Methodological quality and descriptive characteristics of prosthodontic-related systematic reviews.

PubMed

Aziz, T; Compton, S; Nassar, U; Matthews, D; Ansari, K; Flores-Mir, C

2013-04-01

Ideally, healthcare systematic reviews (SRs) should be beneficial to practicing professionals in making evidence-based clinical decisions. However, the conclusions drawn from SRs are directly related to the quality of the SR and of the included studies. The aim was to investigate the methodological quality and key descriptive characteristics of SRs published in prosthodontics. Methodological quality was analysed using the Assessment of Multiple Reviews (AMSTAR) tool. Several electronic resources (MEDLINE, EMBASE, Web of Science and American Dental Association's Evidence-based Dentistry website) were searched. In total 106 SRs were located. Key descriptive characteristics and methodological quality features were gathered and assessed, and descriptive and inferential statistical testing performed. Most SRs in this sample originated from the European continent followed by North America. Two to five authors conducted most SRs; the majority was affiliated with academic institutions and had prior experience publishing SRs. The majority of SRs were published in specialty dentistry journals, with implant or implant-related topics, the primary topics of interest for most. According to AMSTAR, most quality aspects were adequately fulfilled by less than half of the reviews. Publication bias and grey literature searches were the most poorly adhered components. Overall, the methodological quality of the prosthodontic-related systematic was deemed limited. Future recommendations would include authors to have prior training in conducting SRs and for journals to include a universal checklist that should be adhered to address all key characteristics of an unbiased SR process. © 2013 Blackwell Publishing Ltd.

HRD Practices and Talent Management in the Companies with the Employer Brand

ERIC Educational Resources Information Center

Kucherov, Dmitry; Zavyalova, Elena

2012-01-01

Purpose: The employer brand could be a key factor of competitiveness for a company in a contemporary labour market. The purpose of this paper is to identify the features of human resource development (HRD) practices and talent management in companies with employer brand (CEBs). Design/methodology/approach: The authors examined three economic…

Unruly Practices: What a Sociology of Translations Can Offer to Educational Policy Analysis

ERIC Educational Resources Information Center

Hamilton, Mary

2011-01-01

This paper argues for the utility of ANT as a philosophical and methodological approach to policy analysis. It introduces the key features of a recent educational policy reform initiative, Skills for Life and illustrates the argument by looking at three "moments" (in Callon's 1986 terminology) in the life of this initiative, applying the…

Stereoscopic Feature Tracking System for Retrieving Velocity of Surface Waters

NASA Astrophysics Data System (ADS)

Zuniga Zamalloa, C. C.; Landry, B. J.

2017-12-01

The present work is concerned with the surface velocity retrieval of flows using a stereoscopic setup and finding the correspondence in the images via feature tracking (FT). The feature tracking provides a key benefit of substantially reducing the level of user input. In contrast to other commonly used methods (e.g., normalized cross-correlation), FT does not require the user to prescribe interrogation window sizes and removes the need for masking when specularities are present. The results of the current FT methodology are comparable to those obtained via Large Scale Particle Image Velocimetry while requiring little to no user input which allowed for rapid, automated processing of imagery.

Factors Associated with the Utilization and Quality of Prenatal Care in Western Rural Regions of China

ERIC Educational Resources Information Center

Dongxu, Wang; Yuhui, Shi; Stewart, Donald; Chun, Chang; Chaoyang, Li

2012-01-01

Purpose: The paper seeks to identify key features of prenatal care utilization and quality in western regions of China and to determine the factors affecting the quality of prenatal care. Design/methodology/approach: A descriptive, cross-sectional study was conducted. The instrument for the study was a 10-stem respondent-administered, structured…

Estimating the Occurrence of Child Maltreatment and Risk-Factor Effects: Benefits of a Mixed-Design Strategy in Epidemiologic Research.

ERIC Educational Resources Information Center

Bertolli, Jeanne; And Others

1995-01-01

This article discusses methodologic limitations of four observational study designs (ecologic, case-control, cross-sectional, and cohort) that dominate the child abuse and neglect literature and identifies key features of an "ideal" study of child maltreatment. It proposes a new mixed-design strategy, which improves ability to identify child…

Modelling the Preferences of Students for Alternative Assignment Designs Using the Discrete Choice Experiment Methodology

ERIC Educational Resources Information Center

Kennelly, Brendan; Flannery, Darragh; Considine, John; Doherty, Edel; Hynes, Stephen

2014-01-01

This paper outlines how a discrete choice experiment (DCE) can be used to learn more about how students are willing to trade off various features of assignments such as the nature and timing of feedback and the method used to submit assignments. A DCE identifies plausible levels of the key attributes of a good or service and then presents the…

Employing an ethnographic approach: key characteristics.

PubMed

Lambert, Veronica; Glacken, Michele; McCarron, Mary

2011-01-01

Nurses are increasingly embracing ethnography as a useful research methodology. This paper presents an overview of some of the main characteristics we considered and the challenges encountered when using ethnography to explore the nature of communication between children and health professionals in a children's hospital. There is no consensual definition or single procedure to follow when using ethnography. This is largely attributable to the re-contextualisation of ethnography over time through diversification in and across many disciplines. Thus, it is imperative to consider some of ethnography's trademark features. To identify core trademark features of ethnography, we collated data following a scoping review of pertinent ethnographic textbooks, journal articles, attendance at ethnographic workshops and discussions with principle ethnographers. This is a methodological paper. Essentially, ethnography is a field-orientated activity that has cultural interpretations at its core, although the levels of those interpretations vary. We identified six trademark features to be considered when embracing an ethnographic approach: naturalism; context; multiple data sources; small case numbers; 'emic' and 'etic' perspectives, and ethical considerations. Ethnography has an assortment of meanings, so it is not often used in a wholly orthodox way and does not fall under the auspices of one epistemological belief. Yet, there are core criteria and trademark features that researchers should take into account alongside their particular epistemological beliefs when embracing an ethnographic inquiry. We hope this paper promotes a clearer vision of the methodological processes to consider when embarking on ethnography and creates an avenue for others to disseminate their experiences of and challenges encountered when applying ethnography's trademark features in different healthcare contexts.

Vein matching using artificial neural network in vein authentication systems

NASA Astrophysics Data System (ADS)

Noori Hoshyar, Azadeh; Sulaiman, Riza

2011-10-01

Personal identification technology as security systems is developing rapidly. Traditional authentication modes like key; password; card are not safe enough because they could be stolen or easily forgotten. Biometric as developed technology has been applied to a wide range of systems. According to different researchers, vein biometric is a good candidate among other biometric traits such as fingerprint, hand geometry, voice, DNA and etc for authentication systems. Vein authentication systems can be designed by different methodologies. All the methodologies consist of matching stage which is too important for final verification of the system. Neural Network is an effective methodology for matching and recognizing individuals in authentication systems. Therefore, this paper explains and implements the Neural Network methodology for finger vein authentication system. Neural Network is trained in Matlab to match the vein features of authentication system. The Network simulation shows the quality of matching as 95% which is a good performance for authentication system matching.

An Overview of Prognosis Health Management Research at Glenn Research Center for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Goldberg, Robert K.; Lerch, Bradley A.; Saleeb, Atef F.

