recovery, storage, exchange, and waste management

DOE PAGES

McCartney, John S.; Sanchez, Marcelo; Tomac, Ingrid

2016-02-17

Energy geotechnics involves the use of geotechnical principles to understand and engineer the coupled thermo-hydro-chemo-mechanical processes encountered in collecting, exchanging, storing, and protecting energy resources in the subsurface. In addition to research on these fundamental coupled processes and characterization of relevant material properties, applied research is being performed to develop analytical tools for the design and analysis of different geo-energy applications. In conclusion, the aims of this paper are to discuss the fundamental physics and constitutive models that are common to these different applications, and to summarize recent advances in the development of relevant analytical tools.

Energy geotechnics: Advances in subsurface energy recovery, storage, exchange, and waste management

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCartney, John S.; Sanchez, Marcelo; Tomac, Ingrid

Energy geotechnics involves the use of geotechnical principles to understand and engineer the coupled thermo-hydro-chemo-mechanical processes encountered in collecting, exchanging, storing, and protecting energy resources in the subsurface. In addition to research on these fundamental coupled processes and characterization of relevant material properties, applied research is being performed to develop analytical tools for the design and analysis of different geo-energy applications. In conclusion, the aims of this paper are to discuss the fundamental physics and constitutive models that are common to these different applications, and to summarize recent advances in the development of relevant analytical tools.

Toward a Visualization-Supported Workflow for Cyber Alert Management using Threat Models and Human-Centered Design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Franklin, Lyndsey; Pirrung, Megan A.; Blaha, Leslie M.

Cyber network analysts follow complex processes in their investigations of potential threats to their network. Much research is dedicated to providing automated tool support in the effort to make their tasks more efficient, accurate, and timely. This tool support comes in a variety of implementations from machine learning algorithms that monitor streams of data to visual analytic environments for exploring rich and noisy data sets. Cyber analysts, however, often speak of a need for tools which help them merge the data they already have and help them establish appropriate baselines against which to compare potential anomalies. Furthermore, existing threat modelsmore » that cyber analysts regularly use to structure their investigation are not often leveraged in support tools. We report on our work with cyber analysts to understand they analytic process and how one such model, the MITRE ATT&CK Matrix [32], is used to structure their analytic thinking. We present our efforts to map specific data needed by analysts into the threat model to inform our eventual visualization designs. We examine data mapping for gaps where the threat model is under-supported by either data or tools. We discuss these gaps as potential design spaces for future research efforts. We also discuss the design of a prototype tool that combines machine-learning and visualization components to support cyber analysts working with this threat model.« less

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012).

PubMed

Marek, Lukáš; Tuček, Pavel; Pászto, Vít

2015-01-28

Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution. We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics. Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk. We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.

Trends in Process Analytical Technology: Present State in Bioprocessing.

PubMed

Jenzsch, Marco; Bell, Christian; Buziol, Stefan; Kepert, Felix; Wegele, Harald; Hakemeyer, Christian

2017-08-04

Process analytical technology (PAT), the regulatory initiative for incorporating quality in pharmaceutical manufacturing, is an area of intense research and interest. If PAT is effectively applied to bioprocesses, this can increase process understanding and control, and mitigate the risk from substandard drug products to both manufacturer and patient. To optimize the benefits of PAT, the entire PAT framework must be considered and each elements of PAT must be carefully selected, including sensor and analytical technology, data analysis techniques, control strategies and algorithms, and process optimization routines. This chapter discusses the current state of PAT in the biopharmaceutical industry, including several case studies demonstrating the degree of maturity of various PAT tools. Graphical Abstract Hierarchy of QbD components.

Potential of Near-Infrared Chemical Imaging as Process Analytical Technology Tool for Continuous Freeze-Drying.

PubMed

Brouckaert, Davinia; De Meyer, Laurens; Vanbillemont, Brecht; Van Bockstal, Pieter-Jan; Lammens, Joris; Mortier, Séverine; Corver, Jos; Vervaet, Chris; Nopens, Ingmar; De Beer, Thomas

2018-04-03

Near-infrared chemical imaging (NIR-CI) is an emerging tool for process monitoring because it combines the chemical selectivity of vibrational spectroscopy with spatial information. Whereas traditional near-infrared spectroscopy is an attractive technique for water content determination and solid-state investigation of lyophilized products, chemical imaging opens up possibilities for assessing the homogeneity of these critical quality attributes (CQAs) throughout the entire product. In this contribution, we aim to evaluate NIR-CI as a process analytical technology (PAT) tool for at-line inspection of continuously freeze-dried pharmaceutical unit doses based on spin freezing. The chemical images of freeze-dried mannitol samples were resolved via multivariate curve resolution, allowing us to visualize the distribution of mannitol solid forms throughout the entire cake. Second, a mannitol-sucrose formulation was lyophilized with variable drying times for inducing changes in water content. Analyzing the corresponding chemical images via principal component analysis, vial-to-vial variations as well as within-vial inhomogeneity in water content could be detected. Furthermore, a partial least-squares regression model was constructed for quantifying the water content in each pixel of the chemical images. It was hence concluded that NIR-CI is inherently a most promising PAT tool for continuously monitoring freeze-dried samples. Although some practicalities are still to be solved, this analytical technique could be applied in-line for CQA evaluation and for detecting the drying end point.

Development of analytical cell support for vitrification at the West Valley Demonstration Project. Topical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barber, F.H.; Borek, T.T.; Christopher, J.Z.

1997-12-01

Analytical and Process Chemistry (A&PC) support is essential to the high-level waste vitrification campaign at the West Valley Demonstration Project (WVDP). A&PC characterizes the waste, providing information necessary to formulate the recipe for the target radioactive glass product. High-level waste (HLW) samples are prepared and analyzed in the analytical cells (ACs) and Sample Storage Cell (SSC) on the third floor of the main plant. The high levels of radioactivity in the samples require handling them in the shielded cells with remote manipulators. The analytical hot cells and third floor laboratories were refurbished to ensure optimal uninterrupted operation during the vitrificationmore » campaign. New and modified instrumentation, tools, sample preparation and analysis techniques, and equipment and training were required for A&PC to support vitrification. Analytical Cell Mockup Units (ACMUs) were designed to facilitate method development, scientist and technician training, and planning for analytical process flow. The ACMUs were fabricated and installed to simulate the analytical cell environment and dimensions. New techniques, equipment, and tools could be evaluated m in the ACMUs without the consequences of generating or handling radioactive waste. Tools were fabricated, handling and disposal of wastes was addressed, and spatial arrangements for equipment were refined. As a result of the work at the ACMUs the remote preparation and analysis methods and the equipment and tools were ready for installation into the ACs and SSC m in July 1995. Before use m in the hot cells, all remote methods had been validated and four to eight technicians were trained on each. Fine tuning of the procedures has been ongoing at the ACs based on input from A&PC technicians. Working at the ACs presents greater challenges than had development at the ACMUs. The ACMU work and further refinements m in the ACs have resulted m in a reduction m in analysis turnaround time (TAT).« less

Development of a Computer-based Benchmarking and Analytical Tool. Benchmarking and Energy & Water Savings Tool in Dairy Plants (BEST-Dairy)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Tengfang; Flapper, Joris; Ke, Jing

The overall goal of the project is to develop a computer-based benchmarking and energy and water savings tool (BEST-Dairy) for use in the California dairy industry – including four dairy processes – cheese, fluid milk, butter, and milk powder.

Practice Evaluation Strategies Among Social Workers: Why an Evidence-Informed Dual-Process Theory Still Matters.

PubMed

Davis, Thomas D

2017-01-01

Practice evaluation strategies range in style from the formal-analytic tools of single-subject designs, rapid assessment instruments, algorithmic steps in evidence-informed practice, and computer software applications, to the informal-interactive tools of clinical supervision, consultation with colleagues, use of client feedback, and clinical experience. The purpose of this article is to provide practice researchers in social work with an evidence-informed theory that is capable of explaining both how and why social workers use practice evaluation strategies to self-monitor the effectiveness of their interventions in terms of client change. The author delineates the theoretical contours and consequences of what is called dual-process theory. Drawing on evidence-informed advances in the cognitive and social neurosciences, the author identifies among everyday social workers a theoretically stable, informal-interactive tool preference that is a cognitively necessary, sufficient, and stand-alone preference that requires neither the supplementation nor balance of formal-analytic tools. The author's delineation of dual-process theory represents a theoretical contribution in the century-old attempt to understand how and why social workers evaluate their practice the way they do.

Chemometrics in analytical chemistry-part I: history, experimental design and data analysis tools.

PubMed

Brereton, Richard G; Jansen, Jeroen; Lopes, João; Marini, Federico; Pomerantsev, Alexey; Rodionova, Oxana; Roger, Jean Michel; Walczak, Beata; Tauler, Romà

2017-10-01

Chemometrics has achieved major recognition and progress in the analytical chemistry field. In the first part of this tutorial, major achievements and contributions of chemometrics to some of the more important stages of the analytical process, like experimental design, sampling, and data analysis (including data pretreatment and fusion), are summarised. The tutorial is intended to give a general updated overview of the chemometrics field to further contribute to its dissemination and promotion in analytical chemistry.

Process Damping and Cutting Tool Geometry in Machining

NASA Astrophysics Data System (ADS)

Taylor, C. M.; Sims, N. D.; Turner, S.

2011-12-01

Regenerative vibration, or chatter, limits the performance of machining processes. Consequences of chatter include tool wear and poor machined surface finish. Process damping by tool-workpiece contact can reduce chatter effects and improve productivity. Process damping occurs when the flank (also known as the relief face) of the cutting tool makes contact with waves on the workpiece surface, created by chatter motion. Tool edge features can act to increase the damping effect. This paper examines how a tool's edge condition combines with the relief angle to affect process damping. An analytical model of cutting with chatter leads to a two-section curve describing how process damped vibration amplitude changes with surface speed for radiussed tools. The tool edge dominates the process damping effect at the lowest surface speeds, with the flank dominating at higher speeds. A similar curve is then proposed regarding tools with worn edges. Experimental data supports the notion of the two-section curve. A rule of thumb is proposed which could be useful to machine operators, regarding tool wear and process damping. The question is addressed, should a tool of a given geometry, used for a given application, be considered as sharp, radiussed or worn regarding process damping.

SensePath: Understanding the Sensemaking Process Through Analytic Provenance.

PubMed

Nguyen, Phong H; Xu, Kai; Wheat, Ashley; Wong, B L William; Attfield, Simon; Fields, Bob

2016-01-01

Sensemaking is described as the process of comprehension, finding meaning and gaining insight from information, producing new knowledge and informing further action. Understanding the sensemaking process allows building effective visual analytics tools to make sense of large and complex datasets. Currently, it is often a manual and time-consuming undertaking to comprehend this: researchers collect observation data, transcribe screen capture videos and think-aloud recordings, identify recurring patterns, and eventually abstract the sensemaking process into a general model. In this paper, we propose a general approach to facilitate such a qualitative analysis process, and introduce a prototype, SensePath, to demonstrate the application of this approach with a focus on browser-based online sensemaking. The approach is based on a study of a number of qualitative research sessions including observations of users performing sensemaking tasks and post hoc analyses to uncover their sensemaking processes. Based on the study results and a follow-up participatory design session with HCI researchers, we decided to focus on the transcription and coding stages of thematic analysis. SensePath automatically captures user's sensemaking actions, i.e., analytic provenance, and provides multi-linked views to support their further analysis. A number of other requirements elicited from the design session are also implemented in SensePath, such as easy integration with existing qualitative analysis workflow and non-intrusive for participants. The tool was used by an experienced HCI researcher to analyze two sensemaking sessions. The researcher found the tool intuitive and considerably reduced analysis time, allowing better understanding of the sensemaking process.

Analytics to Better Interpret and Use Large Amounts of Heterogeneous Data

NASA Astrophysics Data System (ADS)

Mathews, T. J.; Baskin, W. E.; Rinsland, P. L.

2014-12-01

Data scientists at NASA's Atmospheric Science Data Center (ASDC) are seasoned software application developers who have worked with the creation, archival, and distribution of large datasets (multiple terabytes and larger). In order for ASDC data scientists to effectively implement the most efficient processes for cataloging and organizing data access applications, they must be intimately familiar with data contained in the datasets with which they are working. Key technologies that are critical components to the background of ASDC data scientists include: large RBMSs (relational database management systems) and NoSQL databases; web services; service-oriented architectures; structured and unstructured data access; as well as processing algorithms. However, as prices of data storage and processing decrease, sources of data increase, and technologies advance - granting more people to access to data at real or near-real time - data scientists are being pressured to accelerate their ability to identify and analyze vast amounts of data. With existing tools this is becoming exceedingly more challenging to accomplish. For example, NASA Earth Science Data and Information System (ESDIS) alone grew from having just over 4PBs of data in 2009 to nearly 6PBs of data in 2011. This amount then increased to roughly10PBs of data in 2013. With data from at least ten new missions to be added to the ESDIS holdings by 2017, the current volume will continue to grow exponentially and drive the need to be able to analyze more data even faster. Though there are many highly efficient, off-the-shelf analytics tools available, these tools mainly cater towards business data, which is predominantly unstructured. Inadvertently, there are very few known analytics tools that interface well to archived Earth science data, which is predominantly heterogeneous and structured. This presentation will identify use cases for data analytics from an Earth science perspective in order to begin to identify specific tools that may be able to address those challenges.

A results-based process for evaluation of diverse visual analytics tools

NASA Astrophysics Data System (ADS)

Rubin, Gary; Berger, David H.

2013-05-01

With the pervasiveness of still and full-motion imagery in commercial and military applications, the need to ingest and analyze these media has grown rapidly in recent years. Additionally, video hosting and live camera websites provide a near real-time view of our changing world with unprecedented spatial coverage. To take advantage of these controlled and crowd-sourced opportunities, sophisticated visual analytics (VA) tools are required to accurately and efficiently convert raw imagery into usable information. Whether investing in VA products or evaluating algorithms for potential development, it is important for stakeholders to understand the capabilities and limitations of visual analytics tools. Visual analytics algorithms are being applied to problems related to Intelligence, Surveillance, and Reconnaissance (ISR), facility security, and public safety monitoring, to name a few. The diversity of requirements means that a onesize- fits-all approach to performance assessment will not work. We present a process for evaluating the efficacy of algorithms in real-world conditions, thereby allowing users and developers of video analytics software to understand software capabilities and identify potential shortcomings. The results-based approach described in this paper uses an analysis of end-user requirements and Concept of Operations (CONOPS) to define Measures of Effectiveness (MOEs), test data requirements, and evaluation strategies. We define metrics that individually do not fully characterize a system, but when used together, are a powerful way to reveal both strengths and weaknesses. We provide examples of data products, such as heatmaps, performance maps, detection timelines, and rank-based probability-of-detection curves.

A Simpli ed, General Approach to Simulating from Multivariate Copula Functions

Treesearch

Barry Goodwin

2012-01-01

Copulas have become an important analytic tool for characterizing multivariate distributions and dependence. One is often interested in simulating data from copula estimates. The process can be analytically and computationally complex and usually involves steps that are unique to a given parametric copula. We describe an alternative approach that uses \\probability{...

Design and Implementation of a Learning Analytics Toolkit for Teachers

ERIC Educational Resources Information Center

Dyckhoff, Anna Lea; Zielke, Dennis; Bultmann, Mareike; Chatti, Mohamed Amine; Schroeder, Ulrik

2012-01-01

Learning Analytics can provide powerful tools for teachers in order to support them in the iterative process of improving the effectiveness of their courses and to collaterally enhance their students' performance. In this paper, we present the theoretical background, design, implementation, and evaluation details of eLAT, a Learning Analytics…

Direct analysis in real time mass spectrometry, a process analytical technology tool for real-time process monitoring in botanical drug manufacturing.

PubMed

Wang, Lu; Zeng, Shanshan; Chen, Teng; Qu, Haibin

2014-03-01

A promising process analytical technology (PAT) tool has been introduced for batch processes monitoring. Direct analysis in real time mass spectrometry (DART-MS), a means of rapid fingerprint analysis, was applied to a percolation process with multi-constituent substances for an anti-cancer botanical preparation. Fifteen batches were carried out, including ten normal operations and five abnormal batches with artificial variations. The obtained multivariate data were analyzed by a multi-way partial least squares (MPLS) model. Control trajectories were derived from eight normal batches, and the qualification was tested by R(2) and Q(2). Accuracy and diagnosis capability of the batch model were then validated by the remaining batches. Assisted with high performance liquid chromatography (HPLC) determination, process faults were explained by corresponding variable contributions. Furthermore, a batch level model was developed to compare and assess the model performance. The present study has demonstrated that DART-MS is very promising in process monitoring in botanical manufacturing. Compared with general PAT tools, DART-MS offers a particular account on effective compositions and can be potentially used to improve batch quality and process consistency of samples in complex matrices. Copyright © 2014 Elsevier B.V. All rights reserved.

Mixed Initiative Visual Analytics Using Task-Driven Recommendations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cook, Kristin A.; Cramer, Nicholas O.; Israel, David

2015-12-07

Visual data analysis is composed of a collection of cognitive actions and tasks to decompose, internalize, and recombine data to produce knowledge and insight. Visual analytic tools provide interactive visual interfaces to data to support tasks involved in discovery and sensemaking, including forming hypotheses, asking questions, and evaluating and organizing evidence. Myriad analytic models can be incorporated into visual analytic systems, at the cost of increasing complexity in the analytic discourse between user and system. Techniques exist to increase the usability of interacting with such analytic models, such as inferring data models from user interactions to steer the underlying modelsmore » of the system via semantic interaction, shielding users from having to do so explicitly. Such approaches are often also referred to as mixed-initiative systems. Researchers studying the sensemaking process have called for development of tools that facilitate analytic sensemaking through a combination of human and automated activities. However, design guidelines do not exist for mixed-initiative visual analytic systems to support iterative sensemaking. In this paper, we present a candidate set of design guidelines and introduce the Active Data Environment (ADE) prototype, a spatial workspace supporting the analytic process via task recommendations invoked by inferences on user interactions within the workspace. ADE recommends data and relationships based on a task model, enabling users to co-reason with the system about their data in a single, spatial workspace. This paper provides an illustrative use case, a technical description of ADE, and a discussion of the strengths and limitations of the approach.« less

Technology to improve quality and accountability.

PubMed

Kay, Jonathan

2006-01-01

A body of evidence has been accumulated to demonstrate that current practice is not sufficiently safe for several stages of central laboratory testing. In particular, while analytical and perianalytical steps that take place within the laboratory are subjected to quality control procedures, this is not the case for several pre- and post-analytical steps. The ubiquitous application of auto-identification technology seems to represent a valuable tool for reducing error rates. A series of projects in Oxford has attempted to improve processes which support several areas of laboratory medicine, including point-of-care testing, blood transfusion, delivery and interpretation of reports, and support of decision-making by clinicians. The key tools are auto-identification, Internet communication technology, process re-engineering, and knowledge management.

Optimization of turning process through the analytic flank wear modelling

NASA Astrophysics Data System (ADS)

Del Prete, A.; Franchi, R.; De Lorenzis, D.

2018-05-01

In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

3D FEM Simulation of Flank Wear in Turning

NASA Astrophysics Data System (ADS)

Attanasio, Aldo; Ceretti, Elisabetta; Giardini, Claudio

2011-05-01

This work deals with tool wear simulation. Studying the influence of tool wear on tool life, tool substitution policy and influence on final part quality, surface integrity, cutting forces and power consumption it is important to reduce the global process costs. Adhesion, abrasion, erosion, diffusion, corrosion and fracture are some of the phenomena responsible of the tool wear depending on the selected cutting parameters: cutting velocity, feed rate, depth of cut, …. In some cases these wear mechanisms are described by analytical models as a function of process variables (temperature, pressure and sliding velocity along the cutting surface). These analytical models are suitable to be implemented in FEM codes and they can be utilized to simulate the tool wear. In the present paper a commercial 3D FEM software has been customized to simulate the tool wear during turning operations when cutting AISI 1045 carbon steel with uncoated tungsten carbide tip. The FEM software was improved by means of a suitable subroutine able to modify the tool geometry on the basis of the estimated tool wear as the simulation goes on. Since for the considered couple of tool-workpiece material the main phenomena generating wear are the abrasive and the diffusive ones, the tool wear model implemented into the subroutine was obtained as combination between the Usui's and the Takeyama and Murata's models. A comparison between experimental and simulated flank tool wear curves is reported demonstrating that it is possible to simulate the tool wear development.

Nonlinear Growth Curves in Developmental Research

ERIC Educational Resources Information Center

Grimm, Kevin J.; Ram, Nilam; Hamagami, Fumiaki

2011-01-01

Developmentalists are often interested in understanding change processes, and growth models are the most common analytic tool for examining such processes. Nonlinear growth curves are especially valuable to developmentalists because the defining characteristics of the growth process such as initial levels, rates of change during growth spurts, and…

A tool for selective inline quantification of co-eluting proteins in chromatography using spectral analysis and partial least squares regression.

PubMed

Brestrich, Nina; Briskot, Till; Osberghaus, Anna; Hubbuch, Jürgen

2014-07-01

Selective quantification of co-eluting proteins in chromatography is usually performed by offline analytics. This is time-consuming and can lead to late detection of irregularities in chromatography processes. To overcome this analytical bottleneck, a methodology for selective protein quantification in multicomponent mixtures by means of spectral data and partial least squares regression was presented in two previous studies. In this paper, a powerful integration of software and chromatography hardware will be introduced that enables the applicability of this methodology for a selective inline quantification of co-eluting proteins in chromatography. A specific setup consisting of a conventional liquid chromatography system, a diode array detector, and a software interface to Matlab® was developed. The established tool for selective inline quantification was successfully applied for a peak deconvolution of a co-eluting ternary protein mixture consisting of lysozyme, ribonuclease A, and cytochrome c on SP Sepharose FF. Compared to common offline analytics based on collected fractions, no loss of information regarding the retention volumes and peak flanks was observed. A comparison between the mass balances of both analytical methods showed, that the inline quantification tool can be applied for a rapid determination of pool yields. Finally, the achieved inline peak deconvolution was successfully applied to make product purity-based real-time pooling decisions. This makes the established tool for selective inline quantification a valuable approach for inline monitoring and control of chromatographic purification steps and just in time reaction on process irregularities. © 2014 Wiley Periodicals, Inc.

Swarm intelligence metaheuristics for enhanced data analysis and optimization.

PubMed

Hanrahan, Grady

2011-09-21

The swarm intelligence (SI) computing paradigm has proven itself as a comprehensive means of solving complicated analytical chemistry problems by emulating biologically-inspired processes. As global optimum search metaheuristics, associated algorithms have been widely used in training neural networks, function optimization, prediction and classification, and in a variety of process-based analytical applications. The goal of this review is to provide readers with critical insight into the utility of swarm intelligence tools as methods for solving complex chemical problems. Consideration will be given to algorithm development, ease of implementation and model performance, detailing subsequent influences on a number of application areas in the analytical, bioanalytical and detection sciences.

Explorative visual analytics on interval-based genomic data and their metadata.

PubMed

Jalili, Vahid; Matteucci, Matteo; Masseroli, Marco; Ceri, Stefano

2017-12-04

With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSE under GPLv3 open-source license.

The Rack-Gear Tool Generation Modelling. Non-Analytical Method Developed in CATIA, Using the Relative Generating Trajectories Method

NASA Astrophysics Data System (ADS)

Teodor, V. G.; Baroiu, N.; Susac, F.; Oancea, N.

2016-11-01

The modelling of a curl of surfaces associated with a pair of rolling centrodes, when it is known the profile of the rack-gear's teeth profile, by direct measuring, as a coordinate matrix, has as goal the determining of the generating quality for an imposed kinematics of the relative motion of tool regarding the blank. In this way, it is possible to determine the generating geometrical error, as a base of the total error. The generation modelling allows highlighting the potential errors of the generating tool, in order to correct its profile, previously to use the tool in machining process. A method developed in CATIA is proposed, based on a new method, namely the method of “relative generating trajectories”. They are presented the analytical foundation, as so as some application for knows models of rack-gear type tools used on Maag teething machines.

Mathematical support for automated geometry analysis of lathe machining of oblique peakless round-nose tools

NASA Astrophysics Data System (ADS)

Filippov, A. V.; Tarasov, S. Yu; Podgornyh, O. A.; Shamarin, N. N.; Filippova, E. O.

2017-01-01

Automatization of engineering processes requires developing relevant mathematical support and a computer software. Analysis of metal cutting kinematics and tool geometry is a necessary key task at the preproduction stage. This paper is focused on developing a procedure for determining the geometry of oblique peakless round-nose tool lathe machining with the use of vector/matrix transformations. Such an approach allows integration into modern mathematical software packages in distinction to the traditional analytic description. Such an advantage is very promising for developing automated control of the preproduction process. A kinematic criterion for the applicable tool geometry has been developed from the results of this study. The effect of tool blade inclination and curvature on the geometry-dependent process parameters was evaluated.

Perspectives on bioanalytical mass spectrometry and automation in drug discovery.

PubMed

Janiszewski, John S; Liston, Theodore E; Cole, Mark J

2008-11-01

The use of high speed synthesis technologies has resulted in a steady increase in the number of new chemical entities active in the drug discovery research stream. Large organizations can have thousands of chemical entities in various stages of testing and evaluation across numerous projects on a weekly basis. Qualitative and quantitative measurements made using LC/MS are integrated throughout this process from early stage lead generation through candidate nomination. Nearly all analytical processes and procedures in modern research organizations are automated to some degree. This includes both hardware and software automation. In this review we discuss bioanalytical mass spectrometry and automation as components of the analytical chemistry infrastructure in pharma. Analytical chemists are presented as members of distinct groups with similar skillsets that build automated systems, manage test compounds, assays and reagents, and deliver data to project teams. The ADME-screening process in drug discovery is used as a model to highlight the relationships between analytical tasks in drug discovery. Emerging software and process automation tools are described that can potentially address gaps and link analytical chemistry related tasks. The role of analytical chemists and groups in modern 'industrialized' drug discovery is also discussed.

Enabling Big Geoscience Data Analytics with a Cloud-Based, MapReduce-Enabled and Service-Oriented Workflow Framework

PubMed Central

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists. PMID:25742012

Enabling big geoscience data analytics with a cloud-based, MapReduce-enabled and service-oriented workflow framework.

PubMed

Li, Zhenlong; Yang, Chaowei; Jin, Baoxuan; Yu, Manzhu; Liu, Kai; Sun, Min; Zhan, Matthew

2015-01-01

Geoscience observations and model simulations are generating vast amounts of multi-dimensional data. Effectively analyzing these data are essential for geoscience studies. However, the tasks are challenging for geoscientists because processing the massive amount of data is both computing and data intensive in that data analytics requires complex procedures and multiple tools. To tackle these challenges, a scientific workflow framework is proposed for big geoscience data analytics. In this framework techniques are proposed by leveraging cloud computing, MapReduce, and Service Oriented Architecture (SOA). Specifically, HBase is adopted for storing and managing big geoscience data across distributed computers. MapReduce-based algorithm framework is developed to support parallel processing of geoscience data. And service-oriented workflow architecture is built for supporting on-demand complex data analytics in the cloud environment. A proof-of-concept prototype tests the performance of the framework. Results show that this innovative framework significantly improves the efficiency of big geoscience data analytics by reducing the data processing time as well as simplifying data analytical procedures for geoscientists.

Exhaled breath condensate – from an analytical point of view

PubMed Central

Dodig, Slavica; Čepelak, Ivana

2013-01-01

Over the past three decades, the goal of many researchers is analysis of exhaled breath condensate (EBC) as noninvasively obtained sample. A total quality in laboratory diagnostic processes in EBC analysis was investigated: pre-analytical (formation, collection, storage of EBC), analytical (sensitivity of applied methods, standardization) and post-analytical (interpretation of results) phases. EBC analysis is still used as a research tool. Limitations referred to pre-analytical, analytical, and post-analytical phases of EBC analysis are numerous, e.g. low concentrations of EBC constituents, single-analyte methods lack in sensitivity, and multi-analyte has not been fully explored, and reference values are not established. When all, pre-analytical, analytical and post-analytical requirements are met, EBC biomarkers as well as biomarker patterns can be selected and EBC analysis can hopefully be used in clinical practice, in both, the diagnosis and in the longitudinal follow-up of patients, resulting in better outcome of disease. PMID:24266297

A note on a simplified and general approach to simulating from multivariate copula functions

Treesearch

Barry K. Goodwin

2013-01-01

Copulas have become an important analytic tool for characterizing multivariate distributions and dependence. One is often interested in simulating data from copula estimates. The process can be analytically and computationally complex and usually involves steps that are unique to a given parametric copula. We describe an alternative approach that uses ‘Probability-...

PipeCraft: Flexible open-source toolkit for bioinformatics analysis of custom high-throughput amplicon sequencing data.

PubMed

Anslan, Sten; Bahram, Mohammad; Hiiesalu, Indrek; Tedersoo, Leho

2017-11-01

High-throughput sequencing methods have become a routine analysis tool in environmental sciences as well as in public and private sector. These methods provide vast amount of data, which need to be analysed in several steps. Although the bioinformatics may be applied using several public tools, many analytical pipelines allow too few options for the optimal analysis for more complicated or customized designs. Here, we introduce PipeCraft, a flexible and handy bioinformatics pipeline with a user-friendly graphical interface that links several public tools for analysing amplicon sequencing data. Users are able to customize the pipeline by selecting the most suitable tools and options to process raw sequences from Illumina, Pacific Biosciences, Ion Torrent and Roche 454 sequencing platforms. We described the design and options of PipeCraft and evaluated its performance by analysing the data sets from three different sequencing platforms. We demonstrated that PipeCraft is able to process large data sets within 24 hr. The graphical user interface and the automated links between various bioinformatics tools enable easy customization of the workflow. All analytical steps and options are recorded in log files and are easily traceable. © 2017 John Wiley & Sons Ltd.

A tool for exploring the dynamics of innovative interventions for public health: the critical event card.

PubMed

Figueiro, Ana Claudia; de Araújo Oliveira, Sydia Rosana; Hartz, Zulmira; Couturier, Yves; Bernier, Jocelyne; do Socorro Machado Freire, Maria; Samico, Isabella; Medina, Maria Guadalupe; de Sa, Ronice Franco; Potvin, Louise

2017-03-01

Public health interventions are increasingly represented as complex systems. Research tools for capturing the dynamic of interventions processes, however, are practically non-existent. This paper describes the development and proof of concept process of an analytical tool, the critical event card (CEC), which supports the representation and analysis of complex interventions' evolution, based on critical events. Drawing on the actor-network theory (ANT), we developed and field-tested the tool using three innovative health interventions in northeastern Brazil. Interventions were aimed to promote health equity through intersectoral approaches; were engaged in participatory evaluation and linked to professional training programs. The CEC developing involve practitioners and researchers from projects. Proof of concept was based on document analysis, face-to-face interviews and focus groups. Analytical categories from CEC allow identifying and describing critical events as milestones in the evolution of complex interventions. Categories are (1) event description; (2) actants (human and non-human) involved; (3) interactions between actants; (4) mediations performed; (5) actions performed; (6) inscriptions produced; and (7) consequences for interventions. The CEC provides a tool to analyze and represent intersectoral internvetions' complex and dynamic evolution.

Using 3D Printing for Rapid Prototyping of Characterization Tools for Investigating Powder Blend Behavior.

PubMed

Hirschberg, Cosima; Boetker, Johan P; Rantanen, Jukka; Pein-Hackelbusch, Miriam

2018-02-01

There is an increasing need to provide more detailed insight into the behavior of particulate systems. The current powder characterization tools are developed empirically and in many cases, modification of existing equipment is difficult. More flexible tools are needed to provide understanding of complex powder behavior, such as mixing process and segregation phenomenon. An approach based on the fast prototyping of new powder handling geometries and interfacing solutions for process analytical tools is reported. This study utilized 3D printing for rapid prototyping of customized geometries; overall goal was to assess mixing process of powder blends at small-scale with a combination of spectroscopic and mechanical monitoring. As part of the segregation evaluation studies, the flowability of three different paracetamol/filler-blends at different ratios was investigated, inter alia to define the percolation thresholds. Blends with a paracetamol wt% above the percolation threshold were subsequently investigated in relation to their segregation behavior. Rapid prototyping using 3D printing allowed designing two funnels with tailored flow behavior (funnel flow) of model formulations, which could be monitored with an in-line near-infrared (NIR) spectrometer. Calculating the root mean square (RMS) of the scores of the two first principal components of the NIR spectra visualized spectral variation as a function of process time. In a same setup, mechanical properties (basic flow energy) of the powder blend were monitored during blending. Rapid prototyping allowed for fast modification of powder testing geometries and easy interfacing with process analytical tools, opening new possibilities for more detailed powder characterization.

VisualUrText: A Text Analytics Tool for Unstructured Textual Data

NASA Astrophysics Data System (ADS)

Zainol, Zuraini; Jaymes, Mohd T. H.; Nohuddin, Puteri N. E.

2018-05-01

The growing amount of unstructured text over Internet is tremendous. Text repositories come from Web 2.0, business intelligence and social networking applications. It is also believed that 80-90% of future growth data is available in the form of unstructured text databases that may potentially contain interesting patterns and trends. Text Mining is well known technique for discovering interesting patterns and trends which are non-trivial knowledge from massive unstructured text data. Text Mining covers multidisciplinary fields involving information retrieval (IR), text analysis, natural language processing (NLP), data mining, machine learning statistics and computational linguistics. This paper discusses the development of text analytics tool that is proficient in extracting, processing, analyzing the unstructured text data and visualizing cleaned text data into multiple forms such as Document Term Matrix (DTM), Frequency Graph, Network Analysis Graph, Word Cloud and Dendogram. This tool, VisualUrText, is developed to assist students and researchers for extracting interesting patterns and trends in document analyses.

Feature Geo Analytics and Big Data Processing: Hybrid Approaches for Earth Science and Real-Time Decision Support

NASA Astrophysics Data System (ADS)

Wright, D. J.; Raad, M.; Hoel, E.; Park, M.; Mollenkopf, A.; Trujillo, R.

2016-12-01

Introduced is a new approach for processing spatiotemporal big data by leveraging distributed analytics and storage. A suite of temporally-aware analysis tools summarizes data nearby or within variable windows, aggregates points (e.g., for various sensor observations or vessel positions), reconstructs time-enabled points into tracks (e.g., for mapping and visualizing storm tracks), joins features (e.g., to find associations between features based on attributes, spatial relationships, temporal relationships or all three simultaneously), calculates point densities, finds hot spots (e.g., in species distributions), and creates space-time slices and cubes (e.g., in microweather applications with temperature, humidity, and pressure, or within human mobility studies). These "feature geo analytics" tools run in both batch and streaming spatial analysis mode as distributed computations across a cluster of servers on typical "big" data sets, where static data exist in traditional geospatial formats (e.g., shapefile) locally on a disk or file share, attached as static spatiotemporal big data stores, or streamed in near-real-time. In other words, the approach registers large datasets or data stores with ArcGIS Server, then distributes analysis across a cluster of machines for parallel processing. Several brief use cases will be highlighted based on a 16-node server cluster at 14 Gb RAM per node, allowing, for example, the buffering of over 8 million points or thousands of polygons in 1 minute. The approach is "hybrid" in that ArcGIS Server integrates open-source big data frameworks such as Apache Hadoop and Apache Spark on the cluster in order to run the analytics. In addition, the user may devise and connect custom open-source interfaces and tools developed in Python or Python Notebooks; the common denominator being the familiar REST API.

The Earth Data Analytic Services (EDAS) Framework

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

Computational overlay metrology with adaptive data analytics

NASA Astrophysics Data System (ADS)

Schmitt-Weaver, Emil; Subramony, Venky; Ullah, Zakir; Matsunobu, Masazumi; Somasundaram, Ravin; Thomas, Joel; Zhang, Linmiao; Thul, Klaus; Bhattacharyya, Kaustuve; Goossens, Ronald; Lambregts, Cees; Tel, Wim; de Ruiter, Chris

2017-03-01

With photolithography as the fundamental patterning step in the modern nanofabrication process, every wafer within a semiconductor fab will pass through a lithographic apparatus multiple times. With more than 20,000 sensors producing more than 700GB of data per day across multiple subsystems, the combination of a light source and lithographic apparatus provide a massive amount of information for data analytics. This paper outlines how data analysis tools and techniques that extend insight into data that traditionally had been considered unmanageably large, known as adaptive analytics, can be used to show how data collected before the wafer is exposed can be used to detect small process dependent wafer-towafer changes in overlay.

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments

PubMed Central

Koch, Stefan; Bueschl, Christoph; Doppler, Maria; Simader, Alexandra; Meng-Reiterer, Jacqueline; Lemmens, Marc; Schuhmacher, Rainer

2016-01-01

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio (m/z) values and retention times) that serves as a reference, the tool recognizes both m/z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m/z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley. PMID:27827849

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments.

PubMed

Koch, Stefan; Bueschl, Christoph; Doppler, Maria; Simader, Alexandra; Meng-Reiterer, Jacqueline; Lemmens, Marc; Schuhmacher, Rainer

2016-11-02

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio ( m / z ) values and retention times) that serves as a reference, the tool recognizes both m / z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m / z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley.

Contamination-Free Manufacturing: Tool Component Qualification, Verification and Correlation with Wafers

NASA Astrophysics Data System (ADS)

Tan, Samantha H.; Chen, Ning; Liu, Shi; Wang, Kefei

2003-09-01

As part of the semiconductor industry "contamination-free manufacturing" effort, significant emphasis has been placed on reducing potential sources of contamination from process equipment and process equipment components. Process tools contain process chambers and components that are exposed to the process environment or process chemistry and in some cases are in direct contact with production wafers. Any contamination from these sources must be controlled or eliminated in order to maintain high process yields, device performance, and device reliability. This paper discusses new nondestructive analytical methods for quantitative measurement of the cleanliness of metal, quartz, polysilicon and ceramic components that are used in process equipment tools. The goal of these new procedures is to measure the effectiveness of cleaning procedures and to verify whether a tool component part is sufficiently clean for installation and subsequent routine use in the manufacturing line. These procedures provide a reliable "qualification method" for tool component certification and also provide a routine quality control method for reliable operation of cleaning facilities. Cost advantages to wafer manufacturing include higher yields due to improved process cleanliness and elimination of yield loss and downtime resulting from the installation of "bad" components in process tools. We also discuss a representative example of wafer contamination having been linked to a specific process tool component.

Raman spectroscopy as a process analytical technology for pharmaceutical manufacturing and bioprocessing.

PubMed

Esmonde-White, Karen A; Cuellar, Maryann; Uerpmann, Carsten; Lenain, Bruno; Lewis, Ian R

2017-01-01

Adoption of Quality by Design (QbD) principles, regulatory support of QbD, process analytical technology (PAT), and continuous manufacturing are major factors effecting new approaches to pharmaceutical manufacturing and bioprocessing. In this review, we highlight new technology developments, data analysis models, and applications of Raman spectroscopy, which have expanded the scope of Raman spectroscopy as a process analytical technology. Emerging technologies such as transmission and enhanced reflection Raman, and new approaches to using available technologies, expand the scope of Raman spectroscopy in pharmaceutical manufacturing, and now Raman spectroscopy is successfully integrated into real-time release testing, continuous manufacturing, and statistical process control. Since the last major review of Raman as a pharmaceutical PAT in 2010, many new Raman applications in bioprocessing have emerged. Exciting reports of in situ Raman spectroscopy in bioprocesses complement a growing scientific field of biological and biomedical Raman spectroscopy. Raman spectroscopy has made a positive impact as a process analytical and control tool for pharmaceutical manufacturing and bioprocessing, with demonstrated scientific and financial benefits throughout a product's lifecycle.

Species authentication and geographical origin discrimination of herbal medicines by near infrared spectroscopy: A review.

PubMed

Wang, Pei; Yu, Zhiguo

2015-10-01

Near infrared (NIR) spectroscopy as a rapid and nondestructive analytical technique, integrated with chemometrics, is a powerful process analytical tool for the pharmaceutical industry and is becoming an attractive complementary technique for herbal medicine analysis. This review mainly focuses on the recent applications of NIR spectroscopy in species authentication of herbal medicines and their geographical origin discrimination.

Big data analytics in immunology: a knowledge-based approach.

PubMed

Zhang, Guang Lan; Sun, Jing; Chitkushev, Lou; Brusic, Vladimir

2014-01-01

With the vast amount of immunological data available, immunology research is entering the big data era. These data vary in granularity, quality, and complexity and are stored in various formats, including publications, technical reports, and databases. The challenge is to make the transition from data to actionable knowledge and wisdom and bridge the knowledge gap and application gap. We report a knowledge-based approach based on a framework called KB-builder that facilitates data mining by enabling fast development and deployment of web-accessible immunological data knowledge warehouses. Immunological knowledge discovery relies heavily on both the availability of accurate, up-to-date, and well-organized data and the proper analytics tools. We propose the use of knowledge-based approaches by developing knowledgebases combining well-annotated data with specialized analytical tools and integrating them into analytical workflow. A set of well-defined workflow types with rich summarization and visualization capacity facilitates the transformation from data to critical information and knowledge. By using KB-builder, we enabled streamlining of normally time-consuming processes of database development. The knowledgebases built using KB-builder will speed up rational vaccine design by providing accurate and well-annotated data coupled with tailored computational analysis tools and workflow.

THREAT ANTICIPATION AND DECEPTIVE REASONING USING BAYESIAN BELIEF NETWORKS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allgood, Glenn O; Olama, Mohammed M; Lake, Joe E

Recent events highlight the need for tools to anticipate threats posed by terrorists. Assessing these threats requires combining information from disparate data sources such as analytic models, simulations, historical data, sensor networks, and user judgments. These disparate data can be combined in a coherent, analytically defensible, and understandable manner using a Bayesian belief network (BBN). In this paper, we develop a BBN threat anticipatory model based on a deceptive reasoning algorithm using a network engineering process that treats the probability distributions of the BBN nodes within the broader context of the system development process.

Knowledge management in a waste based biorefinery in the QbD paradigm.

PubMed

Rathore, Anurag S; Chopda, Viki R; Gomes, James

2016-09-01

Shifting resource base from fossil feedstock to renewable raw materials for production of chemical products has opened up an area of novel applications of industrial biotechnology-based process tools. This review aims to provide a concise and focused discussion on recent advances in knowledge management to facilitate efficient and optimal operation of a biorefinery. Application of quality by design (QbD) and process analytical technology (PAT) as tools for knowledge creation and management at different levels has been highlighted. Role of process integration, government policies, knowledge exchange through collaboration, and use of databases and computational tools have also been touched upon. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analytical and Experimental Investigation of Process Loads on Incremental Severe Plastic Deformation

NASA Astrophysics Data System (ADS)

Okan Görtan, Mehmet

2017-05-01

From the processing point of view, friction is a major problem in the severe plastic deformation (SPD) using equal channel angular pressing (ECAP) process. Incremental ECAP can be used in order to optimize frictional effects during SPD. A new incremental ECAP has been proposed recently. This new process called as equal channel angular swaging (ECAS) combines the conventional ECAP and the incremental bulk metal forming method rotary swaging. ECAS tool system consists of two dies with an angled channel that contains two shear zones. During ECAS process, two forming tool halves, which are concentrically arranged around the workpiece, perform high frequency radial movements with short strokes, while samples are pushed through these. The oscillation direction nearly coincides with the shearing direction in the workpiece. The most important advantages in comparison to conventional ECAP are a significant reduction in the forces in material feeding direction plus the potential to be extended to continuous processing. In the current study, the mechanics of the ECAS process is investigated using slip line field approach. An analytical model is developed to predict process loads. The proposed model is validated using experiments and FE simulations.

A new tool for the evaluation of the analytical procedure: Green Analytical Procedure Index.

PubMed

Płotka-Wasylka, J

2018-05-01

A new means for assessing analytical protocols relating to green analytical chemistry attributes has been developed. The new tool, called GAPI (Green Analytical Procedure Index), evaluates the green character of an entire analytical methodology, from sample collection to final determination, and was created using such tools as the National Environmental Methods Index (NEMI) or Analytical Eco-Scale to provide not only general but also qualitative information. In GAPI, a specific symbol with five pentagrams can be used to evaluate and quantify the environmental impact involved in each step of an analytical methodology, mainly from green through yellow to red depicting low, medium to high impact, respectively. The proposed tool was used to evaluate analytical procedures applied in the determination of biogenic amines in wine samples, and polycyclic aromatic hydrocarbon determination by EPA methods. GAPI tool not only provides an immediately perceptible perspective to the user/reader but also offers exhaustive information on evaluated procedures. Copyright © 2018 Elsevier B.V. All rights reserved.

Recognising Health Care Assistants' Prior Learning through a Caring Ideology

ERIC Educational Resources Information Center

Sandberg, Fredrik

2010-01-01

This article critically appraises a process of recognising prior learning (RPL) using analytical tools from Habermas' theory of communicative action. The RPL process is part of an in-service training program for health care assistants where the goal is to become a licensed practical nurse. Data about the RPL process were collected using interviews…

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Data to decisions.

PubMed

White, B J; Amrine, D E; Larson, R L

2018-04-14

Big data are frequently used in many facets of business and agronomy to enhance knowledge needed to improve operational decisions. Livestock operations collect data of sufficient quantity to perform predictive analytics. Predictive analytics can be defined as a methodology and suite of data evaluation techniques to generate a prediction for specific target outcomes. The objective of this manuscript is to describe the process of using big data and the predictive analytic framework to create tools to drive decisions in livestock production, health, and welfare. The predictive analytic process involves selecting a target variable, managing the data, partitioning the data, then creating algorithms, refining algorithms, and finally comparing accuracy of the created classifiers. The partitioning of the datasets allows model building and refining to occur prior to testing the predictive accuracy of the model with naive data to evaluate overall accuracy. Many different classification algorithms are available for predictive use and testing multiple algorithms can lead to optimal results. Application of a systematic process for predictive analytics using data that is currently collected or that could be collected on livestock operations will facilitate precision animal management through enhanced livestock operational decisions.

A national analytical quality assurance program: Developing guidelines and analytical tools for the forest inventory and analysis program

Treesearch

Phyllis C. Adams; Glenn A. Christensen

2012-01-01

A rigorous quality assurance (QA) process assures that the data and information provided by the Forest Inventory and Analysis (FIA) program meet the highest possible standards of precision, completeness, representativeness, comparability, and accuracy. FIA relies on its analysts to check the final data quality prior to release of a State’s data to the national FIA...

Process Analytical Technology for High Shear Wet Granulation: Wet Mass Consistency Reported by In-Line Drag Flow Force Sensor Is Consistent With Powder Rheology Measured by At-Line FT4 Powder Rheometer.

PubMed

Narang, Ajit S; Sheverev, Valery; Freeman, Tim; Both, Douglas; Stepaniuk, Vadim; Delancy, Michael; Millington-Smith, Doug; Macias, Kevin; Subramanian, Ganeshkumar

2016-01-01

Drag flow force (DFF) sensor that measures the force exerted by wet mass in a granulator on a thin cylindrical probe was shown as a promising process analytical technology for real-time in-line high-resolution monitoring of wet mass consistency during high shear wet granulation. Our previous studies indicated that this process analytical technology tool could be correlated to granulation end point established independently through drug product critical quality attributes. In this study, the measurements of flow force by a DFF sensor, taken during wet granulation of 3 placebo formulations with different binder content, are compared with concurrent at line FT4 Powder Rheometer characterization of wet granules collected at different time points of the processing. The wet mass consistency measured by the DFF sensor correlated well with the granulation's resistance to flow and interparticulate interactions as measured by FT4 Powder Rheometer. This indicated that the force pulse magnitude measured by the DFF sensor was indicative of fundamental material properties (e.g., shear viscosity and granule size/density), as they were changing during the granulation process. These studies indicate that DFF sensor can be a valuable tool for wet granulation formulation and process development and scale up, as well as for routine monitoring and control during manufacturing. Copyright © 2016. Published by Elsevier Inc.

Examining the Impact of Culture and Human Elements on OLAP Tools Usefulness

ERIC Educational Resources Information Center

Sharoupim, Magdy S.

2010-01-01

The purpose of the present study was to examine the impact of culture and human-related elements on the On-line Analytical Processing (OLAP) usability in generating decision-making information. The use of OLAP technology has evolved rapidly and gained momentum, mainly due to the ability of OLAP tools to examine and query large amounts of data sets…

Information for Institutional Renewal.

ERIC Educational Resources Information Center

Spencer, Richard L.

1979-01-01

Discusses a planning, management, and evaluation system, an objective-based planning process, research databases, analytical reports, and transactional data as state-of-the-art tools available to generate data which link research directly to planning for institutional renewal. (RC)

Using Fuzzy Analytic Hierarchy Process multicriteria and Geographical information system for coastal vulnerability analysis in Morocco: The case of Mohammedia

NASA Astrophysics Data System (ADS)

Tahri, Meryem; Maanan, Mohamed; Hakdaoui, Mustapha

2016-04-01

This paper shows a method to assess the vulnerability of coastal risks such as coastal erosion or submarine applying Fuzzy Analytic Hierarchy Process (FAHP) and spatial analysis techniques with Geographic Information System (GIS). The coast of the Mohammedia located in Morocco was chosen as the study site to implement and validate the proposed framework by applying a GIS-FAHP based methodology. The coastal risk vulnerability mapping follows multi-parametric causative factors as sea level rise, significant wave height, tidal range, coastal erosion, elevation, geomorphology and distance to an urban area. The Fuzzy Analytic Hierarchy Process methodology enables the calculation of corresponding criteria weights. The result shows that the coastline of the Mohammedia is characterized by a moderate, high and very high level of vulnerability to coastal risk. The high vulnerability areas are situated in the east at Monika and Sablette beaches. This technical approach is based on the efficiency of the Geographic Information System tool based on Fuzzy Analytical Hierarchy Process to help decision maker to find optimal strategies to minimize coastal risks.

Search Analytics: Automated Learning, Analysis, and Search with Open Source

NASA Astrophysics Data System (ADS)

Hundman, K.; Mattmann, C. A.; Hyon, J.; Ramirez, P.

2016-12-01

The sheer volume of unstructured scientific data makes comprehensive human analysis impossible, resulting in missed opportunities to identify relationships, trends, gaps, and outliers. As the open source community continues to grow, tools like Apache Tika, Apache Solr, Stanford's DeepDive, and Data-Driven Documents (D3) can help address this challenge. With a focus on journal publications and conference abstracts often in the form of PDF and Microsoft Office documents, we've initiated an exploratory NASA Advanced Concepts project aiming to use the aforementioned open source text analytics tools to build a data-driven justification for the HyspIRI Decadal Survey mission. We call this capability Search Analytics, and it fuses and augments these open source tools to enable the automatic discovery and extraction of salient information. In the case of HyspIRI, a hyperspectral infrared imager mission, key findings resulted from the extractions and visualizations of relationships from thousands of unstructured scientific documents. The relationships include links between satellites (e.g. Landsat 8), domain-specific measurements (e.g. spectral coverage) and subjects (e.g. invasive species). Using the above open source tools, Search Analytics mined and characterized a corpus of information that would be infeasible for a human to process. More broadly, Search Analytics offers insights into various scientific and commercial applications enabled through missions and instrumentation with specific technical capabilities. For example, the following phrases were extracted in close proximity within a publication: "In this study, hyperspectral images…with high spatial resolution (1 m) were analyzed to detect cutleaf teasel in two areas. …Classification of cutleaf teasel reached a users accuracy of 82 to 84%." Without reading a single paper we can use Search Analytics to automatically identify that a 1 m spatial resolution provides a cutleaf teasel detection users accuracy of 82-84%, which could have tangible, direct downstream implications for crop protection. Automatically assimilating this information expedites and supplements human analysis, and, ultimately, Search Analytics and its foundation of open source tools will result in more efficient scientific investment and research.

The Climate Data Analytic Services (CDAS) Framework.

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2016-12-01

Faced with unprecedented growth in climate data volume and demand, NASA has developed the Climate Data Analytic Services (CDAS) framework. This framework enables scientists to execute data processing workflows combining common analysis operations in a high performance environment close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted climate data analysis tools (ESMF, CDAT, NCO, etc.). A dynamic caching architecture enables interactive response times. CDAS utilizes Apache Spark for parallelization and a custom array framework for processing huge datasets within limited memory spaces. CDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using either direct web service calls, a python script, a unix-like shell client, or a javascript-based web application. Client packages in python, scala, or javascript contain everything needed to make CDAS requests. The CDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service permits decision makers to investigate climate changes around the globe, inspect model trends and variability, and compare multiple reanalysis datasets.

Real-time imaging as an emerging process analytical technology tool for monitoring of fluid bed coating process.