2009-01-01

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include (1) diagnostic/detection methodology, (2) prognosis/lifing methodology, (3) diagnostic/prognosis linkage, (4) experimental validation, and (5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multimechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

An Overview of Prognosis Health Management Research at GRC for Gas Turbine Engine Structures With Special Emphasis on Deformation and Damage Modeling

NASA Technical Reports Server (NTRS)

Arnold, Steven M.; Goldberg, Robert K.; Lerch, Bradley A.; Saleeb, Atef F.

2009-01-01

Herein a general, multimechanism, physics-based viscoelastoplastic model is presented in the context of an integrated diagnosis and prognosis methodology which is proposed for structural health monitoring, with particular applicability to gas turbine engine structures. In this methodology, diagnostics and prognostics will be linked through state awareness variable(s). Key technologies which comprise the proposed integrated approach include 1) diagnostic/detection methodology, 2) prognosis/lifing methodology, 3) diagnostic/prognosis linkage, 4) experimental validation and 5) material data information management system. A specific prognosis lifing methodology, experimental characterization and validation and data information management are the focal point of current activities being pursued within this integrated approach. The prognostic lifing methodology is based on an advanced multi-mechanism viscoelastoplastic model which accounts for both stiffness and/or strength reduction damage variables. Methods to characterize both the reversible and irreversible portions of the model are discussed. Once the multiscale model is validated the intent is to link it to appropriate diagnostic methods to provide a full-featured structural health monitoring system.

Approaches to Children’s Exposure Assessment: Case Study with Diethylhexylphthalate (DEHP)

PubMed Central

Ginsberg, Gary; Ginsberg, Justine; Foos, Brenda

2016-01-01

Children’s exposure assessment is a key input into epidemiology studies, risk assessment and source apportionment. The goals of this article are to describe a methodology for children’s exposure assessment that can be used for these purposes and to apply the methodology to source apportionment for the case study chemical, diethylhexylphthalate (DEHP). A key feature is the comparison of total (aggregate) exposure calculated via a pathways approach to that derived from a biomonitoring approach. The 4-step methodology and its results for DEHP are: (1) Prioritization of life stages and exposure pathways, with pregnancy, breast-fed infants, and toddlers the focus of the case study and pathways selected that are relevant to these groups; (2) Estimation of pathway-specific exposures by life stage wherein diet was found to be the largest contributor for pregnant women, breast milk and mouthing behavior for the nursing infant and diet, house dust, and mouthing for toddlers; (3) Comparison of aggregate exposure by pathways vs biomonitoring-based approaches wherein good concordance was found for toddlers and pregnant women providing confidence in the exposure assessment; (4) Source apportionment in which DEHP presence in foods, children’s products, consumer products and the built environment are discussed with respect to early life mouthing, house dust and dietary exposure. A potential fifth step of the method involves the calculation of exposure doses for risk assessment which is described but outside the scope for the current case study. In summary, the methodology has been used to synthesize the available information to identify key sources of early life exposure to DEHP. PMID:27376320

On Designing Multicore-Aware Simulators for Systems Biology Endowed with OnLine Statistics

PubMed Central

Calcagno, Cristina; Coppo, Mario

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed. PMID:25050327

The clinico-radiological paradox of cognitive function and MRI burden of white matter lesions in people with multiple sclerosis: A systematic review and meta-analysis.

PubMed

Mollison, Daisy; Sellar, Robin; Bastin, Mark; Mollison, Denis; Chandran, Siddharthan; Wardlaw, Joanna; Connick, Peter

2017-01-01

Moderate correlation exists between the imaging quantification of brain white matter lesions and cognitive performance in people with multiple sclerosis (MS). This may reflect the greater importance of other features, including subvisible pathology, or methodological limitations of the primary literature. To summarise the cognitive clinico-radiological paradox and explore the potential methodological factors that could influence the assessment of this relationship. Systematic review and meta-analysis of primary research relating cognitive function to white matter lesion burden. Fifty papers met eligibility criteria for review, and meta-analysis of overall results was possible in thirty-two (2050 participants). Aggregate correlation between cognition and T2 lesion burden was r = -0.30 (95% confidence interval: -0.34, -0.26). Wide methodological variability was seen, particularly related to key factors in the cognitive data capture and image analysis techniques. Resolving the persistent clinico-radiological paradox will likely require simultaneous evaluation of multiple components of the complex pathology using optimum measurement techniques for both cognitive and MRI feature quantification. We recommend a consensus initiative to support common standards for image analysis in MS, enabling benchmarking while also supporting ongoing innovation.

On designing multicore-aware simulators for systems biology endowed with OnLine statistics.

PubMed

Aldinucci, Marco; Calcagno, Cristina; Coppo, Mario; Damiani, Ferruccio; Drocco, Maurizio; Sciacca, Eva; Spinella, Salvatore; Torquati, Massimo; Troina, Angelo

2014-01-01

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.

Systematic review of mobile health behavioural interventions to improve uptake of HIV testing for vulnerable and key populations.

PubMed

Conserve, Donaldson F; Jennings, Larissa; Aguiar, Carolina; Shin, Grace; Handler, Lara; Maman, Suzanne

2017-02-01

Introduction This systematic narrative review examined the empirical evidence on the effectiveness of mobile health (mHealth) behavioural interventions designed to increase the uptake of HIV testing among vulnerable and key populations. Methods MEDLINE/PubMed, Embase, Web of Science, and Global Health electronic databases were searched. Studies were eligible for inclusion if they were published between 2005 and 2015, evaluated an mHealth intervention, and reported an outcome relating to HIV testing. We also reviewed the bibliographies of retrieved studies for other relevant citations. The methodological rigor of selected articles was assessed, and narrative analyses were used to synthesize findings from mixed methodologies. Results A total of seven articles met the inclusion criteria. Most mHealth interventions employed a text-messaging feature and were conducted in middle- and high-income countries. The methodological rigor was moderate among studies. The current literature suggests that mHealth interventions can have significant positive effects on HIV testing initiation among vulnerable and key populations, as well as the general public. In some cases, null results were observed. Qualitative themes relating to the use of mobile technologies to increase HIV testing included the benefits of having low-cost, confidential, and motivational communication. Reported barriers included cellular network restrictions, poor linkages with physical testing services, and limited knowledge of appropriate text-messaging dose. Discussion MHealth interventions may prove beneficial in reducing the proportion of undiagnosed persons living with HIV, particularly among vulnerable and key populations. However, more rigorous and tailored interventions are needed to assess the effectiveness of widespread use.

Systematic review of mobile-health behavioral interventions to improve uptake of HIV testing for vulnerable and key populations

PubMed Central

Conserve, Donaldson F.; Jennings, Larissa; Aguiar, Carolina; Shin, Grace; Handler, Lara; Maman, Suzanne

2016-01-01

Objective This systematic narrative review examined the empirical evidence on the effectiveness of mobile health (mHealth) behavioral interventions designed to increase uptake of HIV testing among vulnerable and key populations. Methods MEDLINE/PubMed, Embase, Web of Science, and Global Health electronic databases were searched. Studies were eligible for inclusion if they were published between 2005 and 2015, evaluated an mHealth intervention, and reported an outcome relating to HIV testing. We also reviewed the bibliographies of retrieved studies for other relevant citations. The methodological rigor of selected articles was assessed, and narrative analyses were used to synthesize findings from mixed methodologies. Results A total of seven articles met the inclusion criteria. Most mHealth interventions employed a text-messaging feature and were conducted in middle- and high-income countries. The methodological rigor was moderate among studies. The current literature suggests that mHealth interventions can have significant positive effects on HIV testing initiation among vulnerable and key populations, as well as the general public. In some cases, null results were observed. Qualitative themes relating to use of mobile technologies to increase HIV testing included the benefits of having low-cost, confidential, and motivational communication. Reported barriers included cellular network restrictions, poor linkages with physical testing services, and limited knowledge of appropriate text-messaging dose. Conclusions MHealth interventions may prove beneficial in reducing the proportion of undiagnosed persons living with HIV, particularly among vulnerable and key populations. However, more rigorous and tailored intervention trials are needed to assess the effectiveness of widespread use. PMID:27056905

Feasibility of an International Multiple Sclerosis Rehabilitation Data Repository

PubMed Central

Bradford, Elissa Held; Baert, Ilse; Finlayson, Marcia; Feys, Peter

2018-01-01

Abstract Background: Multiple sclerosis (MS) rehabilitation evidence is limited due to methodological factors, which may be addressed by a data repository. We describe the perceived challenges of, motivators for, interest in participating in, and key features of an international MS rehabilitation data repository. Methods: A multimethod sequential investigation was performed with the results of two focus groups, using nominal group technique, and study aims informing the development of an online questionnaire. Percentage agreement and key quotations illustrated questionnaire findings. Subgroup comparisons were made between clinicians and researchers and between participants in North America and Europe. Results: Rehabilitation professionals from 25 countries participated (focus groups: n = 21; questionnaire: n = 166). The top ten challenges (C) and motivators (M) identified by the focus groups were database control/management (C); ethical/legal concerns (C); data quality (C); time, effort, and cost (C); best practice (M); uniformity (C); sustainability (C); deeper analysis (M); collaboration (M); and identifying research needs (M). Percentage agreement with questionnaire statements regarding challenges to, motivators for, interest in, and key features of a successful repository was at least 80%, 85%, 72%, and 83%, respectively, across each group of statements. Questionnaire subgroup analysis revealed a few differences (P < .05), including that clinicians more strongly identified with improving best practice as a motivator. Conclusions: Findings support clinician and researcher interest in and potential for success of an international MS rehabilitation data repository if prioritized challenges and motivators are addressed and key features are included. PMID:29507539

Feasibility of an International Multiple Sclerosis Rehabilitation Data Repository: Perceived Challenges and Motivators for Sharing Data.

PubMed

Bradford, Elissa Held; Baert, Ilse; Finlayson, Marcia; Feys, Peter; Wagner, Joanne

2018-01-01

Multiple sclerosis (MS) rehabilitation evidence is limited due to methodological factors, which may be addressed by a data repository. We describe the perceived challenges of, motivators for, interest in participating in, and key features of an international MS rehabilitation data repository. A multimethod sequential investigation was performed with the results of two focus groups, using nominal group technique, and study aims informing the development of an online questionnaire. Percentage agreement and key quotations illustrated questionnaire findings. Subgroup comparisons were made between clinicians and researchers and between participants in North America and Europe. Rehabilitation professionals from 25 countries participated (focus groups: n = 21; questionnaire: n = 166). The top ten challenges (C) and motivators (M) identified by the focus groups were database control/management (C); ethical/legal concerns (C); data quality (C); time, effort, and cost (C); best practice (M); uniformity (C); sustainability (C); deeper analysis (M); collaboration (M); and identifying research needs (M). Percentage agreement with questionnaire statements regarding challenges to, motivators for, interest in, and key features of a successful repository was at least 80%, 85%, 72%, and 83%, respectively, across each group of statements. Questionnaire subgroup analysis revealed a few differences (P < .05), including that clinicians more strongly identified with improving best practice as a motivator. Findings support clinician and researcher interest in and potential for success of an international MS rehabilitation data repository if prioritized challenges and motivators are addressed and key features are included.

A geometric multigrid preconditioning strategy for DPG system matrices

DOE PAGES

Roberts, Nathan V.; Chan, Jesse

2017-08-23

Here, the discontinuous Petrov–Galerkin (DPG) methodology of Demkowicz and Gopalakrishnan (2010, 2011) guarantees the optimality of the solution in an energy norm, and provides several features facilitating adaptive schemes. A key question that has not yet been answered in general – though there are some results for Poisson, e.g.– is how best to precondition the DPG system matrix, so that iterative solvers may be used to allow solution of large-scale problems.

Methodological Challenges to Economic Evaluations of Vaccines: Is a Common Approach Still Possible?

PubMed

Jit, Mark; Hutubessy, Raymond

2016-06-01

Economic evaluation of vaccination is a key tool to inform effective spending on vaccines. However, many evaluations have been criticised for failing to capture features of vaccines which are relevant to decision makers. These include broader societal benefits (such as improved educational achievement, economic growth and political stability), reduced health disparities, medical innovation, reduced hospital beds pressures, greater peace of mind and synergies in economic benefits with non-vaccine interventions. Also, the fiscal implications of vaccination programmes are not always made explicit. Alternative methodological frameworks have been proposed to better capture these benefits. However, any broadening of the methodology for economic evaluation must also involve evaluations of non-vaccine interventions, and hence may not always benefit vaccines given a fixed health-care budget. The scope of an economic evaluation must consider the budget from which vaccines are funded, and the decision-maker's stated aims for that spending to achieve.

No evidence for intervention-dependent influence of methodological features on treatment effect.

PubMed

Jacobs, Wilco C H; Kruyt, Moyo C; Moojen, Wouter A; Verbout, Ab J; Oner, F Cumhur

2013-12-01

The goal of this systematic review was to evaluate if the influence of methodological features on treatment effect differs between types of intervention. MEDLINE, Embase, Web of Science, Cochrane methodology register, and reference lists were searched for meta-epidemiologic studies on the influence of methodological features on treatment effect. Studies analyzing influence of methodological features related to internal validity were included. We made a distinction among surgical, pharmaceutical, and therapeutical as separate types of intervention. Heterogeneity was calculated to identify differences among these types. Fourteen meta-epidemiologic studies were found with 51 estimates of influence of methodological features on treatment effect. Heterogeneity was observed among the intervention types for randomization. Surgical intervention studies showed a larger treatment effect when randomized; this was in contrast to pharmaceutical studies that found the opposite. For allocation concealment and double blinding, the influence of methodological features on the treatment effect was comparable across different types of intervention. For the remaining methodological features, there were insufficient observations. The influence of allocation concealment and double blinding on the treatment effect is consistent across studies of different interventional types. The influence of randomization although, may be different between surgical and nonsurgical studies. Copyright © 2013 Elsevier Inc. All rights reserved.

Health Worker Focused Distributed Simulation for Improving Capability of Health Systems in Liberia.