PubMed

Naidu, Venkata Ramana; Deshpande, Rucha S; Syed, Moinuddin R; Wakte, Pravin S

2018-07-01

A direct imaging system (Eyecon TM ) was used as a Process Analytical Technology (PAT) tool to monitor fluid bed coating process. Eyecon TM generated real-time onscreen images, particle size and shape information of two identically manufactured laboratory-scale batches. Eyecon TM has accuracy of measuring the particle size increase of ±1 μm on particles in the size range of 50-3000 μm. Eyecon TM captured data every 2 s during the entire process. The moving average of D90 particle size values recorded by Eyecon TM were calculated for every 30 min to calculate the radial coating thickness of coated particles. After the completion of coating process, the radial coating thickness was found to be 11.3 and 9.11 μm, with a standard deviation of ±0.68 and 1.8 μm for Batch 1 and Batch 2, respectively. The coating thickness was also correlated with percent weight build-up by gel permeation chromatography (GPC) and dissolution. GPC indicated weight build-up of 10.6% and 9.27% for Batch 1 and Batch 2, respectively. In conclusion, weight build-up of 10% can also be correlated with 10 ± 2 μm increase in the coating thickness of pellets, indicating the potential applicability of real-time imaging as an endpoint determination tool for fluid bed coating process.

OPTHYLIC: An Optimised Tool for Hybrid Limits Computation

NASA Astrophysics Data System (ADS)

Busato, Emmanuel; Calvet, David; Theveneaux-Pelzer, Timothée

2018-05-01

A software tool, computing observed and expected upper limits on Poissonian process rates using a hybrid frequentist-Bayesian CLs method, is presented. This tool can be used for simple counting experiments where only signal, background and observed yields are provided or for multi-bin experiments where binned distributions of discriminating variables are provided. It allows the combination of several channels and takes into account statistical and systematic uncertainties, as well as correlations of systematic uncertainties between channels. It has been validated against other software tools and analytical calculations, for several realistic cases.

hydropower biological evaluation tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

This software is a set of analytical tools to evaluate the physical and biological performance of existing, refurbished, or newly installed conventional hydro-turbines nationwide where fish passage is a regulatory concern. The current version is based on information collected by the Sensor Fish. Future version will include other technologies. The tool set includes data acquisition, data processing, and biological response tools with applications to various turbine designs and other passage alternatives. The associated database is centralized, and can be accessed remotely. We have demonstrated its use for various applications including both turbines and spillways

Thermodynamics of Gas Turbine Cycles with Analytic Derivatives in OpenMDAO

NASA Technical Reports Server (NTRS)

Gray, Justin; Chin, Jeffrey; Hearn, Tristan; Hendricks, Eric; Lavelle, Thomas; Martins, Joaquim R. R. A.

2016-01-01

A new equilibrium thermodynamics analysis tool was built based on the CEA method using the OpenMDAO framework. The new tool provides forward and adjoint analytic derivatives for use with gradient based optimization algorithms. The new tool was validated against the original CEA code to ensure an accurate analysis and the analytic derivatives were validated against finite-difference approximations. Performance comparisons between analytic and finite difference methods showed a significant speed advantage for the analytic methods. To further test the new analysis tool, a sample optimization was performed to find the optimal air-fuel equivalence ratio, , maximizing combustion temperature for a range of different pressures. Collectively, the results demonstrate the viability of the new tool to serve as the thermodynamic backbone for future work on a full propulsion modeling tool.

On the analysis of the double Hopf bifurcation in machining processes via centre manifold reduction

NASA Astrophysics Data System (ADS)

Molnar, T. G.; Dombovari, Z.; Insperger, T.; Stepan, G.

2017-11-01

The single-degree-of-freedom model of orthogonal cutting is investigated to study machine tool vibrations in the vicinity of a double Hopf bifurcation point. Centre manifold reduction and normal form calculations are performed to investigate the long-term dynamics of the cutting process. The normal form of the four-dimensional centre subsystem is derived analytically, and the possible topologies in the infinite-dimensional phase space of the system are revealed. It is shown that bistable parameter regions exist where unstable periodic and, in certain cases, unstable quasi-periodic motions coexist with the equilibrium. Taking into account the non-smoothness caused by loss of contact between the tool and the workpiece, the boundary of the bistable region is also derived analytically. The results are verified by numerical continuation. The possibility of (transient) chaotic motions in the global non-smooth dynamics is shown.

Platform for Automated Real-Time High Performance Analytics on Medical Image Data.

PubMed

Allen, William J; Gabr, Refaat E; Tefera, Getaneh B; Pednekar, Amol S; Vaughn, Matthew W; Narayana, Ponnada A

2018-03-01

Biomedical data are quickly growing in volume and in variety, providing clinicians an opportunity for better clinical decision support. Here, we demonstrate a robust platform that uses software automation and high performance computing (HPC) resources to achieve real-time analytics of clinical data, specifically magnetic resonance imaging (MRI) data. We used the Agave application programming interface to facilitate communication, data transfer, and job control between an MRI scanner and an off-site HPC resource. In this use case, Agave executed the graphical pipeline tool GRAphical Pipeline Environment (GRAPE) to perform automated, real-time, quantitative analysis of MRI scans. Same-session image processing will open the door for adaptive scanning and real-time quality control, potentially accelerating the discovery of pathologies and minimizing patient callbacks. We envision this platform can be adapted to other medical instruments, HPC resources, and analytics tools.

Individual human cell responses to low doses of chemicals studied by synchrotron infrared spectromicroscopy

NASA Astrophysics Data System (ADS)

Holman, Hoi-Ying N.; Goth-Goldstein, Regine; Blakely, Elanor A.; Bjornstad, Kathy; Martin, Michael C.; McKinney, Wayne R.

2000-05-01

Vibrational spectroscopy, when combined with synchrotron radiation-based (SR) microscopy, is a powerful new analytical tool with high spatial resolution for detecting biochemical changes in the individual living cells. In contrast to other microscopy methods that require fixing, drying, staining or labeling, SR-FTIR microscopy probes intact living cells providing a composite view of all of the molecular response and the ability to monitor the response over time in the same cell. Observed spectral changes include all types of lesions induced in that cell as well as cellular responses to external and internal stresses. These spectral changes combined with other analytical tools may provide a fundamental understanding of the key molecular mechanisms induced in response to stresses created by low- doses of chemicals. In this study we used the high spatial - resolution SR-FTIR vibrational spectromicroscopy as a sensitive analytical tool to detect chemical- and radiation- induced changes in individual human cells. Our preliminary spectral measurements indicate that this technique is sensitive enough to detect changes in nucleic acids and proteins of cells treated with environmentally relevant concentrations of dioxin. This technique has the potential to distinguish changes from exogenous or endogenous oxidative processes. Future development of this technique will allow rapid monitoring of cellular processes such as drug metabolism, early detection of disease, bio- compatibility of implant materials, cellular repair mechanisms, self assembly of cellular apparatus, cell differentiation and fetal development.

Investigating Analytic Tools for e-Book Design in Early Literacy Learning

ERIC Educational Resources Information Center

Roskos, Kathleen; Brueck, Jeremy; Widman, Sarah

2009-01-01

Toward the goal of better e-book design to support early literacy learning, this study investigates analytic tools for examining design qualities of e-books for young children. Three research-based analytic tools related to e-book design were applied to a mixed genre collection of 50 e-books from popular online sites. Tool performance varied…

Investigation of wear phenomena by microscopy

NASA Technical Reports Server (NTRS)

Buckley, D. H.

1982-01-01

The various wear mechanisms involved in the loss of material from metallic and nonmetallic surfaces are discussed. The results presented indicate how various microscopy techniques used in conjunction with other analytical tools can assist in the elucidation of a wear mechanism. Without question, microscopy is the single most important tool for the study of the wear of surfaces, to assess and address inherent mechanisms of the material removal process.

Relationships between models used to analyze fire and fuel management alternatives

Treesearch

Nicholas L. Crookston; Werner A. Kurz; Sarah J. Beukema; Elizabeth D. Reinhardt

2000-01-01

Needs for analytical tools, the roles existing tools play, the processes they represent, and how they might interact are elements of key findings generated during a workshop held in Seattle February 17-18, 1999. The workshop was attended by 26 Joint Fire Science Program (JFSP) stakeholders and researchers. A focus of the workshop was the Fire and Fuels Extension to the...

Analytic hierarchy process (AHP) as a tool in asset allocation

NASA Astrophysics Data System (ADS)

Zainol Abidin, Siti Nazifah; Mohd Jaffar, Maheran

2013-04-01

Allocation capital investment into different assets is the best way to balance the risk and reward. This can prevent from losing big amount of money. Thus, the aim of this paper is to help investors in making wise investment decision in asset allocation. This paper proposes modifying and adapting Analytic Hierarchy Process (AHP) model. The AHP model is widely used in various fields of study that are related in decision making. The results of the case studies show that the proposed model can categorize stocks and determine the portion of capital investment. Hence, it can assist investors in decision making process and reduce the risk of loss in stock market investment.

In-Line Detection and Measurement of Molecular Contamination in Semiconductor Process Solutions

NASA Astrophysics Data System (ADS)

Wang, Jason; West, Michael; Han, Ye; McDonald, Robert C.; Yang, Wenjing; Ormond, Bob; Saini, Harmesh

2005-09-01

This paper discusses a fully automated metrology tool for detection and quantitative measurement of contamination, including cationic, anionic, metallic, organic, and molecular species present in semiconductor process solutions. The instrument is based on an electrospray ionization time-of-flight mass spectrometer (ESI-TOF/MS) platform. The tool can be used in diagnostic or analytical modes to understand process problems in addition to enabling routine metrology functions. Metrology functions include in-line contamination measurement with near real-time trend analysis. This paper discusses representative organic and molecular contamination measurement results in production process problem solving efforts. The examples include the analysis and identification of organic compounds in SC-1 pre-gate clean solution; urea, NMP (N-Methyl-2-pyrrolidone) and phosphoric acid contamination in UPW; and plasticizer and an organic sulfur-containing compound found in isopropyl alcohol (IPA). It is expected that these unique analytical and metrology capabilities will improve the understanding of the effect of organic and molecular contamination on device performance and yield. This will permit the development of quantitative correlations between contamination levels and process degradation. It is also expected that the ability to perform routine process chemistry metrology will lead to corresponding improvements in manufacturing process control and yield, the ability to avoid excursions and will improve the overall cost effectiveness of the semiconductor manufacturing process.

Process Improvement Through Tool Integration in Aero-Mechanical Design

NASA Technical Reports Server (NTRS)

Briggs, Clark

2010-01-01

Emerging capabilities in commercial design tools promise to significantly improve the multi-disciplinary and inter-disciplinary design and analysis coverage for aerospace mechanical engineers. This paper explores the analysis process for two example problems of a wing and flap mechanical drive system and an aircraft landing gear door panel. The examples begin with the design solid models and include various analysis disciplines such as structural stress and aerodynamic loads. Analytical methods include CFD, multi-body dynamics with flexible bodies and structural analysis. Elements of analysis data management, data visualization and collaboration are also included.

Model and Analytic Processes for Export License Assessments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, Sandra E.; Whitney, Paul D.; Weimar, Mark R.

2011-09-29

This paper represents the Department of Energy Office of Nonproliferation Research and Development (NA-22) Simulations, Algorithms and Modeling (SAM) Program's first effort to identify and frame analytical methods and tools to aid export control professionals in effectively predicting proliferation intent; a complex, multi-step and multi-agency process. The report focuses on analytical modeling methodologies that alone, or combined, may improve the proliferation export control license approval process. It is a follow-up to an earlier paper describing information sources and environments related to international nuclear technology transfer. This report describes the decision criteria used to evaluate modeling techniques and tools to determinemore » which approaches will be investigated during the final 2 years of the project. The report also details the motivation for why new modeling techniques and tools are needed. The analytical modeling methodologies will enable analysts to evaluate the information environment for relevance to detecting proliferation intent, with specific focus on assessing risks associated with transferring dual-use technologies. Dual-use technologies can be used in both weapons and commercial enterprises. A decision-framework was developed to evaluate which of the different analytical modeling methodologies would be most appropriate conditional on the uniqueness of the approach, data availability, laboratory capabilities, relevance to NA-22 and Office of Arms Control and Nonproliferation (NA-24) research needs and the impact if successful. Modeling methodologies were divided into whether they could help micro-level assessments (e.g., help improve individual license assessments) or macro-level assessment. Macro-level assessment focuses on suppliers, technology, consumers, economies, and proliferation context. Macro-level assessment technologies scored higher in the area of uniqueness because less work has been done at the macro level. An approach to developing testable hypotheses for the macro-level assessment methodologies is provided. The outcome of this works suggests that we should develop a Bayes Net for micro-level analysis and continue to focus on Bayes Net, System Dynamics and Economic Input/Output models for assessing macro-level problems. Simultaneously, we need to develop metrics for assessing intent in export control, including the risks and consequences associated with all aspects of export control.« less

A Model of Risk Analysis in Analytical Methodology for Biopharmaceutical Quality Control.

PubMed

Andrade, Cleyton Lage; Herrera, Miguel Angel De La O; Lemes, Elezer Monte Blanco

2018-01-01

One key quality control parameter for biopharmaceutical products is the analysis of residual cellular DNA. To determine small amounts of DNA (around 100 pg) that may be in a biologically derived drug substance, an analytical method should be sensitive, robust, reliable, and accurate. In principle, three techniques have the ability to measure residual cellular DNA: radioactive dot-blot, a type of hybridization; threshold analysis; and quantitative polymerase chain reaction. Quality risk management is a systematic process for evaluating, controlling, and reporting of risks that may affects method capabilities and supports a scientific and practical approach to decision making. This paper evaluates, by quality risk management, an alternative approach to assessing the performance risks associated with quality control methods used with biopharmaceuticals, using the tool hazard analysis and critical control points. This tool provides the possibility to find the steps in an analytical procedure with higher impact on method performance. By applying these principles to DNA analysis methods, we conclude that the radioactive dot-blot assay has the largest number of critical control points, followed by quantitative polymerase chain reaction, and threshold analysis. From the analysis of hazards (i.e., points of method failure) and the associated method procedure critical control points, we conclude that the analytical methodology with the lowest risk for performance failure for residual cellular DNA testing is quantitative polymerase chain reaction. LAY ABSTRACT: In order to mitigate the risk of adverse events by residual cellular DNA that is not completely cleared from downstream production processes, regulatory agencies have required the industry to guarantee a very low level of DNA in biologically derived pharmaceutical products. The technique historically used was radioactive blot hybridization. However, the technique is a challenging method to implement in a quality control laboratory: It is laborious, time consuming, semi-quantitative, and requires a radioisotope. Along with dot-blot hybridization, two alternatives techniques were evaluated: threshold analysis and quantitative polymerase chain reaction. Quality risk management tools were applied to compare the techniques, taking into account the uncertainties, the possibility of circumstances or future events, and their effects upon method performance. By illustrating the application of these tools with DNA methods, we provide an example of how they can be used to support a scientific and practical approach to decision making and can assess and manage method performance risk using such tools. This paper discusses, considering the principles of quality risk management, an additional approach to the development and selection of analytical quality control methods using the risk analysis tool hazard analysis and critical control points. This tool provides the possibility to find the method procedural steps with higher impact on method reliability (called critical control points). Our model concluded that the radioactive dot-blot assay has the larger number of critical control points, followed by quantitative polymerase chain reaction and threshold analysis. Quantitative polymerase chain reaction is shown to be the better alternative analytical methodology in residual cellular DNA analysis. © PDA, Inc. 2018.

Visual Analytics for Law Enforcement: Deploying a Service-Oriented Analytic Framework for Web-based Visualization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dowson, Scott T.; Bruce, Joseph R.; Best, Daniel M.

2009-04-14

This paper presents key components of the Law Enforcement Information Framework (LEIF) that provides communications, situational awareness, and visual analytics tools in a service-oriented architecture supporting web-based desktop and handheld device users. LEIF simplifies interfaces and visualizations of well-established visual analytical techniques to improve usability. Advanced analytics capability is maintained by enhancing the underlying processing to support the new interface. LEIF development is driven by real-world user feedback gathered through deployments at three operational law enforcement organizations in the US. LEIF incorporates a robust information ingest pipeline supporting a wide variety of information formats. LEIF also insulates interface and analyticalmore » components from information sources making it easier to adapt the framework for many different data repositories.« less

Factors Influencing the Internet Resource Users' Satisfaction: An Analytical Study on Omani Undergraduate Learners

ERIC Educational Resources Information Center

Sriram, B.

2016-01-01

The internet resources are one of the important knowledge sharing tools in day-to-day business processes. These internet resources have greater impact on education field too. The learning processes have become comparatively easy due to these electronic resources. The online resources help the students to acquire the required knowledge through…

Foucauldian Iterative Learning Conversations--An Example of Organisational Change: Developing Conjoint-Work between EPS and Social Workers

ERIC Educational Resources Information Center

Apter, Brian

2014-01-01

An organisational change-process in a UK local authority (LA) over two years is examined using transcribed excerpts from three meetings. The change-process is analysed using a Foucauldian analytical tool--Iterative Learning Conversations (ILCS). An Educational Psychology Service was changed from being primarily an education-focussed…

33 CFR 385.33 - Revisions to models and analytical tools.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Management District, and other non-Federal sponsors shall rely on the best available science including models..., and assessment of projects. The selection of models and analytical tools shall be done in consultation... system-wide simulation models and analytical tools used in the evaluation and assessment of projects, and...

Look@NanoSIMS--a tool for the analysis of nanoSIMS data in environmental microbiology.

PubMed

Polerecky, Lubos; Adam, Birgit; Milucka, Jana; Musat, Niculina; Vagner, Tomas; Kuypers, Marcel M M

2012-04-01

We describe an open-source freeware programme for high throughput analysis of nanoSIMS (nanometre-scale secondary ion mass spectrometry) data. The programme implements basic data processing and analytical functions, including display and drift-corrected accumulation of scanned planes, interactive and semi-automated definition of regions of interest (ROIs), and export of the ROIs' elemental and isotopic composition in graphical and text-based formats. Additionally, the programme offers new functions that were custom-designed to address the needs of environmental microbiologists. Specifically, it allows manual and automated classification of ROIs based on the information that is derived either from the nanoSIMS dataset itself (e.g. from labelling achieved by halogen in situ hybridization) or is provided externally (e.g. as a fluorescence in situ hybridization image). Moreover, by implementing post-processing routines coupled to built-in statistical tools, the programme allows rapid synthesis and comparative analysis of results from many different datasets. After validation of the programme, we illustrate how these new processing and analytical functions increase flexibility, efficiency and depth of the nanoSIMS data analysis. Through its custom-made and open-source design, the programme provides an efficient, reliable and easily expandable tool that can help a growing community of environmental microbiologists and researchers from other disciplines process and analyse their nanoSIMS data. © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

Applying SF-Based Genre Approaches to English Writing Class

ERIC Educational Resources Information Center

Wu, Yan; Dong, Hailin

2009-01-01

By exploring genre approaches in systemic functional linguistics and examining the analytic tools that can be applied to the process of English learning and teaching, this paper seeks to find a way of applying genre approaches to English writing class.

Developing Healthcare Data Analytics APPs with Open Data Science Tools.

PubMed

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.

Analytical quality by design: a tool for regulatory flexibility and robust analytics.

PubMed

Peraman, Ramalingam; Bhadraya, Kalva; Padmanabha Reddy, Yiragamreddy

2015-01-01

Very recently, Food and Drug Administration (FDA) has approved a few new drug applications (NDA) with regulatory flexibility for quality by design (QbD) based analytical approach. The concept of QbD applied to analytical method development is known now as AQbD (analytical quality by design). It allows the analytical method for movement within method operable design region (MODR). Unlike current methods, analytical method developed using analytical quality by design (AQbD) approach reduces the number of out-of-trend (OOT) results and out-of-specification (OOS) results due to the robustness of the method within the region. It is a current trend among pharmaceutical industry to implement analytical quality by design (AQbD) in method development process as a part of risk management, pharmaceutical development, and pharmaceutical quality system (ICH Q10). Owing to the lack explanatory reviews, this paper has been communicated to discuss different views of analytical scientists about implementation of AQbD in pharmaceutical quality system and also to correlate with product quality by design and pharmaceutical analytical technology (PAT).

Analytical Quality by Design: A Tool for Regulatory Flexibility and Robust Analytics

PubMed Central

Bhadraya, Kalva; Padmanabha Reddy, Yiragamreddy

2015-01-01

Very recently, Food and Drug Administration (FDA) has approved a few new drug applications (NDA) with regulatory flexibility for quality by design (QbD) based analytical approach. The concept of QbD applied to analytical method development is known now as AQbD (analytical quality by design). It allows the analytical method for movement within method operable design region (MODR). Unlike current methods, analytical method developed using analytical quality by design (AQbD) approach reduces the number of out-of-trend (OOT) results and out-of-specification (OOS) results due to the robustness of the method within the region. It is a current trend among pharmaceutical industry to implement analytical quality by design (AQbD) in method development process as a part of risk management, pharmaceutical development, and pharmaceutical quality system (ICH Q10). Owing to the lack explanatory reviews, this paper has been communicated to discuss different views of analytical scientists about implementation of AQbD in pharmaceutical quality system and also to correlate with product quality by design and pharmaceutical analytical technology (PAT). PMID:25722723

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2008-01-01

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization (MDAO) tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

Structural Model Tuning Capability in an Object-Oriented Multidisciplinary Design, Analysis, and Optimization Tool

NASA Technical Reports Server (NTRS)

Lung, Shun-fat; Pak, Chan-gi

2008-01-01

Updating the finite element model using measured data is a challenging problem in the area of structural dynamics. The model updating process requires not only satisfactory correlations between analytical and experimental results, but also the retention of dynamic properties of structures. Accurate rigid body dynamics are important for flight control system design and aeroelastic trim analysis. Minimizing the difference between analytical and experimental results is a type of optimization problem. In this research, a multidisciplinary design, analysis, and optimization [MDAO] tool is introduced to optimize the objective function and constraints such that the mass properties, the natural frequencies, and the mode shapes are matched to the target data as well as the mass matrix being orthogonalized.

Hasse diagram as a green analytical metrics tool: ranking of methods for benzo[a]pyrene determination in sediments.

PubMed

Bigus, Paulina; Tsakovski, Stefan; Simeonov, Vasil; Namieśnik, Jacek; Tobiszewski, Marek

2016-05-01

This study presents an application of the Hasse diagram technique (HDT) as the assessment tool to select the most appropriate analytical procedures according to their greenness or the best analytical performance. The dataset consists of analytical procedures for benzo[a]pyrene determination in sediment samples, which were described by 11 variables concerning their greenness and analytical performance. Two analyses with the HDT were performed-the first one with metrological variables and the second one with "green" variables as input data. Both HDT analyses ranked different analytical procedures as the most valuable, suggesting that green analytical chemistry is not in accordance with metrology when benzo[a]pyrene in sediment samples is determined. The HDT can be used as a good decision support tool to choose the proper analytical procedure concerning green analytical chemistry principles and analytical performance merits.

Exascale computing and big data

DOE PAGES

Reed, Daniel A.; Dongarra, Jack

2015-06-25

Scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics. The tools and cultures of high-performance computing and big data analytics have diverged, to the detriment of both; unification is essential to address a spectrum of major research domains. The challenges of scale tax our ability to transmit data, compute complicated functions on that data, or store a substantial part of it; new approaches are required to meet these challenges. Finally, the international nature of science demands further development of advanced computer architectures and global standards for processing data, even as international competition complicates themore » openness of the scientific process.« less

Fluorescence Spectroscopy for the Monitoring of Food Processes.

PubMed

Ahmad, Muhammad Haseeb; Sahar, Amna; Hitzmann, Bernd

Different analytical techniques have been used to examine the complexity of food samples. Among them, fluorescence spectroscopy cannot be ignored in developing rapid and non-invasive analytical methodologies. It is one of the most sensitive spectroscopic approaches employed in identification, classification, authentication, quantification, and optimization of different parameters during food handling, processing, and storage and uses different chemometric tools. Chemometrics helps to retrieve useful information from spectral data utilized in the characterization of food samples. This contribution discusses in detail the potential of fluorescence spectroscopy of different foods, such as dairy, meat, fish, eggs, edible oil, cereals, fruit, vegetables, etc., for qualitative and quantitative analysis with different chemometric approaches.

Exascale computing and big data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reed, Daniel A.; Dongarra, Jack

Scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics. The tools and cultures of high-performance computing and big data analytics have diverged, to the detriment of both; unification is essential to address a spectrum of major research domains. The challenges of scale tax our ability to transmit data, compute complicated functions on that data, or store a substantial part of it; new approaches are required to meet these challenges. Finally, the international nature of science demands further development of advanced computer architectures and global standards for processing data, even as international competition complicates themore » openness of the scientific process.« less

AUVA - Augmented Reality Empowers Visual Analytics to explore Medical Curriculum Data.

PubMed

Nifakos, Sokratis; Vaitsis, Christos; Zary, Nabil

2015-01-01

Medical curriculum data play a key role in the structure and the organization of medical programs in Universities around the world. The effective processing and usage of these data may improve the educational environment of medical students. As a consequence, the new generation of health professionals would have improved skills from the previous ones. This study introduces the process of enhancing curriculum data by the use of augmented reality technology as a management and presentation tool. The final goal is to enrich the information presented from a visual analytics approach applied on medical curriculum data and to sustain low levels of complexity of understanding these data.

Biomanufacturing process analytical technology (PAT) application for downstream processing: Using dissolved oxygen as an indicator of product quality for a protein refolding reaction.

PubMed

Pizarro, Shelly A; Dinges, Rachel; Adams, Rachel; Sanchez, Ailen; Winter, Charles

2009-10-01

Process analytical technology (PAT) is an initiative from the US FDA combining analytical and statistical tools to improve manufacturing operations and ensure regulatory compliance. This work describes the use of a continuous monitoring system for a protein refolding reaction to provide consistency in product quality and process performance across batches. A small-scale bioreactor (3 L) is used to understand the impact of aeration for refolding recombinant human vascular endothelial growth factor (rhVEGF) in a reducing environment. A reverse-phase HPLC assay is used to assess product quality. The goal in understanding the oxygen needs of the reaction and its impact to quality, is to make a product that is efficiently refolded to its native and active form with minimum oxidative degradation from batch to batch. Because this refolding process is heavily dependent on oxygen, the % dissolved oxygen (DO) profile is explored as a PAT tool to regulate process performance at commercial manufacturing scale. A dynamic gassing out approach using constant mass transfer (k(L)a) is used for scale-up of the aeration parameters to manufacturing scale tanks (2,000 L, 15,000 L). The resulting DO profiles of the refolding reaction show similar trends across scales and these are analyzed using rpHPLC. The desired product quality attributes are then achieved through alternating air and nitrogen sparging triggered by changes in the monitored DO profile. This approach mitigates the impact of differences in equipment or feedstock components between runs, and is directly inline with the key goal of PAT to "actively manage process variability using a knowledge-based approach." (c) 2009 Wiley Periodicals, Inc.

From Data to Knowledge – Promising Analytical Tools and Techniques for Capture and Reuse of Corporate Knowledge and to Aid in the State Evaluation Process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Danielson, Gary R.; Augustenborg, Elsa C.; Beck, Andrew E.

2010-10-29

The IAEA is challenged with limited availability of human resources for inspection and data analysis while proliferation threats increase. PNNL has a variety of IT solutions and techniques (at varying levels of maturity and development) that take raw data closer to useful knowledge, thereby assisting with and standardizing the analytical processes. This paper highlights some PNNL tools and techniques which are applicable to the international safeguards community, including: • Intelligent in-situ triage of data prior to reliable transmission to an analysis center resulting in the transmission of smaller and more relevant data sets • Capture of expert knowledge in re-usablemore » search strings tailored to specific mission outcomes • Image based searching fused with text based searching • Use of gaming to discover unexpected proliferation scenarios • Process modeling (e.g. Physical Model) as the basis for an information integration portal, which links to data storage locations along with analyst annotations, categorizations, geographic data, search strings and visualization outputs.« less

Analytic description of the frictionally engaged in-plane bending process incremental swivel bending (ISB)

NASA Astrophysics Data System (ADS)

Frohn, Peter; Engel, Bernd; Groth, Sebastian

2018-05-01

Kinematic forming processes shape geometries by the process parameters to achieve a more universal process utilizations regarding geometric configurations. The kinematic forming process Incremental Swivel Bending (ISB) bends sheet metal strips or profiles in plane. The sequence for bending an arc increment is composed of the steps clamping, bending, force release and feed. The bending moment is frictionally engaged by two clamping units in a laterally adjustable bending pivot. A minimum clamping force hindering the material from slipping through the clamping units is a crucial criterion to achieve a well-defined incremental arc. Therefore, an analytic description of a singular bent increment is developed in this paper. The bending moment is calculated by the uniaxial stress distribution over the profiles' width depending on the bending pivot's position. By a Coulomb' based friction model, necessary clamping force is described in dependence of friction, offset, dimensions of the clamping tools and strip thickness as well as material parameters. Boundaries for the uniaxial stress calculation are given in dependence of friction, tools' dimensions and strip thickness. The results indicate that changing the bending pivot to an eccentric position significantly affects the process' bending moment and, hence, clamping force, which is given in dependence of yield stress and hardening exponent. FE simulations validate the model with satisfactory accordance.

The application of quality risk management to the bacterial endotoxins test: use of hazard analysis and critical control points.

PubMed

Annalaura, Carducci; Giulia, Davini; Stefano, Ceccanti

2013-01-01

Risk analysis is widely used in the pharmaceutical industry to manage production processes, validation activities, training, and other activities. Several methods of risk analysis are available (for example, failure mode and effects analysis, fault tree analysis), and one or more should be chosen and adapted to the specific field where they will be applied. Among the methods available, hazard analysis and critical control points (HACCP) is a methodology that has been applied since the 1960s, and whose areas of application have expanded over time from food to the pharmaceutical industry. It can be easily and successfully applied to several processes because its main feature is the identification, assessment, and control of hazards. It can be also integrated with other tools, such as fishbone diagram and flowcharting. The aim of this article is to show how HACCP can be used to manage an analytical process, propose how to conduct the necessary steps, and provide data templates necessary to document and useful to follow current good manufacturing practices. In the quality control process, risk analysis is a useful tool for enhancing the uniformity of technical choices and their documented rationale. Accordingly, it allows for more effective and economical laboratory management, is capable of increasing the reliability of analytical results, and enables auditors and authorities to better understand choices that have been made. The aim of this article is to show how hazard analysis and critical control points can be used to manage bacterial endotoxins testing and other analytical processes in a formal, clear, and detailed manner.

Investigation of hydrogenation of toluene to methylcyclohexane in a trickle bed reactor by low-field nuclear magnetic resonance spectroscopy.

PubMed

Guthausen, Gisela; von Garnier, Agnes; Reimert, Rainer

2009-10-01

Low-field nuclear magnetic resonance (NMR) spectroscopy is applied to study the hydrogenation of toluene in a lab-scale reactor. A conventional benchtop NMR system was modified to achieve chemical shift resolution. After an off-line validity check of the approach, the reaction product is analyzed on-line during the process, applying chemometric data processing. The conversion of toluene to methylcyclohexane is compared with off-line gas chromatographic analysis. Both classic analytical and chemometric data processing was applied. As the results, which are obtained within a few tens of seconds, are equivalent within the experimental accuracy of both methods, low-field NMR spectroscopy was shown to provide an analytical tool for reaction characterization and immediate feedback.

Analytical solutions of the planar cyclic voltammetry process for two soluble species with equal diffusivities and fast electron transfer using the method of eigenfunction expansions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samin, Adib; Lahti, Erik; Zhang, Jinsuo, E-mail: zhang.3558@osu.edu

Cyclic voltammetry is a powerful tool that is used for characterizing electrochemical processes. Models of cyclic voltammetry take into account the mass transport of species and the kinetics at the electrode surface. Analytical solutions of these models are not well-known due to the complexity of the boundary conditions. In this study we present closed form analytical solutions of the planar voltammetry model for two soluble species with fast electron transfer and equal diffusivities using the eigenfunction expansion method. Our solution methodology does not incorporate Laplace transforms and yields good agreement with the numerical solution. This solution method can be extendedmore » to cases that are more general and may be useful for benchmarking purposes.« less

Stakeholder perspectives on decision-analytic modeling frameworks to assess genetic services policy.

PubMed

Guzauskas, Gregory F; Garrison, Louis P; Stock, Jacquie; Au, Sylvia; Doyle, Debra Lochner; Veenstra, David L

2013-01-01

Genetic services policymakers and insurers often make coverage decisions in the absence of complete evidence of clinical utility and under budget constraints. We evaluated genetic services stakeholder opinions on the potential usefulness of decision-analytic modeling to inform coverage decisions, and asked them to identify genetic tests for decision-analytic modeling studies. We presented an overview of decision-analytic modeling to members of the Western States Genetic Services Collaborative Reimbursement Work Group and state Medicaid representatives and conducted directed content analysis and an anonymous survey to gauge their attitudes toward decision-analytic modeling. Participants also identified and prioritized genetic services for prospective decision-analytic evaluation. Participants expressed dissatisfaction with current processes for evaluating insurance coverage of genetic services. Some participants expressed uncertainty about their comprehension of decision-analytic modeling techniques. All stakeholders reported openness to using decision-analytic modeling for genetic services assessments. Participants were most interested in application of decision-analytic concepts to multiple-disorder testing platforms, such as next-generation sequencing and chromosomal microarray. Decision-analytic modeling approaches may provide a useful decision tool to genetic services stakeholders and Medicaid decision-makers.

Marshall Space Flight Center's Virtual Reality Applications Program 1993

NASA Technical Reports Server (NTRS)

Hale, Joseph P., II

1993-01-01

A Virtual Reality (VR) applications program has been under development at the Marshall Space Flight Center (MSFC) since 1989. Other NASA Centers, most notably Ames Research Center (ARC), have contributed to the development of the VR enabling technologies and VR systems. This VR technology development has now reached a level of maturity where specific applications of VR as a tool can be considered. The objectives of the MSFC VR Applications Program are to develop, validate, and utilize VR as a Human Factors design and operations analysis tool and to assess and evaluate VR as a tool in other applications (e.g., training, operations development, mission support, teleoperations planning, etc.). The long-term goals of this technology program is to enable specialized Human Factors analyses earlier in the hardware and operations development process and develop more effective training and mission support systems. The capability to perform specialized Human Factors analyses earlier in the hardware and operations development process is required to better refine and validate requirements during the requirements definition phase. This leads to a more efficient design process where perturbations caused by late-occurring requirements changes are minimized. A validated set of VR analytical tools must be developed to enable a more efficient process for the design and development of space systems and operations. Similarly, training and mission support systems must exploit state-of-the-art computer-based technologies to maximize training effectiveness and enhance mission support. The approach of the VR Applications Program is to develop and validate appropriate virtual environments and associated object kinematic and behavior attributes for specific classes of applications. These application-specific environments and associated simulations will be validated, where possible, through empirical comparisons with existing, accepted tools and methodologies. These validated VR analytical tools will then be available for use in the design and development of space systems and operations and in training and mission support systems.

Framework for assessing key variable dependencies in loose-abrasive grinding and polishing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taylor, J.S.; Aikens, D.M.; Brown, N.J.

1995-12-01

This memo describes a framework for identifying all key variables that determine the figuring performance of loose-abrasive lapping and polishing machines. This framework is intended as a tool for prioritizing R&D issues, assessing the completeness of process models and experimental data, and for providing a mechanism to identify any assumptions in analytical models or experimental procedures. Future plans for preparing analytical models or performing experiments can refer to this framework in establishing the context of the work.

ANALYTiC: An Active Learning System for Trajectory Classification.

PubMed

Soares Junior, Amilcar; Renso, Chiara; Matwin, Stan

2017-01-01

The increasing availability and use of positioning devices has resulted in large volumes of trajectory data. However, semantic annotations for such data are typically added by domain experts, which is a time-consuming task. Machine-learning algorithms can help infer semantic annotations from trajectory data by learning from sets of labeled data. Specifically, active learning approaches can minimize the set of trajectories to be annotated while preserving good performance measures. The ANALYTiC web-based interactive tool visually guides users through this annotation process.

Green Chemistry Metrics with Special Reference to Green Analytical Chemistry.

PubMed

Tobiszewski, Marek; Marć, Mariusz; Gałuszka, Agnieszka; Namieśnik, Jacek

2015-06-12

The concept of green chemistry is widely recognized in chemical laboratories. To properly measure an environmental impact of chemical processes, dedicated assessment tools are required. This paper summarizes the current state of knowledge in the field of development of green chemistry and green analytical chemistry metrics. The diverse methods used for evaluation of the greenness of organic synthesis, such as eco-footprint, E-Factor, EATOS, and Eco-Scale are described. Both the well-established and recently developed green analytical chemistry metrics, including NEMI labeling and analytical Eco-scale, are presented. Additionally, this paper focuses on the possibility of the use of multivariate statistics in evaluation of environmental impact of analytical procedures. All the above metrics are compared and discussed in terms of their advantages and disadvantages. The current needs and future perspectives in green chemistry metrics are also discussed.

A new frequency approach for light flicker evaluation in electric power systems

NASA Astrophysics Data System (ADS)

Feola, Luigi; Langella, Roberto; Testa, Alfredo

2015-12-01

In this paper, a new analytical estimator for light flicker in frequency domain, which is able to take into account also the frequency components neglected by the classical methods proposed in literature, is proposed. The analytical solutions proposed apply for any generic stationary signal affected by interharmonic distortion. The light flicker analytical estimator proposed is applied to numerous numerical case studies with the goal of showing i) the correctness and the improvements of the analytical approach proposed with respect to the other methods proposed in literature and ii) the accuracy of the results compared to those obtained by means of the classical International Electrotechnical Commission (IEC) flickermeter. The usefulness of the proposed analytical approach is that it can be included in signal processing tools for interharmonic penetration studies for the integration of renewable energy sources in future smart grids.

The generation of criteria for selecting analytical tools for landscape management

Treesearch

Marilyn Duffey-Armstrong

1979-01-01

This paper presents an approach to generating criteria for selecting the analytical tools used to assess visual resources for various landscape management tasks. The approach begins by first establishing the overall parameters for the visual assessment task, and follows by defining the primary requirements of the various sets of analytical tools to be used. Finally,...

Non-enzymatic browning in citrus juice: chemical markers, their detection and ways to improve product quality.

PubMed

Bharate, Sonali S; Bharate, Sandip B

2014-10-01

Citrus juices are widely consumed due to their nutritional benefits and variety of pharmacological properties. Non-enzymatic browning (NEB) is one of the most important chemical reactions responsible for quality and color changes during the heating or prolonged storage of citrus products. The present review covers various aspects of NEB in citrus juice viz. chemistry of NEB, identifiable markers of NEB, analytical methods to identify NEB markers and ways to improve the quality of citrus juice. 2,5-Dimethyl-4-hydroxy-3(2H)-furanone (DMHF) is one of the promising marker formed during browning process with number of analytical methods reported for its analysis; therefore it can be used as an indicator for NEB process. Amongst analytical methods reported, RP-HPLC is more sensitive and accurate method, which can be used as analytical tool. NEB can be prevented by removal of amino acids/ proteins (via ion exchange treatment) or by targeting NEB reactions (e.g. blockage of furfural/ HMF by sulphiting agent).

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

NASA Technical Reports Server (NTRS)

Kempler, Steven; Barbieri, Lindsay

2016-01-01

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

Process analytical technology (PAT) in insect and mammalian cell culture processes: dielectric spectroscopy and focused beam reflectance measurement (FBRM).

PubMed

Druzinec, Damir; Weiss, Katja; Elseberg, Christiane; Salzig, Denise; Kraume, Matthias; Pörtner, Ralf; Czermak, Peter

2014-01-01

Modern bioprocesses demand for a careful definition of the critical process parameters (CPPs) already during the early stages of process development in order to ensure high-quality products and satisfactory yields. In this context, online monitoring tools can be applied to recognize unfavorable changes of CPPs during the production processes and to allow for early interventions in order to prevent losses of production batches due to quality issues. Process analytical technologies such as the dielectric spectroscopy or focused beam reflectance measurement (FBRM) are possible online monitoring tools, which can be applied to monitor cell growth as well as morphological changes. Since the dielectric spectroscopy only captures cells with intact cell membranes, even information about dead cells with ruptured or leaking cell membranes can be derived. The following chapter describes the application of dielectric spectroscopy on various virus-infected and non-infected cell lines with respect to adherent as well as suspension cultures in common stirred tank reactors. The adherent mammalian cell lines Vero (African green monkey kidney cells) and hMSC-TERT (telomerase-immortalized human mesenchymal stem cells) are thereby cultured on microcarrier, which provide the required growth surface and allow the cultivation of these cells even in dynamic culture systems. In turn, the insect-derived cell lines S2 and Sf21 are used as examples for cells typically cultured in suspension. Moreover, the FBRM technology as a further monitoring tool for cell culture applications has been included in this chapter using the example of Drosophila S2 insect cells.

Electrochemical lectin based biosensors as a label-free tool in glycomics

PubMed Central

Bertók, Tomáš; Katrlík, Jaroslav; Gemeiner, Peter; Tkac, Jan

2016-01-01

Glycans and other saccharide moieties attached to proteins and lipids, or present on the surface of a cell, are actively involved in numerous physiological or pathological processes. Their structural flexibility (that is based on the formation of various kinds of linkages between saccharides) is making glycans superb “identity cards”. In fact, glycans can form more “words” or “codes” (i.e., unique sequences) from the same number of “letters” (building blocks) than DNA or proteins. Glycans are physicochemically similar and it is not a trivial task to identify their sequence, or - even more challenging - to link a given glycan to a particular physiological or pathological process. Lectins can recognise differences in glycan compositions even in their bound state and therefore are most useful tools in the task to decipher the “glycocode”. Thus, lectin-based biosensors working in a label-free mode can effectively complement the current weaponry of analytical tools in glycomics. This review gives an introduction into the area of glycomics and then focuses on the design, analytical performance, and practical utility of lectin-based electrochemical label-free biosensors for the detection of isolated glycoproteins or intact cells. PMID:27239071

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends

PubMed Central

2014-01-01

The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis. This so called “big data” challenges traditional analytic tools and will increasingly require novel solutions adapted from other fields. Advances in information and communication technology present the most viable solutions to big data analysis in terms of efficiency and scalability. It is vital those big data solutions are multithreaded and that data access approaches be precisely tailored to large volumes of semi-structured/unstructured data. The MapReduce programming framework uses two tasks common in functional programming: Map and Reduce. MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters. Compared with existing parallel processing paradigms (e.g. grid computing and graphical processing unit (GPU)), MapReduce and Hadoop have two advantages: 1) fault-tolerant storage resulting in reliable data processing by replicating the computing tasks, and cloning the data chunks on different computing nodes across the computing cluster; 2) high-throughput data processing via a batch processing framework and the Hadoop distributed file system (HDFS). Data are stored in the HDFS and made available to the slave nodes for computation. In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. The usage of MapReduce and Hadoop on a distributed system represents a significant advance in clinical big data processing and utilization, and opens up new opportunities in the emerging era of big data analytics. The objective of this paper is to summarize the state-of-the-art efforts in clinical big data analytics and highlight what might be needed to enhance the outcomes of clinical big data analytics tools. This paper is concluded by summarizing the potential usage of the MapReduce programming framework and Hadoop platform to process huge volumes of clinical data in medical health informatics related fields. PMID:25383096

Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends.

PubMed

Mohammed, Emad A; Far, Behrouz H; Naugler, Christopher

2014-01-01

The emergence of massive datasets in a clinical setting presents both challenges and opportunities in data storage and analysis. This so called "big data" challenges traditional analytic tools and will increasingly require novel solutions adapted from other fields. Advances in information and communication technology present the most viable solutions to big data analysis in terms of efficiency and scalability. It is vital those big data solutions are multithreaded and that data access approaches be precisely tailored to large volumes of semi-structured/unstructured data. THE MAPREDUCE PROGRAMMING FRAMEWORK USES TWO TASKS COMMON IN FUNCTIONAL PROGRAMMING: Map and Reduce. MapReduce is a new parallel processing framework and Hadoop is its open-source implementation on a single computing node or on clusters. Compared with existing parallel processing paradigms (e.g. grid computing and graphical processing unit (GPU)), MapReduce and Hadoop have two advantages: 1) fault-tolerant storage resulting in reliable data processing by replicating the computing tasks, and cloning the data chunks on different computing nodes across the computing cluster; 2) high-throughput data processing via a batch processing framework and the Hadoop distributed file system (HDFS). Data are stored in the HDFS and made available to the slave nodes for computation. In this paper, we review the existing applications of the MapReduce programming framework and its implementation platform Hadoop in clinical big data and related medical health informatics fields. The usage of MapReduce and Hadoop on a distributed system represents a significant advance in clinical big data processing and utilization, and opens up new opportunities in the emerging era of big data analytics. The objective of this paper is to summarize the state-of-the-art efforts in clinical big data analytics and highlight what might be needed to enhance the outcomes of clinical big data analytics tools. This paper is concluded by summarizing the potential usage of the MapReduce programming framework and Hadoop platform to process huge volumes of clinical data in medical health informatics related fields.

THE ROLE OF RAMAN SPECTROSCOPY IN THE ANALYTICAL CHEMISTRY OF POTABLE WATER

EPA Science Inventory

Advances in instrumentation are making Raman spectroscopy the tool of choice for an increasing number of chemical applications. For example, many recalcitrant industrial-process monitoring problems have been solved in recent years with in-line Raman spectrometers. Raman is attr...

PRE-QAPP AGREEMENT (PQA) AND ANALYTICAL METHOD CHECKLISTS (AMCS): TOOLS FOR PLANNING RESEARCH PROJECTS

EPA Science Inventory

The Land Remediation and Pollution Control Division (LRPCD) QA Manager strives to assist LRPCD researchers in developing functional planning documents for their research projects. As part of the planning process, several pieces of information are needed, including information re...

THE ROLE OF RAMAN SPECTROSCOPY IN THE ANALYTICAL CHEMISTRY OF POTABLE WATER

EPA Science Inventory

Advances in instrumentation are making Raman spectroscopy the tool of choice for an increasing number of chemical applications. For example, many recalcitrant industrial process monitoring problems have been solved in recent years with in-line Raman spectrometers. Raman is attr...

Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases

PubMed Central

2005-01-01

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB. PMID:16046824

An analytical model to predict and minimize the residual stress of laser cladding process

NASA Astrophysics Data System (ADS)

Tamanna, N.; Crouch, R.; Kabir, I. R.; Naher, S.

2018-02-01

Laser cladding is one of the advanced thermal techniques used to repair or modify the surface properties of high-value components such as tools, military and aerospace parts. Unfortunately, tensile residual stresses generate in the thermally treated area of this process. This work focuses on to investigate the key factors for the formation of tensile residual stress and how to minimize it in the clad when using dissimilar substrate and clad materials. To predict the tensile residual stress, a one-dimensional analytical model has been adopted. Four cladding materials (Al2O3, TiC, TiO2, ZrO2) on the H13 tool steel substrate and a range of preheating temperatures of the substrate, from 300 to 1200 K, have been investigated. Thermal strain and Young's modulus are found to be the key factors of formation of tensile residual stresses. Additionally, it is found that using a preheating temperature of the substrate immediately before laser cladding showed the reduction of residual stress.

Analytical simulation and PROFAT II: a new methodology and a computer automated tool for fault tree analysis in chemical process industries.

PubMed

Khan, F I; Abbasi, S A

2000-07-10

Fault tree analysis (FTA) is based on constructing a hypothetical tree of base events (initiating events) branching into numerous other sub-events, propagating the fault and eventually leading to the top event (accident). It has been a powerful technique used traditionally in identifying hazards in nuclear installations and power industries. As the systematic articulation of the fault tree is associated with assigning probabilities to each fault, the exercise is also sometimes called probabilistic risk assessment. But powerful as this technique is, it is also very cumbersome and costly, limiting its area of application. We have developed a new algorithm based on analytical simulation (named as AS-II), which makes the application of FTA simpler, quicker, and cheaper; thus opening up the possibility of its wider use in risk assessment in chemical process industries. Based on the methodology we have developed a computer-automated tool. The details are presented in this paper.

On-Line Ion Exchange Liquid Chromatography as a Process Analytical Technology for Monoclonal Antibody Characterization in Continuous Bioprocessing.

PubMed

Patel, Bhumit A; Pinto, Nuno D S; Gospodarek, Adrian; Kilgore, Bruce; Goswami, Kudrat; Napoli, William N; Desai, Jayesh; Heo, Jun H; Panzera, Dominick; Pollard, David; Richardson, Daisy; Brower, Mark; Richardson, Douglas D

2017-11-07

Combining process analytical technology (PAT) with continuous production provides a powerful tool to observe and control monoclonal antibody (mAb) fermentation and purification processes. This work demonstrates on-line liquid chromatography (on-line LC) as a PAT tool for monitoring a continuous biologics process and forced degradation studies. Specifically, this work focused on ion exchange chromatography (IEX), which is a critical separation technique to detect charge variants. Product-related impurities, including charge variants, that impact function are classified as critical quality attributes (CQAs). First, we confirmed no significant differences were observed in the charge heterogeneity profile of a mAb through both at-line and on-line sampling and that the on-line method has the ability to rapidly detect changes in protein quality over time. The robustness and versatility of the PAT methods were tested by sampling from two purification locations in a continuous mAb process. The PAT IEX methods used with on-line LC were a weak cation exchange (WCX) separation and a newly developed shorter strong cation exchange (SCX) assay. Both methods provided similar results with the distribution of percent acidic, main, and basic species remaining unchanged over a 2 week period. Second, a forced degradation study showed an increase in acidic species and a decrease in basic species when sampled on-line over 7 days. These applications further strengthen the use of on-line LC to monitor CQAs of a mAb continuously with various PAT IEX analytical methods. Implementation of on-line IEX will enable faster decision making during process development and could potentially be applied to control in biomanufacturing.

Microscale technology and biocatalytic processes: opportunities and challenges for synthesis.

PubMed

Wohlgemuth, Roland; Plazl, Igor; Žnidaršič-Plazl, Polona; Gernaey, Krist V; Woodley, John M

2015-05-01

Despite the expanding presence of microscale technology in chemical synthesis and energy production as well as in biomedical devices and analytical and diagnostic tools, its potential in biocatalytic processes for pharmaceutical and fine chemicals, as well as related industries, has not yet been fully exploited. The aim of this review is to shed light on the strategic advantages of this promising technology for the development and realization of biocatalytic processes and subsequent product recovery steps, demonstrated with examples from the literature. Constraints, opportunities, and the future outlook for the implementation of these key green engineering methods and the role of supporting tools such as mathematical models to establish sustainable production processes are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bioinformatic tools for inferring functional information from plant microarray data: tools for the first steps.

PubMed

Page, Grier P; Coulibaly, Issa

2008-01-01

Microarrays are a very powerful tool for quantifying the amount of RNA in samples; however, their ability to query essentially every gene in a genome, which can number in the tens of thousands, presents analytical and interpretative problems. As a result, a variety of software and web-based tools have been developed to help with these issues. This article highlights and reviews some of the tools for the first steps in the analysis of a microarray study. We have tried for a balance between free and commercial systems. We have organized the tools by topics including image processing tools (Section 2), power analysis tools (Section 3), image analysis tools (Section 4), database tools (Section 5), databases of functional information (Section 6), annotation tools (Section 7), statistical and data mining tools (Section 8), and dissemination tools (Section 9).

Human Subject Research Protocol: Computer-Aided Human Centric Cyber Situation Awareness: Understanding Cognitive Processes of Cyber Analysts

DTIC Science & Technology

2013-11-01

by existing cyber-attack detection tools far exceeds the analysts’ cognitive capabilities. Grounded in perceptual and cognitive theory , many visual...Processes Inspired by the sense-making theory discussed earlier, we model the analytical reasoning process of cyber analysts using three key...analyst are called “working hypotheses”); each hypothesis could trigger further actions to confirm or disconfirm it. New actions will lead to new

Interactive entity resolution in relational data: a visual analytic tool and its evaluation.

PubMed

Kang, Hyunmo; Getoor, Lise; Shneiderman, Ben; Bilgic, Mustafa; Licamele, Louis

2008-01-01

Databases often contain uncertain and imprecise references to real-world entities. Entity resolution, the process of reconciling multiple references to underlying real-world entities, is an important data cleaning process required before accurate visualization or analysis of the data is possible. In many cases, in addition to noisy data describing entities, there is data describing the relationships among the entities. This relational data is important during the entity resolution process; it is useful both for the algorithms which determine likely database references to be resolved and for visual analytic tools which support the entity resolution process. In this paper, we introduce a novel user interface, D-Dupe, for interactive entity resolution in relational data. D-Dupe effectively combines relational entity resolution algorithms with a novel network visualization that enables users to make use of an entity's relational context for making resolution decisions. Since resolution decisions often are interdependent, D-Dupe facilitates understanding this complex process through animations which highlight combined inferences and a history mechanism which allows users to inspect chains of resolution decisions. An empirical study with 12 users confirmed the benefits of the relational context visualization on the performance of entity resolution tasks in relational data in terms of time as well as users' confidence and satisfaction.

Analytic Scattering and Refraction Models for Exoplanet Transit Spectra

NASA Astrophysics Data System (ADS)

Robinson, Tyler D.; Fortney, Jonathan J.; Hubbard, William B.