PubMed

Gale, Thomas C E; Chatterjee, Arunangsu; Mellor, Nicholas E; Allan, Richard J

2016-04-01

The main goal of this study was to produce an adaptable learning platform using virtual learning and distributed simulation, which can be used to train health care workers, across a wide geographical area, key safety messages regarding infection prevention control (IPC). A situationally responsive agile methodology, Scrum, was used to develop a distributed simulation module using short 1-week iterations and continuous synchronous plus asynchronous communication including end users and IPC experts. The module contained content related to standard IPC precautions (including handwashing techniques) and was structured into 3 distinct sections related to donning, doffing, and hazard perception training. Using Scrum methodology, we were able to link concepts applied to best practices in simulation-based medical education (deliberate practice, continuous feedback, self-assessment, and exposure to uncommon events), pedagogic principles related to adult learning (clear goals, contextual awareness, motivational features), and key learning outcomes regarding IPC, as a rapid response initiative to the Ebola outbreak in West Africa. Gamification approach has been used to map learning mechanics to enhance user engagement. The developed IPC module demonstrates how high-frequency, low-fidelity simulations can be rapidly designed using scrum-based agile methodology. Analytics incorporated into the tool can help demonstrate improved confidence and competence of health care workers who are treating patients within an Ebola virus disease outbreak region. These concepts could be used in a range of evolving disasters where rapid development and communication of key learning messages are required.

Curated Collection for Educators: Five Key Papers about the Flipped Classroom Methodology.

PubMed

King, Andrew; Boysen-Osborn, Megan; Cooney, Robert; Mitzman, Jennifer; Misra, Asit; Williams, Jennifer; Dulani, Tina; Gottlieb, Michael

2017-10-25

The flipped classroom (FC) pedagogy is becoming increasingly popular in medical education due to its appeal to the millennial learner and potential benefits in knowledge acquisition. Despite its popularity and effectiveness, the FC educational method is not without challenges. In this article, we identify and summarize several key papers relevant to medical educators interested in exploring the FC teaching methodology. The authors identified an extensive list of papers relevant to FC pedagogy via online discussions within the Academic Life in Emergency Medicine (ALiEM) Faculty Incubator. This list was augmented by an open call on Twitter (utilizing the #meded, #FOAMed, and #flippedclassroom hashtags) yielding a list of 33 papers. We then conducted a three-round modified Delphi process within the authorship group, which included both junior and senior clinician educators, to identify the most impactful papers for educators interested in FC pedagogy. The three-round modified Delphi process ranked all of the selected papers and selected the five most highly-rated papers for inclusion. The authorship group reviewed and summarized these papers with specific consideration given to their value to junior faculty educators and faculty developers interested in the flipped classroom approach. The list of papers featured in this article serves as a key reading list for junior clinician educators and faculty developers interested in the flipped classroom technique. The associated commentaries contextualize the importance of these papers for medical educators aiming to optimize their understanding and implementation of the flipped classroom methodology in their teaching and through faculty development.

Evaluation of the effectiveness of color attributes for video indexing

NASA Astrophysics Data System (ADS)

Chupeau, Bertrand; Forest, Ronan

2001-10-01

Color features are reviewed and their effectiveness assessed in the application framework of key-frame clustering for abstracting unconstrained video. Existing color spaces and associated quantization schemes are first studied. Description of global color distribution by means of histograms is then detailed. In our work, 12 combinations of color space and quantization were selected, together with 12 histogram metrics. Their respective effectiveness with respect to picture similarity measurement was evaluated through a query-by-example scenario. For that purpose, a set of still-picture databases was built by extracting key frames from several video clips, including news, documentaries, sports and cartoons. Classical retrieval performance evaluation criteria were adapted to the specificity of our testing methodology.

Evaluation of the effectiveness of color attributes for video indexing

NASA Astrophysics Data System (ADS)

Chupeau, Bertrand; Forest, Ronan

2001-01-01

Color features are reviewed and their effectiveness assessed in the application framework of key-frame clustering for abstracting unconstrained video. Existing color spaces and associated quantization schemes are first studied. Description of global color distribution by means of histograms is then detailed. In our work, twelve combinations of color space and quantization were selected, together with twelve histogram metrics. Their respective effectiveness with respect to picture similarity measurement was evaluated through a query-be-example scenario. For that purpose, a set of still-picture databases was built by extracting key-frames from several video clips, including news, documentaries, sports and cartoons. Classical retrieval performance evaluation criteria were adapted to the specificity of our testing methodology.

Evaluation of the effectiveness of color attributes for video indexing

NASA Astrophysics Data System (ADS)

Chupeau, Bertrand; Forest, Ronan

2000-12-01

Color features are reviewed and their effectiveness assessed in the application framework of key-frame clustering for abstracting unconstrained video. Existing color spaces and associated quantization schemes are first studied. Description of global color distribution by means of histograms is then detailed. In our work, twelve combinations of color space and quantization were selected, together with twelve histogram metrics. Their respective effectiveness with respect to picture similarity measurement was evaluated through a query-be-example scenario. For that purpose, a set of still-picture databases was built by extracting key-frames from several video clips, including news, documentaries, sports and cartoons. Classical retrieval performance evaluation criteria were adapted to the specificity of our testing methodology.

Modelling Aṣṭādhyāyī: An Approach Based on the Methodology of Ancillary Disciplines (Vedāṅga)

NASA Astrophysics Data System (ADS)

Mishra, Anand

This article proposes a general model based on the common methodological approach of the ancillary disciplines (Vedāṅga) associated with the Vedas taking examples from Śikṣā, Chandas, Vyākaraṇa and Prātiśā khya texts. It develops and elaborates this model further to represent the contents and processes of Aṣṭādhyāyī. Certain key features are added to my earlier modelling of Pāṇinian system of Sanskrit grammar. This includes broader coverage of the Pāṇinian meta-language, mechanism for automatic application of rules and positioning the grammatical system within the procedural complexes of ancillary disciplines.

New technology and regional studies in human ecology: A Papua New Guinea example

NASA Technical Reports Server (NTRS)

Morren, George E. B., Jr.

1991-01-01

Two key issues in using technologies such as digital image processing and geographic information systems are a conceptually and methodologically valid research design and the exploitation of varied sources of data. With this realized, the new technologies offer anthropologists the opportunity to test hypotheses about spatial and temporal variations in the features of interest within a regionally coherent mosaic of social groups and landscapes. Current research on the Mountain OK of Papua New Guinea is described with reference to these issues.

Human nonverbal courtship behavior--a brief historical review.

PubMed

Moore, Monica M

2010-03-01

This article reviews research findings documenting the nature of nonverbal courtship behavior compiled through both observation and self-report methods. I briefly present the major theoretical perspectives guiding research methodologies used in the field and in the laboratory. Studies of verbal courtship, including those conducted via computer, via text messaging, or through personal advertisement, are not included in this review. The article ends by elucidating some key features of human nonverbal courtship behavior that have become apparent after scrutinizing these data.