2017-12-01

Observations of exoplanet transit spectra are essential to understanding the physics and chemistry of distant worlds. The effects of opacity sources and many physical processes combine to set the shape of a transit spectrum. Two such key processes—refraction and cloud and/or haze forward-scattering—have seen substantial recent study. However, models of these processes are typically complex, which prevents their incorporation into observational analyses and standard transit spectrum tools. In this work, we develop analytic expressions that allow for the efficient parameterization of forward-scattering and refraction effects in transit spectra. We derive an effective slant optical depth that includes a correction for forward-scattered light, and present an analytic form of this correction. We validate our correction against a full-physics transit spectrum model that includes scattering, and we explore the extent to which the omission of forward-scattering effects may bias models. Also, we verify a common analytic expression for the location of a refractive boundary, which we express in terms of the maximum pressure probed in a transit spectrum. This expression is designed to be easily incorporated into existing tools, and we discuss how the detection of a refractive boundary could help indicate the background atmospheric composition by constraining the bulk refractivity of the atmosphere. Finally, we show that opacity from Rayleigh scattering and collision-induced absorption will outweigh the effects of refraction for Jupiter-like atmospheres whose equilibrium temperatures are above 400-500 K.

Data-driven ranch management: A vision for sustainable ranching

USDA-ARS?s Scientific Manuscript database

Introduction The 21st century has ushered in an era of tiny, inexpensive electronics with impressive capabilities for sensing the environment. Also emerging are new technologies for communicating data to computer systems where new analytical tools can process the data. Many of these technologies w...

The geospatial modeling interface (GMI) framework for deploying and assessing environmental models

USDA-ARS?s Scientific Manuscript database

Geographical information systems (GIS) software packages have been used for close to three decades as analytical tools in environmental management for geospatial data assembly, processing, storage, and visualization of input data and model output. However, with increasing availability and use of ful...

Social Information Processing Analysis (SIPA): Coding Ongoing Human Communication.

ERIC Educational Resources Information Center

Fisher, B. Aubrey; And Others

1979-01-01

The purpose of this paper is to present a new analytical system to be used in communication research. Unlike many existing systems devised ad hoc, this research tool, a system for interaction analysis, is embedded in a conceptual rationale based on modern systems theory. (Author)

The engineering investigation of aircraft accidents

NASA Technical Reports Server (NTRS)

Anderson, S. B.

1982-01-01

The organization and plan for an investigation, procedures used at the scene of the accident, engineering aspects covered in the main investigation, use of special analytical techniques and simulation tools, and use of flight recorder data are discussed. Examples of investigations are used to illustrate the processes used.

Glycoprotein Enrichment Analytical Techniques: Advantages and Disadvantages.

PubMed

Zhu, R; Zacharias, L; Wooding, K M; Peng, W; Mechref, Y

2017-01-01

Protein glycosylation is one of the most important posttranslational modifications. Numerous biological functions are related to protein glycosylation. However, analytical challenges remain in the glycoprotein analysis. To overcome the challenges associated with glycoprotein analysis, many analytical techniques were developed in recent years. Enrichment methods were used to improve the sensitivity of detection, while HPLC and mass spectrometry methods were developed to facilitate the separation of glycopeptides/proteins and enhance detection, respectively. Fragmentation techniques applied in modern mass spectrometers allow the structural interpretation of glycopeptides/proteins, while automated software tools started replacing manual processing to improve the reliability and throughput of the analysis. In this chapter, the current methodologies of glycoprotein analysis were discussed. Multiple analytical techniques are compared, and advantages and disadvantages of each technique are highlighted. © 2017 Elsevier Inc. All rights reserved.

CHAPTER 7: Glycoprotein Enrichment Analytical Techniques: Advantages and Disadvantages

PubMed Central

Zhu, Rui; Zacharias, Lauren; Wooding, Kerry M.; Peng, Wenjing; Mechref, Yehia

2017-01-01

Protein glycosylation is one of the most important posttranslational modifications. Numerous biological functions are related to protein glycosylation. However, analytical challenges remain in the glycoprotein analysis. To overcome the challenges associated with glycoprotein analysis, many analytical techniques were developed in recent years. Enrichment methods were used to improve the sensitivity of detection while HPLC and mass spectrometry methods were developed to facilitate the separation of glycopeptides/proteins and enhance detection, respectively. Fragmentation techniques applied in modern mass spectrometers allow the structural interpretation of glycopeptides/proteins while automated software tools started replacing manual processing to improve the reliability and throughout of the analysis. In this chapter, the current methodologies of glycoprotein analysis were discussed. Multiple analytical techniques are compared, and advantages and disadvantages of each technique are highlighted. PMID:28109440

The use of selective adsorbents in capillary electrophoresis-mass spectrometry for analyte preconcentration and microreactions: a powerful three-dimensional tool for multiple chemical and biological applications.

PubMed

Guzman, N A; Stubbs, R J

2001-10-01

Much attention has recently been directed to the development and application of online sample preconcentration and microreactions in capillary electrophoresis using selective adsorbents based on chemical or biological specificity. The basic principle involves two interacting chemical or biological systems with high selectivity and affinity for each other. These molecular interactions in nature usually involve noncovalent and reversible chemical processes. Properly bound to a solid support, an "affinity ligand" can selectively adsorb a "target analyte" found in a simple or complex mixture at a wide range of concentrations. As a result, the isolated analyte is enriched and highly purified. When this affinity technique, allowing noncovalent chemical interactions and biochemical reactions to occur, is coupled on-line to high-resolution capillary electrophoresis and mass spectrometry, a powerful tool of chemical and biological information is created. This paper describes the concept of biological recognition and affinity interaction on-line with high-resolution separation, the fabrication of an "analyte concentrator-microreactor", optimization conditions of adsorption and desorption, the coupling to mass spectrometry, and various applications of clinical and pharmaceutical interest.

Recombinant drugs-on-a-chip: The usage of capillary electrophoresis and trends in miniaturized systems - A review.

PubMed

Morbioli, Giorgio Gianini; Mazzu-Nascimento, Thiago; Aquino, Adriano; Cervantes, Cesar; Carrilho, Emanuel

2016-09-07

We present here a critical review covering conventional analytical tools of recombinant drug analysis and discuss their evolution towards miniaturized systems foreseeing a possible unique recombinant drug-on-a-chip device. Recombinant protein drugs and/or pro-drug analysis require sensitive and reproducible analytical techniques for quality control to ensure safety and efficacy of drugs according to regulatory agencies. The versatility of miniaturized systems combined with their low-cost could become a major trend in recombinant drugs and bioprocess analysis. Miniaturized systems are capable of performing conventional analytical and proteomic tasks, allowing for interfaces with other powerful techniques, such as mass spectrometry. Microdevices can be applied during the different stages of recombinant drug processing, such as gene isolation, DNA amplification, cell culture, protein expression, protein separation, and analysis. In addition, organs-on-chips have appeared as a viable alternative to testing biodrug pharmacokinetics and pharmacodynamics, demonstrating the capabilities of the miniaturized systems. The integration of individual established microfluidic operations and analytical tools in a single device is a challenge to be overcome to achieve a unique recombinant drug-on-a-chip device. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of electromagnetic interference from power system processing and transmission components for Space Station Freedom

NASA Technical Reports Server (NTRS)

Barber, Peter W.; Demerdash, Nabeel A. O.; Wang, R.; Hurysz, B.; Luo, Z.

1991-01-01

The goal is to analyze the potential effects of electromagnetic interference (EMI) originating from power system processing and transmission components for Space Station Freedom.The approach consists of four steps: (1) develop analytical tools (models and computer programs); (2) conduct parameterization studies; (3) predict the global space station EMI environment; and (4) provide a basis for modification of EMI standards.

New Analytical Monographs on TCM Herbal Drugs for Quality Proof.

PubMed

Wagner, Hildebert; Bauer, Rudolf; Melchart, Dieter

2016-01-01

Regardless of specific national drug regulations there is an international consensus that all TCM drugs must meet stipulated high quality standards focusing on authentication, identification and chemical composition. In addition, safety of all TCM drugs prescribed by physicians has to be guaranteed. During the 25 years history of the TCM hospital Bad Kötzting, 171 TCM drugs underwent an analytical quality proof including thin layer as well as high pressure liquid chromatography. As from now mass spectroscopy will also be available as analytical tool. The findings are compiled and already published in three volumes of analytical monographs. One more volume will be published shortly, and a fifth volume is in preparation. The main issues of the analytical procedure in TCM drugs like authenticity, botanical nomenclature, variability of plant species and parts as well as processing are pointed out and possible ways to overcome them are sketched. © 2016 S. Karger GmbH, Freiburg.

Experimental evaluation of tool run-out in micro milling

NASA Astrophysics Data System (ADS)

Attanasio, Aldo; Ceretti, Elisabetta

2018-05-01

This paper deals with micro milling cutting process focusing the attention on tool run-out measurement. In fact, among the effects of the scale reduction from macro to micro (i.e., size effects) tool run-out plays an important role. This research is aimed at developing an easy and reliable method to measure tool run-out in micro milling based on experimental tests and an analytical model. From an Industry 4.0 perspective this measuring strategy can be integrated into an adaptive system for controlling cutting forces, with the objective of improving the production quality, the process stability, reducing at the same time the tool wear and the machining costs. The proposed procedure estimates the tool run-out parameters from the tool diameter, the channel width, and the phase angle between the cutting edges. The cutting edge phase measurement is based on the force signal analysis. The developed procedure has been tested on data coming from micro milling experimental tests performed on a Ti6Al4V sample. The results showed that the developed procedure can be successfully used for tool run-out estimation.

Competing on analytics.

PubMed

Davenport, Thomas H

2006-01-01

We all know the power of the killer app. It's not just a support tool; it's a strategic weapon. Companies questing for killer apps generally focus all their firepower on the one area that promises to create the greatest competitive advantage. But a new breed of organization has upped the stakes: Amazon, Harrah's, Capital One, and the Boston Red Sox have all dominated their fields by deploying industrial-strength analytics across a wide variety of activities. At a time when firms in many industries offer similar products and use comparable technologies, business processes are among the few remaining points of differentiation--and analytics competitors wring every last drop of value from those processes. Employees hired for their expertise with numbers or trained to recognize their importance are armed with the best evidence and the best quantitative tools. As a result, they make the best decisions. In companies that compete on analytics, senior executives make it clear--from the top down--that analytics is central to strategy. Such organizations launch multiple initiatives involving complex data and statistical analysis, and quantitative activity is managed atthe enterprise (not departmental) level. In this article, professor Thomas H. Davenport lays out the characteristics and practices of these statistical masters and describes some of the very substantial changes other companies must undergo in order to compete on quantitative turf. As one would expect, the transformation requires a significant investment in technology, the accumulation of massive stores of data, and the formulation of company-wide strategies for managing the data. But, at least as important, it also requires executives' vocal, unswerving commitment and willingness to change the way employees think, work, and are treated.

Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform

PubMed Central

Poucke, Sven Van; Zhang, Zhongheng; Schmitz, Martin; Vukicevic, Milan; Laenen, Margot Vander; Celi, Leo Anthony; Deyne, Cathy De

2016-01-01

With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner’s Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research. PMID:26731286

Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform.

PubMed

Van Poucke, Sven; Zhang, Zhongheng; Schmitz, Martin; Vukicevic, Milan; Laenen, Margot Vander; Celi, Leo Anthony; De Deyne, Cathy

2016-01-01

With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner's Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research.

Application of the Life Cycle Analysis and the Building Information Modelling Software in the Architectural Climate Change-Oriented Design Process

NASA Astrophysics Data System (ADS)

Gradziński, Piotr

2017-10-01

Whereas World’s climate is changing (inter alia, under the influence of architecture activity), the author attempts to reorientations design practice primarily in a direction the use and adapt to the climatic conditions. Architectural Design using in early stages of the architectural Design Process of the building, among other Life Cycle Analysis (LCA) and digital analytical tools BIM (Building Information Modelling) defines the overriding requirements which the designer/architect should meet. The first part, the text characterized the architecture activity influences (by consumption, pollution, waste, etc.) and the use of building materials (embodied energy, embodied carbon, Global Warming Potential, etc.) within the meaning of the direct negative environmental impact. The second part, the paper presents the revision of the methods and analytical techniques prevent negative influences. Firstly, showing the study of the building by using the Life Cycle Analysis of the structure (e.g. materials) and functioning (e.g. energy consumptions) of the architectural object (stages: before use, use, after use). Secondly, the use of digital analytical tools for determining the benefits of running multi-faceted simulations in terms of environmental factors (exposure to light, shade, wind) directly affecting shaping the form of the building. The conclusion, author’s research results highlight the fact that indicates the possibility of building design using the above-mentioned elements (LCA, BIM) causes correction, early designs decisions in the design process of architectural form, minimizing the impact on nature, environment. The work refers directly to the architectural-environmental dimensions, orienting the design process of buildings in respect of widely comprehended climatic changes.

Carbon dioxide gas purification and analytical measurement for leading edge 193nm lithography

NASA Astrophysics Data System (ADS)

Riddle Vogt, Sarah; Landoni, Cristian; Applegarth, Chuck; Browning, Matt; Succi, Marco; Pirola, Simona; Macchi, Giorgio

2015-03-01

The use of purified carbon dioxide (CO2) has become a reality for leading edge 193 nm immersion lithography scanners. Traditionally, both dry and immersion 193 nm lithographic processes have constantly purged the optics stack with ultrahigh purity compressed dry air (UHPCDA). CO2 has been utilized for a similar purpose as UHPCDA. Airborne molecular contamniation (AMC) purification technologies and analytical measurement methods have been extensively developed to support the Lithography Tool Manufacturers purity requirements. This paper covers the analytical tests and characterizations carried out to assess impurity removal from 3.0 N CO2 (beverage grade) for its final utilization in 193 nm and EUV scanners.

Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes

NASA Technical Reports Server (NTRS)

Williams Colin P.

1999-01-01

Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.

The Infrastructure of an Integrated Virtual Reality Environment for International Space Welding Experiment

NASA Technical Reports Server (NTRS)

Wang, Peter Hor-Ching

1996-01-01

This study is a continuation of the summer research of 1995 NASA/ASEE Summer Faculty Fellowship Program. This effort is to provide the infrastructure of an integrated Virtual Reality (VR) environment for the International Space Welding Experiment (ISWE) Analytical Tool and Trainer and the Microgravity Science Glovebox (MSG) Analytical Tool study. Due to the unavailability of the MSG CAD files and the 3D-CAD converter, little was done to the MSG study. However, the infrastructure of the integrated VR environment for ISWE is capable of performing the MSG study when the CAD files become available. Two primary goals are established for this research. First, the essential peripheral devices for an integrated VR environment will be studied and developed for the ISWE and MSG studies. Secondly, the training of the flight crew (astronaut) in general orientation, procedures, and location, orientation, and sequencing of the welding samples and tools are built into the VR system for studying the welding process and training the astronaut.

Real-Time Visualization of Network Behaviors for Situational Awareness

DOE Office of Scientific and Technical Information (OSTI.GOV)

Best, Daniel M.; Bohn, Shawn J.; Love, Douglas V.

Plentiful, complex, and dynamic data make understanding the state of an enterprise network difficult. Although visualization can help analysts understand baseline behaviors in network traffic and identify off-normal events, visual analysis systems often do not scale well to operational data volumes (in the hundreds of millions to billions of transactions per day) nor to analysis of emergent trends in real-time data. We present a system that combines multiple, complementary visualization techniques coupled with in-stream analytics, behavioral modeling of network actors, and a high-throughput processing platform called MeDICi. This system provides situational understanding of real-time network activity to help analysts takemore » proactive response steps. We have developed these techniques using requirements gathered from the government users for which the tools are being developed. By linking multiple visualization tools to a streaming analytic pipeline, and designing each tool to support a particular kind of analysis (from high-level awareness to detailed investigation), analysts can understand the behavior of a network across multiple levels of abstraction.« less

Prototyping Visual Learning Analytics Guided by an Educational Theory Informed Goal

ERIC Educational Resources Information Center

Hillaire, Garron; Rappolt-Schlichtmann, Gabrielle; Ducharme, Kim

2016-01-01

Prototype work can support the creation of data visualizations throughout the research and development process through paper prototypes with sketching, designed prototypes with graphic design tools, and functional prototypes to explore how the implementation will work. One challenging aspect of data visualization work is coordinating the expertise…

Past developments and future directions for the AHP in natural resources

Treesearch

Daniel L. Schmoldt; G.A. Mendoza; Jyrki Kangas

2001-01-01

The analytic hierarchy process (AHP) possesses certain characteristics that make it a useful tool for natural resource decision making. The AHP’s capabilities include: participatory decision making, problem structuring and alternative development, group facilitation, consensus building, fairness, qualitative and quantitative information, conflict resolution, decision...

A robust and flexible Geospatial Modeling Interface (GMI) for deploying and evaluating natural resource models

USDA-ARS?s Scientific Manuscript database

Geographical information systems (GIS) software packages have been used for nearly three decades as analytical tools in natural resource management for geospatial data assembly, processing, storage, and visualization of input data and model output. However, with increasing availability and use of fu...

Strategic Teaching: Student Learning through Working the Process

ERIC Educational Resources Information Center

Spanbroek, Nancy

2010-01-01

The designers of our future built environment must possess intellectual tools which will allow them to be disciplined, flexible and analytical thinkers, able to address and resolve new and complex problems. In response, an experimental and collaborative design studio was designed to inspire and build on students' knowledge and their creative…

Individual Human Cell Responses to Low Doses of Chemicals and Radiation Studied by Synchrotron Infrared Spectromicroscopy

NASA Astrophysics Data System (ADS)

Martin, Michael C.; Holman, Hoi-Ying N.; Blakely, Eleanor A.; Goth-Goldstein, Regine; McKinney, Wayne R.

2000-03-01

Vibrational spectroscopy, when combined with synchrotron radiation-based (SR) microscopy, is a powerful new analytical tool with high spatial resolution for detecting biochemical changes in individual living cells. In contrast to other microscopy methods that require fixing, drying, staining or labeling, SR FTIR microscopy probes intact living cells providing a composite view of all of the molecular responses and the ability to monitor the responses over time in the same cell. Observed spectral changes include all types of lesions induced in that cell as well as cellular responses to external and internal stresses. These spectral changes combined with other analytical tools may provide a fundamental understanding of the key molecular mechanisms induced in response to stresses created by low-doses of radiation and chemicals. In this study we used high spatial-resolution SR FTIR vibrational spectromicroscopy at ALS Beamline 1.4.3 as a sensitive analytical tool to detect chemical- and radiation-induced changes in individual human cells. Our preliminary spectral measurements indicate that this technique is sensitive enough to detect changes in nucleic acids and proteins of cells treated with environmentally relevant concentrations of oxidative stresses: bleomycin, hydrogen peroxide, and X-rays. We observe spectral changes that are unique to each exogenous stressor. This technique has the potential to distinguish changes from exogenous or endogenous oxidative processes. Future development of this technique will allow rapid monitoring of cellular processes such as drug metabolism, early detection of disease, bio-compatibility of implant materials, cellular repair mechanisms, self assembly of cellular apparatus, cell differentiation and fetal development.

WetDATA Hub: Democratizing Access to Water Data to Accelerate Innovation through Data Visualization, Predictive Analytics and Artificial Intelligence Applications

NASA Astrophysics Data System (ADS)

Sarni, W.

2017-12-01

Water scarcity and poor quality impacts economic development, business growth, and social well-being. Water has become, in our generation, the foremost critical local, regional, and global issue of our time. Despite these needs, there is no water hub or water technology accelerator solely dedicated to water data and tools. There is a need by the public and private sectors for vastly improved data management and visualization tools. This is the WetDATA opportunity - to develop a water data tech hub dedicated to water data acquisition, analytics, and visualization tools for informed policy and business decisions. WetDATA's tools will help incubate disruptive water data technologies and accelerate adoption of current water data solutions. WetDATA is a Colorado-based (501c3), global hub for water data analytics and technology innovation. WetDATA's vision is to be a global leader in water information, data technology innovation and collaborate with other US and global water technology hubs. ROADMAP * Portal (www.wetdata.org) to provide stakeholders with tools/resources to understand related water risks. * The initial activities will provide education, awareness and tools to stakeholders to support the implementation of the Colorado State Water Plan. * Leverage the Western States Water Council Water Data Exchange database. * Development of visualization, predictive analytics and AI tools to engage with stakeholders and provide actionable data and information. TOOLS Education: Provide information on water issues and risks at the local, state, national and global scale. Visualizations: Development of data analytics and visualization tools based upon the 2030 Water Resources Group methodology to support the implementation of the Colorado State Water Plan. Predictive Analytics: Accessing publically available water databases and using machine learning to develop water availability forecasting tools, and time lapse images to support city / urban planning.

Analytical Tools in School Finance Reform.

ERIC Educational Resources Information Center

Johns, R. L.

This paper discusses the problem of analyzing variations in the educational opportunities provided by different school districts and describes how to assess the impact of school finance alternatives through use of various analytical tools. The author first examines relatively simple analytical methods, including calculation of per-pupil…

Managing complex research datasets using electronic tools: A meta-analysis exemplar

PubMed Central

Brown, Sharon A.; Martin, Ellen E.; Garcia, Theresa J.; Winter, Mary A.; García, Alexandra A.; Brown, Adama; Cuevas, Heather E.; Sumlin, Lisa L.

2013-01-01

Meta-analyses of broad scope and complexity require investigators to organize many study documents and manage communication among several research staff. Commercially available electronic tools, e.g., EndNote, Adobe Acrobat Pro, Blackboard, Excel, and IBM SPSS Statistics (SPSS), are useful for organizing and tracking the meta-analytic process, as well as enhancing communication among research team members. The purpose of this paper is to describe the electronic processes we designed, using commercially available software, for an extensive quantitative model-testing meta-analysis we are conducting. Specific electronic tools improved the efficiency of (a) locating and screening studies, (b) screening and organizing studies and other project documents, (c) extracting data from primary studies, (d) checking data accuracy and analyses, and (e) communication among team members. The major limitation in designing and implementing a fully electronic system for meta-analysis was the requisite upfront time to: decide on which electronic tools to use, determine how these tools would be employed, develop clear guidelines for their use, and train members of the research team. The electronic process described here has been useful in streamlining the process of conducting this complex meta-analysis and enhancing communication and sharing documents among research team members. PMID:23681256

Managing complex research datasets using electronic tools: a meta-analysis exemplar.

PubMed

Brown, Sharon A; Martin, Ellen E; Garcia, Theresa J; Winter, Mary A; García, Alexandra A; Brown, Adama; Cuevas, Heather E; Sumlin, Lisa L

2013-06-01

Meta-analyses of broad scope and complexity require investigators to organize many study documents and manage communication among several research staff. Commercially available electronic tools, for example, EndNote, Adobe Acrobat Pro, Blackboard, Excel, and IBM SPSS Statistics (SPSS), are useful for organizing and tracking the meta-analytic process as well as enhancing communication among research team members. The purpose of this article is to describe the electronic processes designed, using commercially available software, for an extensive, quantitative model-testing meta-analysis. Specific electronic tools improved the efficiency of (a) locating and screening studies, (b) screening and organizing studies and other project documents, (c) extracting data from primary studies, (d) checking data accuracy and analyses, and (e) communication among team members. The major limitation in designing and implementing a fully electronic system for meta-analysis was the requisite upfront time to decide on which electronic tools to use, determine how these tools would be used, develop clear guidelines for their use, and train members of the research team. The electronic process described here has been useful in streamlining the process of conducting this complex meta-analysis and enhancing communication and sharing documents among research team members.

An analytical method for prediction of stability lobes diagram of milling of large-size thin-walled workpiece

NASA Astrophysics Data System (ADS)

Yao, Jiming; Lin, Bin; Guo, Yu

2017-01-01

Different from common thin-walled workpiece, in the process of milling of large-size thin-walled workpiece chatter in the axial direction along the spindle is also likely to happen because of the low stiffness of the workpiece in this direction. An analytical method for prediction of stability lobes of milling of large-size thin-walled workpiece is presented in this paper. In the method, not only frequency response function of the tool point but also frequency response function of the workpiece is considered.

Analytical Design Package (ADP2): A computer aided engineering tool for aircraft transparency design

NASA Technical Reports Server (NTRS)

Wuerer, J. E.; Gran, M.; Held, T. W.

1994-01-01

The Analytical Design Package (ADP2) is being developed as a part of the Air Force Frameless Transparency Program (FTP). ADP2 is an integrated design tool consisting of existing analysis codes and Computer Aided Engineering (CAE) software. The objective of the ADP2 is to develop and confirm an integrated design methodology for frameless transparencies, related aircraft interfaces, and their corresponding tooling. The application of this methodology will generate high confidence for achieving a qualified part prior to mold fabrication. ADP2 is a customized integration of analysis codes, CAE software, and material databases. The primary CAE integration tool for the ADP2 is P3/PATRAN, a commercial-off-the-shelf (COTS) software tool. The open architecture of P3/PATRAN allows customized installations with different applications modules for specific site requirements. Integration of material databases allows the engineer to select a material, and those material properties are automatically called into the relevant analysis code. The ADP2 materials database will be composed of four independent schemas: CAE Design, Processing, Testing, and Logistics Support. The design of ADP2 places major emphasis on the seamless integration of CAE and analysis modules with a single intuitive graphical interface. This tool is being designed to serve and be used by an entire project team, i.e., analysts, designers, materials experts, and managers. The final version of the software will be delivered to the Air Force in Jan. 1994. The Analytical Design Package (ADP2) will then be ready for transfer to industry. The package will be capable of a wide range of design and manufacturing applications.

BFPTool: a software tool for analysis of Biomembrane Force Probe experiments.

PubMed

Šmít, Daniel; Fouquet, Coralie; Doulazmi, Mohamed; Pincet, Frédéric; Trembleau, Alain; Zapotocky, Martin

2017-01-01

The Biomembrane Force Probe is an approachable experimental technique commonly used for single-molecule force spectroscopy and experiments on biological interfaces. The technique operates in the range of forces from 0.1 pN to 1000 pN. Experiments are typically repeated many times, conditions are often not optimal, the captured video can be unstable and lose focus; this makes efficient analysis challenging, while out-of-the-box non-proprietary solutions are not freely available. This dedicated tool was developed to integrate and simplify the image processing and analysis of videomicroscopy recordings from BFP experiments. A novel processing feature, allowing the tracking of the pipette, was incorporated to address a limitation of preceding methods. Emphasis was placed on versatility and comprehensible user interface implemented in a graphical form. An integrated analytical tool was implemented to provide a faster, simpler and more convenient way to process and analyse BFP experiments.

Impact Of The Material Variability On The Stamping Process: Numerical And Analytical Analysis

NASA Astrophysics Data System (ADS)

Ledoux, Yann; Sergent, Alain; Arrieux, Robert

2007-05-01

The finite element simulation is a very useful tool in the deep drawing industry. It is used more particularly for the development and the validation of new stamping tools. It allows to decrease cost and time for the tooling design and set up. But one of the most important difficulties to have a good agreement between the simulation and the real process comes from the definition of the numerical conditions (mesh, punch travel speed, limit conditions,…) and the parameters which model the material behavior. Indeed, in press shop, when the sheet set changes, often a variation of the formed part geometry is observed according to the variability of the material properties between these different sets. This last parameter represents probably one of the main source of process deviation when the process is set up. That's why it is important to study the influence of material data variation on the geometry of a classical stamped part. The chosen geometry is an omega shaped part because of its simplicity and it is representative one in the automotive industry (car body reinforcement). Moreover, it shows important springback deviations. An isotropic behaviour law is assumed. The impact of the statistical deviation of the three law coefficients characterizing the material and the friction coefficient around their nominal values is tested. A Gaussian distribution is supposed and their impact on the geometry variation is studied by FE simulation. An other approach is envisaged consisting in modeling the process variability by a mathematical model and then, in function of the input parameters variability, it is proposed to define an analytical model which leads to find the part geometry variability around the nominal shape. These two approaches allow to predict the process capability as a function of the material parameter variability.

An integrated process analytical technology (PAT) approach to monitoring the effect of supercooling on lyophilization product and process parameters of model monoclonal antibody formulations.

PubMed

Awotwe Otoo, David; Agarabi, Cyrus; Khan, Mansoor A

2014-07-01

The aim of the present study was to apply an integrated process analytical technology (PAT) approach to control and monitor the effect of the degree of supercooling on critical process and product parameters of a lyophilization cycle. Two concentrations of a mAb formulation were used as models for lyophilization. ControLyo™ technology was applied to control the onset of ice nucleation, whereas tunable diode laser absorption spectroscopy (TDLAS) was utilized as a noninvasive tool for the inline monitoring of the water vapor concentration and vapor flow velocity in the spool during primary drying. The instantaneous measurements were then used to determine the effect of the degree of supercooling on critical process and product parameters. Controlled nucleation resulted in uniform nucleation at lower degrees of supercooling for both formulations, higher sublimation rates, lower mass transfer resistance, lower product temperatures at the sublimation interface, and shorter primary drying times compared with the conventional shelf-ramped freezing. Controlled nucleation also resulted in lyophilized cakes with more elegant and porous structure with no visible collapse or shrinkage, lower specific surface area, and shorter reconstitution times compared with the uncontrolled nucleation. Uncontrolled nucleation however resulted in lyophilized cakes with relatively lower residual moisture contents compared with controlled nucleation. TDLAS proved to be an efficient tool to determine the endpoint of primary drying. There was good agreement between data obtained from TDLAS-based measurements and SMART™ technology. ControLyo™ technology and TDLAS showed great potential as PAT tools to achieve enhanced process monitoring and control during lyophilization cycles. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Visual Analytics Tools for Sustainable Lifecycle Design: Current Status, Challenges, and Future Opportunities.

PubMed

Ramanujan, Devarajan; Bernstein, William Z; Chandrasegaran, Senthil K; Ramani, Karthik

2017-01-01

The rapid rise in technologies for data collection has created an unmatched opportunity to advance the use of data-rich tools for lifecycle decision-making. However, the usefulness of these technologies is limited by the ability to translate lifecycle data into actionable insights for human decision-makers. This is especially true in the case of sustainable lifecycle design (SLD), as the assessment of environmental impacts, and the feasibility of making corresponding design changes, often relies on human expertise and intuition. Supporting human sense-making in SLD requires the use of both data-driven and user-driven methods while exploring lifecycle data. A promising approach for combining the two is through the use of visual analytics (VA) tools. Such tools can leverage the ability of computer-based tools to gather, process, and summarize data along with the ability of human-experts to guide analyses through domain knowledge or data-driven insight. In this paper, we review previous research that has created VA tools in SLD. We also highlight existing challenges and future opportunities for such tools in different lifecycle stages-design, manufacturing, distribution & supply chain, use-phase, end-of-life, as well as life cycle assessment. Our review shows that while the number of VA tools in SLD is relatively small, researchers are increasingly focusing on the subject matter. Our review also suggests that VA tools can address existing challenges in SLD and that significant future opportunities exist.

Machine Learning Technologies Translates Vigilant Surveillance Satellite Big Data into Predictive Alerts for Environmental Stressors

NASA Astrophysics Data System (ADS)

Johnson, S. P.; Rohrer, M. E.

2017-12-01

The application of scientific research pertaining to satellite imaging and data processing has facilitated the development of dynamic methodologies and tools that utilize nanosatellites and analytical platforms to address the increasing scope, scale, and intensity of emerging environmental threats to national security. While the use of remotely sensed data to monitor the environment at local and global scales is not a novel proposition, the application of advances in nanosatellites and analytical platforms are capable of overcoming the data availability and accessibility barriers that have historically impeded the timely detection, identification, and monitoring of these stressors. Commercial and university-based applications of these technologies were used to identify and evaluate their capacity as security-motivated environmental monitoring tools. Presently, nanosatellites can provide consumers with 1-meter resolution imaging, frequent revisits, and customizable tasking, allowing users to define an appropriate temporal scale for high resolution data collection that meets their operational needs. Analytical platforms are capable of ingesting increasingly large and diverse volumes of data, delivering complex analyses in the form of interpretation-ready data products and solutions. The synchronous advancement of these technologies creates the capability of analytical platforms to deliver interpretable products from persistently collected high-resolution data that meet varying temporal and geographic scale requirements. In terms of emerging environmental threats, these advances translate into customizable and flexible tools that can respond to and accommodate the evolving nature of environmental stressors. This presentation will demonstrate the capability of nanosatellites and analytical platforms to provide timely, relevant, and actionable information that enables environmental analysts and stakeholders to make informed decisions regarding the prevention, intervention, and prediction of emerging environmental threats.

Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

PubMed

Ebrahimie, Esmaeil; Fruzangohar, Mario; Moussavi Nik, Seyyed Hani; Newman, Morgan

2017-10-01

Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in revealing functional mechanisms underlying observed patterns in transcriptomic, genomic, and proteomic data. The already extensive and increasing use of zebrafish for modeling genetic and other diseases highlights the need to develop a GO analytical tool for this organism. The web tool Comparative GO was originally developed for GO analysis of bacterial data in 2013 ( www.comparativego.com ). We have now upgraded and elaborated this web tool for analysis of zebrafish genetic data using GOs and annotations from the Gene Ontology Consortium.

How do gut feelings feature in tutorial dialogues on diagnostic reasoning in GP traineeship?

PubMed

Stolper, C F; Van de Wiel, M W J; Hendriks, R H M; Van Royen, P; Van Bokhoven, M A; Van der Weijden, T; Dinant, G J

2015-05-01

Diagnostic reasoning is considered to be based on the interaction between analytical and non-analytical cognitive processes. Gut feelings, a specific form of non-analytical reasoning, play a substantial role in diagnostic reasoning by general practitioners (GPs) and may activate analytical reasoning. In GP traineeships in the Netherlands, trainees mostly see patients alone but regularly consult with their supervisors to discuss patients and problems, receive feedback, and improve their competencies. In the present study, we examined the discussions of supervisors and their trainees about diagnostic reasoning in these so-called tutorial dialogues and how gut feelings feature in these discussions. 17 tutorial dialogues focussing on diagnostic reasoning were video-recorded and transcribed and the protocols were analysed using a detailed bottom-up and iterative content analysis and coding procedure. The dialogues were segmented into quotes. Each quote received a content code and a participant code. The number of words per code was used as a unit of analysis to quantitatively compare the contributions to the dialogues made by supervisors and trainees, and the attention given to different topics. The dialogues were usually analytical reflections on a trainee's diagnostic reasoning. A hypothetico-deductive strategy was often used, by listing differential diagnoses and discussing what information guided the reasoning process and might confirm or exclude provisional hypotheses. Gut feelings were discussed in seven dialogues. They were used as a tool in diagnostic reasoning, inducing analytical reflection, sometimes on the entire diagnostic reasoning process. The emphasis in these tutorial dialogues was on analytical components of diagnostic reasoning. Discussing gut feelings in tutorial dialogues seems to be a good educational method to familiarize trainees with non-analytical reasoning. Supervisors need specialised knowledge about these aspects of diagnostic reasoning and how to deal with them in medical education.

Source-term development for a contaminant plume for use by multimedia risk assessment models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whelan, Gene; McDonald, John P.; Taira, Randal Y.

1999-12-01

Multimedia modelers from the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Energy (DOE) are collaborating to conduct a comprehensive and quantitative benchmarking analysis of four intermedia models: DOE's Multimedia Environmental Pollutant Assessment System (MEPAS), EPA's MMSOILS, EPA's PRESTO, and DOE's RESidual RADioactivity (RESRAD). These models represent typical analytically, semi-analytically, and empirically based tools that are utilized in human risk and endangerment assessments for use at installations containing radioactive and/or hazardous contaminants. Although the benchmarking exercise traditionally emphasizes the application and comparison of these models, the establishment of a Conceptual Site Model (CSM) should be viewed with equalmore » importance. This paper reviews an approach for developing a CSM of an existing, real-world, Sr-90 plume at DOE's Hanford installation in Richland, Washington, for use in a multimedia-based benchmarking exercise bet ween MEPAS, MMSOILS, PRESTO, and RESRAD. In an unconventional move for analytically based modeling, the benchmarking exercise will begin with the plume as the source of contamination. The source and release mechanism are developed and described within the context of performing a preliminary risk assessment utilizing these analytical models. By beginning with the plume as the source term, this paper reviews a typical process and procedure an analyst would follow in developing a CSM for use in a preliminary assessment using this class of analytical tool.« less

Simulation supported POD for RT test case-concept and modeling

NASA Astrophysics Data System (ADS)

Gollwitzer, C.; Bellon, C.; Deresch, A.; Ewert, U.; Jaenisch, G.-R.; Zscherpel, U.; Mistral, Q.

2012-05-01

Within the framework of the European project PICASSO, the radiographic simulator aRTist (analytical Radiographic Testing inspection simulation tool) developed by BAM has been extended for reliability assessment of film and digital radiography. NDT of safety relevant components of aerospace industry requires the proof of probability of detection (POD) of the inspection. Modeling tools can reduce the expense of such extended, time consuming NDT trials, if the result of simulation fits to the experiment. Our analytic simulation tool consists of three modules for the description of the radiation source, the interaction of radiation with test pieces and flaws, and the detection process with special focus on film and digital industrial radiography. It features high processing speed with near-interactive frame rates and a high level of realism. A concept has been developed as well as a software extension for reliability investigations, completed by a user interface for planning automatic simulations with varying parameters and defects. Furthermore, an automatic image analysis procedure is included to evaluate the defect visibility. The radiographic modeling from 3D CAD of aero engine components and quality test samples are compared as a precondition for real trials. This enables the evaluation and optimization of film replacement for application of modern digital equipment for economical NDT and defined POD.

Importance of implementing an analytical quality control system in a core laboratory.

PubMed

Marques-Garcia, F; Garcia-Codesal, M F; Caro-Narros, M R; Contreras-SanFeliciano, T

2015-01-01

The aim of the clinical laboratory is to provide useful information for screening, diagnosis and monitoring of disease. The laboratory should ensure the quality of extra-analytical and analytical process, based on set criteria. To do this, it develops and implements a system of internal quality control, designed to detect errors, and compare its data with other laboratories, through external quality control. In this way it has a tool to detect the fulfillment of the objectives set, and in case of errors, allowing corrective actions to be made, and ensure the reliability of the results. This article sets out to describe the design and implementation of an internal quality control protocol, as well as its periodical assessment intervals (6 months) to determine compliance with pre-determined specifications (Stockholm Consensus(1)). A total of 40 biochemical and 15 immunochemical methods were evaluated using three different control materials. Next, a standard operation procedure was planned to develop a system of internal quality control that included calculating the error of the analytical process, setting quality specifications, and verifying compliance. The quality control data were then statistically depicted as means, standard deviations, and coefficients of variation, as well as systematic, random, and total errors. The quality specifications were then fixed and the operational rules to apply in the analytical process were calculated. Finally, our data were compared with those of other laboratories through an external quality assurance program. The development of an analytical quality control system is a highly structured process. This should be designed to detect errors that compromise the stability of the analytical process. The laboratory should review its quality indicators, systematic, random and total error at regular intervals, in order to ensure that they are meeting pre-determined specifications, and if not, apply the appropriate corrective actions. Copyright © 2015 SECA. Published by Elsevier Espana. All rights reserved.

Enhance your team-based qualitative research.

PubMed

Fernald, Douglas H; Duclos, Christine W

2005-01-01

Qualitative research projects often involve the collaborative efforts of a research team. Challenges inherent in teamwork include changes in membership and differences in analytical style, philosophy, training, experience, and skill. This article discusses teamwork issues and tools and techniques used to improve team-based qualitative research. We drew on our experiences in working on numerous projects of varying, size, duration, and purpose. Through trials of different tools and techniques, expert consultation, and review of the literature, we learned to improve how we build teams, manage information, and disseminate results. Attention given to team members and team processes is as important as choosing appropriate analytical tools and techniques. Attentive team leadership, commitment to early and regular team meetings, and discussion of roles, responsibilities, and expectations all help build more effective teams and establish clear norms. As data are collected and analyzed, it is important to anticipate potential problems from differing skills and styles, and how information and files are managed. Discuss analytical preferences and biases and set clear guidelines and practices for how data will be analyzed and handled. As emerging ideas and findings disperse across team members, common tools (such as summary forms and data grids), coding conventions, intermediate goals or products, and regular documentation help capture essential ideas and insights. In a team setting, little should be left to chance. This article identifies ways to improve team-based qualitative research with more a considered and systematic approach. Qualitative researchers will benefit from further examination and discussion of effective, field-tested, team-based strategies.

Implementation of quality by design toward processing of food products.

PubMed

Rathore, Anurag S; Kapoor, Gautam

2017-05-28

Quality by design (QbD) is a systematic approach that begins with predefined objectives and emphasizes product and process understanding and process control. It is an approach based on principles of sound science and quality risk management. As the food processing industry continues to embrace the idea of in-line, online, and/or at-line sensors and real-time characterization for process monitoring and control, the existing gaps with regard to our ability to monitor multiple parameters/variables associated with the manufacturing process will be alleviated over time. Investments made for development of tools and approaches that facilitate high-throughput analytical and process development, process analytical technology, design of experiments, risk analysis, knowledge management, and enhancement of process/product understanding would pave way for operational and economic benefits later in the commercialization process and across other product pipelines. This article aims to achieve two major objectives. First, to review the progress that has been made in the recent years on the topic of QbD implementation in processing of food products and second, present a case study that illustrates benefits of such QbD implementation.

Modeling of thermal processes arising during shaping gears with internal non-involute teeth

NASA Astrophysics Data System (ADS)

Kanatnikov, N. V.; Kanatnikova, P. A.; Vlasov, V. V.; Pashmentova, A. S.

2018-03-01

The paper presents a model for predicting the thermal processes arising during shaping gears with internal non-involute teeth. The kinematics of cutting is modeled due to the analytical model. Chipping is modeled using the finite element method. The experiment is based on the method of infrared photography of the cutting process. The simulation results showed that the maximum temperatures and heat flows in the tool vary by more than 10% when the rake and clearance angels of the cutting are changed.

Analytical and multibody modeling for the power analysis of standing jumps.

PubMed

Palmieri, G; Callegari, M; Fioretti, S

2015-01-01

Two methods for the power analysis of standing jumps are proposed and compared in this article. The first method is based on a simple analytical formulation which requires as input the coordinates of the center of gravity in three specified instants of the jump. The second method is based on a multibody model that simulates the jumps processing the data obtained by a three-dimensional (3D) motion capture system and the dynamometric measurements obtained by the force platforms. The multibody model is developed with OpenSim, an open-source software which provides tools for the kinematic and dynamic analyses of 3D human body models. The study is focused on two of the typical tests used to evaluate the muscular activity of lower limbs, which are the counter movement jump and the standing long jump. The comparison between the results obtained by the two methods confirms that the proposed analytical formulation is correct and represents a simple tool suitable for a preliminary analysis of total mechanical work and the mean power exerted in standing jumps.

Statistical process control in nursing research.

PubMed

Polit, Denise F; Chaboyer, Wendy

2012-02-01

In intervention studies in which randomization to groups is not possible, researchers typically use quasi-experimental designs. Time series designs are strong quasi-experimental designs but are seldom used, perhaps because of technical and analytic hurdles. Statistical process control (SPC) is an alternative analytic approach to testing hypotheses about intervention effects using data collected over time. SPC, like traditional statistical methods, is a tool for understanding variation and involves the construction of control charts that distinguish between normal, random fluctuations (common cause variation), and statistically significant special cause variation that can result from an innovation. The purpose of this article is to provide an overview of SPC and to illustrate its use in a study of a nursing practice improvement intervention. Copyright © 2011 Wiley Periodicals, Inc.

LipidQC: Method Validation Tool for Visual Comparison to SRM 1950 Using NIST Interlaboratory Comparison Exercise Lipid Consensus Mean Estimate Values.

PubMed

Ulmer, Candice Z; Ragland, Jared M; Koelmel, Jeremy P; Heckert, Alan; Jones, Christina M; Garrett, Timothy J; Yost, Richard A; Bowden, John A

2017-12-19

As advances in analytical separation techniques, mass spectrometry instrumentation, and data processing platforms continue to spur growth in the lipidomics field, more structurally unique lipid species are detected and annotated. The lipidomics community is in need of benchmark reference values to assess the validity of various lipidomics workflows in providing accurate quantitative measurements across the diverse lipidome. LipidQC addresses the harmonization challenge in lipid quantitation by providing a semiautomated process, independent of analytical platform, for visual comparison of experimental results of National Institute of Standards and Technology Standard Reference Material (SRM) 1950, "Metabolites in Frozen Human Plasma", against benchmark consensus mean concentrations derived from the NIST Lipidomics Interlaboratory Comparison Exercise.

Harnessing scientific literature reports for pharmacovigilance. Prototype software analytical tool development and usability testing.

PubMed

Sorbello, Alfred; Ripple, Anna; Tonning, Joseph; Munoz, Monica; Hasan, Rashedul; Ly, Thomas; Francis, Henry; Bodenreider, Olivier

2017-03-22

We seek to develop a prototype software analytical tool to augment FDA regulatory reviewers' capacity to harness scientific literature reports in PubMed/MEDLINE for pharmacovigilance and adverse drug event (ADE) safety signal detection. We also aim to gather feedback through usability testing to assess design, performance, and user satisfaction with the tool. A prototype, open source, web-based, software analytical tool generated statistical disproportionality data mining signal scores and dynamic visual analytics for ADE safety signal detection and management. We leveraged Medical Subject Heading (MeSH) indexing terms assigned to published citations in PubMed/MEDLINE to generate candidate drug-adverse event pairs for quantitative data mining. Six FDA regulatory reviewers participated in usability testing by employing the tool as part of their ongoing real-life pharmacovigilance activities to provide subjective feedback on its practical impact, added value, and fitness for use. All usability test participants cited the tool's ease of learning, ease of use, and generation of quantitative ADE safety signals, some of which corresponded to known established adverse drug reactions. Potential concerns included the comparability of the tool's automated literature search relative to a manual 'all fields' PubMed search, missing drugs and adverse event terms, interpretation of signal scores, and integration with existing computer-based analytical tools. Usability testing demonstrated that this novel tool can automate the detection of ADE safety signals from published literature reports. Various mitigation strategies are described to foster improvements in design, productivity, and end user satisfaction.

Re-evaluating causal modeling with mantel tests in landscape genetics

Treesearch

Samuel A. Cushman; Tzeidle N. Wasserman; Erin L. Landguth; Andrew J. Shirk

2013-01-01

The predominant analytical approach to associate landscape patterns with gene flow processes is based on the association of cost distances with genetic distances between individuals. Mantel and partial Mantel tests have been the dominant statistical tools used to correlate cost distances and genetic distances in landscape genetics. However, the inherent high...

Researching Writing Events: Using Mediated Discourse Analysis to Explore How Students Write Together

ERIC Educational Resources Information Center

Rish, Ryan M.

2015-01-01

This article addresses how mediated discourse theory and related analytical tools can be used to explore how students write together. Considered within a sociocultural framework that conceptualises writing as involving distributed, mediated and dialogic processes of invention, this article presents an investigation of how three high school…

Pedagogy through the Pearl Metaphor: Teaching as a Process of Ongoing Refinement

ERIC Educational Resources Information Center

Craig, Cheryl J.; You, JeongAe; Oh, Suhak

2017-01-01

Using the analytical tools of broadening, burrowing and storying and restorying, this narrative inquiry examines a middle school teachers' knowledge of her pedagogical practices through the strand of pearls' metaphor that she employs to explain her teaching to herself, a beginning teacher whom she mentors and ourselves as researchers. Throughout…

Combining Simulation and Optimization Models for Hardwood Lumber Production

Treesearch

G.A. Mendoza; R.J. Meimban; W.G. Luppold; Philip A. Araman

1991-01-01

Published literature contains a number of optimization and simulation models dealing with the primary processing of hardwood and softwood logs. Simulation models have been developed primarily as descriptive models for characterizing the general operations and performance of a sawmill. Optimization models, on the other hand, were developed mainly as analytical tools for...

Addressing Misconceptions in Geometry through Written Error Analyses

ERIC Educational Resources Information Center

Kembitzky, Kimberle A.

2009-01-01

This study examined the improvement of students' comprehension of geometric concepts through analytical writing about their own misconceptions using a reflective tool called an ERNIe (acronym for ERror aNalyIsis). The purpose of this study was to determine whether the ERNIe process could be used to correct geometric misconceptions, as well as how…

Teacher Acceptance of Evaluation through Productivity Management.

ERIC Educational Resources Information Center

Garrett, A. Warren

This paper describes the purposes of educational evaluation with particular emphasis on school improvement. The evaluation process used was based upon the analytical tools developed and tested by the Educational Productivity Council (EPC) of the University of Texas. An early form of this model and reporting system was introduced to a group of 68…

From Streaming Data to Streaming Insights: The Impact of Data Velocities on Mental Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Endert, Alexander; Pike, William A.; Cook, Kristin A.

The rise of Big Data has influenced the design and technical implementation of visual analytic tools required to handle the increased volumes, velocities, and varieties of data. This has required a set of data management and computational advancements to allow us to store and compute on such datasets. However, as the ultimate goal of visual analytic technology is to enable the discovery and creation of insights from the users, an under-explored area is understanding how these datasets impact their mental models. That is, how have the analytic processes and strategies of users changed? How have users changed their perception ofmore » how to leverage, and ask questions of, these datasets?« less

A Progressive Approach to Teaching Analytics in the Marketing Curriculum

ERIC Educational Resources Information Center

Liu, Yiyuan; Levin, Michael A.

2018-01-01

With the emerging use of analytics tools and methodologies in marketing, marketing educators have provided students training and experiences beyond the soft skills associated with understanding consumer behavior. Previous studies have only discussed how to apply analytics in course designs, tools, and related practices. However, there is a lack of…

Median of patient results as a tool for assessment of analytical stability.

PubMed

Jørgensen, Lars Mønster; Hansen, Steen Ingemann; Petersen, Per Hyltoft; Sölétormos, György

2015-06-15

In spite of the well-established external quality assessment and proficiency testing surveys of analytical quality performance in laboratory medicine, a simple tool to monitor the long-term analytical stability as a supplement to the internal control procedures is often needed. Patient data from daily internal control schemes was used for monthly appraisal of the analytical stability. This was accomplished by using the monthly medians of patient results to disclose deviations from analytical stability, and by comparing divergences with the quality specifications for allowable analytical bias based on biological variation. Seventy five percent of the twenty analytes achieved on two COBASs INTEGRA 800 instruments performed in accordance with the optimum and with the desirable specifications for bias. Patient results applied in analytical quality performance control procedures are the most reliable sources of material as they represent the genuine substance of the measurements and therefore circumvent the problems associated with non-commutable materials in external assessment. Patient medians in the monthly monitoring of analytical stability in laboratory medicine are an inexpensive, simple and reliable tool to monitor the steadiness of the analytical practice. Copyright © 2015 Elsevier B.V. All rights reserved.

Ku-band signal design study. [space shuttle orbiter data processing network

NASA Technical Reports Server (NTRS)

Rubin, I.

1978-01-01

Analytical tools, methods and techniques for assessing the design and performance of the space shuttle orbiter data processing system (DPS) are provided. The computer data processing network is evaluated in the key areas of queueing behavior synchronization and network reliability. The structure of the data processing network is described as well as the system operation principles and the network configuration. The characteristics of the computer systems are indicated. System reliability measures are defined and studied. System and network invulnerability measures are computed. Communication path and network failure analysis techniques are included.

A Combined Experimental and Analytical Modeling Approach to Understanding Friction Stir Welding

NASA Technical Reports Server (NTRS)

Nunes, Arthur C., Jr.; Stewart, Michael B.; Adams, Glynn P.; Romine, Peter

1998-01-01

In the Friction Stir Welding (FSW) process a rotating pin tool joins the sides of a seam by stirring them together. This solid state welding process avoids problems with melting and hot-shortness presented by some difficult-to weld high-performance light alloys. The details of the plastic flow during the process are not well understood and are currently a subject of research. Two candidate models of the FSW process, the Mixed Zone (MZ) and the Single Slip Surface (S3) model are presented and their predictions compared to experimental data.

Finite-difference time-domain modelling of through-the-Earth radio signal propagation

NASA Astrophysics Data System (ADS)

Ralchenko, M.; Svilans, M.; Samson, C.; Roper, M.

2015-12-01

This research seeks to extend the knowledge of how a very low frequency (VLF) through-the-Earth (TTE) radio signal behaves as it propagates underground, by calculating and visualizing the strength of the electric and magnetic fields for an arbitrary geology through numeric modelling. To achieve this objective, a new software tool has been developed using the finite-difference time-domain method. This technique is particularly well suited to visualizing the distribution of electromagnetic fields in an arbitrary geology. The frequency range of TTE radio (400-9000 Hz) and geometrical scales involved (1 m resolution for domains a few hundred metres in size) involves processing a grid composed of millions of cells for thousands of time steps, which is computationally expensive. Graphics processing unit acceleration was used to reduce execution time from days and weeks, to minutes and hours. Results from the new modelling tool were compared to three cases for which an analytic solution is known. Two more case studies were done featuring complex geologic environments relevant to TTE communications that cannot be solved analytically. There was good agreement between numeric and analytic results. Deviations were likely caused by numeric artifacts from the model boundaries; however, in a TTE application in field conditions, the uncertainty in the conductivity of the various geologic formations will greatly outweigh these small numeric errors.

Current Technical Approaches for the Early Detection of Foodborne Pathogens: Challenges and Opportunities.

PubMed

Cho, Il-Hoon; Ku, Seockmo

2017-09-30

The development of novel and high-tech solutions for rapid, accurate, and non-laborious microbial detection methods is imperative to improve the global food supply. Such solutions have begun to address the need for microbial detection that is faster and more sensitive than existing methodologies (e.g., classic culture enrichment methods). Multiple reviews report the technical functions and structures of conventional microbial detection tools. These tools, used to detect pathogens in food and food homogenates, were designed via qualitative analysis methods. The inherent disadvantage of these analytical methods is the necessity for specimen preparation, which is a time-consuming process. While some literature describes the challenges and opportunities to overcome the technical issues related to food industry legal guidelines, there is a lack of reviews of the current trials to overcome technological limitations related to sample preparation and microbial detection via nano and micro technologies. In this review, we primarily explore current analytical technologies, including metallic and magnetic nanomaterials, optics, electrochemistry, and spectroscopy. These techniques rely on the early detection of pathogens via enhanced analytical sensitivity and specificity. In order to introduce the potential combination and comparative analysis of various advanced methods, we also reference a novel sample preparation protocol that uses microbial concentration and recovery technologies. This technology has the potential to expedite the pre-enrichment step that precedes the detection process.

Implementing multiresolution models and families of models: from entity-level simulation to desktop stochastic models and "repro" models

NASA Astrophysics Data System (ADS)

McEver, Jimmie; Davis, Paul K.; Bigelow, James H.

2000-06-01

We have developed and used families of multiresolution and multiple-perspective models (MRM and MRMPM), both in our substantive analytic work for the Department of Defense and to learn more about how such models can be designed and implemented. This paper is a brief case history of our experience with a particular family of models addressing the use of precision fires in interdicting and halting an invading army. Our models were implemented as closed-form analytic solutions, in spreadsheets, and in the more sophisticated AnalyticaTM environment. We also drew on an entity-level simulation for data. The paper reviews the importance of certain key attributes of development environments (visual modeling, interactive languages, friendly use of array mathematics, facilities for experimental design and configuration control, statistical analysis tools, graphical visualization tools, interactive post-processing, and relational database tools). These can go a long way towards facilitating MRMPM work, but many of these attributes are not yet widely available (or available at all) in commercial model-development tools--especially for use with personal computers. We conclude with some lessons learned from our experience.

Extending BPM Environments of Your Choice with Performance Related Decision Support

NASA Astrophysics Data System (ADS)

Fritzsche, Mathias; Picht, Michael; Gilani, Wasif; Spence, Ivor; Brown, John; Kilpatrick, Peter

What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools, process optimizations or a combination of such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.

Analysis of electromagnetic interference from power system processing and transmission components for Space Station Freedom

NASA Technical Reports Server (NTRS)

Barber, Peter W.; Demerdash, Nabeel A. O.; Hurysz, B.; Luo, Z.; Denny, Hugh W.; Millard, David P.; Herkert, R.; Wang, R.

1992-01-01

The goal of this research project was to analyze the potential effects of electromagnetic interference (EMI) originating from power system processing and transmission components for Space Station Freedom. The approach consists of four steps: (1) developing analytical tools (models and computer programs); (2) conducting parameterization (what if?) studies; (3) predicting the global space station EMI environment; and (4) providing a basis for modification of EMI standards.

Planning effectiveness may grow on fault trees.

PubMed

Chow, C W; Haddad, K; Mannino, B

1991-10-01

The first step of a strategic planning process--identifying and analyzing threats and opportunities--requires subjective judgments. By using an analytical tool known as a fault tree, healthcare administrators can reduce the unreliability of subjective decision making by creating a logical structure for problem solving and decision making. A case study of 11 healthcare administrators showed that an analysis technique called prospective hindsight can add to a fault tree's ability to improve a strategic planning process.

Long story short: an introduction to the short-term and long-term Six Sigma quality and its importance in the laboratory medicine for the management of extra-analytical processes.

PubMed

Ialongo, Cristiano; Bernardini, Sergio

2018-06-18

There is a compelling need for quality tools that enable effective control of the extra-analytical phase. In this regard, Six Sigma seems to offer a valid methodological and conceptual opportunity, and in recent times, the International Federation of Clinical Chemistry and Laboratory Medicine has adopted it for indicating the performance requirements for non-analytical laboratory processes. However, the Six Sigma implies a distinction between short-term and long-term quality that is based on the dynamics of the processes. These concepts are still not widespread and applied in the field of laboratory medicine although they are of fundamental importance to exploit the full potential of this methodology. This paper reviews the Six Sigma quality concepts and shows how they originated from Shewhart's control charts, in respect of which they are not an alternative but a completion. It also discusses the dynamic nature of process and how it arises, concerning particularly the long-term dynamic mean variation, and explains why this leads to the fundamental distinction of quality we previously mentioned.

Big data and high-performance analytics in structural health monitoring for bridge management

NASA Astrophysics Data System (ADS)

Alampalli, Sharada; Alampalli, Sandeep; Ettouney, Mohammed

2016-04-01

Structural Health Monitoring (SHM) can be a vital tool for effective bridge management. Combining large data sets from multiple sources to create a data-driven decision-making framework is crucial for the success of SHM. This paper presents a big data analytics framework that combines multiple data sets correlated with functional relatedness to convert data into actionable information that empowers risk-based decision-making. The integrated data environment incorporates near real-time streams of semi-structured data from remote sensors, historical visual inspection data, and observations from structural analysis models to monitor, assess, and manage risks associated with the aging bridge inventories. Accelerated processing of dataset is made possible by four technologies: cloud computing, relational database processing, support from NOSQL database, and in-memory analytics. The framework is being validated on a railroad corridor that can be subjected to multiple hazards. The framework enables to compute reliability indices for critical bridge components and individual bridge spans. In addition, framework includes a risk-based decision-making process that enumerate costs and consequences of poor bridge performance at span- and network-levels when rail networks are exposed to natural hazard events such as floods and earthquakes. Big data and high-performance analytics enable insights to assist bridge owners to address problems faster.

The combined use of analytical tools for exploring tetanus toxin and tetanus toxoid structures.

PubMed

Bayart, Caroline; Peronin, Sébastien; Jean, Elisa; Paladino, Joseph; Talaga, Philippe; Borgne, Marc Le

2017-06-01

Aldehyde detoxification is a process used to convert toxin into toxoid for vaccine applications. In the case of tetanus toxin (TT), formaldehyde is used to obtain the tetanus toxoid (TTd), which is used either for the tetanus vaccine or as carrier protein in conjugate vaccines. Several studies have already been conducted to better understand the exact mechanism of this detoxification. Those studies led to the identification of a number of formaldehyde-induced modifications on lab scale TTd samples. To obtain greater insights of the changes induced by formaldehyde, we used three industrial TTd batches to identify repeatable modifications in the detoxification process. Our strategy was to combine seven analytical tools to map these changes. Mass spectrometry (MS), colorimetric test and amino acid analysis (AAA) were used to study modifications on amino acids. SDS-PAGE, asymmetric flow field flow fractionation (AF4), fluorescence spectroscopy and circular dichroism (CD) were used to study formaldehyde modifications on the whole protein structure. We identified 41 formaldehyde-induced modifications across the 1315 amino acid primary sequence of TT. Of these, five modifications on lysine residues were repeatable across TTd batches. Changes in protein conformation were also observed using SDS-PAGE, AF4 and CD techniques. Each analytical tool brought a piece of information regarding formaldehyde induced-modifications, and all together, these methods provided a comprehensive overview of the structural changes that occurred with detoxification. These results could be the first step leading to site-directed TT mutagenesis studies that may enable the production of a non-toxic equivalent protein without using formaldehyde. Copyright © 2017 Elsevier B.V. All rights reserved.

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

PubMed

Soto, Axel J; Zerva, Chrysoula; Batista-Navarro, Riza; Ananiadou, Sophia

2018-04-15

Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i.e. events) extracted automatically from the literature and organized according to levels of confidence. LitPathExplorer supports pathway modellers and curators alike by: (i) extracting events from the literature that corroborate existing models with evidence; (ii) discovering new events which can update models; and (iii) providing a confidence value for each event that is automatically computed based on linguistic features and article metadata. Our evaluation of event extraction showed a precision of 89% and a recall of 71%. Evaluation of our confidence measure, when used for ranking sampled events, showed an average precision ranging between 61 and 73%, which can be improved to 95% when the user is involved in the semi-supervised learning process. Qualitative evaluation using pair analytics based on the feedback of three domain experts confirmed the utility of our tool within the context of pathway model exploration. LitPathExplorer is available at http://nactem.ac.uk/LitPathExplorer_BI/. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Technical pre-analytical effects on the clinical biochemistry of Atlantic salmon (Salmo salar L.).

PubMed

Braceland, M; Houston, K; Ashby, A; Matthews, C; Haining, H; Rodger, H; Eckersall, P D

2017-01-01

Clinical biochemistry has long been utilized in human and veterinary medicine as a vital diagnostic tool, but despite occasional studies showing its usefulness in monitoring health status in Atlantic salmon (Salmo salar L.), it has not yet been widely utilized within the aquaculture industry. This is due, in part, to a lack of an agreed protocol for collection and processing of blood prior to analysis. Moreover, while the analytical phase of clinical biochemistry is well controlled, there is a growing understanding that technical pre-analytical variables can influence analyte concentrations or activities. In addition, post-analytical interpretation of treatment effects is variable in the literature, thus making the true effect of sample treatment hard to evaluate. Therefore, a number of pre-analytical treatments have been investigated to examine their effect on analyte concentrations and activities. In addition, reference ranges for salmon plasma biochemical analytes have been established to inform veterinary practitioners and the aquaculture industry of the importance of clinical biochemistry in health and disease monitoring. Furthermore, a standardized protocol for blood collection has been proposed. © 2016 The Authors Journal of Fish Diseases Published by John Wiley & Sons Ltd.

Object-Oriented MDAO Tool with Aeroservoelastic Model Tuning Capability

NASA Technical Reports Server (NTRS)

Pak, Chan-gi; Li, Wesley; Lung, Shun-fat

2008-01-01

An object-oriented multi-disciplinary analysis and optimization (MDAO) tool has been developed at the NASA Dryden Flight Research Center to automate the design and analysis process and leverage existing commercial as well as in-house codes to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic and hypersonic aircraft. Once the structural analysis discipline is finalized and integrated completely into the MDAO process, other disciplines such as aerodynamics and flight controls will be integrated as well. Simple and efficient model tuning capabilities based on optimization problem are successfully integrated with the MDAO tool. More synchronized all phases of experimental testing (ground and flight), analytical model updating, high-fidelity simulations for model validation, and integrated design may result in reduction of uncertainties in the aeroservoelastic model and increase the flight safety.

Big data sharing and analysis to advance research in post-traumatic epilepsy.

PubMed

Duncan, Dominique; Vespa, Paul; Pitkanen, Asla; Braimah, Adebayo; Lapinlampi, Nina; Toga, Arthur W

2018-06-01

We describe the infrastructure and functionality for a centralized preclinical and clinical data repository and analytic platform to support importing heterogeneous multi-modal data, automatically and manually linking data across modalities and sites, and searching content. We have developed and applied innovative image and electrophysiology processing methods to identify candidate biomarkers from MRI, EEG, and multi-modal data. Based on heterogeneous biomarkers, we present novel analytic tools designed to study epileptogenesis in animal model and human with the goal of tracking the probability of developing epilepsy over time. Copyright © 2017. Published by Elsevier Inc.

Feasibility and utility of applications of the common data model to multiple, disparate observational health databases

PubMed Central

Makadia, Rupa; Matcho, Amy; Ma, Qianli; Knoll, Chris; Schuemie, Martijn; DeFalco, Frank J; Londhe, Ajit; Zhu, Vivienne; Ryan, Patrick B

2015-01-01

Objectives To evaluate the utility of applying the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) across multiple observational databases within an organization and to apply standardized analytics tools for conducting observational research. Materials and methods Six deidentified patient-level datasets were transformed to the OMOP CDM. We evaluated the extent of information loss that occurred through the standardization process. We developed a standardized analytic tool to replicate the cohort construction process from a published epidemiology protocol and applied the analysis to all 6 databases to assess time-to-execution and comparability of results. Results Transformation to the CDM resulted in minimal information loss across all 6 databases. Patients and observations excluded were due to identified data quality issues in the source system, 96% to 99% of condition records and 90% to 99% of drug records were successfully mapped into the CDM using the standard vocabulary. The full cohort replication and descriptive baseline summary was executed for 2 cohorts in 6 databases in less than 1 hour. Discussion The standardization process improved data quality, increased efficiency, and facilitated cross-database comparisons to support a more systematic approach to observational research. Comparisons across data sources showed consistency in the impact of inclusion criteria, using the protocol and identified differences in patient characteristics and coding practices across databases. Conclusion Standardizing data structure (through a CDM), content (through a standard vocabulary with source code mappings), and analytics can enable an institution to apply a network-based approach to observational research across multiple, disparate observational health databases. PMID:25670757

Experimental and analytical tools for evaluation of Stirling engine rod seal behavior

NASA Technical Reports Server (NTRS)

Krauter, A. I.; Cheng, H. S.

1979-01-01

The first year of a two year experimental and analytical program is reported. The program is directed at the elastohydrodynamic behavior of sliding elastomeric rod seals for the Stirling engine. During the year, experimental and analytical tools were developed for evaluating seal leakage, seal friction, and the fluid film thickness at the seal/cylinder interface.

Analytics for Cyber Network Defense

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plantenga, Todd.; Kolda, Tamara Gibson

2011-06-01

This report provides a brief survey of analytics tools considered relevant to cyber network defense (CND). Ideas and tools come from elds such as statistics, data mining, and knowledge discovery. Some analytics are considered standard mathematical or statistical techniques, while others re ect current research directions. In all cases the report attempts to explain the relevance to CND with brief examples.

Big Data Analytics in Healthcare

PubMed Central

Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S. M. Reza; Beard, Daniel A.

2015-01-01

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined. PMID:26229957

Application of Data Provenance in Healthcare Analytics Software: Information Visualisation of User Activities

PubMed Central

Xu, Shen; Rogers, Toby; Fairweather, Elliot; Glenn, Anthony; Curran, James; Curcin, Vasa

2018-01-01

Data provenance is a technique that describes the history of digital objects. In health data settings, it can be used to deliver auditability and transparency, and to achieve trust in a software system. However, implementing data provenance in analytics software at an enterprise level presents a different set of challenges from the research environments where data provenance was originally devised. In this paper, the challenges of reporting provenance information to the user is presented. Provenance captured from analytics software can be large and complex and visualizing a series of tasks over a long period can be overwhelming even for a domain expert, requiring visual aggregation mechanisms that fit with complex human cognitive activities involved in the process. This research studied how provenance-based reporting can be integrated into a health data analytics software, using the example of Atmolytics visual reporting tool. PMID:29888084

Big Data Analytics in Healthcare.

PubMed

Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S M Reza; Navidi, Fatemeh; Beard, Daniel A; Najarian, Kayvan

2015-01-01

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

Hyperspectral imaging using near infrared spectroscopy to monitor coat thickness uniformity in the manufacture of a transdermal drug delivery system.

PubMed

Pavurala, Naresh; Xu, Xiaoming; Krishnaiah, Yellela S R

2017-05-15

Hyperspectral imaging using near infrared spectroscopy (NIRS) integrates spectroscopy and conventional imaging to obtain both spectral and spatial information of materials. The non-invasive and rapid nature of hyperspectral imaging using NIRS makes it a valuable process analytical technology (PAT) tool for in-process monitoring and control of the manufacturing process for transdermal drug delivery systems (TDS). The focus of this investigation was to develop and validate the use of Near Infra-red (NIR) hyperspectral imaging to monitor coat thickness uniformity, a critical quality attribute (CQA) for TDS. Chemometric analysis was used to process the hyperspectral image and a partial least square (PLS) model was developed to predict the coat thickness of the TDS. The goodness of model fit and prediction were 0.9933 and 0.9933, respectively, indicating an excellent fit to the training data and also good predictability. The % Prediction Error (%PE) for internal and external validation samples was less than 5% confirming the accuracy of the PLS model developed in the present study. The feasibility of the hyperspectral imaging as a real-time process analytical tool for continuous processing was also investigated. When the PLS model was applied to detect deliberate variation in coating thickness, it was able to predict both the small and large variations as well as identify coating defects such as non-uniform regions and presence of air bubbles. Published by Elsevier B.V.

Solar Data and Tools: Resources for Researchers, Industry, and Developers

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-04-01

In partnership with the U.S. Department of Energy SunShot Initiative, the National Renewable Energy Laboratory (NREL) has created a suite of analytical tools and data that can inform decisions about implementing solar and that are increasingly forming the basis of private-sector tools and services to solar consumers. The following solar energy data sets and analytical tools are available free to the public.

Progress in development of coated indexable cemented carbide inserts for machining of iron based work piece materials

NASA Astrophysics Data System (ADS)

Czettl, C.; Pohler, M.

2016-03-01

Increasing demands on material properties of iron based work piece materials, e.g. for the turbine industry, complicate the machining process and reduce the lifetime of the cutting tools. Therefore, improved tool solutions, adapted to the requirements of the desired application have to be developed. Especially, the interplay of macro- and micro geometry, substrate material, coating and post treatment processes is crucial for the durability of modern high performance tool solutions. Improved and novel analytical methods allow a detailed understanding of material properties responsible for the wear behaviour of the tools. Those support the knowledge based development of tailored cutting materials for selected applications. One important factor for such a solution is the proper choice of coating material, which can be synthesized by physical or chemical vapor deposition techniques. Within this work an overview of state-of-the-art coated carbide grades is presented and application examples are shown to demonstrate their high efficiency. Machining processes for a material range from cast iron, low carbon steels to high alloyed steels are covered.

Demonstrating Functional Equivalence of Pilot and Production Scale Freeze-Drying of BCG

PubMed Central

ten Have, R.; Reubsaet, K.; van Herpen, P.; Kersten, G.; Amorij, J.-P.

2016-01-01

Process analytical technology (PAT)-tools were used to monitor freeze-drying of Bacille Calmette-Guérin (BCG) at pilot and production scale. Among the evaluated PAT-tools, there is the novel use of the vacuum valve open/close frequency for determining the endpoint of primary drying at production scale. The duration of primary drying, the BCG survival rate, and the residual moisture content (RMC) were evaluated using two different freeze-drying protocols and were found to be independent of the freeze-dryer scale evidencing functional equivalence. The absence of an effect of the freeze-dryer scale on the process underlines the feasibility of the pilot scale freeze-dryer for further BCG freeze-drying process optimization which may be carried out using a medium without BCG. PMID:26981867

Demonstrating Functional Equivalence of Pilot and Production Scale Freeze-Drying of BCG.

PubMed

Ten Have, R; Reubsaet, K; van Herpen, P; Kersten, G; Amorij, J-P

2016-01-01

Process analytical technology (PAT)-tools were used to monitor freeze-drying of Bacille Calmette-Guérin (BCG) at pilot and production scale. Among the evaluated PAT-tools, there is the novel use of the vacuum valve open/close frequency for determining the endpoint of primary drying at production scale. The duration of primary drying, the BCG survival rate, and the residual moisture content (RMC) were evaluated using two different freeze-drying protocols and were found to be independent of the freeze-dryer scale evidencing functional equivalence. The absence of an effect of the freeze-dryer scale on the process underlines the feasibility of the pilot scale freeze-dryer for further BCG freeze-drying process optimization which may be carried out using a medium without BCG.

Predicting adverse hemodynamic events in critically ill patients.

PubMed

Yoon, Joo H; Pinsky, Michael R

2018-06-01

The art of predicting future hemodynamic instability in the critically ill has rapidly become a science with the advent of advanced analytical processed based on computer-driven machine learning techniques. How these methods have progressed beyond severity scoring systems to interface with decision-support is summarized. Data mining of large multidimensional clinical time-series databases using a variety of machine learning tools has led to our ability to identify alert artifact and filter it from bedside alarms, display real-time risk stratification at the bedside to aid in clinical decision-making and predict the subsequent development of cardiorespiratory insufficiency hours before these events occur. This fast evolving filed is primarily limited by linkage of high-quality granular to physiologic rationale across heterogeneous clinical care domains. Using advanced analytic tools to glean knowledge from clinical data streams is rapidly becoming a reality whose clinical impact potential is great.

Source-term development for a contaminant plume for use by multimedia risk assessment models

NASA Astrophysics Data System (ADS)

Whelan, Gene; McDonald, John P.; Taira, Randal Y.; Gnanapragasam, Emmanuel K.; Yu, Charley; Lew, Christine S.; Mills, William B.

2000-02-01

Multimedia modelers from the US Environmental Protection Agency (EPA) and US Department of Energy (DOE) are collaborating to conduct a comprehensive and quantitative benchmarking analysis of four intermedia models: MEPAS, MMSOILS, PRESTO, and RESRAD. These models represent typical analytically based tools that are used in human-risk and endangerment assessments at installations containing radioactive and hazardous contaminants. The objective is to demonstrate an approach for developing an adequate source term by simplifying an existing, real-world, 90Sr plume at DOE's Hanford installation in Richland, WA, for use in a multimedia benchmarking exercise between MEPAS, MMSOILS, PRESTO, and RESRAD. Source characteristics and a release mechanism are developed and described; also described is a typical process and procedure that an analyst would follow in developing a source term for using this class of analytical tool in a preliminary assessment.

Discovery of Information Diffusion Process in Social Networks

NASA Astrophysics Data System (ADS)

Kim, Kwanho; Jung, Jae-Yoon; Park, Jonghun

Information diffusion analysis in social networks is of significance since it enables us to deeply understand dynamic social interactions among users. In this paper, we introduce approaches to discovering information diffusion process in social networks based on process mining. Process mining techniques are applied from three perspectives: social network analysis, process discovery and community recognition. We then present experimental results by using a real-life social network data. The proposed techniques are expected to employ as new analytical tools in online social networks such as blog and wikis for company marketers, politicians, news reporters and online writers.

Mining Mathematics in Textbook Lessons

ERIC Educational Resources Information Center

Ronda, Erlina; Adler, Jill

2017-01-01

In this paper, we propose an analytic tool for describing the mathematics made available to learn in a "textbook lesson". The tool is an adaptation of the Mathematics Discourse in Instruction (MDI) analytic tool that we developed to analyze what is made available to learn in teachers' lessons. Our motivation to adapt the use of the MDI…

Fire behavior modeling-a decision tool

Treesearch

Jack Cohen; Bill Bradshaw

1986-01-01

The usefulness of an analytical model as a fire management decision tool is determined by the correspondence of its descriptive capability to the specific decision context. Fire managers must determine the usefulness of fire models as a decision tool when applied to varied situations. Because the wildland fire phenomenon is complex, analytical fire spread models will...

Guidance for the Design and Adoption of Analytic Tools.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bandlow, Alisa

2015-12-01

The goal is to make software developers aware of common issues that can impede the adoption of analytic tools. This paper provides a summary of guidelines, lessons learned and existing research to explain what is currently known about what analysts want and how to better understand what tools they do and don't need.

Study of an ultrasound-based process analytical tool for homogenization of nanoparticulate pharmaceutical vehicles.

PubMed

Cavegn, Martin; Douglas, Ryan; Akkermans, Guy; Kuentz, Martin

2011-08-01

There are currently no adequate process analyzers for nanoparticulate viscosity enhancers. This article aims to evaluate ultrasonic resonator technology as a monitoring tool for homogenization of nanoparticulate gels. Aqueous dispersions of colloidal microcrystalline cellulose (MCC) and a mixture of clay particles with xanthan gum were compared with colloidal silicon dioxide in oil. The processing was conducted using a laboratory-scale homogenizing vessel. The study investigated first the homogenization kinetics of the different systems to focus then on process factors in the case of colloidal MCC. Moreover, rheological properties were analyzed offline to assess the structure of the resulting gels. Results showed the suitability of ultrasound velocimetry to monitor the homogenization process. The obtained data were fitted using a novel heuristic model. It was possible to identify characteristic homogenization times for each formulation. The subsequent study of the process factors demonstrated that ultrasonic process analysis was equally sensitive as offline rheological measurements in detecting subtle manufacturing changes. It can be concluded that the ultrasonic method was able to successfully assess homogenization of nanoparticulate viscosity enhancers. This novel technique can become a vital tool for development and production of pharmaceutical suspensions in the future. Copyright © 2011 Wiley-Liss, Inc.

On the Use of Machine Learning Techniques for the Mechanical Characterization of Soft Biological Tissues.

PubMed

Cilla, M; Pérez-Rey, I; Martínez, M A; Peña, Estefania; Martínez, Javier

2018-06-23

Motivated by the search for new strategies for fitting a material model, a new approach is explored in the present work. The use of numerical and complex algorithms based on machine learning techniques such as support vector machines for regression, bagged decision trees and artificial neural networks is proposed for solving the parameter identification of constitutive laws for soft biological tissues. First, the mathematical tools were trained with analytical uniaxial data (circumferential and longitudinal directions) as inputs, and their corresponding material parameters of the Gasser, Ogden and Holzapfel strain energy function as outputs. The train and test errors show great efficiency during the training process in finding correlations between inputs and outputs; besides, the correlation coefficients were very close to 1. Second, the tool was validated with unseen observations of analytical circumferential and longitudinal uniaxial data. The results show an excellent agreement between the prediction of the material parameters of the SEF and the analytical curves. Finally, data from real circumferential and longitudinal uniaxial tests on different cardiovascular tissues were fitted, thus the material model of these tissues was predicted. We found that the method was able to consistently identify model parameters, and we believe that the use of these numerical tools could lead to an improvement in the characterization of soft biological tissues. This article is protected by copyright. All rights reserved.

Turbomachinery noise

NASA Astrophysics Data System (ADS)

Groeneweg, John F.; Sofrin, Thomas G.; Rice, Edward J.; Gliebe, Phillip R.

1991-08-01

Summarized here are key advances in experimental techniques and theoretical applications which point the way to a broad understanding and control of turbomachinery noise. On the experimental side, the development of effective inflow control techniques makes it possible to conduct, in ground based facilities, definitive experiments in internally controlled blade row interactions. Results can now be valid indicators of flight behavior and can provide a firm base for comparison with analytical results. Inflow control coupled with detailed diagnostic tools such as blade pressure measurements can be used to uncover the more subtle mechanisms such as rotor strut interaction, which can set tone levels for some engine configurations. Initial mappings of rotor wake-vortex flow fields have provided a data base for a first generation semiempirical flow disturbance model. Laser velocimetry offers a nonintrusive method for validating and improving the model. Digital data systems and signal processing algorithms are bringing mode measurement closer to a working tool that can be frequently applied to a real machine such as a turbofan engine. On the analytical side, models of most of the links in the chain from turbomachine blade source to far field observation point have been formulated. Three dimensional lifting surface theory for blade rows, including source noncompactness and cascade effects, blade row transmission models incorporating mode and frequency scattering, and modal radiation calculations, including hybrid numerical-analytical approaches, are tools which await further application.

2015 Army Science Planning and Strategy Meeting Series: Outcomes and Conclusions

DTIC Science & Technology

2017-12-21

modeling and nanoscale characterization tools to enable efficient design of hybridized manufacturing ; realtime, multiscale computational capability...to enable predictive analytics for expeditionary on-demand manufacturing • Discovery of design principles to enable programming advanced genetic...goals, significant research is needed to mature the fundamental materials science, processing and manufacturing sciences, design methodologies, data

Using the 5Ps Leadership Analysis to Examine the Battle of Antietam: An Explanation and Case Study

ERIC Educational Resources Information Center

Hull, Bradley Z.; Allen, Scott J.

2012-01-01

The authors describe an exploratory analytical tool called "The 5Ps Leadership Analysis" (Personal Attributes, Position, Purpose, Practices/Processes, and Product) as a heuristic for better understanding the complexities of leadership. Using "The 5Ps Leadership Analysis," the authors explore the leadership of General Robert E.…

Notes for a Theory of Evaluation: How Writers Judge Their Own Work.

ERIC Educational Resources Information Center

Miller, Susan

A review of descriptions of the composing process and of the analytical tools developed to measure, describe, and judge student writing suggests that a comprehensive theory of evaluation is an important next step for composition theorists and researchers who want to understand how people learn to write. A study involving three groups of…

Networks in Action: New Actors and Practices in Education Policy in Brazil

ERIC Educational Resources Information Center

Shiroma, Eneida Oto

2014-01-01

This paper focuses on the role of networks in the policy-making process in education and discusses the potential of network analysis as an analytical tool for education policy research. Drawing on publically available data from personal or institutional websites, this paper reports the findings from research carried out between 2005 and 2011.…

Rhetorical Construction of Cells in Science and in a Science Classroom.

ERIC Educational Resources Information Center

Tsatsarelis, Charalampos; Ogborn, Jon; Jewitt, Carey; Kress, Gunther

2001-01-01

Discusses the process of the construction of entities following a social semiotic approach that enables the use of new analytical tools and describes the rhetoric used in construction. Based on an analysis of the historical formation of the notion of cells by scientists, and analysis of a lesson on the microscopic observation of onion cells.…

World Wide Web Indexes and Hierarchical Lists: Finding Tools for the Internet.

ERIC Educational Resources Information Center

Munson, Kurt I.

1996-01-01

In World Wide Web indexing: (1) the creation process is automated; (2) the indexes are merely descriptive, not analytical of document content; (3) results may be sorted differently depending on the search engine; and (4) indexes link directly to the resources. This article compares the indexing methods and querying options of the search engines…

Prerequisites for Systems Analysts: Analytic and Management Demands of a New Approach to Educational Administration.

ERIC Educational Resources Information Center

Ammentorp, William

There is much to be gained by using systems analysis in educational administration. Most administrators, presently relying on classical statistical techniques restricted to problems having few variables, should be trained to use more sophisticated tools such as systems analysis. The systems analyst, interested in the basic processes of a group or…

Rethinking Models of Professional Learning as Tools: A Conceptual Analysis to Inform Research and Practice

ERIC Educational Resources Information Center

Boylan, Mark; Coldwell, Mike; Maxwell, Bronwen; Jordan, Julie

2018-01-01

One approach to designing, researching or evaluating professional learning experiences is to use models of learning processes. Here we analyse and critique five significant contemporary analytical models: three variations on path models, proposed by Guskey, by Desimone and by Clarke and Hollingsworth; a model using a systemic conceptualisation of…

Pre-analytical issues in the haemostasis laboratory: guidance for the clinical laboratories.

PubMed

Magnette, A; Chatelain, M; Chatelain, B; Ten Cate, H; Mullier, F

2016-01-01

Ensuring quality has become a daily requirement in laboratories. In haemostasis, even more than in other disciplines of biology, quality is determined by a pre-analytical step that encompasses all procedures, starting with the formulation of the medical question, and includes patient preparation, sample collection, handling, transportation, processing, and storage until time of analysis. This step, based on a variety of manual activities, is the most vulnerable part of the total testing process and is a major component of the reliability and validity of results in haemostasis and constitutes the most important source of erroneous or un-interpretable results. Pre-analytical errors may occur throughout the testing process and arise from unsuitable, inappropriate or wrongly handled procedures. Problems may arise during the collection of blood specimens such as misidentification of the sample, use of inadequate devices or needles, incorrect order of draw, prolonged tourniquet placing, unsuccessful attempts to locate the vein, incorrect use of additive tubes, collection of unsuitable samples for quality or quantity, inappropriate mixing of a sample, etc. Some factors can alter the result of a sample constituent after collection during transportation, preparation and storage. Laboratory errors can often have serious adverse consequences. Lack of standardized procedures for sample collection accounts for most of the errors encountered within the total testing process. They can also have clinical consequences as well as a significant impact on patient care, especially those related to specialized tests as these are often considered as "diagnostic". Controlling pre-analytical variables is critical since this has a direct influence on the quality of results and on their clinical reliability. The accurate standardization of the pre-analytical phase is of pivotal importance for achieving reliable results of coagulation tests and should reduce the side effects of the influence factors. This review is a summary of the most important recommendations regarding the importance of pre-analytical factors for coagulation testing and should be a tool to increase awareness about the importance of pre-analytical factors for coagulation testing.

Development and biological applications of optical tweezers and Raman spectroscopy

NASA Astrophysics Data System (ADS)

Xie, Chang'an

Optical tweezers is a three-dimensional manipulation tool that employs a gradient force that originates from the single highly focused laser beam. Raman spectroscopy is a molecular analytical tool that can give a highly unique "fingerprint" for each substance by measuring the unique vibrations of its molecules. The combination of these two optical techniques offers a new tool for the manipulation and identification of single biological cells and microscopic particles. In this thesis, we designed and implemented a Laser-Tweezers-Raman-Spectroscopy (LTRS) system, also called the Raman-tweezers, for the simultaneous capture and analysis of both biological particles and non-biological particles. We show that microparticles can be conveniently captured at the focus of a laser beam and the Raman spectra of trapped particles can be acquired with high quality. The LTRS system overcomes the intrinsic Brownian motion and cell motility of microparticles in solution and provides a promising tool for in situ identifying suspicious agents. In order to increase the signal to noise ratio, several schemes were employed in LTRS system to reduce the blank noise and the fluorescence signal coming from analytes and the surrounding background. These techniques include near-infrared excitation, optical levitation, confocal microscopy, and frequency-shifted Raman difference. The LTRS system has been applied for the study in cell biology at the single cell level. With the built Raman-tweezers system, we studied the dynamic physiological processes of single living cells, including cell cycle, the transcription and translation of recombinant protein in transgenic yeast cells and the T cell activation. We also studied cell damage and associated biochemical processes in optical traps, UV radiations, and evaluated heating by near-infrared Raman spectroscopy. These studies show that the Raman-tweezers system is feasible to provide rapid and reliable diagnosis of cellular disorders and can be used as a valuable tool to study cellular processes within single living cells or intracellular organelles and may aid research in molecular and cellular biology.

IT vendor selection model by using structural equation model & analytical hierarchy process

NASA Astrophysics Data System (ADS)

Maitra, Sarit; Dominic, P. D. D.

2012-11-01

Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

Experimentally validated mathematical model of analyte uptake by permeation passive samplers.

PubMed

Salim, F; Ioannidis, M; Górecki, T

2017-11-15

A mathematical model describing the sampling process in a permeation-based passive sampler was developed and evaluated numerically. The model was applied to the Waterloo Membrane Sampler (WMS), which employs a polydimethylsiloxane (PDMS) membrane as a permeation barrier, and an adsorbent as a receiving phase. Samplers of this kind are used for sampling volatile organic compounds (VOC) from air and soil gas. The model predicts the spatio-temporal variation of sorbed and free analyte concentrations within the sampler components (membrane, sorbent bed and dead volume), from which the uptake rate throughout the sampling process can be determined. A gradual decline in the uptake rate during the sampling process is predicted, which is more pronounced when sampling higher concentrations. Decline of the uptake rate can be attributed to diminishing analyte concentration gradient within the membrane, which results from resistance to mass transfer and the development of analyte concentration gradients within the sorbent bed. The effects of changing the sampler component dimensions on the rate of this decline in the uptake rate can be predicted from the model. Performance of the model was evaluated experimentally for sampling of toluene vapors under controlled conditions. The model predictions proved close to the experimental values. The model provides a valuable tool to predict changes in the uptake rate during sampling, to assign suitable exposure times at different analyte concentration levels, and to optimize the dimensions of the sampler in a manner that minimizes these changes during the sampling period.

SAM Radiochemical Methods Query

EPA Pesticide Factsheets

Laboratories measuring target radiochemical analytes in environmental samples can use this online query tool to identify analytical methods in EPA's Selected Analytical Methods for Environmental Remediation and Recovery for select radiochemical analytes.

Multivariate analysis in the pharmaceutical industry: enabling process understanding and improvement in the PAT and QbD era.

PubMed

Ferreira, Ana P; Tobyn, Mike

2015-01-01

In the pharmaceutical industry, chemometrics is rapidly establishing itself as a tool that can be used at every step of product development and beyond: from early development to commercialization. This set of multivariate analysis methods allows the extraction of information contained in large, complex data sets thus contributing to increase product and process understanding which is at the core of the Food and Drug Administration's Process Analytical Tools (PAT) Guidance for Industry and the International Conference on Harmonisation's Pharmaceutical Development guideline (Q8). This review is aimed at providing pharmaceutical industry professionals an introduction to multivariate analysis and how it is being adopted and implemented by companies in the transition from "quality-by-testing" to "quality-by-design". It starts with an introduction to multivariate analysis and the two methods most commonly used: principal component analysis and partial least squares regression, their advantages, common pitfalls and requirements for their effective use. That is followed with an overview of the diverse areas of application of multivariate analysis in the pharmaceutical industry: from the development of real-time analytical methods to definition of the design space and control strategy, from formulation optimization during development to the application of quality-by-design principles to improve manufacture of existing commercial products.

Multi-parameter flow cytometry as a process analytical technology (PAT) approach for the assessment of bacterial ghost production.

PubMed

Langemann, Timo; Mayr, Ulrike Beate; Meitz, Andrea; Lubitz, Werner; Herwig, Christoph

2016-01-01

Flow cytometry (FCM) is a tool for the analysis of single-cell properties in a cell suspension. In this contribution, we present an improved FCM method for the assessment of E-lysis in Enterobacteriaceae. The result of the E-lysis process is empty bacterial envelopes-called bacterial ghosts (BGs)-that constitute potential products in the pharmaceutical field. BGs have reduced light scattering properties when compared with intact cells. In combination with viability information obtained from staining samples with the membrane potential-sensitive fluorescent dye bis-(1,3-dibutylarbituric acid) trimethine oxonol (DiBAC4(3)), the presented method allows to differentiate between populations of viable cells, dead cells, and BGs. Using a second fluorescent dye RH414 as a membrane marker, non-cellular background was excluded from the data which greatly improved the quality of the results. Using true volumetric absolute counting, the FCM data correlated well with cell count data obtained from colony-forming units (CFU) for viable populations. Applicability of the method to several Enterobacteriaceae (different Escherichia coli strains, Salmonella typhimurium, Shigella flexneri 2a) could be shown. The method was validated as a resilient process analytical technology (PAT) tool for the assessment of E-lysis and for particle counting during 20-l batch processes for the production of Escherichia coli Nissle 1917 BGs.

Application of process analytical technology for monitoring freeze-drying of an amorphous protein formulation: use of complementary tools for real-time product temperature measurements and endpoint detection.

PubMed

Schneid, Stefan C; Johnson, Robert E; Lewis, Lavinia M; Stärtzel, Peter; Gieseler, Henning

2015-05-01

Process analytical technology (PAT) and quality by design have gained importance in all areas of pharmaceutical development and manufacturing. One important method for monitoring of critical product attributes and process optimization in laboratory scale freeze-drying is manometric temperature measurement (MTM). A drawback of this innovative technology is that problems are encountered when processing high-concentrated amorphous materials, particularly protein formulations. In this study, a model solution of bovine serum albumin and sucrose was lyophilized at both conservative and aggressive primary drying conditions. Different temperature sensors were employed to monitor product temperatures. The residual moisture content at primary drying endpoints as indicated by temperature sensors and batch PAT methods was quantified from extracted sample vials. The data from temperature probes were then used to recalculate critical product parameters, and the results were compared with MTM data. The drying endpoints indicated by the temperature sensors were not suitable for endpoint indication, in contrast to the batch methods endpoints. The accuracy of MTM Pice data was found to be influenced by water reabsorption. Recalculation of Rp and Pice values based on data from temperature sensors and weighed vials was possible. Overall, extensive information about critical product parameters could be obtained using data from complementary PAT tools. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

PubMed Central

Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

2015-01-01

Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. PMID:25848413

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

PubMed

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms.

PubMed

Matero, Sanni; van Den Berg, Frans; Poutiainen, Sami; Rantanen, Jukka; Pajander, Jari

2013-05-01

The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed. Copyright © 2013 Wiley Periodicals, Inc.

An Application of X-Ray Fluorescence as Process Analytical Technology (PAT) to Monitor Particle Coating Processes.

PubMed

Nakano, Yoshio; Katakuse, Yoshimitsu; Azechi, Yasutaka

2018-06-01

An attempt to apply X-Ray Fluorescence (XRF) analysis to evaluate small particle coating process as a Process Analytical Technologies (PAT) was made. The XRF analysis was used to monitor coating level in small particle coating process with at-line manner. The small particle coating process usually consists of multiple coating processes. This study was conducted by a simple coating particles prepared by first coating of a model compound (DL-methionine) and second coating by talc on spherical microcrystalline cellulose cores. The particles with two layered coating are enough to demonstrate the small particle coating process. From the result by the small particle coating process, it was found that the XRF signal played different roles, resulting that XRF signals by first coating (layering) and second coating (mask coating) could demonstrate the extent with different mechanisms for the coating process. Furthermore, the particle coating of the different particle size has also been investigated to evaluate size effect of these coating processes. From these results, it was concluded that the XRF could be used as a PAT in monitoring particle coating processes and become powerful tool in pharmaceutical manufacturing.

Teaching Theory Construction With Initial Grounded Theory Tools: A Reflection on Lessons and Learning.

PubMed

Charmaz, Kathy

2015-12-01

This article addresses criticisms of qualitative research for spawning studies that lack analytic development and theoretical import. It focuses on teaching initial grounded theory tools while interviewing, coding, and writing memos for the purpose of scaling up the analytic level of students' research and advancing theory construction. Adopting these tools can improve teaching qualitative methods at all levels although doctoral education is emphasized here. What teachers cover in qualitative methods courses matters. The pedagogy presented here requires a supportive environment and relies on demonstration, collective participation, measured tasks, progressive analytic complexity, and accountability. Lessons learned from using initial grounded theory tools are exemplified in a doctoral student's coding and memo-writing excerpts that demonstrate progressive analytic development. The conclusion calls for increasing the number and depth of qualitative methods courses and for creating a cadre of expert qualitative methodologists. © The Author(s) 2015.

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

PubMed

Caetano, Fabiana A; Dirk, Brennan S; Tam, Joshua H K; Cavanagh, P Craig; Goiko, Maria; Ferguson, Stephen S G; Pasternak, Stephen H; Dikeakos, Jimmy D; de Bruyn, John R; Heit, Bryan

2015-12-01

Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

Social sustainability in healthcare facilities: a rating tool for analysing and improving social aspects in environments of care.

PubMed

Capolongo, Stefano; Gola, Marco; di Noia, Michela; Nickolova, Maria; Nachiero, Dario; Rebecchi, Andrea; Settimo, Gaetano; Vittori, Gail; Buffoli, Maddalena

2016-01-01

Nowadays several rating systems exist for the evaluation of the sustainability of buildings, but often their focus is limited to environmental and efficiency aspects. Hospitals are complex constructions in which many variables affect hospital processes. Therefore, a research group has developed a tool for the evaluation of sustainability in healthcare facilities. The paper analyses social sustainability issues through a tool which evaluates users' perception from a the quality and well-being perspective. It presents a hierarchical structure composed of a criteria and indicators system which is organised through a weighing system calculated by using the Analytic Network Process. The output is the definition of a tool which evaluates how Humanisation, Comfort and Distribution criteria can affect the social sustainability of a building. Starting from its application, it is evident that the instrument enables the improvement of healthcare facilities through several design and organisational suggestions for achieving healing and sustainable architectures.

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2010 CFR

2010-07-01

... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life... empirical tools should be used to support the life safety equivalency evaluation? 102-80.120 Section 102-80...

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2011 CFR

2011-01-01

... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life... empirical tools should be used to support the life safety equivalency evaluation? 102-80.120 Section 102-80...

Web Analytics

EPA Pesticide Factsheets

EPA’s Web Analytics Program collects, analyzes, and provides reports on traffic, quality assurance, and customer satisfaction metrics for EPA’s website. The program uses a variety of analytics tools, including Google Analytics and CrazyEgg.

Analytical method of waste allocation in waste management systems: Concept, method and case study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bergeron, Francis C., E-mail: francis.b.c@videotron.ca

Waste is not a rejected item to dispose anymore but increasingly a secondary resource to exploit, influencing waste allocation among treatment operations in a waste management (WM) system. The aim of this methodological paper is to present a new method for the assessment of the WM system, the “analytical method of the waste allocation process” (AMWAP), based on the concept of the “waste allocation process” defined as the aggregation of all processes of apportioning waste among alternative waste treatment operations inside or outside the spatial borders of a WM system. AMWAP contains a conceptual framework and an analytical approach. Themore » conceptual framework includes, firstly, a descriptive model that focuses on the description and classification of the WM system. It includes, secondly, an explanatory model that serves to explain and to predict the operation of the WM system. The analytical approach consists of a step-by-step analysis for the empirical implementation of the conceptual framework. With its multiple purposes, AMWAP provides an innovative and objective modular method to analyse a WM system which may be integrated in the framework of impact assessment methods and environmental systems analysis tools. Its originality comes from the interdisciplinary analysis of the WAP and to develop the conceptual framework. AMWAP is applied in the framework of an illustrative case study on the household WM system of Geneva (Switzerland). It demonstrates that this method provides an in-depth and contextual knowledge of WM. - Highlights: • The study presents a new analytical method based on the waste allocation process. • The method provides an in-depth and contextual knowledge of the waste management system. • The paper provides a reproducible procedure for professionals, experts and academics. • It may be integrated into impact assessment or environmental system analysis tools. • An illustrative case study is provided based on household waste management in Geneva.« less

A graph algebra for scalable visual analytics.

PubMed

Shaverdian, Anna A; Zhou, Hao; Michailidis, George; Jagadish, Hosagrahar V

2012-01-01

Visual analytics (VA), which combines analytical techniques with advanced visualization features, is fast becoming a standard tool for extracting information from graph data. Researchers have developed many tools for this purpose, suggesting a need for formal methods to guide these tools' creation. Increased data demands on computing requires redesigning VA tools to consider performance and reliability in the context of analysis of exascale datasets. Furthermore, visual analysts need a way to document their analyses for reuse and results justification. A VA graph framework encapsulated in a graph algebra helps address these needs. Its atomic operators include selection and aggregation. The framework employs a visual operator and supports dynamic attributes of data to enable scalable visual exploration of data.

Considerations on the Use of Custom Accelerators for Big Data Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castellana, Vito G.; Tumeo, Antonino; Minutoli, Marco

Accelerators, including Graphic Processing Units (GPUs) for gen- eral purpose computation, many-core designs with wide vector units (e.g., Intel Phi), have become a common component of many high performance clusters. The appearance of more stable and reliable tools tools that can automatically convert code written in high-level specifications with annotations (such as C or C++) to hardware de- scription languages (High-Level Synthesis - HLS), is also setting the stage for a broader use of reconfigurable devices (e.g., Field Pro- grammable Gate Arrays - FPGAs) in high performance system for the implementation of custom accelerators, helped by the fact that newmore » processors include advanced cache-coherent interconnects for these components. In this chapter, we briefly survey the status of the use of accelerators in high performance systems targeted at big data analytics applications. We argue that, although the progress in the use of accelerators for this class of applications has been sig- nificant, differently from scientific simulations there still are gaps to close. This is particularly true for the ”irregular” behaviors exhibited by no-SQL, graph databases. We focus our attention on the limits of HLS tools for data analytics and graph methods, and discuss a new architectural template that better fits the requirement of this class of applications. We validate the new architectural templates by mod- ifying the Graph Engine for Multithreaded System (GEMS) frame- work to support accelerators generated with such a methodology, and testing with queries coming from the Lehigh University Benchmark (LUBM). The architectural template enables better supporting the task and memory level parallelism present in graph methods by sup- porting a new control model and a enhanced memory interface. We show that out solution allows generating parallel accelerators, pro- viding speed ups with respect to conventional HLS flows. We finally draw conclusions and present a perspective on the use of reconfig- urable devices and Design Automation tools for data analytics.« less

Advanced Video Analysis Needs for Human Performance Evaluation

NASA Technical Reports Server (NTRS)

Campbell, Paul D.

1994-01-01

Evaluators of human task performance in space missions make use of video as a primary source of data. Extraction of relevant human performance information from video is often a labor-intensive process requiring a large amount of time on the part of the evaluator. Based on the experiences of several human performance evaluators, needs were defined for advanced tools which could aid in the analysis of video data from space missions. Such tools should increase the efficiency with which useful information is retrieved from large quantities of raw video. They should also provide the evaluator with new analytical functions which are not present in currently used methods. Video analysis tools based on the needs defined by this study would also have uses in U.S. industry and education. Evaluation of human performance from video data can be a valuable technique in many industrial and institutional settings where humans are involved in operational systems and processes.

Cause-and-effect mapping of critical events.

PubMed

Graves, Krisanne; Simmons, Debora; Galley, Mark D

2010-06-01

Health care errors are routinely reported in the scientific and public press and have become a major concern for most Americans. In learning to identify and analyze errors health care can develop some of the skills of a learning organization, including the concept of systems thinking. Modern experts in improving quality have been working in other high-risk industries since the 1920s making structured organizational changes through various frameworks for quality methods including continuous quality improvement and total quality management. When using these tools, it is important to understand systems thinking and the concept of processes within organization. Within these frameworks of improvement, several tools can be used in the analysis of errors. This article introduces a robust tool with a broad analytical view consistent with systems thinking, called CauseMapping (ThinkReliability, Houston, TX, USA), which can be used to systematically analyze the process and the problem at the same time. Copyright 2010 Elsevier Inc. All rights reserved.

THz spectroscopy: An emerging technology for pharmaceutical development and pharmaceutical Process Analytical Technology (PAT) applications

NASA Astrophysics Data System (ADS)

Wu, Huiquan; Khan, Mansoor

2012-08-01

As an emerging technology, THz spectroscopy has gained increasing attention in the pharmaceutical area during the last decade. This attention is due to the fact that (1) it provides a promising alternative approach for in-depth understanding of both intermolecular interaction among pharmaceutical molecules and pharmaceutical product quality attributes; (2) it provides a promising alternative approach for enhanced process understanding of certain pharmaceutical manufacturing processes; and (3) the FDA pharmaceutical quality initiatives, most noticeably, the Process Analytical Technology (PAT) initiative. In this work, the current status and progress made so far on using THz spectroscopy for pharmaceutical development and pharmaceutical PAT applications are reviewed. In the spirit of demonstrating the utility of first principles modeling approach for addressing model validation challenge and reducing unnecessary model validation "burden" for facilitating THz pharmaceutical PAT applications, two scientific case studies based on published THz spectroscopy measurement results are created and discussed. Furthermore, other technical challenges and opportunities associated with adapting THz spectroscopy as a pharmaceutical PAT tool are highlighted.

Modeling and Visualizing Flow of Chemical Agents Across Complex Terrain

NASA Technical Reports Server (NTRS)

Kao, David; Kramer, Marc; Chaderjian, Neal

2005-01-01

Release of chemical agents across complex terrain presents a real threat to homeland security. Modeling and visualization tools are being developed that capture flow fluid terrain interaction as well as point dispersal downstream flow paths. These analytic tools when coupled with UAV atmospheric observations provide predictive capabilities to allow for rapid emergency response as well as developing a comprehensive preemptive counter-threat evacuation plan. The visualization tools involve high-end computing and massive parallel processing combined with texture mapping. We demonstrate our approach across a mountainous portion of North California under two contrasting meteorological conditions. Animations depicting flow over this geographical location provide immediate assistance in decision support and crisis management.

Simulation validation and management

NASA Astrophysics Data System (ADS)

Illgen, John D.

1995-06-01

Illgen Simulation Technologies, Inc., has been working interactive verification and validation programs for the past six years. As a result, they have evolved a methodology that has been adopted and successfully implemented by a number of different verification and validation programs. This methodology employs a unique case of computer-assisted software engineering (CASE) tools to reverse engineer source code and produce analytical outputs (flow charts and tables) that aid the engineer/analyst in the verification and validation process. We have found that the use of CASE tools saves time,which equate to improvements in both schedule and cost. This paper will describe the ISTI-developed methodology and how CASe tools are used in its support. Case studies will be discussed.

The Geoinformatica free and open source software stack

NASA Astrophysics Data System (ADS)

Jolma, A.