Baicalein Reduces Airway Injury in Allergen and IL-13 Induced Airway Inflammation

PubMed Central

Mabalirajan, Ulaganathan; Ahmad, Tanveer; Rehman, Rakhshinda; Leishangthem, Geeta Devi; Dinda, Amit Kumar; Agrawal, Anurag; Ghosh, Balaram; Sharma, Surendra Kumar

2013-01-01

Background Baicalein, a bioflavone present in the dry roots of Scutellaria baicalensis Georgi, is known to reduce eotaxin production in human fibroblasts. However, there are no reports of its anti-asthma activity or its effect on airway injury. Methodology/Principal Findings In a standard experimental asthma model, male Balb/c mice that were sensitized with ovalbumin (OVA), treated with baicalein (10 mg/kg, ip) or a vehicle control, either during (preventive use) or after OVA challenge (therapeutic use). In an alternate model, baicalein was administered to male Balb/c mice which were given either IL-4 or IL-13 intranasally. Features of asthma were determined by estimating airway hyperresponsiveness (AHR), histopathological changes and biochemical assays of key inflammatory molecules. Airway injury was determined with apoptotic assays, transmission electron microscopy and assessing key mitochondrial functions. Baicalein treatment reduced AHR and inflammation in both experimental models. TGF-β1, sub-epithelial fibrosis and goblet cell metaplasia, were also reduced. Furthermore, baicalein treatment significantly reduced 12/15-LOX activity, features of mitochondrial dysfunctions, and apoptosis of bronchial epithelia. Conclusion/Significance Our findings demonstrate that baicalein can attenuate important features of asthma, possibly through the reduction of airway injury and restoration of mitochondrial function. PMID:23646158

Assessing validity of observational intervention studies - the Benchmarking Controlled Trials.

PubMed

Malmivaara, Antti

2016-09-01

Benchmarking Controlled Trial (BCT) is a concept which covers all observational studies aiming to assess impact of interventions or health care system features to patients and populations. To create and pilot test a checklist for appraising methodological validity of a BCT. The checklist was created by extracting the most essential elements from the comprehensive set of criteria in the previous paper on BCTs. Also checklists and scientific papers on observational studies and respective systematic reviews were utilized. Ten BCTs published in the Lancet and in the New England Journal of Medicine were used to assess feasibility of the created checklist. The appraised studies seem to have several methodological limitations, some of which could be avoided in planning, conducting and reporting phases of the studies. The checklist can be used for planning, conducting, reporting, reviewing, and critical reading of observational intervention studies. However, the piloted checklist should be validated in further studies. Key messages Benchmarking Controlled Trial (BCT) is a concept which covers all observational studies aiming to assess impact of interventions or health care system features to patients and populations. This paper presents a checklist for appraising methodological validity of BCTs and pilot-tests the checklist with ten BCTs published in leading medical journals. The appraised studies seem to have several methodological limitations, some of which could be avoided in planning, conducting and reporting phases of the studies. The checklist can be used for planning, conducting, reporting, reviewing, and critical reading of observational intervention studies.

Setting conservation targets for sandy beach ecosystems

NASA Astrophysics Data System (ADS)

Harris, Linda; Nel, Ronel; Holness, Stephen; Sink, Kerry; Schoeman, David

2014-10-01

Representative and adequate reserve networks are key to conserving biodiversity. This begs the question, how much of which features need to be placed in protected areas? Setting specifically-derived conservation targets for most ecosystems is common practice; however, this has never been done for sandy beaches. The aims of this paper, therefore, are to propose a methodology for setting conservation targets for sandy beach ecosystems; and to pilot the proposed method using data describing biodiversity patterns and processes from microtidal beaches in South Africa. First, a classification scheme of valued features of beaches is constructed, including: biodiversity features; unique features; and important processes. Second, methodologies for setting targets for each feature under different data-availability scenarios are described. From this framework, targets are set for features characteristic of microtidal beaches in South Africa, as follows. 1) Targets for dune vegetation types were adopted from a previous assessment, and ranged 19-100%. 2) Targets for beach morphodynamic types (habitats) were set using species-area relationships (SARs). These SARs were derived from species richness data from 142 sampling events around the South African coast (extrapolated to total theoretical species richness estimates using previously-established species-accumulation curve relationships), plotted against the area of the beach (calculated from Google Earth imagery). The species-accumulation factor (z) was 0.22, suggesting a baseline habitat target of 27% is required to protect 75% of the species. This baseline target was modified by heuristic principles, based on habitat rarity and threat status, with final values ranging 27-40%. 3) Species targets were fixed at 20%, modified using heuristic principles based on endemism, threat status, and whether or not beaches play an important role in the species' life history, with targets ranging 20-100%. 4) Targets for processes and 5) important assemblages were set at 50%, following other studies. 6) Finally, a target for an outstanding feature (the Alexandria dunefield) was set at 80% because of its national, international and ecological importance. The greatest shortfall in the current target-setting process is in the lack of empirical models describing the key beach processes, from which robust ecological thresholds can be derived. As for many other studies, our results illustrate that the conservation target of 10% for coastal and marine systems proposed by the Convention on Biological Diversity is too low to conserve sandy beaches and their biota.

Parents' Verbal Communication and Childhood Anxiety: A Systematic Review.

PubMed

Percy, Ray; Creswell, Cathy; Garner, Matt; O'Brien, Doireann; Murray, Lynne

2016-03-01

Parents' verbal communication to their child, particularly the expression of fear-relevant information (e.g., attributions of threat to the environment), is considered to play a key role in children's fears and anxiety. This review considers the extent to which parental verbal communication is associated with child anxiety by examining research that has employed objective observational methods. Using a systematic search strategy, we identified 15 studies that addressed this question. These studies provided some evidence that particular fear-relevant features of parental verbal communication are associated with child anxiety under certain conditions. However, the scope for drawing reliable, general conclusions was limited by extensive methodological variation between studies, particularly in terms of the features of parental verbal communication examined and the context in which communication took place, how child anxiety was measured, and inconsistent consideration of factors that may moderate the verbal communication-child anxiety relationship. We discuss ways in which future research can contribute to this developing evidence base and reduce further methodological inconsistency so as to inform interventions for children with anxiety problems.

Curated Collection for Educators: Five Key Papers about the Flipped Classroom Methodology

PubMed Central

Boysen-Osborn, Megan; Cooney, Robert; Mitzman, Jennifer; Misra, Asit; Williams, Jennifer; Dulani, Tina; Gottlieb, Michael

2017-01-01

The flipped classroom (FC) pedagogy is becoming increasingly popular in medical education due to its appeal to the millennial learner and potential benefits in knowledge acquisition. Despite its popularity and effectiveness, the FC educational method is not without challenges. In this article, we identify and summarize several key papers relevant to medical educators interested in exploring the FC teaching methodology. The authors identified an extensive list of papers relevant to FC pedagogy via online discussions within the Academic Life in Emergency Medicine (ALiEM) Faculty Incubator. This list was augmented by an open call on Twitter (utilizing the #meded, #FOAMed, and #flippedclassroom hashtags) yielding a list of 33 papers. We then conducted a three-round modified Delphi process within the authorship group, which included both junior and senior clinician educators, to identify the most impactful papers for educators interested in FC pedagogy. The three-round modified Delphi process ranked all of the selected papers and selected the five most highly-rated papers for inclusion. The authorship group reviewed and summarized these papers with specific consideration given to their value to junior faculty educators and faculty developers interested in the flipped classroom approach. The list of papers featured in this article serves as a key reading list for junior clinician educators and faculty developers interested in the flipped classroom technique. The associated commentaries contextualize the importance of these papers for medical educators aiming to optimize their understanding and implementation of the flipped classroom methodology in their teaching and through faculty development. PMID:29282445

Advanced piloted aircraft flight control system design methodology. Volume 1: Knowledge base

NASA Technical Reports Server (NTRS)

Mcruer, Duane T.; Myers, Thomas T.

1988-01-01

The development of a comprehensive and electric methodology for conceptual and preliminary design of flight control systems is presented and illustrated. The methodology is focused on the design stages starting with the layout of system requirements and ending when some viable competing system architectures (feedback control structures) are defined. The approach is centered on the human pilot and the aircraft as both the sources of, and the keys to the solution of, many flight control problems. The methodology relies heavily on computational procedures which are highly interactive with the design engineer. To maximize effectiveness, these techniques, as selected and modified to be used together in the methodology, form a cadre of computational tools specifically tailored for integrated flight control system preliminary design purposes. While theory and associated computational means are an important aspect of the design methodology, the lore, knowledge and experience elements, which guide and govern applications are critical features. This material is presented as summary tables, outlines, recipes, empirical data, lists, etc., which encapsulate a great deal of expert knowledge. Much of this is presented in topical knowledge summaries which are attached as Supplements. The composite of the supplements and the main body elements constitutes a first cut at a a Mark 1 Knowledge Base for manned-aircraft flight control.

Advancing scoping study methodology: a web-based survey and consultation of perceptions on terminology, definition and methodological steps.

PubMed

O'Brien, Kelly K; Colquhoun, Heather; Levac, Danielle; Baxter, Larry; Tricco, Andrea C; Straus, Sharon; Wickerson, Lisa; Nayar, Ayesha; Moher, David; O'Malley, Lisa

2016-07-26

Scoping studies (or reviews) are a method used to comprehensively map evidence across a range of study designs in an area, with the aim of informing future research practice, programs and policy. However, no universal agreement exists on terminology, definition or methodological steps. Our aim was to understand the experiences of, and considerations for conducting scoping studies from the perspective of academic and community partners. Primary objectives were to 1) describe experiences conducting scoping studies including strengths and challenges; and 2) describe perspectives on terminology, definition, and methodological steps. We conducted a cross-sectional web-based survey with clinicians, educators, researchers, knowledge users, representatives from community-based organizations, graduate students, and policy stakeholders with experience and/or interest in conducting scoping studies to gain an understanding of experiences and perspectives on the conduct and reporting of scoping studies. We administered an electronic self-reported questionnaire comprised of 22 items related to experiences with scoping studies, strengths and challenges, opinions on terminology, and methodological steps. We analyzed questionnaire data using descriptive statistics and content analytical techniques. Survey results were discussed during a multi-stakeholder consultation to identify key considerations in the conduct and reporting of scoping studies. Of the 83 invitations, 54 individuals (65 %) completed the scoping questionnaire, and 48 (58 %) attended the scoping study meeting from Canada, the United Kingdom and United States. Many scoping study strengths were dually identified as challenges including breadth of scope, and iterative process. No consensus on terminology emerged, however key defining features that comprised a working definition of scoping studies included the exploratory mapping of literature in a field; iterative process, inclusion of grey literature; no quality assessment of included studies, and an optional consultation phase. We offer considerations for the conduct and reporting of scoping studies for researchers, clinicians and knowledge users engaging in this methodology. Lack of consensus on scoping terminology, definition and methodological steps persists. Reasons for this may be attributed to diversity of disciplines adopting this methodology for differing purposes. Further work is needed to establish guidelines on the reporting and methodological quality assessment of scoping studies.

Towards the development of laboratory methods for studying drinking games: Initial findings, methodological considerations, and future directions

PubMed Central

Silvestri, Mark M.; Lewis, Jennifer M.; Borsari, Brian; Correia, Christopher J.

2014-01-01

Background Drinking games are prevalent among college students and are associated with increased alcohol use and negative alcohol-related consequences. There has been substantial growth in research on drinking games. However, the majority of published studies rely on retrospective self-reports of behavior and very few studies have made use of laboratory procedures to systematically observe drinking game behavior. Objectives The current paper draws on the authors’ experiences designing and implementing methods for the study of drinking games in the laboratory. Results The paper addressed the following key design features: (a) drinking game selection; (b) beverage selection; (c) standardizing game play; (d) selection of dependent and independent variables; and (e) creating a realistic drinking game environment. Conclusions The goal of this methodological review paper is to encourage other researchers to pursue laboratory research on drinking game behavior. Use of laboratory-based methodologies will facilitate a better understanding of the dynamics of risky drinking and inform prevention and intervention efforts. PMID:25192209

Understanding Scientific Methodology in the Historical and Experimental Sciences via Language Analysis

NASA Astrophysics Data System (ADS)

Dodick, Jeff; Argamon, Shlomo; Chase, Paul

2009-08-01

A key focus of current science education reforms involves developing inquiry-based learning materials. However, without an understanding of how working scientists actually do science, such learning materials cannot be properly developed. Until now, research on scientific reasoning has focused on cognitive studies of individual scientific fields. However, the question remains as to whether scientists in different fields fundamentally rely on different methodologies. Although many philosophers and historians of science do indeed assert that there is no single monolithic scientific method, this has never been tested empirically. We therefore approach this problem by analyzing patterns of language used by scientists in their published work. Our results demonstrate systematic variation in language use between types of science that are thought to differ in their characteristic methodologies. The features of language use that were found correspond closely to a proposed distinction between Experimental Sciences (e.g., chemistry) and Historical Sciences (e.g., paleontology); thus, different underlying rhetorical and conceptual mechanisms likely operate for scientific reasoning and communication in different contexts.

Hexafluoroisopropyl alcohol mediated synthesis of 2,3-dihydro-4H-pyrido[1,2-a]pyrimidin-4-ones.

PubMed

Alam, Mohammad A; Alsharif, Zakeyah; Alkhattabi, Hessa; Jones, Derika; Delancey, Evan; Gottsponer, Adam; Yang, Tianhong

2016-11-02

An efficient synthesis of novel 2,3-dihydro-4H-pyrido[1,2-a]pyrimidin-4-ones has been reported. Inexpensive and readily available substrates, environmentally benign reaction condition, and product formation up to quantitative yield are the key features of this methodology. Products are formed by the aza-Michael addition followed by intramolecular acyl substitution in a domino process. The polar nature and strong hydrogen bond donor capability of 1,1,1,3,3,3-hexafluoropropan-2-ol is pivotal in this cascade protocol.