2012-04-01

The Geoinformatica free and open source software (FOSS) stack is based mainly on three established FOSS components, namely GDAL, GTK+, and Perl. GDAL provides access to a very large selection of geospatial data formats and data sources, a generic geospatial data model, and a large collection of geospatial analytical and processing functionality. GTK+ and the Cairo graphics library provide generic graphics and graphical user interface capabilities. Perl is a programming language, for which there is a very large set of FOSS modules for a wide range of purposes and which can be used as an integrative tool for building applications. In the Geoinformatica stack, data storages such as FOSS RDBMS PostgreSQL with its geospatial extension PostGIS can be used below the three above mentioned components. The top layer of Geoinformatica consists of a C library and several Perl modules. The C library comprises a general purpose raster algebra library, hydrological terrain analysis functions, and visualization code. The Perl modules define a generic visualized geospatial data layer and subclasses for raster and vector data and graphs. The hydrological terrain functions are already rather old and they suffer for example from the requirement of in-memory rasters. Newer research conducted using the platform include basic geospatial simulation modeling, visualization of ecological data, linking with a Bayesian network engine for spatial risk assessment in coastal areas, and developing standards-based distributed water resources information systems in Internet. The Geoinformatica stack constitutes a platform for geospatial research, which is targeted towards custom analytical tools, prototyping and linking with external libraries. Writing custom analytical tools is supported by the Perl language and the large collection of tools that are available especially in GDAL and Perl modules. Prototyping is supported by the GTK+ library, the GUI tools, and the support for object-oriented programming in Perl. New feature types, geospatial layer classes, and tools as extensions with specific features can be defined, used, and studied. Linking with external libraries is possible using the Perl foreign function interface tools or with generic tools such as Swig. We are interested in implementing and testing linking Geoinformatica with existing or new more specific hydrological FOSS.

Single-scan 2D NMR: An Emerging Tool in Analytical Spectroscopy

PubMed Central

Giraudeau, Patrick; Frydman, Lucio

2016-01-01

Two-dimensional Nuclear Magnetic Resonance (2D NMR) spectroscopy is widely used in chemical and biochemical analyses. Multidimensional NMR is also witnessing an increased use in quantitative and metabolic screening applications. Conventional 2D NMR experiments, however, are affected by inherently long acquisition durations, arising from their need to sample the frequencies involved along their indirect domains in an incremented, scan-by-scan nature. A decade ago a so-called “ultrafast” (UF) approach was proposed, capable to deliver arbitrary 2D NMR spectra involving any kind of homo- or hetero-nuclear correlations, in a single scan. During the intervening years the performance of this sub-second 2D NMR methodology has been greatly improved, and UF 2D NMR is rapidly becoming a powerful analytical tool witnessing an expanded scope of applications. The present reviews summarizes the principles and the main developments which have contributed to the success of this approach, and focuses on applications which have been recently demonstrated in various areas of analytical chemistry –from the real time monitoring of chemical and biochemical processes, to extensions in hyphenated techniques and in quantitative applications. PMID:25014342

The use of a quartz crystal microbalance as an analytical tool to monitor particle/surface and particle/particle interactions under dry ambient and pressurized conditions: a study using common inhaler components.

PubMed

Turner, N W; Bloxham, M; Piletsky, S A; Whitcombe, M J; Chianella, I

2016-12-19

Metered dose inhalers (MDI) and multidose powder inhalers (MPDI) are commonly used for the treatment of chronic obstructive pulmonary diseases and asthma. Currently, analytical tools to monitor particle/particle and particle/surface interaction within MDI and MPDI at the macro-scale do not exist. A simple tool capable of measuring such interactions would ultimately enable quality control of MDI and MDPI, producing remarkable benefits for the pharmaceutical industry and the users of inhalers. In this paper, we have investigated whether a quartz crystal microbalance (QCM) could become such a tool. A QCM was used to measure particle/particle and particle/surface interactions on the macroscale, by additions of small amounts of MDPI components, in the powder form into a gas stream. The subsequent interactions with materials on the surface of the QCM sensor were analyzed. Following this, the sensor was used to measure fluticasone propionate, a typical MDI active ingredient, in a pressurized gas system to assess its interactions with different surfaces under conditions mimicking the manufacturing process. In both types of experiments the QCM was capable of discriminating interactions of different components and surfaces. The results have demonstrated that the QCM is a suitable platform for monitoring macro-scale interactions and could possibly become a tool for quality control of inhalers.

How can knowledge discovery methods uncover spatio-temporal patterns in environmental data?

NASA Astrophysics Data System (ADS)

Wachowicz, Monica

2000-04-01

This paper proposes the integration of KDD, GVis and STDB as a long-term strategy, which will allow users to apply knowledge discovery methods for uncovering spatio-temporal patterns in environmental data. The main goal is to combine innovative techniques and associated tools for exploring very large environmental data sets in order to arrive at valid, novel, potentially useful, and ultimately understandable spatio-temporal patterns. The GeoInsight approach is described using the principles and key developments in the research domains of KDD, GVis, and STDB. The GeoInsight approach aims at the integration of these research domains in order to provide tools for performing information retrieval, exploration, analysis, and visualization. The result is a knowledge-based design, which involves visual thinking (perceptual-cognitive process) and automated information processing (computer-analytical process).

Planungsmodelle und Planungsmethoden. Anhaltspunkte zur Strukturierung und Gestaltung von Planungsprozessen

NASA Astrophysics Data System (ADS)

Diller, Christian; Karic, Sarah; Oberding, Sarah

2017-06-01

The topic of this article ist the question, in which phases oft he political planning process planners apply their methodological set of tools. That for the results of a research-project are presented, which were gained by an examination of planning-cases in learned journals. Firstly it is argued, which model oft he planning-process is most suitable to reflect the regarded cases and how it is positioned to models oft he political process. Thereafter it is analyzed, which types of planning methods are applied in the several stages oft he planning process. The central findings: Although complex, many planning processes can be thouroughly pictured by a linear modell with predominantly simple feedback loops. Even in times of he communicative turn, concerning their set of tools, planners should pay attention to apply not only communicative methods but as well the classical analytical-rational methods. They are helpful especially for the understanding of the political process before and after the actual planning phase.

Non-traditional isotopes in analytical ecogeochemistry assessed by MC-ICP-MS

NASA Astrophysics Data System (ADS)

Prohaska, Thomas; Irrgeher, Johanna; Horsky, Monika; Hanousek, Ondřej; Zitek, Andreas

2014-05-01

Analytical ecogeochemistry deals with the development and application of tools of analytical chemistry to study dynamic biological and ecological processes within ecosystems and across ecosystem boundaries in time. It can be best described as a linkage between modern analytical chemistry and a holistic understanding of ecosystems ('The total human ecosystem') within the frame of transdisciplinary research. One focus of analytical ecogeochemistry is the advanced analysis of elements and isotopes in abiotic and biotic matrices and the application of the results to basic questions in different research fields like ecology, environmental science, climatology, anthropology, forensics, archaeometry and provenancing. With continuous instrumental developments, new isotopic systems have been recognized for their potential to study natural processes and well established systems could be analyzed with improved techniques, especially using multi collector inductively coupled plasma mass spectrometry (MC-ICP-MS). For example, in case of S, isotope ratio measurements at high mass resolution could be achieved at much lower S concentrations with ICP-MS as compared to IRMS, still keeping suitable uncertainty. Almost 50 different isotope systems have been investigated by ICP-MS, so far, with - besides Sr, Pb and U - Ca, Mg, Cd, Li, Hg, Si, Ge and B being the most prominent and considerably pushing the limits of plasma based mass spectrometry also by applying high mass resolution. The use of laser ablation in combination with MC-ICP-MS offers the possibility to achieve isotopic information on high spatial (µm-range) and temporal scale (in case of incrementally growing structures). The information gained with these analytical techniques can be linked between different hierarchical scales in ecosystems, offering means to better understand ecosystem processes. The presentation will highlight the use of different isotopic systems in ecosystem studies accomplished by ICP-MS. Selected examples on combining isotopic systems for the study of ecosystem processes on different spatial scales will underpin the great opportunities substantiated by the field of analytical ecogeochemistry. Moreover, recent developments in plasma mass spectrometry and the application of new isotopic systems require sound metrological approaches in order to prevent scientific conclusions drawn from analytical artifacts.

Assessing analytical comparability of biosimilars: GCSF as a case study.

PubMed

Nupur, Neh; Singh, Sumit Kumar; Narula, Gunjan; Rathore, Anurag S

2016-10-01

The biosimilar industry is witnessing an unprecedented growth with the newer therapeutics increasing in complexity over time. A key step towards development of a biosimilar is to establish analytical comparability with the innovator product, which would otherwise affect the safety/efficacy profile of the product. Choosing appropriate analytical tools that can fulfil this objective by qualitatively and/or quantitatively assessing the critical quality attributes (CQAs) of the product is highly critical for establishing equivalence. These CQAs cover the primary and higher order structures of the product, product related variants and impurities, as well as process related impurities, and host cell related impurities. In the present work, we use such an analytical platform for assessing comparability of five approved Granulocyte Colony Stimulating Factor (GCSF) biosimilars (Emgrast, Lupifil, Colstim, Neukine and Grafeel) to the innovator product, Neupogen(®). The comparability studies involve assessing structural homogeneity, identity, secondary structure, and product related modifications. Physicochemical analytical tools include peptide mapping with mass determination, circular dichroism (CD) spectroscopy, reverse phase chromatography (RPC) and size exclusion chromatography (SEC) have been used in this exercise. Bioactivity assessment include comparison of relative potency through in vitro cell proliferation assays. The results from extensive analytical examination offer robust evidence of structural and biological similarity of the products under consideration with the pertinent innovator product. For the most part, the biosimilar drugs were found to be comparable to the innovator drug anomaly that was identified was that three of the biosimilars had a typical variant which was reported as an oxidized species in the literature. But, upon further investigation using RPC-FLD and ESI-MS we found that this is likely a conformational variant of the biotherapeutic been studied. Copyright © 2016 Elsevier B.V. All rights reserved.

Connecting Analytics and Curriculum Design: Process and Outcomes of Building a Tool to Browse Data Relevant to Course Designers

ERIC Educational Resources Information Center

Dunbar, Robert L.; Dingel, Molly J.; Prat-Resina, Xavier

2014-01-01

The disconnect between data collection and analysis across academic and administrative units within institutions of higher education makes it challenging to incorporate diverse data into curricular design. Understanding the factors related to student retention and success is unlikely to occur by focusing on only one unit at a time. By promoting…

An Analytical Tool to Determine Undergraduate Students' Use of Volume and Pressure when Describing Expansion Work and Technical Work

ERIC Educational Resources Information Center

Nilsson, Tor; Niedderer, Hans

2012-01-01

In undergraduate chemical thermodynamics teachers often include equations and view manipulations of variables as understanding. Undergraduate students are often not able to describe the meaning of these equations. In chemistry, enthalpy and its change are introduced to describe some features of chemical reactions. In the process of measuring heat…

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data.

PubMed

Dinov, Ivo D

2016-01-01

Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be 'team science'.

Challenges and opportunities in analysing students modelling

NASA Astrophysics Data System (ADS)

Blanco-Anaya, Paloma; Justi, Rosária; Díaz de Bustamante, Joaquín

2017-02-01

Modelling-based teaching activities have been designed and analysed from distinct theoretical perspectives. In this paper, we use one of them - the model of modelling diagram (MMD) - as an analytical tool in a regular classroom context. This paper examines the challenges that arise when the MMD is used as an analytical tool to characterise the modelling process experienced by students working in small groups aiming at creating and testing a model of a sedimentary basin from the information provided. The study was conducted in a regular Biology and Geology classroom (16-17 years old students). Data was collected through video recording of the classes, along with written reports and the material models made by each group. The results show the complexity of adapting MMD at two levels: the group modelling and the actual requirements for the activity. Our main challenges were to gather the modelling process of each individual and the group, as well as to identify, from students' speech, which stage of modelling they were performing at a given time. When facing such challenges, we propose some changes in the MMD so that it can be properly used to analyse students performing modelling activities in groups.

The MCNP6 Analytic Criticality Benchmark Suite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Forrest B.

2016-06-16

Analytical benchmarks provide an invaluable tool for verifying computer codes used to simulate neutron transport. Several collections of analytical benchmark problems [1-4] are used routinely in the verification of production Monte Carlo codes such as MCNP® [5,6]. Verification of a computer code is a necessary prerequisite to the more complex validation process. The verification process confirms that a code performs its intended functions correctly. The validation process involves determining the absolute accuracy of code results vs. nature. In typical validations, results are computed for a set of benchmark experiments using a particular methodology (code, cross-section data with uncertainties, and modeling)more » and compared to the measured results from the set of benchmark experiments. The validation process determines bias, bias uncertainty, and possibly additional margins. Verification is generally performed by the code developers, while validation is generally performed by code users for a particular application space. The VERIFICATION_KEFF suite of criticality problems [1,2] was originally a set of 75 criticality problems found in the literature for which exact analytical solutions are available. Even though the spatial and energy detail is necessarily limited in analytical benchmarks, typically to a few regions or energy groups, the exact solutions obtained can be used to verify that the basic algorithms, mathematics, and methods used in complex production codes perform correctly. The present work has focused on revisiting this benchmark suite. A thorough review of the problems resulted in discarding some of them as not suitable for MCNP benchmarking. For the remaining problems, many of them were reformulated to permit execution in either multigroup mode or in the normal continuous-energy mode for MCNP. Execution of the benchmarks in continuous-energy mode provides a significant advance to MCNP verification methods.« less

Supporting cognition in systems biology analysis: findings on users' processes and design implications.

PubMed

Mirel, Barbara

2009-02-13

Current usability studies of bioinformatics tools suggest that tools for exploratory analysis support some tasks related to finding relationships of interest but not the deep causal insights necessary for formulating plausible and credible hypotheses. To better understand design requirements for gaining these causal insights in systems biology analyses a longitudinal field study of 15 biomedical researchers was conducted. Researchers interacted with the same protein-protein interaction tools to discover possible disease mechanisms for further experimentation. Findings reveal patterns in scientists' exploratory and explanatory analysis and reveal that tools positively supported a number of well-structured query and analysis tasks. But for several of scientists' more complex, higher order ways of knowing and reasoning the tools did not offer adequate support. Results show that for a better fit with scientists' cognition for exploratory analysis systems biology tools need to better match scientists' processes for validating, for making a transition from classification to model-based reasoning, and for engaging in causal mental modelling. As the next great frontier in bioinformatics usability, tool designs for exploratory systems biology analysis need to move beyond the successes already achieved in supporting formulaic query and analysis tasks and now reduce current mismatches with several of scientists' higher order analytical practices. The implications of results for tool designs are discussed.

Development of balanced key performance indicators for emergency departments strategic dashboards following analytic hierarchical process.

PubMed

Safdari, Reza; Ghazisaeedi, Marjan; Mirzaee, Mahboobeh; Farzi, Jebrail; Goodini, Azadeh

2014-01-01

Dynamic reporting tools, such as dashboards, should be developed to measure emergency department (ED) performance. However, choosing an effective balanced set of performance measures and key performance indicators (KPIs) is a main challenge to accomplish this. The aim of this study was to develop a balanced set of KPIs for use in ED strategic dashboards following an analytic hierarchical process. The study was carried out in 2 phases: constructing ED performance measures based on balanced scorecard perspectives and incorporating them into analytic hierarchical process framework to select the final KPIs. The respondents placed most importance on ED internal processes perspective especially on measures related to timeliness and accessibility of care in ED. Some measures from financial, customer, and learning and growth perspectives were also selected as other top KPIs. Measures of care effectiveness and care safety were placed as the next priorities too. The respondents placed least importance on disease-/condition-specific "time to" measures. The methodology can be presented as a reference model for development of KPIs in various performance related areas based on a consistent and fair approach. Dashboards that are designed based on such a balanced set of KPIs will help to establish comprehensive performance measurements and fair benchmarks and comparisons.

Feasibility and utility of applications of the common data model to multiple, disparate observational health databases.

PubMed

Voss, Erica A; Makadia, Rupa; Matcho, Amy; Ma, Qianli; Knoll, Chris; Schuemie, Martijn; DeFalco, Frank J; Londhe, Ajit; Zhu, Vivienne; Ryan, Patrick B

2015-05-01

To evaluate the utility of applying the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) across multiple observational databases within an organization and to apply standardized analytics tools for conducting observational research. Six deidentified patient-level datasets were transformed to the OMOP CDM. We evaluated the extent of information loss that occurred through the standardization process. We developed a standardized analytic tool to replicate the cohort construction process from a published epidemiology protocol and applied the analysis to all 6 databases to assess time-to-execution and comparability of results. Transformation to the CDM resulted in minimal information loss across all 6 databases. Patients and observations excluded were due to identified data quality issues in the source system, 96% to 99% of condition records and 90% to 99% of drug records were successfully mapped into the CDM using the standard vocabulary. The full cohort replication and descriptive baseline summary was executed for 2 cohorts in 6 databases in less than 1 hour. The standardization process improved data quality, increased efficiency, and facilitated cross-database comparisons to support a more systematic approach to observational research. Comparisons across data sources showed consistency in the impact of inclusion criteria, using the protocol and identified differences in patient characteristics and coding practices across databases. Standardizing data structure (through a CDM), content (through a standard vocabulary with source code mappings), and analytics can enable an institution to apply a network-based approach to observational research across multiple, disparate observational health databases. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Implementing Operational Analytics using Big Data Technologies to Detect and Predict Sensor Anomalies

NASA Astrophysics Data System (ADS)

Coughlin, J.; Mital, R.; Nittur, S.; SanNicolas, B.; Wolf, C.; Jusufi, R.

2016-09-01

Operational analytics when combined with Big Data technologies and predictive techniques have been shown to be valuable in detecting mission critical sensor anomalies that might be missed by conventional analytical techniques. Our approach helps analysts and leaders make informed and rapid decisions by analyzing large volumes of complex data in near real-time and presenting it in a manner that facilitates decision making. It provides cost savings by being able to alert and predict when sensor degradations pass a critical threshold and impact mission operations. Operational analytics, which uses Big Data tools and technologies, can process very large data sets containing a variety of data types to uncover hidden patterns, unknown correlations, and other relevant information. When combined with predictive techniques, it provides a mechanism to monitor and visualize these data sets and provide insight into degradations encountered in large sensor systems such as the space surveillance network. In this study, data from a notional sensor is simulated and we use big data technologies, predictive algorithms and operational analytics to process the data and predict sensor degradations. This study uses data products that would commonly be analyzed at a site. This study builds on a big data architecture that has previously been proven valuable in detecting anomalies. This paper outlines our methodology of implementing an operational analytic solution through data discovery, learning and training of data modeling and predictive techniques, and deployment. Through this methodology, we implement a functional architecture focused on exploring available big data sets and determine practical analytic, visualization, and predictive technologies.

A Visual Analytics Approach to Structured Data Analysis to Enhance Nonproliferation and Arms Control Verification Activities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gillen, David S.

Analysis activities for Nonproliferation and Arms Control verification require the use of many types of data. Tabular structured data, such as Excel spreadsheets and relational databases, have traditionally been used for data mining activities, where specific queries are issued against data to look for matching results. The application of visual analytics tools to structured data enables further exploration of datasets to promote discovery of previously unknown results. This paper discusses the application of a specific visual analytics tool to datasets related to the field of Arms Control and Nonproliferation to promote the use of visual analytics more broadly in thismore » domain. Visual analytics focuses on analytical reasoning facilitated by interactive visual interfaces (Wong and Thomas 2004). It promotes exploratory analysis of data, and complements data mining technologies where known patterns can be mined for. Also with a human in the loop, they can bring in domain knowledge and subject matter expertise. Visual analytics has not widely been applied to this domain. In this paper, we will focus on one type of data: structured data, and show the results of applying a specific visual analytics tool to answer questions in the Arms Control and Nonproliferation domain. We chose to use the T.Rex tool, a visual analytics tool developed at PNNL, which uses a variety of visual exploration patterns to discover relationships in structured datasets, including a facet view, graph view, matrix view, and timeline view. The facet view enables discovery of relationships between categorical information, such as countries and locations. The graph tool visualizes node-link relationship patterns, such as the flow of materials being shipped between parties. The matrix visualization shows highly correlated categories of information. The timeline view shows temporal patterns in data. In this paper, we will use T.Rex with two different datasets to demonstrate how interactive exploration of the data can aid an analyst with arms control and nonproliferation verification activities. Using a dataset from PIERS (PIERS 2014), we will show how container shipment imports and exports can aid an analyst in understanding the shipping patterns between two countries. We will also use T.Rex to examine a collection of research publications from the IAEA International Nuclear Information System (IAEA 2014) to discover collaborations of concern. We hope this paper will encourage the use of visual analytics structured data analytics in the field of nonproliferation and arms control verification. Our paper outlines some of the challenges that exist before broad adoption of these kinds of tools can occur and offers next steps to overcome these challenges.« less

Pilot testing of SHRP 2 reliability data and analytical products: Minnesota.

DOT National Transportation Integrated Search

2015-01-01

The Minnesota pilot site has undertaken an effort to test data and analytical tools developed through the Strategic Highway Research Program (SHRP) 2 Reliability focus area. The purpose of these tools is to facilitate the improvement of travel time r...

Development of the Gliding Hole of the Dynamics Compression Plate

NASA Astrophysics Data System (ADS)

Salim, U. A.; Suyitno; Magetsari, R.; Mahardika, M.

2017-02-01

The gliding hole of the dynamics compression plate is designed to facilitate relative movement of pedicle screw during surgery application. The gliding hole shape is then geometrically complex. The gliding hole manufactured using machining processes used to employ ball-nose cutting tool. Then, production cost is expensive due to long production time. This study proposed to increase productivity of DCP products by introducing forming process (cold forming). The forming process used to involve any press tool devices. In the closed die forming press tool is designed with little allowance, then work-pieces is trapped in the mould after forming. Therefore, it is very important to determine hole geometry and dimensions of raw material in order to success on forming process. This study optimized the hole sizes with both geometry analytics and experiments. The success of the forming process was performed by increasing the holes size on the raw materials. The holes size need to be prepared is diameter of 5.5 mm with a length of 11.4 mm for the plate thickness 3 mm and diameter of 6 mm with a length of 12.5 mm for the plate thickness 4 mm.

Evaluating supplier quality performance using fuzzy analytical hierarchy process

NASA Astrophysics Data System (ADS)

Ahmad, Nazihah; Kasim, Maznah Mat; Rajoo, Shanmugam Sundram Kalimuthu

2014-12-01

Evaluating supplier quality performance is vital in ensuring continuous supply chain improvement, reducing the operational costs and risks towards meeting customer's expectation. This paper aims to illustrate an application of Fuzzy Analytical Hierarchy Process to prioritize the evaluation criteria in a context of automotive manufacturing in Malaysia. Five main criteria were identified which were quality, cost, delivery, customer serviceand technology support. These criteria had been arranged into hierarchical structure and evaluated by an expert. The relative importance of each criteria was determined by using linguistic variables which were represented as triangular fuzzy numbers. The Center of Gravity defuzzification method was used to convert the fuzzy evaluations into their corresponding crisps values. Such fuzzy evaluation can be used as a systematic tool to overcome the uncertainty evaluation of suppliers' performance which usually associated with human being subjective judgments.

Real-Time XRD Studies of Li-O2 Electrochemical Reaction in Nonaqueous Lithium-Oxygen Battery.

PubMed

Lim, Hyunseob; Yilmaz, Eda; Byon, Hye Ryung

2012-11-01

Understanding of electrochemical process in rechargeable Li-O2 battery has suffered from lack of proper analytical tool, especially related to the identification of chemical species and number of electrons involved in the discharge/recharge process. Here we present a simple and straightforward analytical method for simultaneously attaining chemical and quantified information of Li2O2 (discharge product) and byproducts using in situ XRD measurement. By real-time monitoring of solid-state Li2O2 peak area, the accurate efficiency of Li2O2 formation and the number of electrons can be evaluated during full discharge. Furthermore, by observation of sequential area change of Li2O2 peak during recharge, we found nonlinearity of Li2O2 decomposition rate for the first time in ether-based electrolyte.

Looking back to inform the future: The role of cognition in forest disturbance characterization from remote sensing imagery

NASA Astrophysics Data System (ADS)

Bianchetti, Raechel Anne

Remotely sensed images have become a ubiquitous part of our daily lives. From novice users, aiding in search and rescue missions using tools such as TomNod, to trained analysts, synthesizing disparate data to address complex problems like climate change, imagery has become central to geospatial problem solving. Expert image analysts are continually faced with rapidly developing sensor technologies and software systems. In response to these cognitively demanding environments, expert analysts develop specialized knowledge and analytic skills to address increasingly complex problems. This study identifies the knowledge, skills, and analytic goals of expert image analysts tasked with identification of land cover and land use change. Analysts participating in this research are currently working as part of a national level analysis of land use change, and are well versed with the use of TimeSync, forest science, and image analysis. The results of this study benefit current analysts as it improves their awareness of their mental processes used during the image interpretation process. The study also can be generalized to understand the types of knowledge and visual cues that analysts use when reasoning with imagery for purposes beyond land use change studies. Here a Cognitive Task Analysis framework is used to organize evidence from qualitative knowledge elicitation methods for characterizing the cognitive aspects of the TimeSync image analysis process. Using a combination of content analysis, diagramming, semi-structured interviews, and observation, the study highlights the perceptual and cognitive elements of expert remote sensing interpretation. Results show that image analysts perform several standard cognitive processes, but flexibly employ these processes in response to various contextual cues. Expert image analysts' ability to think flexibly during their analysis process was directly related to their amount of image analysis experience. Additionally, results show that the basic Image Interpretation Elements continue to be important despite technological augmentation of the interpretation process. These results are used to derive a set of design guidelines for developing geovisual analytic tools and training to support image analysis.

Application of non-traditional stable isotopes in analytical ecogeochemistry assessed by MC ICP-MS--A critical review.

PubMed

Irrgeher, Johanna; Prohaska, Thomas

2016-01-01

Analytical ecogeochemistry is an evolving scientific field dedicated to the development of analytical methods and tools and their application to ecological questions. Traditional stable isotopic systems have been widely explored and have undergone continuous development during the last century. The variations of the isotopic composition of light elements (H, O, N, C, and S) have provided the foundation of stable isotope analysis followed by the analysis of traditional geochemical isotope tracers (e.g., Pb, Sr, Nd, Hf). Questions in a considerable diversity of scientific fields have been addressed, many of which can be assigned to the field of ecogeochemistry. Over the past 15 years, other stable isotopes (e.g., Li, Zn, Cu, Cl) have emerged gradually as novel tools for the investigation of scientific topics that arise in ecosystem research and have enabled novel discoveries and explorations. These systems are often referred to as non-traditional isotopes. The small isotopic differences of interest that are increasingly being addressed for a growing number of isotopic systems represent a challenge to the analytical scientist and push the limits of today's instruments constantly. This underlines the importance of a metrologically sound concept of analytical protocols and procedures and a solid foundation of data processing strategies and uncertainty considerations before these small isotopic variations can be interpreted in the context of applied ecosystem research. This review focuses on the development of isotope research in ecogeochemistry, the requirements for successful detection of small isotopic shifts, and highlights the most recent and innovative applications in the field.

Analytical calculation on the determination of steep side wall angles from far field measurements

NASA Astrophysics Data System (ADS)

Cisotto, Luca; Pereira, Silvania F.; Urbach, H. Paul

2018-06-01

In the semiconductor industry, the performance and capabilities of the lithographic process are evaluated by measuring specific structures. These structures are often gratings of which the shape is described by a few parameters such as period, middle critical dimension, height, and side wall angle (SWA). Upon direct measurement or retrieval of these parameters, the determination of the SWA suffers from considerable inaccuracies. Although the scattering effects that steep SWAs have on the illumination can be obtained with rigorous numerical simulations, analytical models constitute a very useful tool to get insights into the problem we are treating. In this paper, we develop an approach based on analytical calculations to describe the scattering of a cliff and a ridge with steep SWAs. We also propose a detection system to determine the SWAs of the structures.

LOX/hydrocarbon rocket engine analytical design methodology development and validation. Volume 1: Executive summary and technical narrative

NASA Technical Reports Server (NTRS)

Pieper, Jerry L.; Walker, Richard E.

1993-01-01

During the past three decades, an enormous amount of resources were expended in the design and development of Liquid Oxygen/Hydrocarbon and Hydrogen (LOX/HC and LOX/H2) rocket engines. A significant portion of these resources were used to develop and demonstrate the performance and combustion stability for each new engine. During these efforts, many analytical and empirical models were developed that characterize design parameters and combustion processes that influence performance and stability. Many of these models are suitable as design tools, but they have not been assembled into an industry-wide usable analytical design methodology. The objective of this program was to assemble existing performance and combustion stability models into a usable methodology capable of producing high performing and stable LOX/hydrocarbon and LOX/hydrogen propellant booster engines.

Benchmarking the Collocation Stand-Alone Library and Toolkit (CSALT)

NASA Technical Reports Server (NTRS)

Hughes, Steven; Knittel, Jeremy; Shoan, Wendy; Kim, Youngkwang; Conway, Claire; Conway, Darrel J.

2017-01-01

This paper describes the processes and results of Verification and Validation (VV) efforts for the Collocation Stand Alone Library and Toolkit (CSALT). We describe the test program and environments, the tools used for independent test data, and comparison results. The VV effort employs classical problems with known analytic solutions, solutions from other available software tools, and comparisons to benchmarking data available in the public literature. Presenting all test results are beyond the scope of a single paper. Here we present high-level test results for a broad range of problems, and detailed comparisons for selected problems.

Benchmarking the Collocation Stand-Alone Library and Toolkit (CSALT)

NASA Technical Reports Server (NTRS)

Hughes, Steven; Knittel, Jeremy; Shoan, Wendy (Compiler); Kim, Youngkwang; Conway, Claire (Compiler); Conway, Darrel

2017-01-01

This paper describes the processes and results of Verification and Validation (V&V) efforts for the Collocation Stand Alone Library and Toolkit (CSALT). We describe the test program and environments, the tools used for independent test data, and comparison results. The V&V effort employs classical problems with known analytic solutions, solutions from other available software tools, and comparisons to benchmarking data available in the public literature. Presenting all test results are beyond the scope of a single paper. Here we present high-level test results for a broad range of problems, and detailed comparisons for selected problems.

Stochastic modelling of the hydrologic operation of rainwater harvesting systems

NASA Astrophysics Data System (ADS)

Guo, Rui; Guo, Yiping

2018-07-01

Rainwater harvesting (RWH) systems are an effective low impact development practice that provides both water supply and runoff reduction benefits. A stochastic modelling approach is proposed in this paper to quantify the water supply reliability and stormwater capture efficiency of RWH systems. The input rainfall series is represented as a marked Poisson process and two typical water use patterns are analytically described. The stochastic mass balance equation is solved analytically, and based on this, explicit expressions relating system performance to system characteristics are derived. The performances of a wide variety of RWH systems located in five representative climatic regions of the United States are examined using the newly derived analytical equations. Close agreements between analytical and continuous simulation results are shown for all the compared cases. In addition, an analytical equation is obtained expressing the required storage size as a function of the desired water supply reliability, average water use rate, as well as rainfall and catchment characteristics. The equations developed herein constitute a convenient and effective tool for sizing RWH systems and evaluating their performances.

Analytic expressions for Atomic Layer Deposition: coverage, throughput, and materials utilization in cross-flow, particle coating, and spatial ALD

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yanguas-Gil, Angel; Elam, Jeffrey W.

2014-05-01

In this work, the authors present analytic models for atomic layer deposition (ALD) in three common experimental configurations: cross-flow, particle coating, and spatial ALD. These models, based on the plug-flow and well-mixed approximations, allow us to determine the minimum dose times and materials utilization for all three configurations. A comparison between the three models shows that throughput and precursor utilization can each be expressed by universal equations, in which the particularity of the experimental system is contained in a single parameter related to the residence time of the precursor in the reactor. For the case of cross-flow reactors, the authorsmore » show how simple analytic expressions for the reactor saturation profiles agree well with experimental results. Consequently, the analytic model can be used to extract information about the ALD surface chemistry (e. g., the reaction probability) by comparing the analytic and experimental saturation profiles, providing a useful tool for characterizing new and existing ALD processes. (C) 2014 American Vacuum Society« less

Neurocognitive inefficacy of the strategy process.

PubMed

Klein, Harold E; D'Esposito, Mark

2007-11-01

The most widely used (and taught) protocols for strategic analysis-Strengths, Weaknesses, Opportunities, and Threats (SWOT) and Porter's (1980) Five Force Framework for industry analysis-have been found to be insufficient as stimuli for strategy creation or even as a basis for further strategy development. We approach this problem from a neurocognitive perspective. We see profound incompatibilities between the cognitive process-deductive reasoning-channeled into the collective mind of strategists within the formal planning process through its tools of strategic analysis (i.e., rational technologies) and the essentially inductive reasoning process actually needed to address ill-defined, complex strategic situations. Thus, strategic analysis protocols that may appear to be and, indeed, are entirely rational and logical are not interpretable as such at the neuronal substrate level where thinking takes place. The analytical structure (or propositional representation) of these tools results in a mental dead end, the phenomenon known in cognitive psychology as functional fixedness. The difficulty lies with the inability of the brain to make out meaningful (i.e., strategy-provoking) stimuli from the mental images (or depictive representations) generated by strategic analysis tools. We propose decreasing dependence on these tools and conducting further research employing brain imaging technology to explore complex data handling protocols with richer mental representation and greater potential for strategy creation.

Developing an analytical tool for evaluating EMS system design changes and their impact on cardiac arrest outcomes: combining geographic information systems with register data on survival rates

PubMed Central

2013-01-01

Background Out-of-hospital cardiac arrest (OHCA) is a frequent and acute medical condition that requires immediate care. We estimate survival rates from OHCA in the area of Stockholm, through developing an analytical tool for evaluating Emergency Medical Services (EMS) system design changes. The study also is an attempt to validate the proposed model used to generate the outcome measures for the study. Methods and results This was done by combining a geographic information systems (GIS) simulation of driving times with register data on survival rates. The emergency resources comprised ambulance alone and ambulance plus fire services. The simulation model predicted a baseline survival rate of 3.9 per cent, and reducing the ambulance response time by one minute increased survival to 4.6 per cent. Adding the fire services as first responders (dual dispatch) increased survival to 6.2 per cent from the baseline level. The model predictions were validated using empirical data. Conclusion We have presented an analytical tool that easily can be generalized to other regions or countries. The model can be used to predict outcomes of cardiac arrest prior to investment in EMS design changes that affect the alarm process, e.g. (1) static changes such as trimming the emergency call handling time or (2) dynamic changes such as location of emergency resources or which resources should carry a defibrillator. PMID:23415045

SAM Methods Query

EPA Pesticide Factsheets

Laboratories measuring target chemical, radiochemical, pathogens, and biotoxin analytes in environmental samples can use this online query tool to identify analytical methods included in EPA's Selected Analytical Methods for Environmental Remediation

FPI: FM Success through Analytics

ERIC Educational Resources Information Center

Hickling, Duane

2013-01-01

The APPA Facilities Performance Indicators (FPI) is perhaps one of the most powerful analytical tools that institutional facilities professionals have at their disposal. It is a diagnostic facilities performance management tool that addresses the essential questions that facilities executives must answer to effectively perform their roles. It…

In-line and Real-time Monitoring of Resonant Acoustic Mixing by Near-infrared Spectroscopy Combined with Chemometric Technology for Process Analytical Technology Applications in Pharmaceutical Powder Blending Systems.

PubMed

Tanaka, Ryoma; Takahashi, Naoyuki; Nakamura, Yasuaki; Hattori, Yusuke; Ashizawa, Kazuhide; Otsuka, Makoto

2017-01-01

Resonant acoustic ® mixing (RAM) technology is a system that performs high-speed mixing by vibration through the control of acceleration and frequency. In recent years, real-time process monitoring and prediction has become of increasing interest, and process analytical technology (PAT) systems will be increasingly introduced into actual manufacturing processes. This study examined the application of PAT with the combination of RAM, near-infrared spectroscopy, and chemometric technology as a set of PAT tools for introduction into actual pharmaceutical powder blending processes. Content uniformity was based on a robust partial least squares regression (PLSR) model constructed to manage the RAM configuration parameters and the changing concentration of the components. As a result, real-time monitoring may be possible and could be successfully demonstrated for in-line real-time prediction of active pharmaceutical ingredients and other additives using chemometric technology. This system is expected to be applicable to the RAM method for the risk management of quality.

Bibliometric mapping: eight decades of analytical chemistry, with special focus on the use of mass spectrometry.

PubMed

Waaijer, Cathelijn J F; Palmblad, Magnus

2015-01-01

In this Feature we use automatic bibliometric mapping tools to visualize the history of analytical chemistry from the 1920s until the present. In particular, we have focused on the application of mass spectrometry in different fields. The analysis shows major shifts in research focus and use of mass spectrometry. We conclude by discussing the application of bibliometric mapping and visualization tools in analytical chemists' research.

Influence of Pre-Analytical Factors on Thymus- and Activation-Regulated Chemokine Quantitation in Plasma

PubMed Central

Zhao, Xuemei; Delgado, Liliana; Weiner, Russell; Laterza, Omar F.

2015-01-01

Thymus- and activation-regulated chemokine (TARC) in serum/plasma associates with the disease activity of atopic dermatitis (AD), and is a promising tool for assessing the response to the treatment of the disease. TARC also exists within platelets, with elevated levels detectable in AD patients. We examined the effects of pre-analytical factors on the quantitation of TARC in human EDTA plasma. TARC levels in platelet-free plasma were significantly lower than those in platelet-containing plasma. After freeze-thaw, TARC levels increased in platelet-containing plasma, but remained unchanged in platelet-free plasma, suggesting TARC was released from the platelets during the freeze-thaw process. In contrast, TARC levels were stable in serum independent of freeze-thaw. These findings underscore the importance of pre-analytical factors to TARC quantitation. Plasma TARC levels should be measured in platelet-free plasma for accurate quantitation. Pre-analytical factors influence the quantitation, interpretation, and implementation of circulating TARC as a biomarker for the development of AD therapeutics. PMID:28936246

Analytical methodology for determination of helicopter IFR precision approach requirements. [pilot workload and acceptance level

NASA Technical Reports Server (NTRS)

Phatak, A. V.

1980-01-01

A systematic analytical approach to the determination of helicopter IFR precision approach requirements is formulated. The approach is based upon the hypothesis that pilot acceptance level or opinion rating of a given system is inversely related to the degree of pilot involvement in the control task. A nonlinear simulation of the helicopter approach to landing task incorporating appropriate models for UH-1H aircraft, the environmental disturbances and the human pilot was developed as a tool for evaluating the pilot acceptance hypothesis. The simulated pilot model is generic in nature and includes analytical representation of the human information acquisition, processing, and control strategies. Simulation analyses in the flight director mode indicate that the pilot model used is reasonable. Results of the simulation are used to identify candidate pilot workload metrics and to test the well known performance-work-load relationship. A pilot acceptance analytical methodology is formulated as a basis for further investigation, development and validation.

SAM Pathogen Methods Query

EPA Pesticide Factsheets

Laboratories measuring target pathogen analytes in environmental samples can use this online query tool to identify analytical methods in EPA's Selected Analytical Methods for Environmental Remediation and Recovery for select pathogens.

Coastal On-line Assessment and Synthesis Tool 2.0

NASA Technical Reports Server (NTRS)

Brown, Richard; Navard, Andrew; Nguyen, Beth

2011-01-01

COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest.

LC-MS based analysis of endogenous steroid hormones in human hair.

PubMed

Gao, Wei; Kirschbaum, Clemens; Grass, Juliane; Stalder, Tobias

2016-09-01

The quantification of endogenous steroid hormone concentrations in hair is increasingly used as a method for obtaining retrospective information on long-term integrated hormone exposure. Several different analytical procedures have been employed for hair steroid analysis, with liquid chromatography-mass spectrometry (LC-MS) being recognized as a particularly powerful analytical tool. Several methodological aspects affect the performance of LC-MS systems for hair steroid analysis, including sample preparation and pretreatment, steroid extraction, post-incubation purification, LC methodology, ionization techniques and MS specifications. Here, we critically review the differential value of such protocol variants for hair steroid hormones analysis, focusing on both analytical quality and practical feasibility issues. Our results show that, when methodological challenges are adequately addressed, LC-MS protocols can not only yield excellent sensitivity and specificity but are also characterized by relatively simple sample processing and short run times. This makes LC-MS based hair steroid protocols particularly suitable as a high-quality option for routine application in research contexts requiring the processing of larger numbers of samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Real-time particle size analysis using focused beam reflectance measurement as a process analytical technology tool for a continuous granulation-drying-milling process.

PubMed

Kumar, Vijay; Taylor, Michael K; Mehrotra, Amit; Stagner, William C

2013-06-01

Focused beam reflectance measurement (FBRM) was used as a process analytical technology tool to perform inline real-time particle size analysis of a proprietary granulation manufactured using a continuous twin-screw granulation-drying-milling process. A significant relationship between D20, D50, and D80 length-weighted chord length and sieve particle size was observed with a p value of <0.0001 and R(2) of 0.886. A central composite response surface statistical design was used to evaluate the effect of granulator screw speed and Comil® impeller speed on the length-weighted chord length distribution (CLD) and particle size distribution (PSD) determined by FBRM and nested sieve analysis, respectively. The effect of granulator speed and mill speed on bulk density, tapped density, Compressibility Index, and Flowability Index were also investigated. An inline FBRM probe placed below the Comil-generated chord lengths and CLD data at designated times. The collection of the milled samples for sieve analysis and PSD evaluation were coordinated with the timing of the FBRM determinations. Both FBRM and sieve analysis resulted in similar bimodal distributions for all ten manufactured batches studied. Within the experimental space studied, the granulator screw speed (650-850 rpm) and Comil® impeller speed (1,000-2,000 rpm) did not have a significant effect on CLD, PSD, bulk density, tapped density, Compressibility Index, and Flowability Index (p value > 0.05).

The role of analytical chemistry in Niger Delta petroleum exploration: a review.

PubMed

Akinlua, Akinsehinwa

2012-06-12

Petroleum and organic matter from which the petroleum is derived are composed of organic compounds with some trace elements. These compounds give an insight into the origin, thermal maturity and paleoenvironmental history of petroleum, which are essential elements in petroleum exploration. The main tool to acquire the geochemical data is analytical techniques. Due to progress in the development of new analytical techniques, many hitherto petroleum exploration problems have been resolved. Analytical chemistry has played a significant role in the development of petroleum resources of Niger Delta. Various analytical techniques that have aided the success of petroleum exploration in the Niger Delta are discussed. The analytical techniques that have helped to understand the petroleum system of the basin are also described. Recent and emerging analytical methodologies including green analytical methods as applicable to petroleum exploration particularly Niger Delta petroleum province are discussed in this paper. Analytical chemistry is an invaluable tool in finding the Niger Delta oils. Copyright © 2011 Elsevier B.V. All rights reserved.

'Big Data' Collaboration: Exploring, Recording and Sharing Enterprise Knowledge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sukumar, Sreenivas R; Ferrell, Regina Kay

2013-01-01

As data sources and data size proliferate, knowledge discovery from "Big Data" is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly-related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis, inference and decision-making lifecycle. We motivate the implementation of an enterprise data-discovery and knowledge recorder tool, called SEEKER based on real world case-study. We demonstrate SEEKER capturing schema and data-element relationships, tracking the data elementsmore » of value based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as digital record of institutional domain knowledge and a documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by avoiding analytic silos, expediting the process of multi-source data integration and intelligently documenting discoveries from fellow analysts.« less

Development of computer-based analytical tool for assessing physical protection system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mardhi, Alim, E-mail: alim-m@batan.go.id; Chulalongkorn University, Faculty of Engineering, Nuclear Engineering Department, 254 Phayathai Road, Pathumwan, Bangkok Thailand. 10330; Pengvanich, Phongphaeth, E-mail: ppengvan@gmail.com

Assessment of physical protection system effectiveness is the priority for ensuring the optimum protection caused by unlawful acts against a nuclear facility, such as unauthorized removal of nuclear materials and sabotage of the facility itself. Since an assessment based on real exercise scenarios is costly and time-consuming, the computer-based analytical tool can offer the solution for approaching the likelihood threat scenario. There are several currently available tools that can be used instantly such as EASI and SAPE, however for our research purpose it is more suitable to have the tool that can be customized and enhanced further. In this work,more » we have developed a computer–based analytical tool by utilizing the network methodological approach for modelling the adversary paths. The inputs are multi-elements in security used for evaluate the effectiveness of the system’s detection, delay, and response. The tool has capability to analyze the most critical path and quantify the probability of effectiveness of the system as performance measure.« less

Control/structure interaction conceptual design tool

NASA Technical Reports Server (NTRS)

Briggs, Hugh C.

1990-01-01

The JPL Control/Structure Interaction Program is developing new analytical methods for designing micro-precision spacecraft with controlled structures. One of these, the Conceptual Design Tool, will illustrate innovative new approaches to the integration of multi-disciplinary analysis and design methods. The tool will be used to demonstrate homogeneity of presentation, uniform data representation across analytical methods, and integrated systems modeling. The tool differs from current 'integrated systems' that support design teams most notably in its support for the new CSI multi-disciplinary engineer. The design tool will utilize a three dimensional solid model of the spacecraft under design as the central data organization metaphor. Various analytical methods, such as finite element structural analysis, control system analysis, and mechanical configuration layout, will store and retrieve data from a hierarchical, object oriented data structure that supports assemblies of components with associated data and algorithms. In addition to managing numerical model data, the tool will assist the designer in organizing, stating, and tracking system requirements.

Development of computer-based analytical tool for assessing physical protection system

NASA Astrophysics Data System (ADS)

Mardhi, Alim; Pengvanich, Phongphaeth

2016-01-01

Assessment of physical protection system effectiveness is the priority for ensuring the optimum protection caused by unlawful acts against a nuclear facility, such as unauthorized removal of nuclear materials and sabotage of the facility itself. Since an assessment based on real exercise scenarios is costly and time-consuming, the computer-based analytical tool can offer the solution for approaching the likelihood threat scenario. There are several currently available tools that can be used instantly such as EASI and SAPE, however for our research purpose it is more suitable to have the tool that can be customized and enhanced further. In this work, we have developed a computer-based analytical tool by utilizing the network methodological approach for modelling the adversary paths. The inputs are multi-elements in security used for evaluate the effectiveness of the system's detection, delay, and response. The tool has capability to analyze the most critical path and quantify the probability of effectiveness of the system as performance measure.

Active controls: A look at analytical methods and associated tools

NASA Technical Reports Server (NTRS)

Newsom, J. R.; Adams, W. M., Jr.; Mukhopadhyay, V.; Tiffany, S. H.; Abel, I.

1984-01-01

A review of analytical methods and associated tools for active controls analysis and design problems is presented. Approaches employed to develop mathematical models suitable for control system analysis and/or design are discussed. Significant efforts have been expended to develop tools to generate the models from the standpoint of control system designers' needs and develop the tools necessary to analyze and design active control systems. Representative examples of these tools are discussed. Examples where results from the methods and tools have been compared with experimental data are also presented. Finally, a perspective on future trends in analysis and design methods is presented.

SAM Biotoxin Methods Query

EPA Pesticide Factsheets

Laboratories measuring target biotoxin analytes in environmental samples can use this online query tool to identify analytical methods included in EPA's Selected Analytical Methods for Environmental Remediation and Recovery for select biotoxins.

SAM Chemical Methods Query

EPA Pesticide Factsheets

Laboratories measuring target chemical, radiochemical, pathogens, and biotoxin analytes in environmental samples can use this online query tool to identify analytical methods in EPA's Selected Analytical Methods for Environmental Remediation and Recovery

Using Learning Analytics to Support Engagement in Collaborative Writing

ERIC Educational Resources Information Center

Liu, Ming; Pardo, Abelardo; Liu, Li

2017-01-01

Online collaborative writing tools provide an efficient way to complete a writing task. However, existing tools only focus on technological affordances and ignore the importance of social affordances in a collaborative learning environment. This article describes a learning analytic system that analyzes writing behaviors, and creates…

Application of Learning Analytics Using Clustering Data Mining for Students' Disposition Analysis

ERIC Educational Resources Information Center

Bharara, Sanyam; Sabitha, Sai; Bansal, Abhay

2018-01-01

Learning Analytics (LA) is an emerging field in which sophisticated analytic tools are used to improve learning and education. It draws from, and is closely tied to, a series of other fields of study like business intelligence, web analytics, academic analytics, educational data mining, and action analytics. The main objective of this research…

Chatter reduction in boring process by using piezoelectric shunt damping with experimental verification

NASA Astrophysics Data System (ADS)

Yigit, Ufuk; Cigeroglu, Ender; Budak, Erhan

2017-09-01

Chatter is a self-excited type of vibration that develops during machining due to process-structure dynamic interactions resulting in modulated chip thickness. Chatter is an important problem as it results in poor surface quality, reduced productivity and tool life. The stability of a cutting process is strongly influenced by the frequency response function (FRF) at the cutting point. In this study, the effect of piezoelectric shunt damping on chatter vibrations in a boring process is studied. In piezoelectric shunt damping method, an electrical impedance is connected to a piezoelectric transducer which is bonded on cutting tool. Electrical impedance of the circuit consisting of piezoceramic transducer and passive shunt is tuned to the desired natural frequency of the cutting tool in order to maximize damping. The optimum damping is achieved in analytical and finite element models (FEM) by using a genetic algorithm focusing on the real part of the tool point FRF rather than the amplitude. Later, a practical boring bar is considered where the optimum circuit parameters are obtained by the FEM. Afterwards, the effect of the optimized piezoelectric shunt damping on the dynamic rigidity and absolute stability limit of the cutting process are investigated experimentally by modal analysis and cutting tests. It is both theoretically and experimentally shown that application of piezoelectric shunt damping results in a significant increase in the absolute stability limit in boring operations.

A Learning Analytics Methodology for Detecting Sentiment in Student Fora: A Case Study in Distance Education

ERIC Educational Resources Information Center

Kagklis, Vasileios; Karatrantou, Anthi; Tantoula, Maria; Panagiotakopoulos, Chris T.; Verykios, Vassilios S.

2015-01-01

Online fora have become not only one of the most popular communication tools in e-learning environments, but also one of the key factors of the learning process, especially in distance learning, as they can provide to the students involved, motivation for collaboration in order to achieve a common goal. The purpose of this study is to analyse data…

Stability of compressible Taylor-Couette flow

NASA Technical Reports Server (NTRS)

Kao, K.; Chow, C.

1992-01-01

The objectives of this paper are to: (1) develop both analytical and numerical tools that can be used to predict the onset of instability and subsequently to simulate the transition process by which the originally laminar flow evolves into a turbulent flow; and (2) conduct the preliminary investigations with the purpose of understanding the mechanisms of the vortical structures of the compressible flow between tow concentric cylinders.

Characterization and measurement of polymer wear

NASA Technical Reports Server (NTRS)

Buckley, D. H.; Aron, P. R.

1984-01-01

Analytical tools which characterize the polymer wear process are discussed. The devices discussed include: visual observation of polymer wear with SEM, the quantification with surface profilometry and ellipsometry, to study the chemistry with AES, XPS and SIMS, to establish interfacial polymer orientation and accordingly bonding with QUARTIR, polymer state with Raman spectroscopy and stresses that develop in polymer films using a X-ray double crystal camera technique.

Phase transformations in steels: Processing, microstructure, and performance

DOE PAGES

Gibbs, Paul J.

2014-04-03

In this study, contemporary steel research is revealing new processing avenues to tailor microstructure and properties that, until recently, were only imaginable. Much of the technological versatility facilitating this development is provided by the understanding and utilization of the complex phase transformation sequences available in ferrous alloys. Today we have the opportunity to explore the diverse phenomena displayed by steels with specialized analytical and experimental tools. Advances in multi-scale characterization techniques provide a fresh perspective into microstructural relationships at the macro- and micro-scale, enabling a fundamental understanding of the role of phase transformations during processing and subsequent deformation.

An approach for investigation of secure access processes at a combined e-learning environment

NASA Astrophysics Data System (ADS)

Romansky, Radi; Noninska, Irina

2017-12-01

The article discuses an approach to investigate processes for regulation the security and privacy control at a heterogenous e-learning environment realized as a combination of traditional and cloud means and tools. Authors' proposal for combined architecture of e-learning system is presented and main subsystems and procedures are discussed. A formalization of the processes for using different types resources (public, private internal and private external) is proposed. The apparatus of Markovian chains (MC) is used for modeling and analytical investigation of the secure access to the resources is used and some assessments are presented.

PAT-tools for process control in pharmaceutical film coating applications.

PubMed

Knop, Klaus; Kleinebudde, Peter

2013-12-05

Recent development of analytical techniques to monitor the coating process of pharmaceutical solid dosage forms such as pellets and tablets are described. The progress from off- or at-line measurements to on- or in-line applications is shown for the spectroscopic methods near infrared (NIR) and Raman spectroscopy as well as for terahertz pulsed imaging (TPI) and image analysis. The common goal of all these methods is to control or at least to monitor the coating process and/or to estimate the coating end point through timely measurements. Copyright © 2013 Elsevier B.V. All rights reserved.

Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning

ERIC Educational Resources Information Center

Kelly, Nick; Thompson, Kate; Yeoman, Pippa

2015-01-01

This paper describes theory-led design as a way of developing novel tools for learning analytics (LA). It focuses upon the domain of automated discourse analysis (ADA) of group learning activities to help an instructor to orchestrate online groups in real-time. The paper outlines the literature on the development of LA tools within the domain of…

Analytical solutions to dissolved contaminant plume evolution with source depletion during carbon dioxide storage.