Assessing health impacts in complex eco-epidemiological settings in the humid tropics: Modular baseline health surveys

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

Winkler, Mirko S., E-mail: mirko.winkler@unibas.ch; University of Basel, P.O. Box, CH-4003 Basel; Divall, Mark J., E-mail: mdivall@shapeconsulting.org

2012-02-15

The quantitative assessment of health impacts has been identified as a crucial feature for realising the full potential of health impact assessment (HIA). In settings where demographic and health data are notoriously scarce, but there is a broad range of ascertainable ecological, environmental, epidemiological and socioeconomic information, a diverse toolkit of data collection strategies becomes relevant for the mainly small-area impacts of interest. We present a modular, cross-sectional baseline health survey study design, which has been developed for HIA of industrial development projects in the humid tropics. The modular nature of our toolkit allows our methodology to be readily adaptedmore » to the prevailing eco-epidemiological characteristics of a given project setting. Central to our design is a broad set of key performance indicators, covering a multiplicity of health outcomes and determinants at different levels and scales. We present experience and key findings from our modular baseline health survey methodology employed in 14 selected sentinel sites within an iron ore mining project in the Republic of Guinea. We argue that our methodology is a generic example of rapid evidence assembly in difficult-to-reach localities, where improvement of the predictive validity of the assessment and establishment of a benchmark for longitudinal monitoring of project impacts and mitigation efforts is needed.« less

Assessing validity of observational intervention studies – the Benchmarking Controlled Trials

PubMed Central

Malmivaara, Antti

2016-01-01

Abstract Background: Benchmarking Controlled Trial (BCT) is a concept which covers all observational studies aiming to assess impact of interventions or health care system features to patients and populations. Aims: To create and pilot test a checklist for appraising methodological validity of a BCT. Methods: The checklist was created by extracting the most essential elements from the comprehensive set of criteria in the previous paper on BCTs. Also checklists and scientific papers on observational studies and respective systematic reviews were utilized. Ten BCTs published in the Lancet and in the New England Journal of Medicine were used to assess feasibility of the created checklist. Results: The appraised studies seem to have several methodological limitations, some of which could be avoided in planning, conducting and reporting phases of the studies. Conclusions: The checklist can be used for planning, conducting, reporting, reviewing, and critical reading of observational intervention studies. However, the piloted checklist should be validated in further studies.Key messagesBenchmarking Controlled Trial (BCT) is a concept which covers all observational studies aiming to assess impact of interventions or health care system features to patients and populations.This paper presents a checklist for appraising methodological validity of BCTs and pilot-tests the checklist with ten BCTs published in leading medical journals. The appraised studies seem to have several methodological limitations, some of which could be avoided in planning, conducting and reporting phases of the studies.The checklist can be used for planning, conducting, reporting, reviewing, and critical reading of observational intervention studies. PMID:27238631

phMRI: methodological considerations for mitigating potential confounding factors

PubMed Central

Bourke, Julius H.; Wall, Matthew B.

2015-01-01

Pharmacological Magnetic Resonance Imaging (phMRI) is a variant of conventional MRI that adds pharmacological manipulations in order to study the effects of drugs, or uses pharmacological probes to investigate basic or applied (e.g., clinical) neuroscience questions. Issues that may confound the interpretation of results from various types of phMRI studies are briefly discussed, and a set of methodological strategies that can mitigate these problems are described. These include strategies that can be employed at every stage of investigation, from study design to interpretation of resulting data, and additional techniques suited for use with clinical populations are also featured. Pharmacological MRI is a challenging area of research that has both significant advantages and formidable difficulties, however with due consideration and use of these strategies many of the key obstacles can be overcome. PMID:25999812

Hyperbolic reformulation of a 1D viscoelastic blood flow model and ADER finite volume schemes

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

Montecinos, Gino I.; Müller, Lucas O.; Toro, Eleuterio F.

2014-06-01

The applicability of ADER finite volume methods to solve hyperbolic balance laws with stiff source terms in the context of well-balanced and non-conservative schemes is extended to solve a one-dimensional blood flow model for viscoelastic vessels, reformulated as a hyperbolic system, via a relaxation time. A criterion for selecting relaxation times is found and an empirical convergence rate assessment is carried out to support this result. The proposed methodology is validated by applying it to a network of viscoelastic vessels for which experimental and numerical results are available. The agreement between the results obtained in the present paper and thosemore » available in the literature is satisfactory. Key features of the present formulation and numerical methodologies, such as accuracy, efficiency and robustness, are fully discussed in the paper.« less

A feature selection approach towards progressive vector transmission over the Internet

NASA Astrophysics Data System (ADS)

Miao, Ru; Song, Jia; Feng, Min

2017-09-01

WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.

Learning Motion Features for Example-Based Finger Motion Estimation for Virtual Characters

NASA Astrophysics Data System (ADS)

Mousas, Christos; Anagnostopoulos, Christos-Nikolaos

2017-09-01

This paper presents a methodology for estimating the motion of a character's fingers based on the use of motion features provided by a virtual character's hand. In the presented methodology, firstly, the motion data is segmented into discrete phases. Then, a number of motion features are computed for each motion segment of a character's hand. The motion features are pre-processed using restricted Boltzmann machines, and by using the different variations of semantically similar finger gestures in a support vector machine learning mechanism, the optimal weights for each feature assigned to a metric are computed. The advantages of the presented methodology in comparison to previous solutions are the following: First, we automate the computation of optimal weights that are assigned to each motion feature counted in our metric. Second, the presented methodology achieves an increase (about 17%) in correctly estimated finger gestures in comparison to a previous method.

Completeness of reporting in abstracts from clinical trials of pre-harvest interventions against foodborne pathogens.

PubMed

Snedeker, Kate G; Canning, Paisley; Totton, Sarah C; Sargeant, Jan M

2012-04-01

Abstracts are the most commonly read part of a journal article, and play an important role as summaries of the articles, and search and screening tools. However, research on abstracts in human biomedicine has shown that abstracts often do not report key methodological features and results. Little research has been done to examine reporting of such features in abstracts from papers detailing pre-harvest food safety trials. Thus, the objective of this study was to assess the quality of reporting of key factors in abstracts detailing trials of pre-harvest food safety interventions. A systematic search algorithm was used to identify all in vivo trials of pre-harvest interventions against foodborne pathogens in PubMed and CAB Direct published from 1999 to October 2009. References were screened for relevance, and 150 were randomly chosen for inclusion in the study. A checklist based on the CONSORT abstract extension and the REFLECT Statement was used to assess the reporting of methodological features and results. All screening and assessment was performed by two independent reviewers with disagreements resolved by consensus. The systematic search returned 3554 unique citations; 356 were found to be relevant and 150 were randomly selected for inclusion. The abstracts were from 51 different journals, and 13 out of 150 were structured. Of the 124 abstracts that reported whether the trial design was deliberate disease challenge or natural exposure, 113 were deliberate challenge and 11 natural exposure. 103 abstracts detailed studies involving poultry, 20 cattle and 15 swine. Most abstracts reported the production stage of the animals (135/150), a hypothesis or objective (123/150), and results for all treatment groups (136/150). However, few abstracts reported on how animals were grouped in housing (25/150), the location of the study (5/150), the primary outcome (2/126), level of treatment allocation (15/150), sample size (63/150) or whether study units were lost to follow up (4/150). Forty-eight (48/150) abstracts reported the name, mode of administration, dose and duration of the intervention(s), while 102 (102/150) reported at least one of these elements. Nine (9/150) abstracts specified that allocation of study units to treatments was randomized, and none of the abstracts reported whether blinding was used (0/150). These results reveal gaps in reporting of methodological features and results. Thus, improving reporting quality in abstracts should be a crucial goal to be pursued by authors, reviewers and journal editors. Copyright © 2011 Elsevier B.V. All rights reserved.

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-06-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

NASA Astrophysics Data System (ADS)

Belgasam, Tarek M.; Zbib, Hussein M.