PubMed

Yang, Yong; Liu, Yongzhong; Yu, Bo; Ding, Tian

2016-06-01

Volatile contaminants may migrate with carbon dioxide (CO2) injection or leakage in subsurface formations, which leads to the risk of the CO2 storage and the ecological environment. This study aims to develop an analytical model that could predict the contaminant migration process induced by CO2 storage. The analytical model with two moving boundaries is obtained through the simplification of the fully coupled model for the CO2-aqueous phase -stagnant phase displacement system. The analytical solutions are confirmed and assessed through the comparison with the numerical simulations of the fully coupled model. Then, some key variables in the analytical solutions, including the critical time, the locations of the dual moving boundaries and the advance velocity, are discussed to present the characteristics of contaminant migration in the multi-phase displacement system. The results show that these key variables are determined by four dimensionless numbers, Pe, RD, Sh and RF, which represent the effects of the convection, the dispersion, the interphase mass transfer and the retention factor of contaminant, respectively. The proposed analytical solutions could be used for tracking the migration of the injected CO2 and the contaminants in subsurface formations, and also provide an analytical tool for other solute transport in multi-phase displacement system. Copyright © 2016 Elsevier B.V. All rights reserved.

[Progress in the application of laser ablation ICP-MS to surface microanalysis in material science].

PubMed

Zhang, Yong; Jia, Yun-hai; Chen, Ji-wen; Shen, Xue-jing; Liu, Ying; Zhao, Leiz; Li, Dong-ling; Hang, Peng-cheng; Zhao, Zhen; Fan, Wan-lun; Wang, Hai-zhou

2014-08-01

In the present paper, apparatus and theory of surface analysis is introduced, and the progress in the application of laser ablation ICP-MS to microanalysis in ferrous, nonferrous and semiconductor field is reviewed in detail. Compared with traditional surface analytical tools, such as SEM/EDS (scanning electron microscopy/energy dispersive spectrum), EPMA (electron probe microanalysis analysis), AES (auger energy spectrum), etc. the advantage is little or no sample preparation, adjustable spatial resolution according to analytical demand, multi-element analysis and high sensitivity. It is now a powerful complementary method to traditional surface analytical tool. With the development of LA-ICP-MS technology maturing, more and more analytical workers will use this powerful tool in the future, and LA-ICP-MS will be a super star in elemental analysis field just like LIBS (Laser-induced breakdown spectroscopy).

Improving Logistics Processes in Industry Using Web Technologies

NASA Astrophysics Data System (ADS)

Jánošík, Ján; Tanuška, Pavol; Václavová, Andrea

2016-12-01

The aim of this paper is to propose the concept of a system that takes advantage of web technologies and integrates them into the management process and management of internal stocks which may relate to external applications and creates the conditions to transform a Computerized Control of Warehouse Stock (CCWS) in the company. The importance of implementing CCWS is in the elimination of the claims caused by the human factor, as well as to allow the processing of information for analytical purposes and their subsequent use to improve internal processes. Using CCWS in the company would also facilitate better use of the potential tools Business Intelligence and Data Mining.

Evaluating the compatibility of multi-functional and intensive urban land uses

NASA Astrophysics Data System (ADS)

Taleai, M.; Sharifi, A.; Sliuzas, R.; Mesgari, M.

2007-12-01

This research is aimed at developing a model for assessing land use compatibility in densely built-up urban areas. In this process, a new model was developed through the combination of a suite of existing methods and tools: geographical information system, Delphi methods and spatial decision support tools: namely multi-criteria evaluation analysis, analytical hierarchy process and ordered weighted average method. The developed model has the potential to calculate land use compatibility in both horizontal and vertical directions. Furthermore, the compatibility between the use of each floor in a building and its neighboring land uses can be evaluated. The method was tested in a built-up urban area located in Tehran, the capital city of Iran. The results show that the model is robust in clarifying different levels of physical compatibility between neighboring land uses. This paper describes the various steps and processes of developing the proposed land use compatibility evaluation model (CEM).

Machine learning and predictive data analytics enabling metrology and process control in IC fabrication

NASA Astrophysics Data System (ADS)

Rana, Narender; Zhang, Yunlin; Wall, Donald; Dirahoui, Bachir; Bailey, Todd C.

2015-03-01

Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.

Computerized Modeling and Loaded Tooth Contact Analysis of Hypoid Gears Manufactured by Face Hobbing Process

NASA Astrophysics Data System (ADS)

Nishino, Takayuki

The face hobbing process has been widely applied in automotive industry. But so far few analytical tools have been developed. This makes it difficult for us to optimize gear design. To settle this situation, this study aims at developing a computerized tool to predict the running performances such as loaded tooth contact pattern, static transmission error and so on. First, based upon kinematical analysis of a cutting machine, a mathematical description of tooth surface generation is given. Second, based upon the theory of gearing and differential geometry, conjugate tooth surfaces are studied. Then contact lines are generated. Third, load distribution along contact lines is formulated. Last, the numerical model is validated by measuring loaded transmission error and loaded tooth contact pattern.

In line NIR quantification of film thickness on pharmaceutical pellets during a fluid bed coating process.

PubMed

Lee, Min-Jeong; Seo, Da-Young; Lee, Hea-Eun; Wang, In-Chun; Kim, Woo-Sik; Jeong, Myung-Yung; Choi, Guang J

2011-01-17

Along with the risk-based approach, process analytical technology (PAT) has emerged as one of the key elements to fully implement QbD (quality-by-design). Near-infrared (NIR) spectroscopy has been extensively applied as an in-line/on-line analytical tool in biomedical and chemical industries. In this study, the film thickness on pharmaceutical pellets was examined for quantification using in-line NIR spectroscopy during a fluid-bed coating process. A precise monitoring of coating thickness and its prediction with a suitable control strategy is crucial to the quality assurance of solid dosage forms including dissolution characteristics. Pellets of a test formulation were manufactured and coated in a fluid-bed by spraying a hydroxypropyl methylcellulose (HPMC) coating solution. NIR spectra were acquired via a fiber-optic probe during the coating process, followed by multivariate analysis utilizing partial least squares (PLS) calibration models. The actual coating thickness of pellets was measured by two separate methods, confocal laser scanning microscopy (CLSM) and laser diffraction particle size analysis (LD-PSA). Both characterization methods gave superb correlation results, and all determination coefficient (R(2)) values exceeded 0.995. In addition, a prediction coating experiment for 70min demonstrated that the end-point can be accurately designated via NIR in-line monitoring with appropriate calibration models. In conclusion, our approach combining in-line NIR monitoring with CLSM and LD-PSA can be applied as an effective PAT tool for fluid-bed pellet coating processes. Copyright © 2010 Elsevier B.V. All rights reserved.

Investigation Organizer

NASA Technical Reports Server (NTRS)

Panontin, Tina; Carvalho, Robert; Keller, Richard

2004-01-01

Contents include the folloving:Overview of the Application; Input Data; Analytical Process; Tool's Output; and Application of the Results of the Analysis.The tool enables the first element through a Web-based application that can be accessed by distributed teams to store and retrieve any type of digital investigation material in a secure environment. The second is accomplished by making the relationships between information explicit through the use of a semantic network-a structure that literally allows an investigator or team to "connect -the-dots." The third element, the significance of the correlated information, is established through causality and consistency tests using a number of different methods embedded within the tool, including fault trees, event sequences, and other accident models. And finally, the evidence gathered and structured within the tool can be directly, electronically archived to preserve the evidence and investigative reasoning.

Applications of Raman Spectroscopy in Biopharmaceutical Manufacturing: A Short Review.

PubMed

Buckley, Kevin; Ryder, Alan G

2017-06-01

The production of active pharmaceutical ingredients (APIs) is currently undergoing its biggest transformation in a century. The changes are based on the rapid and dramatic introduction of protein- and macromolecule-based drugs (collectively known as biopharmaceuticals) and can be traced back to the huge investment in biomedical science (in particular in genomics and proteomics) that has been ongoing since the 1970s. Biopharmaceuticals (or biologics) are manufactured using biological-expression systems (such as mammalian, bacterial, insect cells, etc.) and have spawned a large (>€35 billion sales annually in Europe) and growing biopharmaceutical industry (BioPharma). The structural and chemical complexity of biologics, combined with the intricacy of cell-based manufacturing, imposes a huge analytical burden to correctly characterize and quantify both processes (upstream) and products (downstream). In small molecule manufacturing, advances in analytical and computational methods have been extensively exploited to generate process analytical technologies (PAT) that are now used for routine process control, leading to more efficient processes and safer medicines. In the analytical domain, biologic manufacturing is considerably behind and there is both a huge scope and need to produce relevant PAT tools with which to better control processes, and better characterize product macromolecules. Raman spectroscopy, a vibrational spectroscopy with a number of useful properties (nondestructive, non-contact, robustness) has significant potential advantages in BioPharma. Key among them are intrinsically high molecular specificity, the ability to measure in water, the requirement for minimal (or no) sample pre-treatment, the flexibility of sampling configurations, and suitability for automation. Here, we review and discuss a representative selection of the more important Raman applications in BioPharma (with particular emphasis on mammalian cell culture). The review shows that the properties of Raman have been successfully exploited to deliver unique and useful analytical solutions, particularly for online process monitoring. However, it also shows that its inherent susceptibility to fluorescence interference and the weakness of the Raman effect mean that it can never be a panacea. In particular, Raman-based methods are intrinsically limited by the chemical complexity and wide analyte-concentration-profiles of cell culture media/bioprocessing broths which limit their use for quantitative analysis. Nevertheless, with appropriate foreknowledge of these limitations and good experimental design, robust analytical methods can be produced. In addition, new technological developments such as time-resolved detectors, advanced lasers, and plasmonics offer potential of new Raman-based methods to resolve existing limitations and/or provide new analytical insights.

Concept design theory and model for multi-use space facilities: Analysis of key system design parameters through variance of mission requirements

NASA Astrophysics Data System (ADS)

Reynerson, Charles Martin

This research has been performed to create concept design and economic feasibility data for space business parks. A space business park is a commercially run multi-use space station facility designed for use by a wide variety of customers. Both space hardware and crew are considered as revenue producing payloads. Examples of commercial markets may include biological and materials research, processing, and production, space tourism habitats, and satellite maintenance and resupply depots. This research develops a design methodology and an analytical tool to create feasible preliminary design information for space business parks. The design tool is validated against a number of real facility designs. Appropriate model variables are adjusted to ensure that statistical approximations are valid for subsequent analyses. The tool is used to analyze the effect of various payload requirements on the size, weight and power of the facility. The approach for the analytical tool was to input potential payloads as simple requirements, such as volume, weight, power, crew size, and endurance. In creating the theory, basic principles are used and combined with parametric estimation of data when necessary. Key system parameters are identified for overall system design. Typical ranges for these key parameters are identified based on real human spaceflight systems. To connect the economics to design, a life-cycle cost model is created based upon facility mass. This rough cost model estimates potential return on investments, initial investment requirements and number of years to return on the initial investment. Example cases are analyzed for both performance and cost driven requirements for space hotels, microgravity processing facilities, and multi-use facilities. In combining both engineering and economic models, a design-to-cost methodology is created for more accurately estimating the commercial viability for multiple space business park markets.

IBiSA_Tools: A Computational Toolkit for Ion-Binding State Analysis in Molecular Dynamics Trajectories of Ion Channels.

PubMed

Kasahara, Kota; Kinoshita, Kengo

2016-01-01

Ion conduction mechanisms of ion channels are a long-standing conundrum. Although the molecular dynamics (MD) method has been extensively used to simulate ion conduction dynamics at the atomic level, analysis and interpretation of MD results are not straightforward due to complexity of the dynamics. In our previous reports, we proposed an analytical method called ion-binding state analysis to scrutinize and summarize ion conduction mechanisms by taking advantage of a variety of analytical protocols, e.g., the complex network analysis, sequence alignment, and hierarchical clustering. This approach effectively revealed the ion conduction mechanisms and their dependence on the conditions, i.e., ion concentration and membrane voltage. Here, we present an easy-to-use computational toolkit for ion-binding state analysis, called IBiSA_tools. This toolkit consists of a C++ program and a series of Python and R scripts. From the trajectory file of MD simulations and a structure file, users can generate several images and statistics of ion conduction processes. A complex network named ion-binding state graph is generated in a standard graph format (graph modeling language; GML), which can be visualized by standard network analyzers such as Cytoscape. As a tutorial, a trajectory of a 50 ns MD simulation of the Kv1.2 channel is also distributed with the toolkit. Users can trace the entire process of ion-binding state analysis step by step. The novel method for analysis of ion conduction mechanisms of ion channels can be easily used by means of IBiSA_tools. This software is distributed under an open source license at the following URL: http://www.ritsumei.ac.jp/~ktkshr/ibisa_tools/.

Convergence in full motion video processing, exploitation, and dissemination and activity based intelligence

NASA Astrophysics Data System (ADS)

Phipps, Marja; Lewis, Gina

2012-06-01

Over the last decade, intelligence capabilities within the Department of Defense/Intelligence Community (DoD/IC) have evolved from ad hoc, single source, just-in-time, analog processing; to multi source, digitally integrated, real-time analytics; to multi-INT, predictive Processing, Exploitation and Dissemination (PED). Full Motion Video (FMV) technology and motion imagery tradecraft advancements have greatly contributed to Intelligence, Surveillance and Reconnaissance (ISR) capabilities during this timeframe. Imagery analysts have exploited events, missions and high value targets, generating and disseminating critical intelligence reports within seconds of occurrence across operationally significant PED cells. Now, we go beyond FMV, enabling All-Source Analysts to effectively deliver ISR information in a multi-INT sensor rich environment. In this paper, we explore the operational benefits and technical challenges of an Activity Based Intelligence (ABI) approach to FMV PED. Existing and emerging ABI features within FMV PED frameworks are discussed, to include refined motion imagery tools, additional intelligence sources, activity relevant content management techniques and automated analytics.

A Lean Six Sigma approach to the improvement of the selenium analysis method.

PubMed

Cloete, Bronwyn C; Bester, André

2012-11-02

Reliable results represent the pinnacle assessment of quality of an analytical laboratory, and therefore variability is considered to be a critical quality problem associated with the selenium analysis method executed at Western Cape Provincial Veterinary Laboratory (WCPVL). The elimination and control of variability is undoubtedly of significant importance because of the narrow margin of safety between toxic and deficient doses of the trace element for good animal health. A quality methodology known as Lean Six Sigma was believed to present the most feasible solution for overcoming the adverse effect of variation, through steps towards analytical process improvement. Lean Six Sigma represents a form of scientific method type, which is empirical, inductive and deductive, and systematic, which relies on data, and is fact-based. The Lean Six Sigma methodology comprises five macro-phases, namely Define, Measure, Analyse, Improve and Control (DMAIC). Both qualitative and quantitative laboratory data were collected in terms of these phases. Qualitative data were collected by using quality-tools, namely an Ishikawa diagram, a Pareto chart, Kaizen analysis and a Failure Mode Effect analysis tool. Quantitative laboratory data, based on the analytical chemistry test method, were collected through a controlled experiment. The controlled experiment entailed 13 replicated runs of the selenium test method, whereby 11 samples were repetitively analysed, whilst Certified Reference Material (CRM) was also included in 6 of the runs. Laboratory results obtained from the controlled experiment was analysed by using statistical methods, commonly associated with quality validation of chemistry procedures. Analysis of both sets of data yielded an improved selenium analysis method, believed to provide greater reliability of results, in addition to a greatly reduced cycle time and superior control features. Lean Six Sigma may therefore be regarded as a valuable tool in any laboratory, and represents both a management discipline, and a standardised approach to problem solving and process optimisation.

Yeast Based Sensors

NASA Astrophysics Data System (ADS)

Shimomura-Shimizu, Mifumi; Karube, Isao

Since the first microbial cell sensor was studied by Karube et al. in 1977, many types of yeast based sensors have been developed as analytical tools. Yeasts are known as facultative anaerobes. Facultative anaerobes can survive in both aerobic and anaerobic conditions. The yeast based sensor consisted of a DO electrode and an immobilized omnivorous yeast. In yeast based sensor development, many kinds of yeast have been employed by applying their characteristics to adapt to the analyte. For example, Trichosporon cutaneum was used to estimate organic pollution in industrial wastewater. Yeast based sensors are suitable for online control of biochemical processes and for environmental monitoring. In this review, principles and applications of yeast based sensors are summarized.

Development of a Novel Method for in vivo Determination of Activation Energy of Glucose Transport Across S. cerevisiae Cellular Membranes. A Biosensor-like Approach.

PubMed

Kormes, Diego J; Cortón, Eduardo

2009-01-01

Whereas biosensors have been usually proposed as analytical tools, used to investigate the surrounding media pursuing an analytical answer, we have used a biosensor-like device to characterize the microbial cells immobilized on it. We have studied the kinetics of transport and degradation of glucose at different concentrations and temperatures. When glucose concentrations of 15 and 1.5 mM were assayed, calculated activation energies were 25.2 and 18.4 kcal mol(-1), respectively, in good agreement with previously published data. The opportunity and convenience of using Arrhenius plots to estimate the activation energy in metabolic-related processes is also discussed.

Evaluation of analytical markers characterising different drying methods of parsley leaves (Petroselinum crispum L.).

PubMed

Lechtenberg, M; Zumdick, S; Gerhards, C; Schmidt, T J; Hensel, A

2007-12-01

Drying process of parsley leaves from Petroselinum crispum L. can influence the sensory qualities and aromatic taste of this herbal product. Beside oven-dried material, freeze-dried parsley is getting increasingly into the market. In the course of a search for analytical tools to differentiate oven-dried and lyophilised parsley, a HPLC determination of the 6"-O-malonylapiin to apiin ratio was shown to be a suitable marker system. While the ratio is high for fresh and lyophilised leave material, oven-drying leads to demalonylation and, subsequently, to a low malonylapiin--apiin ratio. Additionally, L*a*b colour measurement can be used for quality control to differentiate between different dried parsley raw materials.

Quantitative Story Telling: Initial steps towards bridging perspectives and tools for a robust nexus assessment

NASA Astrophysics Data System (ADS)

Cabello, Violeta

2017-04-01

This communication will present the advancement of an innovative analytical framework for the analysis of Water-Energy-Food-Climate Nexus termed Quantitative Story Telling (QST). The methodology is currently under development within the H2020 project MAGIC - Moving Towards Adaptive Governance in Complexity: Informing Nexus Security (www.magic-nexus.eu). The key innovation of QST is that it bridges qualitative and quantitative analytical tools into an iterative research process in which each step is built and validated in interaction with stakeholders. The qualitative analysis focusses on the identification of the narratives behind the development of relevant WEFC-Nexus policies and innovations. The quantitative engine is the Multi-Scale Analysis of Societal and Ecosystem Metabolism (MuSIASEM), a resource accounting toolkit capable of integrating multiple analytical dimensions at different scales through relational analysis. Although QST may not be labelled a data-driven but a story-driven approach, I will argue that improving models per se may not lead to an improved understanding of WEF-Nexus problems unless we are capable of generating more robust narratives to frame them. The communication will cover an introduction to MAGIC project, the basic concepts of QST and a case study focussed on agricultural production in a semi-arid region in Southern Spain. Data requirements for this case study and the limitations to find, access or estimate them will be presented alongside a reflection on the relation between analytical scales and data availability.

The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets.

PubMed

Carroll, Adam J; Badger, Murray R; Harvey Millar, A

2010-07-14

Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS) makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP) server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.). Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP) their own data to the server for online processing via a novel raw data processing pipeline. MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to assess data quality and draw their own insights from published metabolomics datasets.

Economic benefit evaluation for renewable energy transmitted by HVDC based on production simulation (PS) and analytic hierarchy process(AHP)

NASA Astrophysics Data System (ADS)

Zhang, Jinfang; Zheng, Kuan; Liu, Jun; Huang, Xinting

2018-02-01

In order to support North and West China’s RE (RE) development and enhance accommodation in reasonable high level, HVDC’s traditional operation curves need some change to follow the output characteristic of RE, which helps to shrink curtailment electricity and curtailment ratio of RE. In this paper, an economic benefit analysis method based on production simulation (PS) and Analytic hierarchy process (AHP) has been proposed. PS is the basic tool to analyze chosen power system operation situation, and AHP method could give a suitable comparison result among many candidate schemes. Based on four different transmission curve combinations, related economic benefit has been evaluated by PS and AHP. The results and related index have shown the efficiency of suggested method, and finally it has been validated that HVDC operation curve in following RE output mode could have benefit in decreasing RE curtailment level and improving economic operation.

High Accuracy Evaluation of the Finite Fourier Transform Using Sampled Data

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

1997-01-01

Many system identification and signal processing procedures can be done advantageously in the frequency domain. A required preliminary step for this approach is the transformation of sampled time domain data into the frequency domain. The analytical tool used for this transformation is the finite Fourier transform. Inaccuracy in the transformation can degrade system identification and signal processing results. This work presents a method for evaluating the finite Fourier transform using cubic interpolation of sampled time domain data for high accuracy, and the chirp Zeta-transform for arbitrary frequency resolution. The accuracy of the technique is demonstrated in example cases where the transformation can be evaluated analytically. Arbitrary frequency resolution is shown to be important for capturing details of the data in the frequency domain. The technique is demonstrated using flight test data from a longitudinal maneuver of the F-18 High Alpha Research Vehicle.

Consistent approach to describing aircraft HIRF protection

NASA Technical Reports Server (NTRS)

Rimbey, P. R.; Walen, D. B.

1995-01-01

The high intensity radiated fields (HIRF) certification process as currently implemented is comprised of an inconsistent combination of factors that tend to emphasize worst case scenarios in assessing commercial airplane certification requirements. By examining these factors which include the process definition, the external HIRF environment, the aircraft coupling and corresponding internal fields, and methods of measuring equipment susceptibilities, activities leading to an approach to appraising airplane vulnerability to HIRF are proposed. This approach utilizes technically based criteria to evaluate the nature of the threat, including the probability of encountering the external HIRF environment. No single test or analytic method comprehensively addresses the full HIRF threat frequency spectrum. Additional tools such as statistical methods must be adopted to arrive at more realistic requirements to reflect commercial aircraft vulnerability to the HIRF threat. Test and analytic data are provided to support the conclusions of this report. This work was performed under NASA contract NAS1-19360, Task 52.

Total analysis systems with Thermochromic Etching Discs technology.

PubMed

Avella-Oliver, Miquel; Morais, Sergi; Carrascosa, Javier; Puchades, Rosa; Maquieira, Ángel

2014-12-16

A new analytical system based on Thermochromic Etching Discs (TED) technology is presented. TED comprises a number of attractive features such as track independency, selective irradiation, a high power laser, and the capability to create useful assay platforms. The analytical versatility of this tool opens up a wide range of possibilities to design new compact disc-based total analysis systems applicable in chemistry and life sciences. In this paper, TED analytical implementation is described and discussed, and their analytical potential is supported by several applications. Microarray immunoassay, immunofiltration assay, solution measurement, and cell culture approaches are herein addressed in order to demonstrate the practical capacity of this system. The analytical usefulness of TED technology is herein demonstrated, describing how to exploit this tool for developing truly integrated analytical systems that provide solutions within the point of care framework.

Maximizing the U.S. Army’s Future Contribution to Global Security Using the Capability Portfolio Analysis Tool (CPAT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, Scott J.; Edwards, Shatiel B.; Teper, Gerald E.

We report that recent budget reductions have posed tremendous challenges to the U.S. Army in managing its portfolio of ground combat systems (tanks and other fighting vehicles), thus placing many important programs at risk. To address these challenges, the Army and a supporting team developed and applied the Capability Portfolio Analysis Tool (CPAT) to optimally invest in ground combat modernization over the next 25–35 years. CPAT provides the Army with the analytical rigor needed to help senior Army decision makers allocate scarce modernization dollars to protect soldiers and maintain capability overmatch. CPAT delivers unparalleled insight into multiple-decade modernization planning usingmore » a novel multiphase mixed-integer linear programming technique and illustrates a cultural shift toward analytics in the Army’s acquisition thinking and processes. CPAT analysis helped shape decisions to continue modernization of the $10 billion Stryker family of vehicles (originally slated for cancellation) and to strategically reallocate over $20 billion to existing modernization programs by not pursuing the Ground Combat Vehicle program as originally envisioned. Ultimately, more than 40 studies have been completed using CPAT, applying operations research methods to optimally prioritize billions of taxpayer dollars and allowing Army acquisition executives to base investment decisions on analytically rigorous evaluations of portfolio trade-offs.« less

Heterogeneous postsurgical data analytics for predictive modeling of mortality risks in intensive care units.

PubMed

Yun Chen; Hui Yang

2014-01-01

The rapid advancements of biomedical instrumentation and healthcare technology have resulted in data-rich environments in hospitals. However, the meaningful information extracted from rich datasets is limited. There is a dire need to go beyond current medical practices, and develop data-driven methods and tools that will enable and help (i) the handling of big data, (ii) the extraction of data-driven knowledge, (iii) the exploitation of acquired knowledge for optimizing clinical decisions. This present study focuses on the prediction of mortality rates in Intensive Care Units (ICU) using patient-specific healthcare recordings. It is worth mentioning that postsurgical monitoring in ICU leads to massive datasets with unique properties, e.g., variable heterogeneity, patient heterogeneity, and time asyncronization. To cope with the challenges in ICU datasets, we developed the postsurgical decision support system with a series of analytical tools, including data categorization, data pre-processing, feature extraction, feature selection, and predictive modeling. Experimental results show that the proposed data-driven methodology outperforms traditional approaches and yields better results based on the evaluation of real-world ICU data from 4000 subjects in the database. This research shows great potentials for the use of data-driven analytics to improve the quality of healthcare services.

Maximizing the U.S. Army’s Future Contribution to Global Security Using the Capability Portfolio Analysis Tool (CPAT)

DOE PAGES

Davis, Scott J.; Edwards, Shatiel B.; Teper, Gerald E.; ...

2016-02-01

We report that recent budget reductions have posed tremendous challenges to the U.S. Army in managing its portfolio of ground combat systems (tanks and other fighting vehicles), thus placing many important programs at risk. To address these challenges, the Army and a supporting team developed and applied the Capability Portfolio Analysis Tool (CPAT) to optimally invest in ground combat modernization over the next 25–35 years. CPAT provides the Army with the analytical rigor needed to help senior Army decision makers allocate scarce modernization dollars to protect soldiers and maintain capability overmatch. CPAT delivers unparalleled insight into multiple-decade modernization planning usingmore » a novel multiphase mixed-integer linear programming technique and illustrates a cultural shift toward analytics in the Army’s acquisition thinking and processes. CPAT analysis helped shape decisions to continue modernization of the $10 billion Stryker family of vehicles (originally slated for cancellation) and to strategically reallocate over $20 billion to existing modernization programs by not pursuing the Ground Combat Vehicle program as originally envisioned. Ultimately, more than 40 studies have been completed using CPAT, applying operations research methods to optimally prioritize billions of taxpayer dollars and allowing Army acquisition executives to base investment decisions on analytically rigorous evaluations of portfolio trade-offs.« less

Mechanistic characterization of chloride interferences in electrothermal atomization systems

USGS Publications Warehouse

Shekiro, J.M.; Skogerboe, R.K.; Taylor, Howard E.

1988-01-01

A computer-controlled spectrometer with a photodiode array detector has been used for wavelength and temperature resolved characterization of the vapor produced by an electrothermal atomizer. The system has been used to study the chloride matrix interference on the atomic absorption spectrometric determination of manganese and copper. The suppression of manganese and copper atom populations by matrix chlorides such as those of calcium and magnesium is due to the gas-phase formation of an analyte chloride species followed by the diffusion of significant fractions of these species from the atom cell prior to completion of the atomization process. The analyte chloride species cannot be formed when matrix chlorides with metal-chloride bond dissociation energies above those of the analyte chlorides are the principal entitles present. The results indicate that multiple wavelength spectrometry used to obtain temperature-resolved spectra is a viable tool in the mechanistic characterization of interference effects observed with electrothermal atomization systems. ?? 1988 American Chemical Society.

Optimization techniques applied to passive measures for in-orbit spacecraft survivability

NASA Technical Reports Server (NTRS)

Mog, Robert A.; Price, D. Marvin

1991-01-01

Spacecraft designers have always been concerned about the effects of meteoroid impacts on mission safety. The engineering solution to this problem has generally been to erect a bumper or shield placed outboard from the spacecraft wall to disrupt/deflect the incoming projectiles. Spacecraft designers have a number of tools at their disposal to aid in the design process. These include hypervelocity impact testing, analytic impact predictors, and hydrodynamic codes. Analytic impact predictors generally provide the best quick-look estimate of design tradeoffs. The most complete way to determine the characteristics of an analytic impact predictor is through optimization of the protective structures design problem formulated with the predictor of interest. Space Station Freedom protective structures design insight is provided through the coupling of design/material requirements, hypervelocity impact phenomenology, meteoroid and space debris environment sensitivities, optimization techniques and operations research strategies, and mission scenarios. Major results are presented.

A Population-Level Data Analytics Portal for Self-Administered Lifestyle and Mental Health Screening.

PubMed

Zhang, Xindi; Warren, Jim; Corter, Arden; Goodyear-Smith, Felicity

2016-01-01

This paper describes development of a prototype data analytics portal for analysis of accumulated screening results from eCHAT (electronic Case-finding and Help Assessment Tool). eCHAT allows individuals to conduct a self-administered lifestyle and mental health screening assessment, with usage to date chiefly in the context of primary care waiting rooms. The intention is for wide roll-out to primary care clinics, including secondary school based clinics, resulting in the accumulation of population-level data. Data from a field trial of eCHAT with sexual health questions tailored to youth were used to support design of a data analytics portal for population-level data. The design process included user personas and scenarios, screen prototyping and a simulator for generating large-scale data sets. The prototype demonstrates the promise of wide-scale self-administered screening data to support a range of users including practice managers, clinical directors and health policy analysts.

Failure Modes and Effects Analysis (FMEA): A Bibliography

NASA Technical Reports Server (NTRS)

2000-01-01

Failure modes and effects analysis (FMEA) is a bottom-up analytical process that identifies process hazards, which helps managers understand vulnerabilities of systems, as well as assess and mitigate risk. It is one of several engineering tools and techniques available to program and project managers aimed at increasing the likelihood of safe and successful NASA programs and missions. This bibliography references 465 documents in the NASA STI Database that contain the major concepts, failure modes or failure analysis, in either the basic index of the major subject terms.

Introduction to the special section "Big'er' Data": Scaling up psychotherapy research in counseling psychology.

PubMed

Owen, Jesse; Imel, Zac E

2016-04-01

This article introduces the special section on utilizing large data sets to explore psychotherapy processes and outcomes. The increased use of technology has provided new opportunities for psychotherapy researchers. In particular, there is a rise in large databases of tens of thousands clients. Additionally, there are new ways to pool valuable resources for meta-analytic processes. At the same time, these tools also come with limitations. These issues are introduced as well as brief overview of the articles. (c) 2016 APA, all rights reserved).

Next generation data harmonization

NASA Astrophysics Data System (ADS)

Armstrong, Chandler; Brown, Ryan M.; Chaves, Jillian; Czerniejewski, Adam; Del Vecchio, Justin; Perkins, Timothy K.; Rudnicki, Ron; Tauer, Greg

2015-05-01

Analysts are presented with a never ending stream of data sources. Often, subsets of data sources to solve problems are easily identified but the process to align data sets is time consuming. However, many semantic technologies do allow for fast harmonization of data to overcome these problems. These include ontologies that serve as alignment targets, visual tools and natural language processing that generate semantic graphs in terms of the ontologies, and analytics that leverage these graphs. This research reviews a developed prototype that employs all these approaches to perform analysis across disparate data sources documenting violent, extremist events.

Integrated development of up- and downstream processes supported by the Cherry-Tag™ for real-time tracking of stability and solubility of proteins.

PubMed

Baumann, Pascal; Bluthardt, Nicolai; Renner, Sarah; Burghardt, Hannah; Osberghaus, Anna; Hubbuch, Jürgen

2015-04-20

Product analytics is the bottleneck of most processes in bioprocess engineering, as it is rather time-consuming. Real-time and in-line product tracing without sample pre-treatment is only possible for few products. The Cherry-Tag™ (Delphi Genetics, Belgium) which can be fused to any target protein allows for straightforward product analytics by VIS absorption measurements. When the fused protein becomes unstable or insoluble, the chromophore function of the group is lost, which makes this technology an ideal screening tool for solubility and stability in up- and downstream process development. The Cherry-Tag™ technology will be presented for the tagged enzyme glutathione-S-transferase (GST) from Escherichia coli in a combined up- and downstream process development study. High-throughput cultivations were carried out in a 48-well format in a BioLector system (m2p-Labs, Germany). The best cultivation setup of highest product titer was scaled up to a 2.5L shake flask culture, followed by a selective affinity chromatography product capturing step. In upstream applications the tag was capable of identifying conditions where insoluble and non-native inclusion bodies were formed. In downstream applications the red-colored product was found to be bound effectively to a GST affinity column. Thus, it was identified to be a native and active protein, as the binding mechanism relies on catalytic activity of the enzyme. The Cherry-Tag™ was found to be a reliable and quantitative tool for real-time tracking of stable and soluble proteins in up- and downstream processing applications. Denaturation and aggregation of the product can be detected in-line at any stage of the process. Critical stages can be identified and subsequently changed or replaced. Copyright © 2015 Elsevier B.V. All rights reserved.

An Analytic Hierarchy Process-based Method to Rank the Critical Success Factors of Implementing a Pharmacy Barcode System.

PubMed

Alharthi, Hana; Sultana, Nahid; Al-Amoudi, Amjaad; Basudan, Afrah

2015-01-01

Pharmacy barcode scanning is used to reduce errors during the medication dispensing process. However, this technology has rarely been used in hospital pharmacies in Saudi Arabia. This article describes the barriers to successful implementation of a barcode scanning system in Saudi Arabia. A literature review was conducted to identify the relevant critical success factors (CSFs) for a successful dispensing barcode system implementation. Twenty-eight pharmacists from a local hospital in Saudi Arabia were interviewed to obtain their perception of these CSFs. In this study, planning (process flow issues and training requirements), resistance (fear of change, communication issues, and negative perceptions about technology), and technology (software, hardware, and vendor support) were identified as the main barriers. The analytic hierarchy process (AHP), one of the most widely used tools for decision making in the presence of multiple criteria, was used to compare and rank these identified CSFs. The results of this study suggest that resistance barriers have a greater impact than planning and technology barriers. In particular, fear of change is the most critical factor, and training is the least critical factor.

A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge.

PubMed

Rahman, M Azizur; Rusteberg, Bernd; Gogu, R C; Lobo Ferreira, J P; Sauter, Martin

2012-05-30

This study reports the development of a new spatial multi-criteria decision analysis (SMCDA) software tool for selecting suitable sites for Managed Aquifer Recharge (MAR) systems. The new SMCDA software tool functions based on the combination of existing multi-criteria evaluation methods with modern decision analysis techniques. More specifically, non-compensatory screening, criteria standardization and weighting, and Analytical Hierarchy Process (AHP) have been combined with Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). This SMCDA tool may be implemented with a wide range of decision maker's preferences. The tool's user-friendly interface helps guide the decision maker through the sequential steps for site selection, those steps namely being constraint mapping, criteria hierarchy, criteria standardization and weighting, and criteria overlay. The tool offers some predetermined default criteria and standard methods to increase the trade-off between ease-of-use and efficiency. Integrated into ArcGIS, the tool has the advantage of using GIS tools for spatial analysis, and herein data may be processed and displayed. The tool is non-site specific, adaptive, and comprehensive, and may be applied to any type of site-selection problem. For demonstrating the robustness of the new tool, a case study was planned and executed at Algarve Region, Portugal. The efficiency of the SMCDA tool in the decision making process for selecting suitable sites for MAR was also demonstrated. Specific aspects of the tool such as built-in default criteria, explicit decision steps, and flexibility in choosing different options were key features, which benefited the study. The new SMCDA tool can be augmented by groundwater flow and transport modeling so as to achieve a more comprehensive approach to the selection process for the best locations of the MAR infiltration basins, as well as the locations of recovery wells and areas of groundwater protection. The new spatial multicriteria analysis tool has already been implemented within the GIS based Gabardine decision support system as an innovative MAR planning tool. Copyright © 2012 Elsevier Ltd. All rights reserved.

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2014 CFR

2014-01-01

...) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Accident and Fire... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life...

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2013 CFR

2013-07-01

...) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Accident and Fire... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life...

41 CFR 102-80.120 - What analytical and empirical tools should be used to support the life safety equivalency...

Code of Federal Regulations, 2012 CFR

2012-01-01

...) FEDERAL MANAGEMENT REGULATION REAL PROPERTY 80-SAFETY AND ENVIRONMENTAL MANAGEMENT Accident and Fire... used to support the life safety equivalency evaluation? Analytical and empirical tools, including fire models and grading schedules such as the Fire Safety Evaluation System (Alternative Approaches to Life...

(Re)braiding to Tell: Using "Trenzas" as a Metaphorical-Analytical Tool in Qualitative Research

ERIC Educational Resources Information Center

Quiñones, Sandra

2016-01-01

Metaphors can be used in qualitative research to illuminate the meanings of participant experiences and examine phenomena from insightful and creative perspectives. The purpose of this paper is to illustrate how I utilized "trenzas" (braids) as a metaphorical and analytical tool for understanding the experiences and perspectives of…

Feasibility model of a high reliability five-year tape transport. Volume 3: Appendices. [detailed drawing and analytical tools used in analyses

NASA Technical Reports Server (NTRS)

Meyers, A. P.; Davidson, W. A.; Gortowski, R. C.

1973-01-01

Detailed drawings of the five year tape transport are presented. Analytical tools used in the various analyses are described. These analyses include: tape guidance, tape stress over crowned rollers, tape pack stress program, response (computer) program, and control system electronics description.

Challenges and Opportunities in Analysing Students Modelling

ERIC Educational Resources Information Center

Blanco-Anaya, Paloma; Justi, Rosária; Díaz de Bustamante, Joaquín

2017-01-01

Modelling-based teaching activities have been designed and analysed from distinct theoretical perspectives. In this paper, we use one of them--the model of modelling diagram (MMD)--as an analytical tool in a regular classroom context. This paper examines the challenges that arise when the MMD is used as an analytical tool to characterise the…

Equity Analytics: A Methodological Approach for Quantifying Participation Patterns in Mathematics Classroom Discourse

ERIC Educational Resources Information Center

Reinholz, Daniel L.; Shah, Niral

2018-01-01

Equity in mathematics classroom discourse is a pressing concern, but analyzing issues of equity using observational tools remains a challenge. In this article, we propose equity analytics as a quantitative approach to analyzing aspects of equity and inequity in classrooms. We introduce a classroom observation tool that focuses on relatively…

Composing Data Parallel Code for a SPARQL Graph Engine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castellana, Vito G.; Tumeo, Antonino; Villa, Oreste

Big data analytics process large amount of data to extract knowledge from them. Semantic databases are big data applications that adopt the Resource Description Framework (RDF) to structure metadata through a graph-based representation. The graph based representation provides several benefits, such as the possibility to perform in memory processing with large amounts of parallelism. SPARQL is a language used to perform queries on RDF-structured data through graph matching. In this paper we present a tool that automatically translates SPARQL queries to parallel graph crawling and graph matching operations. The tool also supports complex SPARQL constructs, which requires more than basicmore » graph matching for their implementation. The tool generates parallel code annotated with OpenMP pragmas for x86 Shared-memory Multiprocessors (SMPs). With respect to commercial database systems such as Virtuoso, our approach reduces memory occupation due to join operations and provides higher performance. We show the scaling of the automatically generated graph-matching code on a 48-core SMP.« less

Comprehensive data resources and analytical tools for pathological association of aminoacyl tRNA synthetases with cancer

PubMed Central

Lee, Ji-Hyun; You, Sungyong; Hyeon, Do Young; Kang, Byeongsoo; Kim, Hyerim; Park, Kyoung Mii; Han, Byungwoo; Hwang, Daehee; Kim, Sunghoon

2015-01-01

Mammalian cells have cytoplasmic and mitochondrial aminoacyl-tRNA synthetases (ARSs) that catalyze aminoacylation of tRNAs during protein synthesis. Despite their housekeeping functions in protein synthesis, recently, ARSs and ARS-interacting multifunctional proteins (AIMPs) have been shown to play important roles in disease pathogenesis through their interactions with disease-related molecules. However, there are lacks of data resources and analytical tools that can be used to examine disease associations of ARS/AIMPs. Here, we developed an Integrated Database for ARSs (IDA), a resource database including cancer genomic/proteomic and interaction data of ARS/AIMPs. IDA includes mRNA expression, somatic mutation, copy number variation and phosphorylation data of ARS/AIMPs and their interacting proteins in various cancers. IDA further includes an array of analytical tools for exploration of disease association of ARS/AIMPs, identification of disease-associated ARS/AIMP interactors and reconstruction of ARS-dependent disease-perturbed network models. Therefore, IDA provides both comprehensive data resources and analytical tools for understanding potential roles of ARS/AIMPs in cancers. Database URL: http://ida.biocon.re.kr/, http://ars.biocon.re.kr/ PMID:25824651

PET-Tool: a software suite for comprehensive processing and managing of Paired-End diTag (PET) sequence data.

PubMed

Chiu, Kuo Ping; Wong, Chee-Hong; Chen, Qiongyu; Ariyaratne, Pramila; Ooi, Hong Sain; Wei, Chia-Lin; Sung, Wing-Kin Ken; Ruan, Yijun

2006-08-25

We recently developed the Paired End diTag (PET) strategy for efficient characterization of mammalian transcriptomes and genomes. The paired end nature of short PET sequences derived from long DNA fragments raised a new set of bioinformatics challenges, including how to extract PETs from raw sequence reads, and correctly yet efficiently map PETs to reference genome sequences. To accommodate and streamline data analysis of the large volume PET sequences generated from each PET experiment, an automated PET data process pipeline is desirable. We designed an integrated computation program package, PET-Tool, to automatically process PET sequences and map them to the genome sequences. The Tool was implemented as a web-based application composed of four modules: the Extractor module for PET extraction; the Examiner module for analytic evaluation of PET sequence quality; the Mapper module for locating PET sequences in the genome sequences; and the Project Manager module for data organization. The performance of PET-Tool was evaluated through the analyses of 2.7 million PET sequences. It was demonstrated that PET-Tool is accurate and efficient in extracting PET sequences and removing artifacts from large volume dataset. Using optimized mapping criteria, over 70% of quality PET sequences were mapped specifically to the genome sequences. With a 2.4 GHz LINUX machine, it takes approximately six hours to process one million PETs from extraction to mapping. The speed, accuracy, and comprehensiveness have proved that PET-Tool is an important and useful component in PET experiments, and can be extended to accommodate other related analyses of paired-end sequences. The Tool also provides user-friendly functions for data quality check and system for multi-layer data management.

CREATE-IP and CREATE-V: Data and Services Update

NASA Astrophysics Data System (ADS)

Carriere, L.; Potter, G. L.; Hertz, J.; Peters, J.; Maxwell, T. P.; Strong, S.; Shute, J.; Shen, Y.; Duffy, D.

2017-12-01

The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center and the Earth System Grid Federation (ESGF) are working together to build a uniform environment for the comparative study and use of a group of reanalysis datasets of particular importance to the research community. This effort is called the Collaborative REAnalysis Technical Environment (CREATE) and it contains two components: the CREATE-Intercomparison Project (CREATE-IP) and CREATE-V. This year's efforts included generating and publishing an atmospheric reanalysis ensemble mean and spread and improving the analytics available through CREATE-V. Related activities included adding access to subsets of the reanalysis data through ArcGIS and expanding the visualization tool to GMAO forecast data. This poster will present the access mechanisms to this data and use cases including example Jupyter Notebook code. The reanalysis ensemble was generated using two methods, first using standard Python tools for regridding, extracting levels and creating the ensemble mean and spread on a virtual server in the NCCS environment. The second was using a new analytics software suite, the Earth Data Analytics Services (EDAS), coupled with a high-performance Data Analytics and Storage System (DASS) developed at the NCCS. Results were compared to validate the EDAS methodologies, and the results, including time to process, will be presented. The ensemble includes selected 6 hourly and monthly variables, regridded to 1.25 degrees, with 24 common levels used for the 3D variables. Use cases for the new data and services will be presented, including the use of EDAS for the backend analytics on CREATE-V, the use of the GMAO forecast aerosol and cloud data in CREATE-V, and the ability to connect CREATE-V data to NCCS ArcGIS services.

Survivability as a Tool for Evaluating Open Source Software

DTIC Science & Technology

2015-06-01

the thesis limited the program development, so it is only able to process project issues (bugs or feature requests), which is an important metric for...Ideally, these insights may provide an analytic framework to generate guidance for decision makers that may support the inclusion of OSS to more...refine their efforts to build quality software and to strengthen their software development communities. 1.4 Research Questions This thesis addresses

Analysis of Volatile Organic Compounds in a Controlled Environment: Ethylene Gas Measurement Studies on Radish

NASA Technical Reports Server (NTRS)

Kong, Suk Bin

2001-01-01

Volatile organic compound(VOC), ethylene gas, was characterized and quantified by GC/FID. 20-50 ppb levels were detected during the growth stages of radish. SPME could be a good analytical tool for the purpose. Low temperature trapping method using dry ice/diethyl ether and liquid nitrogen bath was recommended for the sampling process for GC/PID and GC/MS analysis.

Analyzing large scale genomic data on the cloud with Sparkhit

PubMed Central

Huang, Liren; Krüger, Jan

2018-01-01

Abstract Motivation The increasing amount of next-generation sequencing data poses a fundamental challenge on large scale genomic analytics. Existing tools use different distributed computational platforms to scale-out bioinformatics workloads. However, the scalability of these tools is not efficient. Moreover, they have heavy run time overheads when pre-processing large amounts of data. To address these limitations, we have developed Sparkhit: a distributed bioinformatics framework built on top of the Apache Spark platform. Results Sparkhit integrates a variety of analytical methods. It is implemented in the Spark extended MapReduce model. It runs 92–157 times faster than MetaSpark on metagenomic fragment recruitment and 18–32 times faster than Crossbow on data pre-processing. We analyzed 100 terabytes of data across four genomic projects in the cloud in 21 h, which includes the run times of cluster deployment and data downloading. Furthermore, our application on the entire Human Microbiome Project shotgun sequencing data was completed in 2 h, presenting an approach to easily associate large amounts of public datasets with reference data. Availability and implementation Sparkhit is freely available at: https://rhinempi.github.io/sparkhit/. Contact asczyrba@cebitec.uni-bielefeld.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:29253074

Selection of reference standard during method development using the analytical hierarchy process.

PubMed

Sun, Wan-yang; Tong, Ling; Li, Dong-xiang; Huang, Jing-yi; Zhou, Shui-ping; Sun, Henry; Bi, Kai-shun

2015-03-25

Reference standard is critical for ensuring reliable and accurate method performance. One important issue is how to select the ideal one from the alternatives. Unlike the optimization of parameters, the criteria of the reference standard are always immeasurable. The aim of this paper is to recommend a quantitative approach for the selection of reference standard during method development based on the analytical hierarchy process (AHP) as a decision-making tool. Six alternative single reference standards were assessed in quantitative analysis of six phenolic acids from Salvia Miltiorrhiza and its preparations by using ultra-performance liquid chromatography. The AHP model simultaneously considered six criteria related to reference standard characteristics and method performance, containing feasibility to obtain, abundance in samples, chemical stability, accuracy, precision and robustness. The priority of each alternative was calculated using standard AHP analysis method. The results showed that protocatechuic aldehyde is the ideal reference standard, and rosmarinic acid is about 79.8% ability as the second choice. The determination results successfully verified the evaluation ability of this model. The AHP allowed us comprehensive considering the benefits and risks of the alternatives. It was an effective and practical tool for optimization of reference standards during method development. Copyright © 2015 Elsevier B.V. All rights reserved.

Leveraging Google Trends, Twitter, and Wikipedia to Investigate the Impact of a Celebrity's Death From Rheumatoid Arthritis.

PubMed

Mahroum, Naim; Bragazzi, Nicola Luigi; Sharif, Kassem; Gianfredi, Vincenza; Nucci, Daniele; Rosselli, Roberto; Brigo, Francesco; Adawi, Mohammad; Amital, Howard; Watad, Abdulla

2018-06-01

Technological advancements, such as patient-centered smartphone applications, have enabled to support self-management of the disease. Further, the accessibility to health information through the Internet has grown tremendously. This article aimed to investigate how big data can be useful to assess the impact of a celebrity's rheumatic disease on the public opinion. Variable tools and statistical/computational approaches have been used, including massive data mining of Google Trends, Wikipedia, Twitter, and big data analytics. These tools were mined using an in-house script, which facilitated the process of data collection, parsing, handling, processing, and normalization. From Google Trends, the temporal correlation between "Anna Marchesini" and rheumatoid arthritis (RA) queries resulted 0.66 before Anna Marchesini's death and 0.90 after Anna Marchesini's death. The geospatial correlation between "Anna Marchesini" and RA queries resulted 0.45 before Anna Marchesini's death and 0.52 after Anna Marchesini's death. From Wikitrends, after Anna Marchesini's death, the number of accesses to Wikipedia page for RA has increased 5770%. From Twitter, 1979 tweets have been retrieved. Numbers of likes, retweets, and hashtags have increased throughout time. Novel data streams and big data analytics are effective to assess the impact of a disease in a famous person on the laypeople.

"EMERGING" POLLUTANTS, MASS SPECTROMETRY, AND ...

EPA Pesticide Factsheets

A foundation for Environmental Science - Mass Spectrometry: Historically fundamental to amassing our understanding of environmental processes and chemical pollution is the realm of mass spectrometry - the mainstay of analytical chemistry - the workhorse that supplies much of the definitive data that environmental scientists rely upon for identifying the molecular compositions (and ultimately the structures) of chemicals. This is not to ignore the complementary, critical roles played by the adjunct practices of sample enrichment (via any of various means of selective extraction) and analyte separation (via the myriad forms of chromatography and electrophoresis).While the power of mass spectrometry has long been highly visible to the practicing environmental chemist, it borders on continued obscurity to the lay public and most non-chemists. Even though mass spectrometry has played a long, historic (and largely invisible) role in establishing or undergirdidng our existing knowledge about environmental processes and pollution, what recognition it does enjoy is usually relegated to that of a tool. It is ususally the relevance of ssignificance of the knowledge acquired from the application of the tool that has ultimate meaning to the public and science at large - not how the knowledge was acquired. The research focused on in the subtasks is the development and application of state-of the-art technologies to meet the needs of the public, Office of Water, and ORD in

ASTRYD: A new numerical tool for aircraft cabin and environmental noise prediction

NASA Astrophysics Data System (ADS)

Berhault, J.-P.; Venet, G.; Clerc, C.

ASTRYD is an analytical tool, developed originally for underwater applications, that computes acoustic pressure distribution around three-dimensional bodies in closed spaces like aircraft cabins. The program accepts data from measurements or other simulations, processes them in the time domain, and delivers temporal evolutions of the acoustic pressures and accelerations, as well as the radiated/diffracted pressure at arbitrary points located in the external/internal space. A typical aerospace application is prediction of acoustic load on satellites during the launching phase. An aeronautic application is engine noise distribution on a business jet body for prediction of environmental and cabin noise.

The challenge of big data in public health: an opportunity for visual analytics.

PubMed

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data's volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research.

The Challenge of Big Data in Public Health: An Opportunity for Visual Analytics

PubMed Central

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data’s volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research. PMID:24678376

Development of a robust space power system decision model

NASA Astrophysics Data System (ADS)

Chew, Gilbert; Pelaccio, Dennis G.; Jacobs, Mark; Stancati, Michael; Cataldo, Robert

2001-02-01

NASA continues to evaluate power systems to support human exploration of the Moon and Mars. The system(s) would address all power needs of surface bases and on-board power for space transfer vehicles. Prior studies have examined both solar and nuclear-based alternatives with respect to individual issues such as sizing or cost. What has not been addressed is a comprehensive look at the risks and benefits of the options that could serve as the analytical framework to support a system choice that best serves the needs of the exploration program. This paper describes the SAIC developed Space Power System Decision Model, which uses a formal Two-step Analytical Hierarchy Process (TAHP) methodology that is used in the decision-making process to clearly distinguish candidate power systems in terms of benefits, safety, and risk. TAHP is a decision making process based on the Analytical Hierarchy Process, which employs a hierarchic approach of structuring decision factors by weights, and relatively ranks system design options on a consistent basis. This decision process also includes a level of data gathering and organization that produces a consistent, well-documented assessment, from which the capability of each power system option to meet top-level goals can be prioritized. The model defined on this effort focuses on the comparative assessment candidate power system options for Mars surface application(s). This paper describes the principles of this approach, the assessment criteria and weighting procedures, and the tools to capture and assess the expert knowledge associated with space power system evaluation. .

Development of a software tool to support chemical and biological terrorism intelligence analysis

NASA Astrophysics Data System (ADS)

Hunt, Allen R.; Foreman, William

1997-01-01

AKELA has developed a software tool which uses a systems analytic approach to model the critical processes which support the acquisition of biological and chemical weapons by terrorist organizations. This tool has four major components. The first is a procedural expert system which describes the weapon acquisition process. It shows the relationship between the stages a group goes through to acquire and use a weapon, and the activities in each stage required to be successful. It applies to both state sponsored and small group acquisition. An important part of this expert system is an analysis of the acquisition process which is embodied in a list of observables of weapon acquisition activity. These observables are cues for intelligence collection The second component is a detailed glossary of technical terms which helps analysts with a non- technical background understand the potential relevance of collected information. The third component is a linking capability which shows where technical terms apply to the parts of the acquisition process. The final component is a simple, intuitive user interface which shows a picture of the entire process at a glance and lets the user move quickly to get more detailed information. This paper explains e each of these five model components.

From Ambiguities to Insights: Query-based Comparisons of High-Dimensional Data

NASA Astrophysics Data System (ADS)

Kowalski, Jeanne; Talbot, Conover; Tsai, Hua L.; Prasad, Nijaguna; Umbricht, Christopher; Zeiger, Martha A.

2007-11-01

Genomic technologies will revolutionize drag discovery and development; that much is universally agreed upon. The high dimension of data from such technologies has challenged available data analytic methods; that much is apparent. To date, large-scale data repositories have not been utilized in ways that permit their wealth of information to be efficiently processed for knowledge, presumably due in large part to inadequate analytical tools to address numerous comparisons of high-dimensional data. In candidate gene discovery, expression comparisons are often made between two features (e.g., cancerous versus normal), such that the enumeration of outcomes is manageable. With multiple features, the setting becomes more complex, in terms of comparing expression levels of tens of thousands transcripts across hundreds of features. In this case, the number of outcomes, while enumerable, become rapidly large and unmanageable, and scientific inquiries become more abstract, such as "which one of these (compounds, stimuli, etc.) is not like the others?" We develop analytical tools that promote more extensive, efficient, and rigorous utilization of the public data resources generated by the massive support of genomic studies. Our work innovates by enabling access to such metadata with logically formulated scientific inquires that define, compare and integrate query-comparison pair relations for analysis. We demonstrate our computational tool's potential to address an outstanding biomedical informatics issue of identifying reliable molecular markers in thyroid cancer. Our proposed query-based comparison (QBC) facilitates access to and efficient utilization of metadata through logically formed inquires expressed as query-based comparisons by organizing and comparing results from biotechnologies to address applications in biomedicine.

Identifying problems and generating recommendations for enhancing complex systems: applying the abstraction hierarchy framework as an analytical tool.

PubMed

Xu, Wei

2007-12-01

This study adopts J. Rasmussen's (1985) abstraction hierarchy (AH) framework as an analytical tool to identify problems and pinpoint opportunities to enhance complex systems. The process of identifying problems and generating recommendations for complex systems using conventional methods is usually conducted based on incompletely defined work requirements. As the complexity of systems rises, the sheer mass of data generated from these methods becomes unwieldy to manage in a coherent, systematic form for analysis. There is little known work on adopting a broader perspective to fill these gaps. AH was used to analyze an aircraft-automation system in order to further identify breakdowns in pilot-automation interactions. Four steps follow: developing an AH model for the system, mapping the data generated by various methods onto the AH, identifying problems based on the mapped data, and presenting recommendations. The breakdowns lay primarily with automation operations that were more goal directed. Identified root causes include incomplete knowledge content and ineffective knowledge structure in pilots' mental models, lack of effective higher-order functional domain information displayed in the interface, and lack of sufficient automation procedures for pilots to effectively cope with unfamiliar situations. The AH is a valuable analytical tool to systematically identify problems and suggest opportunities for enhancing complex systems. It helps further examine the automation awareness problems and identify improvement areas from a work domain perspective. Applications include the identification of problems and generation of recommendations for complex systems as well as specific recommendations regarding pilot training, flight deck interfaces, and automation procedures.

Miniaturized Temperature-Controlled Planar Chromatography (Micro-TLC) as a Versatile Technique for Fast Screening of Micropollutants and Biomarkers Derived from Surface Water Ecosystems and During Technological Processes of Wastewater Treatment.

PubMed

Ślączka-Wilk, Magdalena M; Włodarczyk, Elżbieta; Kaleniecka, Aleksandra; Zarzycki, Paweł K

2017-07-01

There is increasing interest in the development of simple analytical systems enabling the fast screening of target components in complex samples. A number of newly invented protocols are based on quasi separation techniques involving microfluidic paper-based analytical devices and/or micro total analysis systems. Under such conditions, the quantification of target components can be performed mainly due to selective detection. The main goal of this paper is to demonstrate that miniaturized planar chromatography has the capability to work as an efficient separation and quantification tool for the analysis of multiple targets within complex environmental samples isolated and concentrated using an optimized SPE method. In particular, we analyzed various samples collected from surface water ecosystems (lakes, rivers, and the Baltic Sea of Middle Pomerania in the northern part of Poland) in different seasons, as well as samples collected during key wastewater technological processes (originating from the "Jamno" wastewater treatment plant in Koszalin, Poland). We documented that the multiple detection of chromatographic spots on RP-18W microplates-under visible light, fluorescence, and fluorescence quenching conditions, and using the visualization reagent phosphomolybdic acid-enables fast and robust sample classification. The presented data reveal that the proposed micro-TLC system is useful, inexpensive, and can be considered as a complementary method for the fast control of treated sewage water discharged by a municipal wastewater treatment plant, particularly for the detection of low-molecular mass micropollutants with polarity ranging from estetrol to progesterone, as well as chlorophyll-related dyes. Due to the low consumption of mobile phases composed of water-alcohol binary mixtures (less than 1 mL/run for the simultaneous separation of up to nine samples), this method can be considered an environmentally friendly and green chemistry analytical tool. The described analytical protocol can be complementary to those involving classical column chromatography (HPLC) or various planar microfluidic devices.

Quality Indicators for Learning Analytics

ERIC Educational Resources Information Center

Scheffel, Maren; Drachsler, Hendrik; Stoyanov, Slavi; Specht, Marcus

2014-01-01

This article proposes a framework of quality indicators for learning analytics that aims to standardise the evaluation of learning analytics tools and to provide a mean to capture evidence for the impact of learning analytics on educational practices in a standardised manner. The criteria of the framework and its quality indicators are based on…

Critical Appraisal Tools and Reporting Guidelines for Evidence-Based Practice.

PubMed

Buccheri, Robin K; Sharifi, Claire

2017-12-01

Nurses engaged in evidence-based practice (EBP) have two important sets of tools: Critical appraisal tools and reporting guidelines. Critical appraisal tools facilitate the appraisal process and guide a consumer of evidence through an objective, analytical, evaluation process. Reporting guidelines, checklists of items that should be included in a publication or report, ensure that the project or guidelines are reported on with clarity, completeness, and transparency. The primary purpose of this paper is to help nurses understand the difference between critical appraisal tools and reporting guidelines. A secondary purpose is to help nurses locate the appropriate tool for the appraisal or reporting of evidence. A systematic search was conducted to find commonly used critical appraisal tools and reporting guidelines for EBP in nursing. This article serves as a resource to help nurse navigate the often-overwhelming terrain of critical appraisal tools and reporting guidelines, and will help both novice and experienced consumers of evidence more easily select the appropriate tool(s) to use for critical appraisal and reporting of evidence. Having the skills to select the appropriate tool or guideline is an essential part of meeting EBP competencies for both practicing registered nurses and advanced practice nurses (Melnyk & Gallagher-Ford, 2015; Melnyk, Gallagher-Ford, & Fineout-Overholt, 2017). Nine commonly used critical appraisal tools and eight reporting guidelines were found and are described in this manuscript. Specific steps for selecting an appropriate tool as well as examples of each tool's use in a publication are provided. Practicing registered nurses and advance practice nurses must be able to critically appraise and disseminate evidence in order to meet EBP competencies. This article is a resource for understanding the difference between critical appraisal tools and reporting guidelines, and identifying and accessing appropriate tools or guidelines. © 2017 Sigma Theta Tau International.

Big Data in industry

NASA Astrophysics Data System (ADS)

Latinović, T. S.; Preradović, D. M.; Barz, C. R.; Latinović, M. T.; Petrica, P. P.; Pop-Vadean, A.

2016-08-01

The amount of data at the global level has grown exponentially. Along with this phenomena, we have a need for a new unit of measure like exabyte, zettabyte, and yottabyte as the last unit measures the amount of data. The growth of data gives a situation where the classic systems for the collection, storage, processing, and visualization of data losing the battle with a large amount, speed, and variety of data that is generated continuously. Many of data that is created by the Internet of Things, IoT (cameras, satellites, cars, GPS navigation, etc.). It is our challenge to come up with new technologies and tools for the management and exploitation of these large amounts of data. Big Data is a hot topic in recent years in IT circles. However, Big Data is recognized in the business world, and increasingly in the public administration. This paper proposes an ontology of big data analytics and examines how to enhance business intelligence through big data analytics as a service by presenting a big data analytics services-oriented architecture. This paper also discusses the interrelationship between business intelligence and big data analytics. The proposed approach in this paper might facilitate the research and development of business analytics, big data analytics, and business intelligence as well as intelligent agents.

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error.

PubMed

Kazmierczak, Steven C; Leen, Todd K; Erdogmus, Deniz; Carreira-Perpinan, Miguel A

2007-01-01

The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has amore » variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.« less

T.Rex

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-06-08

T.Rex is used to explore tabular data sets containing up to ten million records to help rapidly understand a previously unknown data set. Analysis can quickly identify patterns of interest and the records and fields that capture those patterns. T.Rex contains a growing set of deep analytical tools and supports robust export capabilities that selected data can be incorporated into to other specialized tools for further analysis. T.Rex is flexible in ingesting different types and formats of data, allowing the user to interactively experiment and perform trial and error guesses on the structure of the data; and also has amore » variety of linked visual analytic tools that enable exploration of the data to find relevant content, relationships among content, trends within the content, and capture knowledge about the content. Finally, T.Rex has a rich export capability, to extract relevant subsets of a larger data source, to further analyze their data in other analytic tools.« less

Teaching Tectonics to Undergraduates with Web GIS

NASA Astrophysics Data System (ADS)

Anastasio, D. J.; Bodzin, A.; Sahagian, D. L.; Rutzmoser, S.

2013-12-01

Geospatial reasoning skills provide a means for manipulating, interpreting, and explaining structured information and are involved in higher-order cognitive processes that include problem solving and decision-making. Appropriately designed tools, technologies, and curriculum can support spatial learning. We present Web-based visualization and analysis tools developed with Javascript APIs to enhance tectonic curricula while promoting geospatial thinking and scientific inquiry. The Web GIS interface integrates graphics, multimedia, and animations that allow users to explore and discover geospatial patterns that are not easily recognized. Features include a swipe tool that enables users to see underneath layers, query tools useful in exploration of earthquake and volcano data sets, a subduction and elevation profile tool which facilitates visualization between map and cross-sectional views, drafting tools, a location function, and interactive image dragging functionality on the Web GIS. The Web GIS platform is independent and can be implemented on tablets or computers. The GIS tool set enables learners to view, manipulate, and analyze rich data sets from local to global scales, including such data as geology, population, heat flow, land cover, seismic hazards, fault zones, continental boundaries, and elevation using two- and three- dimensional visualization and analytical software. Coverages which allow users to explore plate boundaries and global heat flow processes aided learning in a Lehigh University Earth and environmental science Structural Geology and Tectonics class and are freely available on the Web.

Supported inhibitor for fishing lipases in complex biological media and mass spectrometry identification.

PubMed

Delorme, Vincent; Raux, Brigitt; Puppo, Rémy; Leclaire, Julien; Cavalier, Jean-François; Marc, Sylvain; Kamarajugadda, Pavan-Kumar; Buono, Gérard; Fotiadu, Frédéric; Canaan, Stéphane; Carrière, Frédéric

2014-12-01

A synthetic phosphonate inhibitor designed for lipase inhibition but displaying a broader range of activity was covalently immobilized on a solid support to generate a function-directed tool targeting serine hydrolases. To achieve this goal, straightforward and reliable analytical techniques were developed, allowing the monitoring of the solid support's chemical functionalization, enzyme capture processes and physisorption artifacts. This grafted inhibitor was tested on pure lipases and serine proteases from various origins, and assayed for the selective capture of lipases from several complex biological extracts. The direct identification of captured enzymes by mass spectrometry brought the proof of concept on the efficiency of this supported covalent inhibitor. The features and limitations of this "enzyme-fishing" proteomic tool provide new insight on solid-liquid inhibition process. Copyright © 2014. Published by Elsevier B.V.

EMERGING POLLUTANTS, MASS SPECTROMETRY, AND ...

EPA Pesticide Factsheets

Historically fundamental to amassing our understanding of environmental processes and chemical pollution is the realm of mass spectrometry (MS) - the mainstay of analytical chemistry - the workhorse that supplies definitive data that environmental scientists and engineers reply upon for identifying molecular compositions (and ultimately structures) of chemicals. While the power of MS has long been visible to the practicing environmental chemist, it borders on obscurity to the lay public and many scientists. While MS has played a long, historic (and largely invisible) role in establishing our knowledge of environmental processes and pollution, what recognition it does enjoy is usually relegated to that of a tool. It is usually the relevance or significance of the knowledge acquired from the application of the tool that has ultimate meaning to the public and science at large - not how the data were acquired. Methods (736/800): Mass Spectrometry and the

Evaluating Business Intelligence/Business Analytics Software for Use in the Information Systems Curriculum

ERIC Educational Resources Information Center

Davis, Gary Alan; Woratschek, Charles R.

2015-01-01

Business Intelligence (BI) and Business Analytics (BA) Software has been included in many Information Systems (IS) curricula. This study surveyed current and past undergraduate and graduate students to evaluate various BI/BA tools. Specifically, this study compared several software tools from two of the major software providers in the BI/BA field.…

The four principles: Can they be measured and do they predict ethical decision making?

PubMed Central

2012-01-01

Background The four principles of Beauchamp and Childress - autonomy, non-maleficence, beneficence and justice - have been extremely influential in the field of medical ethics, and are fundamental for understanding the current approach to ethical assessment in health care. This study tests whether these principles can be quantitatively measured on an individual level, and then subsequently if they are used in the decision making process when individuals are faced with ethical dilemmas. Methods The Analytic Hierarchy Process was used as a tool for the measurement of the principles. Four scenarios, which involved conflicts between the medical ethical principles, were presented to participants who then made judgments about the ethicality of the action in the scenario, and their intentions to act in the same manner if they were in the situation. Results Individual preferences for these medical ethical principles can be measured using the Analytic Hierarchy Process. This technique provides a useful tool in which to highlight individual medical ethical values. On average, individuals have a significant preference for non-maleficence over the other principles, however, and perhaps counter-intuitively, this preference does not seem to relate to applied ethical judgements in specific ethical dilemmas. Conclusions People state they value these medical ethical principles but they do not actually seem to use them directly in the decision making process. The reasons for this are explained through the lack of a behavioural model to account for the relevant situational factors not captured by the principles. The limitations of the principles in predicting ethical decision making are discussed. PMID:22606995

The four principles: can they be measured and do they predict ethical decision making?

PubMed

Page, Katie

2012-05-20

The four principles of Beauchamp and Childress--autonomy, non-maleficence, beneficence and justice--have been extremely influential in the field of medical ethics, and are fundamental for understanding the current approach to ethical assessment in health care. This study tests whether these principles can be quantitatively measured on an individual level, and then subsequently if they are used in the decision making process when individuals are faced with ethical dilemmas. The Analytic Hierarchy Process was used as a tool for the measurement of the principles. Four scenarios, which involved conflicts between the medical ethical principles, were presented to participants who then made judgments about the ethicality of the action in the scenario, and their intentions to act in the same manner if they were in the situation. Individual preferences for these medical ethical principles can be measured using the Analytic Hierarchy Process. This technique provides a useful tool in which to highlight individual medical ethical values. On average, individuals have a significant preference for non-maleficence over the other principles, however, and perhaps counter-intuitively, this preference does not seem to relate to applied ethical judgements in specific ethical dilemmas. People state they value these medical ethical principles but they do not actually seem to use them directly in the decision making process. The reasons for this are explained through the lack of a behavioural model to account for the relevant situational factors not captured by the principles. The limitations of the principles in predicting ethical decision making are discussed.

Coordination processes and outcomes in the public service: the challenge of inter-organizational food safety coordination in Norway.

PubMed

Lie, Amund

2011-01-01

In 2004 Norway implemented a food safety reform programme aimed at enhancing inter-organizational coordination processes and outcomes. Has this programme affected inter-organizational coordination processes and outcomes, both vertically and horizontally – and if so how? This article employs the concept of inter-organizational coordination as an analytical tool, examining it in the light of two theoretical perspectives and coupling it with the empirical findings. The argument presented is that the chances of strong coordination outcomes may increase if inter-organizational processes feature a clear division of labour, arenas for coordination, active leadership, a lack of major conflicting goals, and shared obligations.

Real-time assessment of critical quality attributes of a continuous granulation process.

PubMed

Fonteyne, Margot; Vercruysse, Jurgen; Díaz, Damián Córdoba; Gildemyn, Delphine; Vervaet, Chris; Remon, Jean Paul; De Beer, Thomas

2013-02-01

There exists the intention to shift pharmaceutical manufacturing of solid dosage forms from traditional batch production towards continuous production. The currently applied conventional quality control systems, based on sampling and time-consuming off-line analyses in analytical laboratories, would annul the advantages of continuous processing. It is clear that real-time quality assessment and control is indispensable for continuous production. This manuscript evaluates strengths and weaknesses of several complementary Process Analytical Technology (PAT) tools implemented in a continuous wet granulation process, which is part of a fully continuous from powder-to-tablet production line. The use of Raman and NIR-spectroscopy and a particle size distribution analyzer is evaluated for the real-time monitoring of critical parameters during the continuous wet agglomeration of an anhydrous theophylline- lactose blend. The solid state characteristics and particle size of the granules were analyzed in real-time and the critical process parameters influencing these granule characteristics were identified. The temperature of the granulator barrel, the amount of granulation liquid added and, to a lesser extent, the powder feed rate were the parameters influencing the solid state of the active pharmaceutical ingredient (API). A higher barrel temperature and a higher powder feed rate, resulted in larger granules.

Coproducing Aboriginal patient journey mapping tools for improved quality and coordination of care.

PubMed

Kelly, Janet; Dwyer, Judith; Mackean, Tamara; O'Donnell, Kim; Willis, Eileen

2016-12-08

This paper describes the rationale and process for developing a set of Aboriginal patient journey mapping tools with Aboriginal patients, health professionals, support workers, educators and researchers in the Managing Two Worlds Together project between 2008 and 2015. Aboriginal patients and their families from rural and remote areas, and healthcare providers in urban, rural and remote settings, shared their perceptions of the barriers and enablers to quality care in interviews and focus groups, and individual patient journey case studies were documented. Data were thematically analysed. In the absence of suitable existing tools, a new analytical framework and mapping approach was developed. The utility of the tools in other settings was then tested with health professionals, and the tools were further modified for use in quality improvement in health and education settings in South Australia and the Northern Territory. A central set of patient journey mapping tools with flexible adaptations, a workbook, and five sets of case studies describing how staff adapted and used the tools at different sites are available for wider use.

Big Data Tools as Applied to ATLAS Event Data

NASA Astrophysics Data System (ADS)

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 characteristics with different numbers of clients, query complexity, and size of the data retrieved.

Composite Cure Process Modeling and Simulations using COMPRO(Registered Trademark) and Validation of Residual Strains using Fiber Optics Sensors

NASA Technical Reports Server (NTRS)

Sreekantamurthy, Thammaiah; Hudson, Tyler B.; Hou, Tan-Hung; Grimsley, Brian W.

2016-01-01

Composite cure process induced residual strains and warping deformations in composite components present significant challenges in the manufacturing of advanced composite structure. As a part of the Manufacturing Process and Simulation initiative of the NASA Advanced Composite Project (ACP), research is being conducted on the composite cure process by developing an understanding of the fundamental mechanisms by which the process induced factors influence the residual responses. In this regard, analytical studies have been conducted on the cure process modeling of composite structural parts with varied physical, thermal, and resin flow process characteristics. The cure process simulation results were analyzed to interpret the cure response predictions based on the underlying physics incorporated into the modeling tool. In the cure-kinetic analysis, the model predictions on the degree of cure, resin viscosity and modulus were interpreted with reference to the temperature distribution in the composite panel part and tool setup during autoclave or hot-press curing cycles. In the fiber-bed compaction simulation, the pore pressure and resin flow velocity in the porous media models, and the compaction strain responses under applied pressure were studied to interpret the fiber volume fraction distribution predictions. In the structural simulation, the effect of temperature on the resin and ply modulus, and thermal coefficient changes during curing on predicted mechanical strains and chemical cure shrinkage strains were studied to understand the residual strains and stress response predictions. In addition to computational analysis, experimental studies were conducted to measure strains during the curing of laminated panels by means of optical fiber Bragg grating sensors (FBGs) embedded in the resin impregnated panels. The residual strain measurements from laboratory tests were then compared with the analytical model predictions. The paper describes the cure process procedures and residual strain predications, and discusses pertinent experimental results from the validation studies.

Real-time determination of critical quality attributes using near-infrared spectroscopy: a contribution for Process Analytical Technology (PAT).

PubMed

Rosas, Juan G; Blanco, Marcel; González, Josep M; Alcalà, Manel

2012-08-15

Process Analytical Technology (PAT) is playing a central role in current regulations on pharmaceutical production processes. Proper understanding of all operations and variables connecting the raw materials to end products is one of the keys to ensuring quality of the products and continuous improvement in their production. Near infrared spectroscopy (NIRS) has been successfully used to develop faster and non-invasive quantitative methods for real-time predicting critical quality attributes (CQA) of pharmaceutical granulates (API content, pH, moisture, flowability, angle of repose and particle size). NIR spectra have been acquired from the bin blender after granulation process in a non-classified area without the need of sample withdrawal. The methodology used for data acquisition, calibration modelling and method application in this context is relatively inexpensive and can be easily implemented by most pharmaceutical laboratories. For this purpose, Partial Least-Squares (PLS) algorithm was used to calculate multivariate calibration models, that provided acceptable Root Mean Square Error of Predictions (RMSEP) values (RMSEP(API)=1.0 mg/g; RMSEP(pH)=0.1; RMSEP(Moisture)=0.1%; RMSEP(Flowability)=0.6 g/s; RMSEP(Angle of repose)=1.7° and RMSEP(Particle size)=2.5%) that allowed the application for routine analyses of production batches. The proposed method affords quality assessment of end products and the determination of important parameters with a view to understanding production processes used by the pharmaceutical industry. As shown here, the NIRS technique is a highly suitable tool for Process Analytical Technologies. Copyright © 2012 Elsevier B.V. All rights reserved.

Effective dialogue: enhanced public engagement as a legitimising tool for municipal waste management decision-making.

PubMed

Garnett, Kenisha; Cooper, Tim

2014-12-01

The complexity of municipal waste management decision-making has increased in recent years, accompanied by growing scrutiny from stakeholders, including local communities. This complexity reflects a socio-technical framing of the risks and social impacts associated with selecting technologies and sites for waste treatment and disposal facilities. Consequently there is growing pressure on local authorities for stakeholders (including communities) to be given an early opportunity to shape local waste policy in order to encourage swift planning, development and acceptance of the technologies needed to meet statutory targets to divert waste from landfill. This paper presents findings from a research project that explored the use of analytical-deliberative processes as a legitimising tool for waste management decision-making. Adopting a mixed methods approach, the study revealed that communicating the practical benefits of more inclusive forms of engagement is proving difficult even though planning and policy delays are hindering development and implementation of waste management infrastructure. Adopting analytical-deliberative processes at a more strategic level will require local authorities and practitioners to demonstrate how expert-citizen deliberations may foster progress in resolving controversial issues, through change in individuals, communities and institutions. The findings suggest that a significant shift in culture will be necessary for local authorities to realise the potential of more inclusive decision processes. This calls for political actors and civic society to collaborate in institutionalising public involvement in both strategic and local planning structures. Copyright © 2014 Elsevier Ltd. All rights reserved.

Visual analysis of online social media to open up the investigation of stance phenomena

PubMed Central

Kucher, Kostiantyn; Schamp-Bjerede, Teri; Kerren, Andreas; Paradis, Carita; Sahlgren, Magnus

2015-01-01

Online social media are a perfect text source for stance analysis. Stance in human communication is concerned with speaker attitudes, beliefs, feelings and opinions. Expressions of stance are associated with the speakers' view of what they are talking about and what is up for discussion and negotiation in the intersubjective exchange. Taking stance is thus crucial for the social construction of meaning. Increased knowledge of stance can be useful for many application fields such as business intelligence, security analytics, or social media monitoring. In order to process large amounts of text data for stance analyses, linguists need interactive tools to explore the textual sources as well as the processed data based on computational linguistics techniques. Both original texts and derived data are important for refining the analyses iteratively. In this work, we present a visual analytics tool for online social media text data that can be used to open up the investigation of stance phenomena. Our approach complements traditional linguistic analysis techniques and is based on the analysis of utterances associated with two stance categories: sentiment and certainty. Our contributions include (1) the description of a novel web-based solution for analyzing the use and patterns of stance meanings and expressions in human communication over time; and (2) specialized techniques used for visualizing analysis provenance and corpus overview/navigation. We demonstrate our approach by means of text media on a highly controversial scandal with regard to expressions of anger and provide an expert review from linguists who have been using our tool. PMID:29249903

Visual analysis of online social media to open up the investigation of stance phenomena.

PubMed

Kucher, Kostiantyn; Schamp-Bjerede, Teri; Kerren, Andreas; Paradis, Carita; Sahlgren, Magnus

2016-04-01

Online social media are a perfect text source for stance analysis. Stance in human communication is concerned with speaker attitudes, beliefs, feelings and opinions. Expressions of stance are associated with the speakers' view of what they are talking about and what is up for discussion and negotiation in the intersubjective exchange. Taking stance is thus crucial for the social construction of meaning. Increased knowledge of stance can be useful for many application fields such as business intelligence, security analytics, or social media monitoring. In order to process large amounts of text data for stance analyses, linguists need interactive tools to explore the textual sources as well as the processed data based on computational linguistics techniques. Both original texts and derived data are important for refining the analyses iteratively. In this work, we present a visual analytics tool for online social media text data that can be used to open up the investigation of stance phenomena. Our approach complements traditional linguistic analysis techniques and is based on the analysis of utterances associated with two stance categories: sentiment and certainty. Our contributions include (1) the description of a novel web-based solution for analyzing the use and patterns of stance meanings and expressions in human communication over time; and (2) specialized techniques used for visualizing analysis provenance and corpus overview/navigation. We demonstrate our approach by means of text media on a highly controversial scandal with regard to expressions of anger and provide an expert review from linguists who have been using our tool.

Process mining is an underutilized clinical research tool in transfusion medicine.

PubMed

Quinn, Jason G; Conrad, David M; Cheng, Calvino K

2017-03-01

To understand inventory performance, transfusion services commonly use key performance indicators (KPIs) as summary descriptors of inventory efficiency that are graphed, trended, and used to benchmark institutions. Here, we summarize current limitations in KPI-based evaluation of blood bank inventory efficiency and propose process mining as an ideal methodology for application to inventory management research to improve inventory flows and performance. The transit of a blood product from inventory receipt to final disposition is complex and relates to many internal and external influences, and KPIs may be inadequate to fully understand the complexity of the blood supply chain and how units interact with its processes. Process mining lends itself well to analysis of blood bank inventories, and modern laboratory information systems can track nearly all of the complex processes that occur in the blood bank. Process mining is an analytical tool already used in other industries and can be applied to blood bank inventory management and research through laboratory information systems data using commercial applications. Although the current understanding of real blood bank inventories is value-centric through KPIs, it potentially can be understood from a process-centric lens using process mining. © 2017 AABB.

Health informatics and analytics - building a program to integrate business analytics across clinical and administrative disciplines.

PubMed

Tremblay, Monica Chiarini; Deckard, Gloria J; Klein, Richard

2016-07-01

Health care organizations must develop integrated health information systems to respond to the numerous government mandates driving the movement toward reimbursement models emphasizing value-based and accountable care. Success in this transition requires integrated data analytics, supported by the combination of health informatics, interoperability, business process design, and advanced decision support tools. This case study presents the development of a master's level cross- and multidisciplinary informatics program offered through a business school. The program provides students from diverse backgrounds with the knowledge, leadership, and practical application skills of health informatics, information systems, and data analytics that bridge the interests of clinical and nonclinical professionals. This case presents the actions taken and challenges encountered in navigating intra-university politics, specifying curriculum, recruiting the requisite interdisciplinary faculty, innovating the educational format, managing students with diverse educational and professional backgrounds, and balancing multiple accreditation agencies. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The NASA Reanalysis Ensemble Service - Advanced Capabilities for Integrated Reanalysis Access and Intercomparison

NASA Astrophysics Data System (ADS)

Tamkin, G.; Schnase, J. L.; Duffy, D.; Li, J.; Strong, S.; Thompson, J. H.

2017-12-01

NASA's efforts to advance climate analytics-as-a-service are making new capabilities available to the research community: (1) A full-featured Reanalysis Ensemble Service (RES) comprising monthly means data from multiple reanalysis data sets, accessible through an enhanced set of extraction, analytic, arithmetic, and intercomparison operations. The operations are made accessible through NASA's climate data analytics Web services and our client-side Climate Data Services Python library, CDSlib; (2) A cloud-based, high-performance Virtual Real-Time Analytics Testbed supporting a select set of climate variables. This near real-time capability enables advanced technologies like Spark and Hadoop-based MapReduce analytics over native NetCDF files; and (3) A WPS-compliant Web service interface to our climate data analytics service that will enable greater interoperability with next-generation systems such as ESGF. The Reanalysis Ensemble Service includes the following: - New API that supports full temporal, spatial, and grid-based resolution services with sample queries - A Docker-ready RES application to deploy across platforms - Extended capabilities that enable single- and multiple reanalysis area average, vertical average, re-gridding, standard deviation, and ensemble averages - Convenient, one-stop shopping for commonly used data products from multiple reanalyses including basic sub-setting and arithmetic operations (e.g., avg, sum, max, min, var, count, anomaly) - Full support for the MERRA-2 reanalysis dataset in addition to, ECMWF ERA-Interim, NCEP CFSR, JMA JRA-55 and NOAA/ESRL 20CR… - A Jupyter notebook-based distribution mechanism designed for client use cases that combines CDSlib documentation with interactive scenarios and personalized project management - Supporting analytic services for NASA GMAO Forward Processing datasets - Basic uncertainty quantification services that combine heterogeneous ensemble products with comparative observational products (e.g., reanalysis, observational, visualization) - The ability to compute and visualize multiple reanalysis for ease of inter-comparisons - Automated tools to retrieve and prepare data collections for analytic processing

Multi-parameters monitoring during traditional Chinese medicine concentration process with near infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Liu, Ronghua; Sun, Qiaofeng; Hu, Tian; Li, Lian; Nie, Lei; Wang, Jiayue; Zhou, Wanhui; Zang, Hengchang

2018-03-01

As a powerful process analytical technology (PAT) tool, near infrared (NIR) spectroscopy has been widely used in real-time monitoring. In this study, NIR spectroscopy was applied to monitor multi-parameters of traditional Chinese medicine (TCM) Shenzhiling oral liquid during the concentration process to guarantee the quality of products. Five lab scale batches were employed to construct quantitative models to determine five chemical ingredients and physical change (samples density) during concentration process. The paeoniflorin, albiflorin, liquiritin and samples density were modeled by partial least square regression (PLSR), while the content of the glycyrrhizic acid and cinnamic acid were modeled by support vector machine regression (SVMR). Standard normal variate (SNV) and/or Savitzkye-Golay (SG) smoothing with derivative methods were adopted for spectra pretreatment. Variable selection methods including correlation coefficient (CC), competitive adaptive reweighted sampling (CARS) and interval partial least squares regression (iPLS) were performed for optimizing the models. The results indicated that NIR spectroscopy was an effective tool to successfully monitoring the concentration process of Shenzhiling oral liquid.

Method development and qualification of capillary zone electrophoresis for investigation of therapeutic monoclonal antibody quality.

PubMed

Suba, Dávid; Urbányi, Zoltán; Salgó, András

2016-10-01

Capillary electrophoresis techniques are widely used in the analytical biotechnology. Different electrophoretic techniques are very adequate tools to monitor size-and charge heterogenities of protein drugs. Method descriptions and development studies of capillary zone electrophoresis (CZE) have been described in literature. Most of them are performed based on the classical one-factor-at-time (OFAT) approach. In this study a very simple method development approach is described for capillary zone electrophoresis: a "two-phase-four-step" approach is introduced which allows a rapid, iterative method development process and can be a good platform for CZE method. In every step the current analytical target profile and an appropriate control strategy were established to monitor the current stage of development. A very good platform was established to investigate intact and digested protein samples. Commercially available monoclonal antibody was chosen as model protein for the method development study. The CZE method was qualificated after the development process and the results were presented. The analytical system stability was represented by the calculated RSD% value of area percentage and migration time of the selected peaks (<0.8% and <5%) during the intermediate precision investigation. Copyright © 2016 Elsevier B.V. All rights reserved.

New Tools and New Biology: Recent Miniaturized Systems for Molecular and Cellular Biology

PubMed Central

Hamon, Morgan; Hong, Jong Wook

2013-01-01

Recent advances in applied physics and chemistry have led to the development of novel microfluidic systems. Microfluidic systems allow minute amounts of reagents to be processed using μm-scale channels and offer several advantages over conventional analytical devices for use in biological sciences: faster, more accurate and more reproducible analytical performance, reduced cell and reagent consumption, portability, and integration of functional components in a single chip. In this review, we introduce how microfluidics has been applied to biological sciences. We first present an overview of the fabrication of microfluidic systems and describe the distinct technologies available for biological research. We then present examples of microsystems used in biological sciences, focusing on applications in molecular and cellular biology. PMID:24305843

Design of High Field Solenoids made of High Temperature Superconductors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bartalesi, Antonio; /Pisa U.

2010-12-01

This thesis starts from the analytical mechanical analysis of a superconducting solenoid, loaded by self generated Lorentz forces. Also, a finite element model is proposed and verified with the analytical results. To study the anisotropic behavior of a coil made by layers of superconductor and insulation, a finite element meso-mechanic model is proposed and designed. The resulting material properties are then used in the main solenoid analysis. In parallel, design work is performed as well: an existing Insert Test Facility (ITF) is adapted and structurally verified to support a coil made of YBa{sub 2}Cu{sub 3}O{sub 7}, a High Temperature Superconductormore » (HTS). Finally, a technological winding process was proposed and the required tooling is designed.« less

Development of a Novel Method for in vivo Determination of Activation Energy of Glucose Transport Across S. cerevisiae Cellular Membranes. A Biosensor-like Approach

PubMed Central

Kormes, Diego J.; Cortón, Eduardo

2009-01-01

Whereas biosensors have been usually proposed as analytical tools, used to investigate the surrounding media pursuing an analytical answer, we have used a biosensor-like device to characterize the microbial cells immobilized on it. We have studied the kinetics of transport and degradation of glucose at different concentrations and temperatures. When glucose concentrations of 15 and 1.5 mM were assayed, calculated activation energies were 25.2 and 18.4 kcal mol−1, respectively, in good agreement with previously published data. The opportunity and convenience of using Arrhenius plots to estimate the activation energy in metabolic-related processes is also discussed. PMID:22573975

Diagnostic criteria for the characterization of quasireversible electron transfer reactions by cyclic square wave voltammetry.

PubMed

Mann, Megan A; Helfrick, John C; Bottomley, Lawrence A

2014-08-19

Theory for cyclic square wave voltammetry of quasireversible electron transfer reactions is presented and experimentally verified. The impact of empirical parameters on the shape of the current-voltage curve is examined. From the trends, diagnostic criteria enabling the use of this waveform as a tool for mechanistic analysis of electrode reaction processes are presented. These criteria were experimentally confirmed using Eu(3+)/Eu(2+), a well-established quasireversible analyte. Using cyclic square wave voltammetry, both the electron transfer coefficient and rate were calculated for this analyte and found to be in excellent agreement with literature. When properly applied, these criteria will enable nonexperts in voltammetry to assign the electrode reaction mechanism and accurately measure electrode reaction kinetics.

VIS-NIR spectroscopy as a process analytical technology for compositional characterization of film biopolymers and correlation with their mechanical properties.

PubMed

Barbin, Douglas Fernandes; Valous, Nektarios A; Dias, Adriana Passos; Camisa, Jaqueline; Hirooka, Elisa Yoko; Yamashita, Fabio

2015-11-01

There is an increasing interest in the use of polysaccharides and proteins for the production of biodegradable films. Visible and near-infrared (VIS-NIR) spectroscopy is a reliable analytical tool for objective analyses of biological sample attributes. The objective is to investigate the potential of VIS-NIR spectroscopy as a process analytical technology for compositional characterization of biodegradable materials and correlation to their mechanical properties. Biofilms were produced by single-screw extrusion with different combinations of polybutylene adipate-co-terephthalate, whole oat flour, glycerol, magnesium stearate, and citric acid. Spectral data were recorded in the range of 400-2498nm at 2nm intervals. Partial least square regression was used to investigate the correlation between spectral information and mechanical properties. Results show that spectral information is influenced by the major constituent components, as they are clustered according to polybutylene adipate-co-terephthalate content. Results for regression models using the spectral information as predictor of tensile properties achieved satisfactory results, with coefficients of prediction (R(2)C) of 0.83, 0.88 and 0.92 (calibration models) for elongation, tensile strength, and Young's modulus, respectively. Results corroborate the correlation of NIR spectra with tensile properties, showing that NIR spectroscopy has potential as a rapid analytical technology for non-destructive assessment of the mechanical properties of the films. Copyright © 2015 Elsevier B.V. All rights reserved.

At-line process analytical technology (PAT) for more efficient scale up of biopharmaceutical microfiltration unit operations.

PubMed

Watson, Douglas S; Kerchner, Kristi R; Gant, Sean S; Pedersen, Joseph W; Hamburger, James B; Ortigosa, Allison D; Potgieter, Thomas I

2016-01-01

Tangential flow microfiltration (MF) is a cost-effective and robust bioprocess separation technique, but successful full scale implementation is hindered by the empirical, trial-and-error nature of scale-up. We present an integrated approach leveraging at-line process analytical technology (PAT) and mass balance based modeling to de-risk MF scale-up. Chromatography-based PAT was employed to improve the consistency of an MF step that had been a bottleneck in the process used to manufacture a therapeutic protein. A 10-min reverse phase ultra high performance liquid chromatography (RP-UPLC) assay was developed to provide at-line monitoring of protein concentration. The method was successfully validated and method performance was comparable to previously validated methods. The PAT tool revealed areas of divergence from a mass balance-based model, highlighting specific opportunities for process improvement. Adjustment of appropriate process controls led to improved operability and significantly increased yield, providing a successful example of PAT deployment in the downstream purification of a therapeutic protein. The general approach presented here should be broadly applicable to reduce risk during scale-up of filtration processes and should be suitable for feed-forward and feed-back process control. © 2015 American Institute of Chemical Engineers.

Using Hybrid Simulation/Analytical Queueing Networks to Capacitate USAF Air Mobility Command Passenger Terminals

DTIC Science & Technology

2012-03-01

Simulation Simulation is a flexible tool for modeling airport operations , which has made the method a staple for airport systems analysts. Animation...be derived to define the character- istics of the airport terminal and describe the nature of the systems [sic] operation ”, which makes discrete...This system decomposition method, however, disregards the effects of network structure on performance measures. Real-life processes do not operate

Information Processing in Nursing Information Systems: An Evaluation Study from a Developing Country.

PubMed

Samadbeik, Mahnaz; Shahrokhi, Nafiseh; Saremian, Marzieh; Garavand, Ali; Birjandi, Mahdi

2017-01-01

In recent years, information technology has been introduced in the nursing departments of many hospitals to support their daily tasks. Nurses are the largest end user group in Hospital Information Systems (HISs). This study was designed to evaluate data processing in the Nursing Information Systems (NISs) utilized in many university hospitals in Iran. This was a cross-sectional study. The population comprised all nurse managers and NIS users of the five training hospitals in Khorramabad city ( N = 71). The nursing subset of HIS-Monitor questionnaire was used to collect the data. Data were analyzed by the descriptive-analytical method and the inductive content analysis. The results indicated that the nurses participating in the study did not take a desirable advantage of paper (2.02) and computerized (2.34) information processing tools to perform nursing tasks. Moreover, the less work experience nurses have, the further they utilize computer tools for processing patient discharge information. The "readability of patient information" and "repetitive and time-consuming documentation" were stated as the most important expectations and problems regarding the HIS by the participating nurses, respectively. The nurses participating in the present study used to utilize paper and computerized information processing tools together to perform nursing practices. Therefore, it is recommended that the nursing process redesign coincides with NIS implementation in the health care centers.

IBM's Health Analytics and Clinical Decision Support.

PubMed

Kohn, M S; Sun, J; Knoop, S; Shabo, A; Carmeli, B; Sow, D; Syed-Mahmood, T; Rapp, W

2014-08-15

This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation.

GenomicTools: a computational platform for developing high-throughput analytics in genomics.

PubMed

Tsirigos, Aristotelis; Haiminen, Niina; Bilal, Erhan; Utro, Filippo

2012-01-15

Recent advances in sequencing technology have resulted in the dramatic increase of sequencing data, which, in turn, requires efficient management of computational resources, such as computing time, memory requirements as well as prototyping of computational pipelines. We present GenomicTools, a flexible computational platform, comprising both a command-line set of tools and a C++ API, for the analysis and manipulation of high-throughput sequencing data such as DNA-seq, RNA-seq, ChIP-seq and MethylC-seq. GenomicTools implements a variety of mathematical operations between sets of genomic regions thereby enabling the prototyping of computational pipelines that can address a wide spectrum of tasks ranging from pre-processing and quality control to meta-analyses. Additionally, the GenomicTools platform is designed to analyze large datasets of any size by minimizing memory requirements. In practical applications, where comparable, GenomicTools outperforms existing tools in terms of both time and memory usage. The GenomicTools platform (version 2.0.0) was implemented in C++. The source code, documentation, user manual, example datasets and scripts are available online at http://code.google.com/p/ibm-cbc-genomic-tools.

Concurrence of big data analytics and healthcare: A systematic review.

PubMed

Mehta, Nishita; Pandit, Anil

2018-06-01

The application of Big Data analytics in healthcare has immense potential for improving the quality of care, reducing waste and error, and reducing the cost of care. This systematic review of literature aims to determine the scope of Big Data analytics in healthcare including its applications and challenges in its adoption in healthcare. It also intends to identify the strategies to overcome the challenges. A systematic search of the articles was carried out on five major scientific databases: ScienceDirect, PubMed, Emerald, IEEE Xplore and Taylor & Francis. The articles on Big Data analytics in healthcare published in English language literature from January 2013 to January 2018 were considered. Descriptive articles and usability studies of Big Data analytics in healthcare and medicine were selected. Two reviewers independently extracted information on definitions of Big Data analytics; sources and applications of Big Data analytics in healthcare; challenges and strategies to overcome the challenges in healthcare. A total of 58 articles were selected as per the inclusion criteria and analyzed. The analyses of these articles found that: (1) researchers lack consensus about the operational definition of Big Data in healthcare; (2) Big Data in healthcare comes from the internal sources within the hospitals or clinics as well external sources including government, laboratories, pharma companies, data aggregators, medical journals etc.; (3) natural language processing (NLP) is most widely used Big Data analytical technique for healthcare and most of the processing tools used for analytics are based on Hadoop; (4) Big Data analytics finds its application for clinical decision support; optimization of clinical operations and reduction of cost of care (5) major challenge in adoption of Big Data analytics is non-availability of evidence of its practical benefits in healthcare. This review study unveils that there is a paucity of information on evidence of real-world use of Big Data analytics in healthcare. This is because, the usability studies have considered only qualitative approach which describes potential benefits but does not take into account the quantitative study. Also, majority of the studies were from developed countries which brings out the need for promotion of research on Healthcare Big Data analytics in developing countries. Copyright © 2018 Elsevier B.V. All rights reserved.

Harnessing Scientific Literature Reports for Pharmacovigilance

PubMed Central

Ripple, Anna; Tonning, Joseph; Munoz, Monica; Hasan, Rashedul; Ly, Thomas; Francis, Henry; Bodenreider, Olivier

2017-01-01

Summary Objectives We seek to develop a prototype software analytical tool to augment FDA regulatory reviewers’ capacity to harness scientific literature reports in PubMed/MEDLINE for pharmacovigilance and adverse drug event (ADE) safety signal detection. We also aim to gather feedback through usability testing to assess design, performance, and user satisfaction with the tool. Methods A prototype, open source, web-based, software analytical tool generated statistical disproportionality data mining signal scores and dynamic visual analytics for ADE safety signal detection and management. We leveraged Medical Subject Heading (MeSH) indexing terms assigned to published citations in PubMed/MEDLINE to generate candidate drug-adverse event pairs for quantitative data mining. Six FDA regulatory reviewers participated in usability testing by employing the tool as part of their ongoing real-life pharmacovigilance activities to provide subjective feedback on its practical impact, added value, and fitness for use. Results All usability test participants cited the tool’s ease of learning, ease of use, and generation of quantitative ADE safety signals, some of which corresponded to known established adverse drug reactions. Potential concerns included the comparability of the tool’s automated literature search relative to a manual ‘all fields’ PubMed search, missing drugs and adverse event terms, interpretation of signal scores, and integration with existing computer-based analytical tools. Conclusions Usability testing demonstrated that this novel tool can automate the detection of ADE safety signals from published literature reports. Various mitigation strategies are described to foster improvements in design, productivity, and end user satisfaction. PMID:28326432

moocRP: Enabling Open Learning Analytics with an Open Source Platform for Data Distribution, Analysis, and Visualization

ERIC Educational Resources Information Center

Pardos, Zachary A.; Whyte, Anthony; Kao, Kevin

2016-01-01

In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload…

Adequacy of surface analytical tools for studying the tribology of ceramics

NASA Technical Reports Server (NTRS)

Sliney, H. E.

1986-01-01

Surface analytical tools are very beneficial in tribological studies of ceramics. Traditional methods of optical microscopy, XRD, XRF, and SEM should be combined with newer surface sensitive techniques especially AES and XPS. ISS and SIMS can also be useful in providing additional compositon details. Tunneling microscopy and electron energy loss spectroscopy are less known techniques that may also prove useful.

Understanding Emotions as Situated, Embodied, and Fissured: Thinking with Theory to Create an Analytical Tool

ERIC Educational Resources Information Center

Kuby, Candace R.

2014-01-01

An emerging theoretical perspective is that emotions are a verb or something we do in relation to others. Studies that demonstrate ways to analyze emotions from a performative stance are scarce. In this article, a new analytical tool is introduced; a critical performative analysis of emotion (CPAE) that draws upon three theoretical perspectives:…

Analytical Tools for Affordability Analysis

DTIC Science & Technology

2015-05-01

function (Womer)  Unit cost as a function of learning and rate  Learning with forgetting (Benkard)  Learning depreciates over time  Discretionary...Analytical Tools for Affordability Analysis David Tate Cost Analysis and Research Division Institute for Defense Analyses Report Documentation...ES) Institute for Defense Analyses, Cost Analysis and Research Division,4850 Mark Center Drive,Alexandria,VA,22311-1882 8. PERFORMING ORGANIZATION

Social Capital: An Analytical Tool for Exploring Lifelong Learning and Community Development. CRLRA Discussion Paper.

ERIC Educational Resources Information Center

Kilpatrick, Sue; Field, John; Falk, Ian

The possibility of using the concept of social capital as an analytical tool for exploring lifelong learning and community development was examined. The following were among the topics considered: (1) differences between definitions of the concept of social capital that are based on collective benefit and those that define social capital as a…

The Metaphorical Department Head: Using Metaphors as Analytic Tools to Investigate the Role of Department Head

ERIC Educational Resources Information Center

Paranosic, Nikola; Riveros, Augusto

2017-01-01

This paper reports the results of a study that examined the ways a group of department heads in Ontario, Canada, describe their role. Despite their ubiquity and importance, department heads have been seldom investigated in the educational leadership literature. The study uses the metaphor as an analytic tool to examine the ways participants talked…

Analytical Tools for Behavioral Influences Operations

DTIC Science & Technology

2003-12-01

NASIC’s Investment in Analytical Capabilities ....................................................... 56 6.2 Study Limitations...get started. This project is envisioned as a foundation for future work by NASIC analysts. They will use the tools identified in this study to...capabilities Though this study took all three categories into account, most (90%) of the focus for the SRA team’s effort was on identifying and analyzing

e-Healthcare in India: critical success factors for sustainable health systems.

PubMed

Taneja, Udita; Sushil

2007-01-01

As healthcare enterprises seek to move towards an integrated, sustainable healthcare delivery model an IT-enabled or e-Healthcare strategy is being increasingly adopted. In this study we identified the critical success factors influencing the effectiveness of an e-Healthcare strategy in India. The performance assessment criteria used to measure effectiveness were increasing reach and reducing cost of healthcare delivery. A survey of healthcare providers was conducted. Analytic Hierarchy Process (AHP) and Interpretive Structural Modeling (ISM) were the analytical tools used to determine the relative importance of the critical success factors in influencing effectiveness of e-Healthcare and their interplay with each other. To succeed in e-Healthcare initiatives the critical success factors that need to be in place are appropriate government policies, literacy levels, and telecommunications and power infrastructure in the country. The focus should not be on the IT tools and biomedical engineering technologies as is most often the case. Instead the nontechnology factors such as healthcare provider and consumer mindsets should be addressed to increase acceptance of, and enhance the effectiveness of, sustainable e-Healthcare services.

Development of a new analytical tool for assessing the mutagen 2-methyl-1,4-dinitro-pyrrole in meat products by LC-ESI-MS/MS.

PubMed

Molognoni, Luciano; Daguer, Heitor; de Sá Ploêncio, Leandro Antunes; Yotsuyanagi, Suzana Eri; da Silva Correa Lemos, Ana Lucia; Joussef, Antonio Carlos; De Dea Lindner, Juliano

2018-08-01

The use of sorbate and nitrite in meat processing may lead to the formation of 2-methyl-1,4-dinitro-pyrrole (DNMP), a mutagenic compound. This work was aimed at developing and validating an analytical method for the quantitation of DNMP by liquid chromatography-tandem mass spectrometry. Full validation was performed in accordance to Commission Decision 2002/657/EC and method applicability was checked in several samples of meat products. A simple procedure, with low temperature partitioning solid-liquid extraction, was developed. The nitrosation during the extraction was monitored by the N-nitroso-DL-pipecolic acid content. Chromatographic separation was achieved in 8 min with di-isopropyl-3-aminopropyl silane bound to hydroxylated silica as stationary phase. Samples of bacon and cooked sausage yielded the highest concentrations of DNMP (68 ± 3 and 50 ± 3 μg kg -1 , respectively). The developed method proved to be a reliable, selective, and sensitive tool for DNMP measurements in meat products. Copyright © 2018 Elsevier B.V. All rights reserved.

Concept for Inclusion of Analytical and Computational Capability in Optical Plume Anomaly Detection (OPAD) for Measurement of Neutron Flux

NASA Technical Reports Server (NTRS)

Patrick, Marshall Clint; Cooper, Anita E.; Powers, W. T.

2004-01-01

Researchers are working on many fronts to make possible high-speed, automated classification and quantification of constituent materials in numerous environments. NASA's Marshall Space Flight Center has implemented a system for rocket engine flowfields/plumes. The Optical Plume Anomaly Detector (OPAD) system was designed to utilize emission and absorption spectroscopy for monitoring molecular and atomic particulates in gas plasma. An accompanying suite of tools and analytical package designed to utilize information collected by OPAD is known as the Engine Diagnostic Filtering System (EDiFiS). The current combination of these systems identifies atomic and molecular species and quantifies mass loss rates in H2/O2 rocket plumes. Capabilities for real-time processing are being advanced on several fronts, including an effort to hardware encode components of the EDiFiS for health monitoring and management. This paper addresses the OPAD with its tool suites, and discusses what is considered a natural progression: a concept for taking OPAD to the next logical level of high energy physics, incorporating fermion and boson particle analyses in measurement of neutron flux.

Historical perspective on risk assessment in the federal government.

PubMed

Graham, J D

1995-09-01

This article traces the evolution of risk assessment as an essential analytical tool in the federal government. In many programs and agencies, decisions cannot be made without the benefit of information from risk assessment. Although this analytical tool influences important public health and economic decisions, there is widespread dissatisfaction with the day-to-day practice of risk assessment. The article describes the sources of dissatisfaction that have been voiced by scientists, regulators, interest groups and ordinary citizens. Problems include the use of arbitrary exposure scenarios, the misuse of the 'carcinogen' label, the excessive reliance on animal cancer tests, the lack of formal uncertainty analysis the low priority assigned to noncancer endpoints, the poor communication of risk estimates and the neglect of inequities in the distribution of risk. Despite these limitations, the article argues that more danger rests in efforts to make decisions without any risk assessment. Recent Congressional and Administration interest in risk assessment is encouraging because it offers promise to learn from past mistakes and set in motion steps to enhance the risk assessment process.

Cyberhubs: Virtual Research Environments for Astronomy

NASA Astrophysics Data System (ADS)

Herwig, Falk; Andrassy, Robert; Annau, Nic; Clarkson, Ondrea; Côté, Benoit; D’Sa, Aaron; Jones, Sam; Moa, Belaid; O’Connell, Jericho; Porter, David; Ritter, Christian; Woodward, Paul

2018-05-01

Collaborations in astronomy and astrophysics are faced with numerous cyber-infrastructure challenges, such as large data sets, the need to combine heterogeneous data sets, and the challenge to effectively collaborate on those large, heterogeneous data sets with significant processing requirements and complex science software tools. The cyberhubs system is an easy-to-deploy package for small- to medium-sized collaborations based on the Jupyter and Docker technology, which allows web-browser-enabled, remote, interactive analytic access to shared data. It offers an initial step to address these challenges. The features and deployment steps of the system are described, as well as the requirements collection through an account of the different approaches to data structuring, handling, and available analytic tools for the NuGrid and PPMstar collaborations. NuGrid is an international collaboration that creates stellar evolution and explosion physics and nucleosynthesis simulation data. The PPMstar collaboration performs large-scale 3D stellar hydrodynamics simulations of interior convection in the late phases of stellar evolution. Examples of science that is currently performed on cyberhubs, in the areas of 3D stellar hydrodynamic simulations, stellar evolution and nucleosynthesis, and Galactic chemical evolution, are presented.

A quality by design study applied to an industrial pharmaceutical fluid bed granulation.

PubMed

Lourenço, Vera; Lochmann, Dirk; Reich, Gabriele; Menezes, José C; Herdling, Thorsten; Schewitz, Jens

2012-06-01

The pharmaceutical industry is encouraged within Quality by Design (QbD) to apply science-based manufacturing principles to assure quality not only of new but also of existing processes. This paper presents how QbD principles can be applied to an existing industrial pharmaceutical fluid bed granulation (FBG) process. A three-step approach is presented as follows: (1) implementation of Process Analytical Technology (PAT) monitoring tools at the industrial scale process, combined with multivariate data analysis (MVDA) of process and PAT data to increase the process knowledge; (2) execution of scaled-down designed experiments at a pilot scale, with adequate PAT monitoring tools, to investigate the process response to intended changes in Critical Process Parameters (CPPs); and finally (3) the definition of a process Design Space (DS) linking CPPs to Critical to Quality Attributes (CQAs), within which product quality is ensured by design, and after scale-up enabling its use at the industrial process scale. The proposed approach was developed for an existing industrial process. Through enhanced process knowledge established a significant reduction in product CQAs, variability already within quality specifications ranges was achieved by a better choice of CPPs values. The results of such step-wise development and implementation are described. Copyright © 2012 Elsevier B.V. All rights reserved.

Monitoring of antisolvent crystallization of sodium scutellarein by combined FBRM-PVM-NIR.

PubMed

Liu, Xuesong; Sun, Di; Wang, Feng; Wu, Yongjiang; Chen, Yong; Wang, Longhu

2011-06-01

Antisolvent crystallization can be used as an alternative to cooling or evaporation for the separation and purification of solid product in the pharmaceutical industry. To improve the process understanding of antisolvent crystallization, the use of in-line tools is vital. In this study, the process analytical technology (PAT) tools including focused beam reflectance measurement (FBRM), particle video microscope (PVM), and near-infrared spectroscopy (NIRS) were utilized to monitor antisolvent crystallization of sodium scutellarein. FBRM was used to monitor chord count and chord length distribution of sodium scutellarein particles in the crystallizer, and PVM, as an in-line video camera, provided pictures imaging particle shape and dimension. In addition, a quantitative model of PLS was established by in-line NIRS to detect the concentration of sodium scutellarein in the solvent and good calibration statistics were obtained (r(2) = 0.976) with the residual predictive deviation value of 11.3. The discussion over sensitivities, strengths, and weaknesses of the PAT tools may be helpful in selection of suitable PAT techniques. These in-line techniques eliminate the need for sample preparation and offer a time-saving approach to understand and monitor antisolvent crystallization process. Copyright © 2011 Wiley-Liss, Inc.

Human/autonomy collaboration for the automated generation of intelligence products

NASA Astrophysics Data System (ADS)

DiBona, Phil; Schlachter, Jason; Kuter, Ugur; Goldman, Robert

2017-05-01

Intelligence Analysis remains a manual process despite trends toward autonomy in information processing. Analysts need agile decision-­-support tools that can adapt to the evolving information needs of the mission, allowing the analyst to pose novel analytic questions. Our research enables the analysts to only provide a constrained English specification of what the intelligence product should be. Using HTN planning, the autonomy discovers, decides, and generates a workflow of algorithms to create the intelligence product. Therefore, the analyst can quickly and naturally communicate to the autonomy what information product is needed, rather than how to create it.

Crossing disciplines and scales to understand the critical zone

USGS Publications Warehouse

Brantley, S.L.; Goldhaber, M.B.; Vala, Ragnarsdottir K.

2007-01-01

The Critical Zone (CZ) is the system of coupled chemical, biological, physical, and geological processes operating together to support life at the Earth's surface. While our understanding of this zone has increased over the last hundred years, further advance requires scientists to cross disciplines and scales to integrate understanding of processes in the CZ, ranging in scale from the mineral-water interface to the globe. Despite the extreme heterogeneities manifest in the CZ, patterns are observed at all scales. Explanations require the use of new computational and analytical tools, inventive interdisciplinary approaches, and growing networks of sites and people.

Quality of Big Data in health care.

PubMed

Sukumar, Sreenivas R; Natarajan, Ramachandran; Ferrell, Regina K

2015-01-01

The current trend in Big Data analytics and in particular health information technology is toward building sophisticated models, methods and tools for business, operational and clinical intelligence. However, the critical issue of data quality required for these models is not getting the attention it deserves. The purpose of this paper is to highlight the issues of data quality in the context of Big Data health care analytics. The insights presented in this paper are the results of analytics work that was done in different organizations on a variety of health data sets. The data sets include Medicare and Medicaid claims, provider enrollment data sets from both public and private sources, electronic health records from regional health centers accessed through partnerships with health care claims processing entities under health privacy protected guidelines. Assessment of data quality in health care has to consider: first, the entire lifecycle of health data; second, problems arising from errors and inaccuracies in the data itself; third, the source(s) and the pedigree of the data; and fourth, how the underlying purpose of data collection impact the analytic processing and knowledge expected to be derived. Automation in the form of data handling, storage, entry and processing technologies is to be viewed as a double-edged sword. At one level, automation can be a good solution, while at another level it can create a different set of data quality issues. Implementation of health care analytics with Big Data is enabled by a road map that addresses the organizational and technological aspects of data quality assurance. The value derived from the use of analytics should be the primary determinant of data quality. Based on this premise, health care enterprises embracing Big Data should have a road map for a systematic approach to data quality. Health care data quality problems can be so very specific that organizations might have to build their own custom software or data quality rule engines. Today, data quality issues are diagnosed and addressed in a piece-meal fashion. The authors recommend a data lifecycle approach and provide a road map, that is more appropriate with the dimensions of Big Data and fits different stages in the analytical workflow.

Critical Appraisal Toolkit (CAT) for assessing multiple types of evidence

PubMed Central

Moralejo, D; Ogunremi, T; Dunn, K

2017-01-01

Healthcare professionals are often expected to critically appraise research evidence in order to make recommendations for practice and policy development. Here we describe the Critical Appraisal Toolkit (CAT) currently used by the Public Health Agency of Canada. The CAT consists of: algorithms to identify the type of study design, three separate tools (for appraisal of analytic studies, descriptive studies and literature reviews), additional tools to support the appraisal process, and guidance for summarizing evidence and drawing conclusions about a body of evidence. Although the toolkit was created to assist in the development of national guidelines related to infection prevention and control, clinicians, policy makers and students can use it to guide appraisal of any health-related quantitative research. Participants in a pilot test completed a total of 101 critical appraisals and found that the CAT was user-friendly and helpful in the process of critical appraisal. Feedback from participants of the pilot test of the CAT informed further revisions prior to its release. The CAT adds to the arsenal of available tools and can be especially useful when the best available evidence comes from non-clinical trials and/or studies with weak designs, where other tools may not be easily applied. PMID:29770086

Milestones on a Shoestring: A Cost-Effective, Semi-automated Implementation of the New ACGME Requirements for Radiology.

PubMed

Schmitt, J Eric; Scanlon, Mary H; Servaes, Sabah; Levin, Dayna; Cook, Tessa S

2015-10-01

The advent of the ACGME's Next Accreditation System represents a significant new challenge for residencies and fellowships, owing to its requirements for more complex and detailed information. We developed a system of online assessment tools to provide comprehensive coverage of the twelve ACGME Milestones and digitized them using freely available cloud-based productivity tools. These tools include a combination of point-of-care procedural assessments, electronic quizzes, online modules, and other data entry forms. Using free statistical analytic tools, we also developed an automated system for management, processing, and data reporting. After one year of use, our Milestones project has resulted in the submission of over 20,000 individual data points. The use of automated statistical methods to generate resident-specific profiles has allowed for dynamic reports of individual residents' progress. These profiles both summarize data and also allow program directors access to more granular information as needed. Informatics-driven strategies for data assessment and processing represent feasible solutions to Milestones assessment and analysis, reducing the potential administrative burden for program directors, residents, and staff. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

In situ monitoring of cocrystals in formulation development using low-frequency Raman spectroscopy.

PubMed

Otaki, Takashi; Tanabe, Yuta; Kojima, Takashi; Miura, Masaru; Ikeda, Yukihiro; Koide, Tatsuo; Fukami, Toshiro

2018-05-05

In recent years, to guarantee a quality-by-design approach to the development of pharmaceutical products, it is important to identify properties of raw materials and excipients in order to determine critical process parameters and critical quality attributes. Feedback obtained from real-time analyses using various process analytical technology (PAT) tools has been actively investigated. In this study, in situ monitoring using low-frequency (LF) Raman spectroscopy (10-200 cm -1 ), which may have higher discriminative ability among polymorphs than near-infrared spectroscopy and conventional Raman spectroscopy (200-1800 cm -1 ), was investigated as a possible application to PAT. This is because LF-Raman spectroscopy obtains information about intermolecular and/or lattice vibrations in the solid state. The monitoring results obtained from Furosemide/Nicotinamide cocrystal indicate that LF-Raman spectroscopy is applicable to in situ monitoring of suspension and fluidized bed granulation processes, and is an effective technique as a PAT tool to detect the conversion risk of cocrystals. LF-Raman spectroscopy is also used as a PAT tool to monitor reactions, crystallizations, and manufacturing processes of drug substances and products. In addition, a sequence of conversion behaviors of Furosemide/Nicotinamide cocrystals was determined by performing in situ monitoring for the first time. Copyright © 2018 Elsevier B.V. All rights reserved.

Use of the MATRIXx Integrated Toolkit on the Microwave Anisotropy Probe Attitude Control System

NASA Technical Reports Server (NTRS)

Ward, David K.; Andrews, Stephen F.; McComas, David C.; ODonnell, James R., Jr.

1999-01-01

Recent advances in analytical software tools allow the analysis, simulation, flight code, and documentation of an algorithm to be generated from a single source, all within one integrated analytical design package. NASA's Microwave Anisotropy Probe project has used one such package, Integrated Systems' MATRIXx suite, in the design of the spacecraft's Attitude Control System. The project's experience with the linear analysis, simulation, code generation, and documentation tools will be presented and compared with more traditional development tools. In particular, the quality of the flight software generated will be examined in detail. Finally, lessons learned on each of the tools will be shared.

Identification of "At Risk" Students Using Learning Analytics: The Ethical Dilemmas of Intervention Strategies in a Higher Education Institution

ERIC Educational Resources Information Center

Lawson, Celeste; Beer, Colin; Rossi, Dolene; Moore, Teresa; Fleming, Julie

2016-01-01

Learning analytics is an emerging field in which sophisticated analytic tools are used to inform and improve learning and teaching. Researchers within a regional university in Australia identified an association between interaction and student success in online courses and subsequently developed a learning analytics system aimed at informing…

Distributed Aerodynamic Sensing and Processing Toolbox

NASA Technical Reports Server (NTRS)

Brenner, Martin; Jutte, Christine; Mangalam, Arun

2011-01-01

A Distributed Aerodynamic Sensing and Processing (DASP) toolbox was designed and fabricated for flight test applications with an Aerostructures Test Wing (ATW) mounted under the fuselage of an F-15B on the Flight Test Fixture (FTF). DASP monitors and processes the aerodynamics with the structural dynamics using nonintrusive, surface-mounted, hot-film sensing. This aerodynamic measurement tool benefits programs devoted to static/dynamic load alleviation, body freedom flutter suppression, buffet control, improvement of aerodynamic efficiency through cruise control, supersonic wave drag reduction through shock control, etc. This DASP toolbox measures local and global unsteady aerodynamic load distribution with distributed sensing. It determines correlation between aerodynamic observables (aero forces) and structural dynamics, and allows control authority increase through aeroelastic shaping and active flow control. It offers improvements in flutter suppression and, in particular, body freedom flutter suppression, as well as aerodynamic performance of wings for increased range/endurance of manned/ unmanned flight vehicles. Other improvements include inlet performance with closed-loop active flow control, and development and validation of advanced analytical and computational tools for unsteady aerodynamics.

A workflow learning model to improve geovisual analytics utility

PubMed Central

Roth, Robert E; MacEachren, Alan M; McCabe, Craig A

2011-01-01

Introduction This paper describes the design and implementation of the G-EX Portal Learn Module, a web-based, geocollaborative application for organizing and distributing digital learning artifacts. G-EX falls into the broader context of geovisual analytics, a new research area with the goal of supporting visually-mediated reasoning about large, multivariate, spatiotemporal information. Because this information is unprecedented in amount and complexity, GIScientists are tasked with the development of new tools and techniques to make sense of it. Our research addresses the challenge of implementing these geovisual analytics tools and techniques in a useful manner. Objectives The objective of this paper is to develop and implement a method for improving the utility of geovisual analytics software. The success of software is measured by its usability (i.e., how easy the software is to use?) and utility (i.e., how useful the software is). The usability and utility of software can be improved by refining the software, increasing user knowledge about the software, or both. It is difficult to achieve transparent usability (i.e., software that is immediately usable without training) of geovisual analytics software because of the inherent complexity of the included tools and techniques. In these situations, improving user knowledge about the software through the provision of learning artifacts is as important, if not more so, than iterative refinement of the software itself. Therefore, our approach to improving utility is focused on educating the user. Methodology The research reported here was completed in two steps. First, we developed a model for learning about geovisual analytics software. Many existing digital learning models assist only with use of the software to complete a specific task and provide limited assistance with its actual application. To move beyond task-oriented learning about software use, we propose a process-oriented approach to learning based on the concept of scientific workflows. Second, we implemented an interface in the G-EX Portal Learn Module to demonstrate the workflow learning model. The workflow interface allows users to drag learning artifacts uploaded to the G-EX Portal onto a central whiteboard and then annotate the workflow using text and drawing tools. Once completed, users can visit the assembled workflow to get an idea of the kind, number, and scale of analysis steps, view individual learning artifacts associated with each node in the workflow, and ask questions about the overall workflow or individual learning artifacts through the associated forums. An example learning workflow in the domain of epidemiology is provided to demonstrate the effectiveness of the approach. Results/Conclusions In the context of geovisual analytics, GIScientists are not only responsible for developing software to facilitate visually-mediated reasoning about large and complex spatiotemporal information, but also for ensuring that this software works. The workflow learning model discussed in this paper and demonstrated in the G-EX Portal Learn Module is one approach to improving the utility of geovisual analytics software. While development of the G-EX Portal Learn Module is ongoing, we expect to release the G-EX Portal Learn Module by Summer 2009. PMID:21983545

A workflow learning model to improve geovisual analytics utility.

PubMed

Roth, Robert E; Maceachren, Alan M; McCabe, Craig A

2009-01-01

INTRODUCTION: This paper describes the design and implementation of the G-EX Portal Learn Module, a web-based, geocollaborative application for organizing and distributing digital learning artifacts. G-EX falls into the broader context of geovisual analytics, a new research area with the goal of supporting visually-mediated reasoning about large, multivariate, spatiotemporal information. Because this information is unprecedented in amount and complexity, GIScientists are tasked with the development of new tools and techniques to make sense of it. Our research addresses the challenge of implementing these geovisual analytics tools and techniques in a useful manner. OBJECTIVES: The objective of this paper is to develop and implement a method for improving the utility of geovisual analytics software. The success of software is measured by its usability (i.e., how easy the software is to use?) and utility (i.e., how useful the software is). The usability and utility of software can be improved by refining the software, increasing user knowledge about the software, or both. It is difficult to achieve transparent usability (i.e., software that is immediately usable without training) of geovisual analytics software because of the inherent complexity of the included tools and techniques. In these situations, improving user knowledge about the software through the provision of learning artifacts is as important, if not more so, than iterative refinement of the software itself. Therefore, our approach to improving utility is focused on educating the user. METHODOLOGY: The research reported here was completed in two steps. First, we developed a model for learning about geovisual analytics software. Many existing digital learning models assist only with use of the software to complete a specific task and provide limited assistance with its actual application. To move beyond task-oriented learning about software use, we propose a process-oriented approach to learning based on the concept of scientific workflows. Second, we implemented an interface in the G-EX Portal Learn Module to demonstrate the workflow learning model. The workflow interface allows users to drag learning artifacts uploaded to the G-EX Portal onto a central whiteboard and then annotate the workflow using text and drawing tools. Once completed, users can visit the assembled workflow to get an idea of the kind, number, and scale of analysis steps, view individual learning artifacts associated with each node in the workflow, and ask questions about the overall workflow or individual learning artifacts through the associated forums. An example learning workflow in the domain of epidemiology is provided to demonstrate the effectiveness of the approach. RESULTS/CONCLUSIONS: In the context of geovisual analytics, GIScientists are not only responsible for developing software to facilitate visually-mediated reasoning about large and complex spatiotemporal information, but also for ensuring that this software works. The workflow learning model discussed in this paper and demonstrated in the G-EX Portal Learn Module is one approach to improving the utility of geovisual analytics software. While development of the G-EX Portal Learn Module is ongoing, we expect to release the G-EX Portal Learn Module by Summer 2009.

CI-KNOW: Cyberinfrastructure Knowledge Networks on the Web. A Social Network Enabled Recommender System for Locating Resources in Cyberinfrastructures

NASA Astrophysics Data System (ADS)

Green, H. D.; Contractor, N. S.; Yao, Y.

2006-12-01

A knowledge network is a multi-dimensional network created from the interactions and interconnections among the scientists, documents, data, analytic tools, and interactive collaboration spaces (like forums and wikis) associated with a collaborative environment. CI-KNOW is a suite of software tools that leverages automated data collection, social network theories, analysis techniques and algorithms to infer an individual's interests and expertise based on their interactions and activities within a knowledge network. The CI-KNOW recommender system mines the knowledge network associated with a scientific community's use of cyberinfrastructure tools and uses relational metadata to record connections among entities in the knowledge network. Recent developments in social network theories and methods provide the backbone for a modular system that creates recommendations from relational metadata. A network navigation portlet allows users to locate colleagues, documents, data or analytic tools in the knowledge network and to explore their networks through a visual, step-wise process. An internal auditing portlet offers administrators diagnostics to assess the growth and health of the entire knowledge network. The first instantiation of the prototype CI-KNOW system is part of the Environmental Cyberinfrastructure Demonstration project at the National Center for Supercomputing Applications, which supports the activities of hydrologic and environmental science communities (CLEANER and CUAHSI) under the umbrella of the WATERS network environmental observatory planning activities (http://cleaner.ncsa.uiuc.edu). This poster summarizes the key aspects of the CI-KNOW system, highlighting the key inputs, calculation mechanisms, and output modalities.

Graphical Descriptives: A Way to Improve Data Transparency and Methodological Rigor in Psychology.

PubMed

Tay, Louis; Parrigon, Scott; Huang, Qiming; LeBreton, James M

2016-09-01

Several calls have recently been issued to the social sciences for enhanced transparency of research processes and enhanced rigor in the methodological treatment of data and data analytics. We propose the use of graphical descriptives (GDs) as one mechanism for responding to both of these calls. GDs provide a way to visually examine data. They serve as quick and efficient tools for checking data distributions, variable relations, and the potential appropriateness of different statistical analyses (e.g., do data meet the minimum assumptions for a particular analytic method). Consequently, we believe that GDs can promote increased transparency in the journal review process, encourage best practices for data analysis, and promote a more inductive approach to understanding psychological data. We illustrate the value of potentially including GDs as a step in the peer-review process and provide a user-friendly online resource (www.graphicaldescriptives.org) for researchers interested in including data visualizations in their research. We conclude with suggestions on how GDs can be expanded and developed to enhance transparency. © The Author(s) 2016.

Assessment of infant formula quality and composition using Vis-NIR, MIR and Raman process analytical technologies.

PubMed

Wang, Xiao; Esquerre, Carlos; Downey, Gerard; Henihan, Lisa; O'Callaghan, Donal; O'Donnell, Colm

2018-06-01

In this study, visible and near-infrared (Vis-NIR), mid-infrared (MIR) and Raman process analytical technologies were investigated for assessment of infant formula quality and compositional parameters namely preheat temperature, storage temperature, storage time, fluorescence of advanced Maillard products and soluble tryptophan (FAST) index, soluble protein, fat and surface free fat (SFF) content. PLS-DA models developed using spectral data with appropriate data pre-treatment and significant variables selected using Martens' uncertainty test had good accuracy for the discrimination of preheat temperature (92.3-100%) and storage temperature (91.7-100%). The best PLS regression models developed yielded values for the ratio of prediction error to deviation (RPD) of 3.6-6.1, 2.1-2.7, 1.7-2.9, 1.6-2.6 and 2.5-3.0 for storage time, FAST index, soluble protein, fat and SFF content prediction respectively. Vis-NIR, MIR and Raman were demonstrated to be potential PAT tools for process control and quality assurance applications in infant formula and dairy ingredient manufacture. Copyright © 2018 Elsevier B.V. All rights reserved.

Feasibility study on the use of groupware support for NASA source evaluation boards

NASA Technical Reports Server (NTRS)

Bishop, Peter C.; Yoes, Cissy

1991-01-01

Groupware is a class of computer based systems that support groups engaged in a common task (or goal) and that provide an interface to a shared environment. A potential application for groupware is the source evaluation board (SEB) process used in the procurement of government contracts. This study was undertaken to (1) identify parts of the SEB process which are candidates for groupware supports; and (2) identify tools which could be used to support the candidate process. Two processes of the SEB were identified as good candidates for groupware support: (1) document generation - a coordination and communication process required to present and document the findings of an SEB; and (2) group decision making - a highly analytical and integrative decision process requiring a clear and supportable outcome.

Emergent FDA biodefense issues for microarray technology: process analytical technology.

PubMed

Weinberg, Sandy

2004-11-01

A successful biodefense strategy relies upon any combination of four approaches. A nation can protect its troops and citizenry first by advanced mass vaccination, second, by responsive ring vaccination, and third, by post-exposure therapeutic treatment (including vaccine therapies). Finally, protection can be achieved by rapid detection followed by exposure limitation (suites and air filters) or immediate treatment (e.g., antibiotics, rapid vaccines and iodine pills). All of these strategies rely upon or are enhanced by microarray technologies. Microarrays can be used to screen, engineer and test vaccines. They are also used to construct early detection tools. While effective biodefense utilizes a variety of tactical tools, microarray technology is a valuable arrow in that quiver.

Current and future bioanalytical approaches for stroke assessment.

PubMed

Pullagurla, Swathi R; Baird, Alison E; Adamski, Mateusz G; Soper, Steven A

2015-01-01

Efforts are underway to develop novel platforms for stroke diagnosis to meet the criteria for effective treatment within the narrow time window mandated by the FDA-approved therapeutic (<3 h). Blood-based biomarkers could be used for rapid stroke diagnosis and coupled with new analytical tools, could serve as an attractive platform for managing stroke-related diseases. In this review, we will discuss the physiological processes associated with stroke and current diagnostic tools as well as their associated shortcomings. We will then review information on blood-based biomarkers and various detection technologies. In particular, point of care testing that permits small blood volumes required for the analysis and rapid turn-around time measurements of multiple markers will be presented.

Sustainability Tools Inventory Initial Gap Analysis

EPA Science Inventory

This report identifies a suite of tools that address a comprehensive set of community sustainability concerns. The objective is to discover whether "gaps" exist in the tool suite’s analytic capabilities. These tools address activities that significantly influence resource consu...

New Tools to Prepare ACE Cross-section Files for MCNP Analytic Test Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Forrest B.

Monte Carlo calculations using one-group cross sections, multigroup cross sections, or simple continuous energy cross sections are often used to: (1) verify production codes against known analytical solutions, (2) verify new methods and algorithms that do not involve detailed collision physics, (3) compare Monte Carlo calculation methods with deterministic methods, and (4) teach fundamentals to students. In this work we describe 2 new tools for preparing the ACE cross-section files to be used by MCNP ® for these analytic test problems, simple_ace.pl and simple_ace_mg.pl.

Innovations in coating technology.

PubMed

Behzadi, Sharareh S; Toegel, Stefan; Viernstein, Helmut

2008-01-01

Despite representing one of the oldest pharmaceutical techniques, coating of dosage forms is still frequently used in pharmaceutical manufacturing. The aims of coating range from simply masking the taste or odour of drugs to the sophisticated controlling of site and rate of drug release. The high expectations for different coating technologies have required great efforts regarding the development of reproducible and controllable production processes. Basically, improvements in coating methods have focused on particle movement, spraying systems, and air and energy transport. Thereby, homogeneous distribution of coating material and increased drying efficiency should be accomplished in order to achieve high end product quality. Moreover, given the claim of the FDA to design the end product quality already during the manufacturing process (Quality by Design), the development of analytical methods for the analysis, management and control of coating processes has attracted special attention during recent years. The present review focuses on recent patents claiming improvements in pharmaceutical coating technology and intends to first familiarize the reader with the available procedures and to subsequently explain the application of different analytical tools. Aiming to structure this comprehensive field, coating technologies are primarily divided into pan and fluidized bed coating methods. Regarding pan coating procedures, pans rotating around inclined, horizontal and vertical axes are reviewed separately. On the other hand, fluidized bed technologies are subdivided into those involving fluidized and spouted beds. Then, continuous processing techniques and improvements in spraying systems are discussed in dedicated chapters. Finally, currently used analytical methods for the understanding and management of coating processes are reviewed in detail in the last section of the review.

Facilitating participatory multilevel decision-making by using interactive mental maps.

PubMed

Pfeiffer, Constanze; Glaser, Stephanie; Vencatesan, Jayshree; Schliermann-Kraus, Elke; Drescher, Axel; Glaser, Rüdiger

2008-11-01

Participation of citizens in political, economic or social decisions is increasingly recognized as a precondition to foster sustainable development processes. Since spatial information is often important during planning and decision making, participatory mapping gains in popularity. However, little attention has been paid to the fact that information must be presented in a useful way to reach city planners and policy makers. Above all, the importance of visualisation tools to support collaboration, analytical reasoning, problem solving and decision-making in analysing and planning processes has been underestimated. In this paper, we describe how an interactive mental map tool has been developed in a highly interdisciplinary disaster management project in Chennai, India. We moved from a hand drawn mental maps approach to an interactive mental map tool. This was achieved by merging socio-economic and geospatial data on infrastructure, local perceptions, coping and adaptation strategies with remote sensing data and modern technology of map making. This newly developed interactive mapping tool allowed for insights into different locally-constructed realities and facilitated the communication of results to the wider public and respective policy makers. It proved to be useful in visualising information and promoting participatory decision-making processes. We argue that the tool bears potential also for health research projects. The interactive mental map can be used to spatially and temporally assess key health themes such as availability of, and accessibility to, existing health care services, breeding sites of disease vectors, collection and storage of water, waste disposal, location of public toilets or defecation sites.

Engine Icing Data - An Analytics Approach

NASA Technical Reports Server (NTRS)

Fitzgerald, Brooke A.; Flegel, Ashlie B.

2017-01-01

Engine icing researchers at the NASA Glenn Research Center use the Escort data acquisition system in the Propulsion Systems Laboratory (PSL) to generate and collect a tremendous amount of data every day. Currently these researchers spend countless hours processing and formatting their data, selecting important variables, and plotting relationships between variables, all by hand, generally analyzing data in a spreadsheet-style program (such as Microsoft Excel). Though spreadsheet-style analysis is familiar and intuitive to many, processing data in spreadsheets is often unreproducible and small mistakes are easily overlooked. Spreadsheet-style analysis is also time inefficient. The same formatting, processing, and plotting procedure has to be repeated for every dataset, which leads to researchers performing the same tedious data munging process over and over instead of making discoveries within their data. This paper documents a data analysis tool written in Python hosted in a Jupyter notebook that vastly simplifies the analysis process. From the file path of any folder containing time series datasets, this tool batch loads every dataset in the folder, processes the datasets in parallel, and ingests them into a widget where users can search for and interactively plot subsets of columns in a number of ways with a click of a button, easily and intuitively comparing their data and discovering interesting dynamics. Furthermore, comparing variables across data sets and integrating video data (while extremely difficult with spreadsheet-style programs) is quite simplified in this tool. This tool has also gathered interest outside the engine icing branch, and will be used by researchers across NASA Glenn Research Center. This project exemplifies the enormous benefit of automating data processing, analysis, and visualization, and will help researchers move from raw data to insight in a much smaller time frame.

Nuclear magnetic resonance and high-performance liquid chromatography techniques for the characterization of bioactive compounds from Humulus lupulus L. (hop).

PubMed

Bertelli, Davide; Brighenti, Virginia; Marchetti, Lucia; Reik, Anna; Pellati, Federica

2018-06-01

Humulus lupulus L. (hop) represents one of the most cultivated crops, it being a key ingredient in the brewing process. Many health-related properties have been described for hop extracts, making this plant gain more interest in the field of pharmaceutical and nutraceutical research. Among the analytical tools available for the phytochemical characterization of plant extracts, quantitative nuclear magnetic resonance (qNMR) represents a new and powerful technique. In this ambit, the present study was aimed at the development of a new, simple, and efficient qNMR method for the metabolite fingerprinting of bioactive compounds in hop cones, taking advantage of the novel ERETIC 2 tool. To the best of our knowledge, this is the first attempt to apply this method to complex matrices of natural origin, such as hop extracts. The qNMR method set up in this study was applied to the quantification of both prenylflavonoids and bitter acids in eight hop cultivars. The performance of this analytical method was compared with that of HPLC-UV/DAD, which represents the most frequently used technique in the field of natural product analysis. The quantitative data obtained for hop samples by means of the two aforementioned techniques highlighted that the amount of bioactive compounds was slightly higher when qNMR was applied, although the order of magnitude of the values was the same. The accuracy of qNMR was comparable to that of the chromatographic method, thus proving to be a reliable tool for the analysis of these secondary metabolites in hop extracts. Graphical abstract Graphical abstract related to the extraction and analytical methods applied in this work for the analysis of bioactive compounds in Humulus lupulus L. (hop) cones.

Learner Dashboards a Double-Edged Sword? Students' Sense-Making of a Collaborative Critical Reading and Learning Analytics Environment for Fostering 21st-Century Literacies

ERIC Educational Resources Information Center

Pei-Ling Tan, Jennifer; Koh, Elizabeth; Jonathan, Christin; Yang, Simon

2017-01-01

The affordances of learning analytics (LA) tools and solutions are being increasingly harnessed for enhancing 21st century pedagogical and learning strategies and outcomes. However, use cases and empirical understandings of students' experiences with LA tools and environments aimed at fostering 21st century literacies, especially in the K-12…

Visual Information for the Desktop, version 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

2006-03-29

VZIN integrates visual analytics capabilities into popular desktop tools to aid a user in searching and understanding an information space. VZIN allows users to Drag-Drop-Visualize-Explore-Organize information within tools such as Microsoft Office, Windows Explorer, Excel, and Outlook. VZIN is tailorable to specific client or industry requirements. VZIN follows the desktop metaphors so that advanced analytical capabilities are available with minimal user training.

Commentary on "Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning"

ERIC Educational Resources Information Center

Teplovs, Chris

2015-01-01

This commentary reflects on the contributions to learning analytics and theory by a paper that describes how multiple theoretical frameworks were woven together to inform the creation of a new, automated discourse analysis tool. The commentary highlights the contributions of the original paper, provides some alternative approaches, and touches on…

Real-Time Process Analytics in Emergency Healthcare.

PubMed

Koufi, Vassiliki; Malamateniou, Flora; Prentza, Adrianna; Vassilacopoulos, George

2017-01-01

Emergency medical systems (EMS) are considered to be amongst the most crucial systems as they involve a variety of activities which are performed from the time of a call to an ambulance service till the time of patient's discharge from the emergency department of a hospital. These activities are closely interrelated so that collaboration and coordination becomes a vital issue for patients and for emergency healthcare service performance. The utilization of standard workflow technology in the context of Service Oriented Architecture can provide an appropriate technological infrastructure for defining and automating EMS processes that span organizational boundaries so that to create and empower collaboration and coordination among the participating organizations. In such systems, the utilization of leading-edge analytics tools can prove important as it can facilitate real-time extraction and visualization of useful insights from the mountains of generated data pertaining to emergency case management. This paper presents a framework which provides healthcare professionals with just-in-time insight within and across emergency healthcare processes by performing real-time analysis on process-related data in order to better support decision making and identify potential critical risks that may affect the provision of emergency care to patients.

An Analytic Network Process approach for the environmental aspect selection problem — A case study for a hand blender

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bereketli Zafeirakopoulos, Ilke, E-mail: ibereketli@gsu.edu.tr; Erol Genevois, Mujde, E-mail: merol@gsu.edu.tr

Life Cycle Assessment is a tool to assess, in a systematic way, the environmental aspects and its potential environmental impacts and resources used throughout a product's life cycle. It is widely accepted and considered as one of the most powerful tools to support decision-making processes used in ecodesign and sustainable production in order to learn about the most problematic parts and life cycle phases of a product and to have a projection for future improvements. However, since Life Cycle Assessment is a cost and time intensive method, companies do not intend to carry out a full version of it, exceptmore » for large corporate ones. Especially for small and medium sized enterprises, which do not have enough budget for and knowledge on sustainable production and ecodesign approaches, focusing only on the most important possible environmental aspect is unavoidable. In this direction, finding the right environmental aspect to work on is crucial for the companies. In this study, a multi-criteria decision-making methodology, Analytic Network Process is proposed to select the most relevant environmental aspect. The proposed methodology aims at providing a simplified environmental assessment to producers. It is applied for a hand blender, which is a member of the Electrical and Electronic Equipment family. The decision criteria for the environmental aspects and relations of dependence are defined. The evaluation is made by the Analytic Network Process in order to create a realistic approach to inter-dependencies among the criteria. The results are computed via the Super Decisions software. Finally, it is observed that the procedure is completed in less time, with less data, with less cost and in a less subjective way than conventional approaches. - Highlights: • We present a simplified environmental assessment methodology to support LCA. • ANP is proposed to select the most relevant environmental aspect. • ANP deals well with the interdependencies between aspects and impacts. • The methodology is less subjective, less complicated, and less time–money consuming. • The proposed methodology is suitable for use by SMEs.« less

IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics

PubMed Central

2016-01-01

Background We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS). The latest entry of Watson Analytics into the field of analytical software products provides users with enhanced functions that are not available in many existing programs. For example, Watson Analytics automatically analyzes datasets, examines data quality, and determines the optimal statistical approach. Users can request exploratory, predictive, and visual analytics. Using natural language processing (NLP), users are able to submit additional questions for analyses in a quick response format. This analytical package is available free to academic institutions (faculty and students) that plan to use the tools for noncommercial purposes. Objective To report the features of IBMWA and discuss how this software subjectively and objectively compares to other data mining programs. Methods The salient features of the IBMWA program were examined and compared with other common analytical platforms, using validated health datasets. Results Using a validated dataset, IBMWA delivered similar predictions compared with several commercial and open source data mining software applications. The visual analytics generated by IBMWA were similar to results from programs such as Microsoft Excel and Tableau Software. In addition, assistance with data preprocessing and data exploration was an inherent component of the IBMWA application. Sensitivity and specificity were not included in the IBMWA predictive analytics results, nor were odds ratios, confidence intervals, or a confusion matrix. Conclusions IBMWA is a new alternative for data analytics software that automates descriptive, predictive, and visual analytics. This program is very user-friendly but requires data preprocessing, statistical conceptual understanding, and domain expertise. PMID:27729304

IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics.

PubMed

Hoyt, Robert Eugene; Snider, Dallas; Thompson, Carla; Mantravadi, Sarita

2016-10-11

We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS). The latest entry of Watson Analytics into the field of analytical software products provides users with enhanced functions that are not available in many existing programs. For example, Watson Analytics automatically analyzes datasets, examines data quality, and determines the optimal statistical approach. Users can request exploratory, predictive, and visual analytics. Using natural language processing (NLP), users are able to submit additional questions for analyses in a quick response format. This analytical package is available free to academic institutions (faculty and students) that plan to use the tools for noncommercial purposes. To report the features of IBMWA and discuss how this software subjectively and objectively compares to other data mining programs. The salient features of the IBMWA program were examined and compared with other common analytical platforms, using validated health datasets. Using a validated dataset, IBMWA delivered similar predictions compared with several commercial and open source data mining software applications. The visual analytics generated by IBMWA were similar to results from programs such as Microsoft Excel and Tableau Software. In addition, assistance with data preprocessing and data exploration was an inherent component of the IBMWA application. Sensitivity and specificity were not included in the IBMWA predictive analytics results, nor were odds ratios, confidence intervals, or a confusion matrix. IBMWA is a new alternative for data analytics software that automates descriptive, predictive, and visual analytics. This program is very user-friendly but requires data preprocessing, statistical conceptual understanding, and domain expertise.

Verification of out-of-control situations detected by "average of normal" approach.

PubMed

Liu, Jiakai; Tan, Chin Hon; Loh, Tze Ping; Badrick, Tony

2016-11-01

"Average of normal" (AoN) or "moving average" is increasingly used as an adjunct quality control tool in laboratory practice. Little guidance exists on how to verify if an out-of-control situation in the AoN chart is due to a shift in analytical performance, or underlying patient characteristics. Through simulation based on clinical data, we examined 1) the location of the last apparently stable period in the AoN control chart after an analytical shift, and 2) an approach to verify if the observed shift is related to an analytical shift by repeat testing of archived patient samples from the stable period for 21 common analytes. The number of blocks of results to look back for the stable period increased with the duration of the analytical shift, and was larger when smaller AoN block sizes were used. To verify an analytical shift, 3 archived samples from the analytically stable period should be retested. In particular, the process is deemed to have shifted if a difference of >2 analytical standard deviations (i.e. 1:2s rejection rule) between the original and retested results are observed in any of the 3 samples produced. The probability of Type-1 error (i.e., false rejection) and power (i.e., detecting true analytical shift) of this rule are <0.1 and >0.9, respectively. The use of appropriately archived patient samples to verify an apparent analytical shift is preferred to quality control materials. Nonetheless, the above findings may also apply to quality control materials, barring matrix effects. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Analysis of Decisions Made Using the Analytic Hierarchy Process

DTIC Science & Technology

2013-09-01

country petroleum pipelines (Dey, 2003), deciding how best to manage U.S. watersheds (De Steiguer, Duberstein, and Lopes, 2003), and the U. S. Army...many benefits to its use. Primarily these fall under the heading of managing chaos. Specifically, the AHP is a tool that can be used to simplify and...originally. The commonly used scenario is this: the waiter asks if you want chicken or fish, and you reply fish. The waiter then remembers that steak is

The neuronal differentiation process involves a series of antioxidant proteins.

PubMed

Oh, J-E; Karlmark Raja, K; Shin, J-H; Hengstschläger, M; Pollak, A; Lubec, G

2005-11-01

Involvement of individual antioxidant proteins (AOXP) and antioxidants in the differentiation process has been already reported. A systematic search strategy for detecting differentially regulated AOXP in neuronal differentiation, however, has not been published so far. The aim of this study was to provide an analytical tool identifying AOXP and to generate a differentiation-related AOXP expressional pattern. The undifferentiated N1E-115 neuroblastoma cell line was switched into a neuronal phenotype by DMSO treatment and used for proteomic experiments: We used two-dimensional gel electrophoresis followed by unambiguous mass spectrometrical (MALDI-TOF-TOF) identification of proteins to generate a map of AOXP. 16 AOXP were unambiguously determined in both cell lines; catalase, thioredoxin domain-containing protein 4 and hypothetical glutaredoxin/glutathione S-transferase C terminus-containing protein were detectable in the undifferentiated cells only. Five AOXP were observed in both, undifferentiated and differentiated cells and thioredoxin, thioredoxin-like protein p19, thioredoxin reductase 1, superoxide dismutases (Mn and Cu-Zn), glutathione synthetase, glutathione S-transferase P1 and Mu1 were detected in differentiated cells exclusively. Herein a differential expressional pattern is presented that reveals so far unpublished antioxidant principles involved in neuronal differentiation by a protein chemical approach, unambiguously identifying AOXP. This finding not only shows concomitant determination of AOXP but also serves as an analytical tool and forms the basis for design of future studies addressing AOXP and differentiation per se.

Nonlinear Growth Curves in Developmental Research

PubMed Central

Grimm, Kevin J.; Ram, Nilam; Hamagami, Fumiaki

2011-01-01

Developmentalists are often interested in understanding change processes and growth models are the most common analytic tool for examining such processes. Nonlinear growth curves are especially valuable to developmentalists because the defining characteristics of the growth process such as initial levels, rates of change during growth spurts, and asymptotic levels can be estimated. A variety of growth models are described beginning with the linear growth model and moving to nonlinear models of varying complexity. A detailed discussion of nonlinear models is provided, highlighting the added insights into complex developmental processes associated with their use. A collection of growth models are fit to repeated measures of height from participants of the Berkeley Growth and Guidance Studies from early childhood through adulthood. PMID:21824131

Rapid determination of major bioactive isoflavonoid compounds during the extraction process of kudzu (Pueraria lobata) by near-infrared transmission spectroscopy.

PubMed

Wang, Pei; Zhang, Hui; Yang, Hailong; Nie, Lei; Zang, Hengchang

2015-02-25

Near-infrared (NIR) spectroscopy has been developed into an indispensable tool for both academic research and industrial quality control in a wide field of applications. The feasibility of NIR spectroscopy to monitor the concentration of puerarin, daidzin, daidzein and total isoflavonoid (TIF) during the extraction process of kudzu (Pueraria lobata) was verified in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and derivative. Partial least square regression (PLSR) was used to establish calibration models. Three different variable selection methods, including correlation coefficient method, interval partial least squares (iPLS), and successive projections algorithm (SPA) were performed and compared with models based on all of the variables. The results showed that the approach was very efficient and environmentally friendly for rapid determination of the four quality indices (QIs) in the kudzu extraction process. This method established may have the potential to be used as a process analytical technological (PAT) tool in the future. Copyright © 2014 Elsevier B.V. All rights reserved.

An interactive website for analytical method comparison and bias estimation.

PubMed

Bahar, Burak; Tuncel, Ayse F; Holmes, Earle W; Holmes, Daniel T

2017-12-01

Regulatory standards mandate laboratories to perform studies to ensure accuracy and reliability of their test results. Method comparison and bias estimation are important components of these studies. We developed an interactive website for evaluating the relative performance of two analytical methods using R programming language tools. The website can be accessed at https://bahar.shinyapps.io/method_compare/. The site has an easy-to-use interface that allows both copy-pasting and manual entry of data. It also allows selection of a regression model and creation of regression and difference plots. Available regression models include Ordinary Least Squares, Weighted-Ordinary Least Squares, Deming, Weighted-Deming, Passing-Bablok and Passing-Bablok for large datasets. The server processes the data and generates downloadable reports in PDF or HTML format. Our website provides clinical laboratories a practical way to assess the relative performance of two analytical methods. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

From Theory Use to Theory Building in Learning Analytics: A Commentary on "Learning Analytics to Support Teachers during Synchronous CSCL"

ERIC Educational Resources Information Center

Chen, Bodong

2015-01-01

In this commentary on Van Leeuwen (2015, this issue), I explore the relation between theory and practice in learning analytics. Specifically, I caution against adhering to one specific theoretical doctrine while ignoring others, suggest deeper applications of cognitive load theory to understanding teaching with analytics tools, and comment on…

Shared decision-making – transferring research into practice: the Analytic Hierarchy Process (AHP)

PubMed Central

Dolan, James G.

2008-01-01

Objective To illustrate how the Analytic Hierarchy Process (AHP) can be used to promote shared decision-making and enhance clinician-patient communication. Methods Tutorial review. Results The AHP promotes shared decision making by creating a framework that is used to define the decision, summarize the information available, prioritize information needs, elicit preferences and values, and foster meaningful communication among decision stakeholders. Conclusions The AHP and related multi-criteria methods have the potential for improving the quality of clinical decisions and overcoming current barriers to implementing shared decision making in busy clinical settings. Further research is needed to determine the best way to implement these tools and to determine their effectiveness. Practice Implications Many clinical decisions involve preference-based trade-offs between competing risks and benefits. The AHP is a well-developed method that provides a practical approach for improving patient-provider communication, clinical decision-making, and the quality of patient care in these situations. PMID:18760559

Nanopipettes as Monitoring Probes for the Single Living Cell: State of the Art and Future Directions in Molecular Biology.

PubMed

Bulbul, Gonca; Chaves, Gepoliano; Olivier, Joseph; Ozel, Rifat Emrah; Pourmand, Nader

2018-06-06

Examining the behavior of a single cell within its natural environment is valuable for understanding both the biological processes that control the function of cells and how injury or disease lead to pathological change of their function. Single-cell analysis can reveal information regarding the causes of genetic changes, and it can contribute to studies on the molecular basis of cell transformation and proliferation. By contrast, whole tissue biopsies can only yield information on a statistical average of several processes occurring in a population of different cells. Electrowetting within a nanopipette provides a nanobiopsy platform for the extraction of cellular material from single living cells. Additionally, functionalized nanopipette sensing probes can differentiate analytes based on their size, shape or charge density, making the technology uniquely suited to sensing changes in single-cell dynamics. In this review, we highlight the potential of nanopipette technology as a non-destructive analytical tool to monitor single living cells, with particular attention to integration into applications in molecular biology.

QFD-ANP Approach for the Conceptual Design of Research Vessels: A Case Study

NASA Astrophysics Data System (ADS)

Venkata Subbaiah, Kambagowni; Yeshwanth Sai, Koneru; Suresh, Challa

2016-10-01

Conceptual design is a subset of concept art wherein a new idea of product is created instead of a visual representation which would directly be used in a final product. The purpose is to understand the needs of conceptual design which are being used in engineering designs and to clarify the current conceptual design practice. Quality function deployment (QFD) is a customer oriented design approach for developing new or improved products and services to enhance customer satisfaction. House of quality (HOQ) has been traditionally used as planning tool of QFD which translates customer requirements (CRs) into design requirements (DRs). Factor analysis is carried out in order to reduce the CR portions of HOQ. The analytical hierarchical process is employed to obtain the priority ratings of CR's which are used in constructing HOQ. This paper mainly discusses about the conceptual design of an oceanographic research vessel using analytical network process (ANP) technique. Finally the QFD-ANP integrated methodology helps to establish the importance ratings of DRs.

Multi-disciplinary optimization of aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1990-01-01

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Multidisciplinary optimization of aeroservoelastic systems using reduced-size models

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1992-01-01

Efficient analytical and computational tools for simultaneous optimal design of the structural and control components of aeroservoelastic systems are presented. The optimization objective is to achieve aircraft performance requirements and sufficient flutter and control stability margins with a minimal weight penalty and without violating the design constraints. Analytical sensitivity derivatives facilitate an efficient optimization process which allows a relatively large number of design variables. Standard finite element and unsteady aerodynamic routines are used to construct a modal data base. Minimum State aerodynamic approximations and dynamic residualization methods are used to construct a high accuracy, low order aeroservoelastic model. Sensitivity derivatives of flutter dynamic pressure, control stability margins and control effectiveness with respect to structural and control design variables are presented. The performance requirements are utilized by equality constraints which affect the sensitivity derivatives. A gradient-based optimization algorithm is used to minimize an overall cost function. A realistic numerical example of a composite wing with four controls is used to demonstrate the modeling technique, the optimization process, and their accuracy and efficiency.

Toward best practice: leveraging the electronic patient record as a clinical data warehouse.

PubMed

Ledbetter, C S; Morgan, M W

2001-01-01

Automating clinical and administrative processes via an electronic patient record (EPR) gives clinicians the point-of-care tools they need to deliver better patient care. However, to improve clinical practice as a whole and then evaluate it, healthcare must go beyond basic automation and convert EPR data into aggregated, multidimensional information. Unfortunately, few EPR systems have the established, powerful analytical clinical data warehouses (CDWs) required for this conversion. This article describes how an organization can support best practice by leveraging a CDW that is fully integrated into its EPR and clinical decision support (CDS) system. The article (1) discusses the requirements for comprehensive CDS, including on-line analytical processing (OLAP) of data at both transactional and aggregate levels, (2) suggests that the transactional data acquired by an OLTP EPR system must be remodeled to support retrospective, population-based, aggregate analysis of those data, and (3) concludes that this aggregate analysis is best provided by a separate CDW system.

Microgenetic Learning Analytics Methods: Workshop Report

ERIC Educational Resources Information Center

Aghababyan, Ani; Martin, Taylor; Janisiewicz, Philip; Close, Kevin

2016-01-01

Learning analytics is an emerging discipline and, as such, benefits from new tools and methodological approaches. This work reviews and summarizes our workshop on microgenetic data analysis techniques using R, held at the second annual Learning Analytics Summer Institute in Cambridge, Massachusetts, on 30 June 2014. Specifically, this paper…

IBM’s Health Analytics and Clinical Decision Support

PubMed Central

Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

2014-01-01

Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

Sense-making for intelligence analysis on social media data

NASA Astrophysics Data System (ADS)

Pritzkau, Albert

2016-05-01

Social networks, in particular online social networks as a subset, enable the analysis of social relationships which are represented by interaction, collaboration, or other sorts of influence between people. Any set of people and their internal social relationships can be modelled as a general social graph. These relationships are formed by exchanging emails, making phone calls, or carrying out a range of other activities that build up the network. This paper presents an overview of current approaches to utilizing social media as a ubiquitous sensor network in the context of national and global security. Exploitation of social media is usually an interdisciplinary endeavour, in which the relevant technologies and methods are identified and linked in order ultimately demonstrate selected applications. Effective and efficient intelligence is usually accomplished in a combined human and computer effort. Indeed, the intelligence process heavily depends on combining a human's flexibility, creativity, and cognitive ability with the bandwidth and processing power of today's computers. To improve the usability and accuracy of the intelligence analysis we will have to rely on data-processing tools at the level of natural language. Especially the collection and transformation of unstructured data into actionable, structured data requires scalable computational algorithms ranging from Artificial Intelligence, via Machine Learning, to Natural Language Processing (NLP). To support intelligence analysis on social media data, social media analytics is concerned with developing and evaluating computational tools and frameworks to collect, monitor, analyze, summarize, and visualize social media data. Analytics methods are employed to extract of significant patterns that might not be obvious. As a result, different data representations rendering distinct aspects of content and interactions serve as a means to adapt the focus of the intelligence analysis to specific information requests.

Process defects and in situ monitoring methods in metal powder bed fusion: a review

NASA Astrophysics Data System (ADS)

Grasso, Marco; Colosimo, Bianca Maria

2017-04-01

Despite continuous technological enhancements of metal Additive Manufacturing (AM) systems, the lack of process repeatability and stability still represents a barrier for the industrial breakthrough. The most relevant metal AM applications currently involve industrial sectors (e.g. aerospace and bio-medical) where defects avoidance is fundamental. Because of this, there is the need to develop novel in situ monitoring tools able to keep under control the stability of the process on a layer-by-layer basis, and to detect the onset of defects as soon as possible. On the one hand, AM systems must be equipped with in situ sensing devices able to measure relevant quantities during the process, a.k.a. process signatures. On the other hand, in-process data analytics and statistical monitoring techniques are required to detect and localize the defects in an automated way. This paper reviews the literature and the commercial tools for in situ monitoring of powder bed fusion (PBF) processes. It explores the different categories of defects and their main causes, the most relevant process signatures and the in situ sensing approaches proposed so far. Particular attention is devoted to the development of automated defect detection rules and the study of process control strategies, which represent two critical fields for the development of future smart PBF systems.