2018-03-01

The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the development of a clear understanding of the effect of various microstructural parameters on the energy absorption in these materials. Accordingly, DP steelmakers are interested in predicting the effect of various microscopic factors as well as optimizing microstructural properties for application in crash-relevant components of vehicle bodies. This study presents a microstructure-based approach using a multiscale material and structure model. In this approach, Digimat and LS-DYNA software were coupled and employed to provide a full micro-macro multiscale material model, which is then used to simulate tensile tests. Microstructures with varied ferrite grain sizes, martensite volume fractions, and carbon content in DP steels were studied. The impact of these microstructural features at different strain rates on energy absorption characteristics of DP steels is investigated numerically using an elasto-viscoplastic constitutive model. The model is implemented in a multiscale finite-element framework. A comprehensive statistical parametric study using response surface methodology is performed to determine the optimum microstructural features for a required tensile toughness at different strain rates. The simulation results are validated using experimental data found in the literature. The developed methodology proved to be effective for investigating the influence and interaction of key microscopic properties on the energy absorption characteristics of DP steels. Furthermore, it is shown that this method can be used to identify optimum microstructural conditions at different strain-rate conditions.

Health coaching to improve healthy lifestyle behaviors: an integrative review.

PubMed

Olsen, Jeanette M; Nesbitt, Bonnie J

2010-01-01

Chronic diseases account for 70% of U.S. deaths. Health coaching may help patients adopt healthy lifestyle behaviors that prevent and control diseases. This integrative review analyzed health coaching studies for evidence of effectiveness and to identify key program features. Multiple electronic databases were utilized, yielding a final sample of 15 documents. The search was limited to peer-reviewed research articles published between 1999 and 2008. Studies were further analyzed if they (1) specifically cited coaching as a program intervention, and (2) applied the intervention to research. Articles describing various quantitative and qualitative methodologies were critically analyzed using a systematic method. Data were synthesized using a matrix format according to purpose, method, intervention, findings, critique, and quality rating. All 15 studies utilized nonprobability sampling, 7 (47%) with randomized intervention and control groups. Significant improvements in one or more of the behaviors of nutrition, physical activity, weight management, or medication adherence were identified in six (40%) of the studies. Common features of effective programs were goal setting (73%), motivational interviewing (27%), and collaboration with health care providers (20%). Health coaching studies with well-specified methodologies and more rigorous designs are needed to strengthen findings; however, this behavioral change intervention suggests promise.

Combining Feature Selection and Integration—A Neural Model for MT Motion Selectivity

PubMed Central

Beck, Cornelia; Neumann, Heiko

2011-01-01

Background The computation of pattern motion in visual area MT based on motion input from area V1 has been investigated in many experiments and models attempting to replicate the main mechanisms. Two different core conceptual approaches were developed to explain the findings. In integrationist models the key mechanism to achieve pattern selectivity is the nonlinear integration of V1 motion activity. In contrast, selectionist models focus on the motion computation at positions with 2D features. Methodology/Principal Findings Recent experiments revealed that neither of the two concepts alone is sufficient to explain all experimental data and that most of the existing models cannot account for the complex behaviour found. MT pattern selectivity changes over time for stimuli like type II plaids from vector average to the direction computed with an intersection of constraint rule or by feature tracking. Also, the spatial arrangement of the stimulus within the receptive field of a MT cell plays a crucial role. We propose a recurrent neural model showing how feature integration and selection can be combined into one common architecture to explain these findings. The key features of the model are the computation of 1D and 2D motion in model area V1 subpopulations that are integrated in model MT cells using feedforward and feedback processing. Our results are also in line with findings concerning the solution of the aperture problem. Conclusions/Significance We propose a new neural model for MT pattern computation and motion disambiguation that is based on a combination of feature selection and integration. The model can explain a range of recent neurophysiological findings including temporally dynamic behaviour. PMID:21814543

Virtual lock-and-key approach: the in silico revival of Fischer model by means of molecular descriptors.

PubMed

Lauria, Antonino; Tutone, Marco; Almerico, Anna Maria

2011-09-01

In the last years the application of computational methodologies in the medicinal chemistry fields has found an amazing development. All the efforts were focused on the searching of new leads featuring a close affinity on a specific biological target. Thus, different molecular modeling approaches in simulation of molecular behavior for a specific biological target were employed. In spite of the increasing reliability of computational methodologies, not always the designed lead, once synthesized and screened, are suitable for the chosen biological target. To give another chance to these compounds, this work tries to resume the old concept of Fischer lock-and-key model. The same can be done for the "re-purposing" of old drugs. In fact, it is known that drugs may have many physiological targets, therefore it may be useful to identify them. This aspect, called "polypharmacology", is known to be therapeutically essential in the different treatments. The proposed protocol, the virtual lock-and-key approach (VLKA), consists in the "virtualization" of biological targets through the respectively known inhibitors. In order to release a real lock it is necessary the key fits the pins of the lock. The molecular descriptors could be considered as pins. A tested compound can be considered a potential inhibitor of a biological target if the values of its molecular descriptors fall in the calculated range values for the set of known inhibitors. The proposed protocol permits to transform a biological target in a "lock model" starting from its known inhibitors. To release a real lock all pins must fit. In the proposed protocol, it was supposed that the higher is the number of fit pins, the higher will be the affinity to the considered biological target. Therefore, each biological target was converted in a sequence of "weighted" molecular descriptor range values (locks) by using the structural features of the known inhibitors. Each biological target lock was tested by performing a molecular descriptors "fitting" on known inhibitors not used in the model construction (keys or test set). The results showed a good predictive capability of the protocol (confidence level 80%). This method gives interesting and convenient results because of the user-defined descriptors and biological targets choice in the process of new inhibitors discovery. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Hexafluoroisopropyl alcohol mediated synthesis of 2,3-dihydro-4H-pyrido[1,2-a]pyrimidin-4-ones

PubMed Central

Alam, Mohammad A.; Alsharif, Zakeyah; Alkhattabi, Hessa; Jones, Derika; Delancey, Evan; Gottsponer, Adam; Yang, Tianhong

2016-01-01

An efficient synthesis of novel 2,3-dihydro-4H-pyrido[1,2-a]pyrimidin-4-ones has been reported. Inexpensive and readily available substrates, environmentally benign reaction condition, and product formation up to quantitative yield are the key features of this methodology. Products are formed by the aza-Michael addition followed by intramolecular acyl substitution in a domino process. The polar nature and strong hydrogen bond donor capability of 1,1,1,3,3,3-hexafluoropropan-2-ol is pivotal in this cascade protocol. PMID:27805054

A review of clinical practice guidelines for lung cancer

PubMed Central

Ball, David; Silvestri, Gerard A.

2013-01-01

Clinical practice guidelines are important evidence-based resources to guide complex clinical decision making. However, it is challenging for health professionals to keep abreast available guidelines and to know how and where to access relevant guidelines. This review examines currently available guidelines for lung cancer published in the English language. Important key features are listed for each identified guideline. The methodology, approaches to dissemination and implementation, and associated resources are summarised. General challenges in the area of guideline development are highlighted. The potential to collaborate more widely across lung cancer guideline developers by sharing literature searches and assessments is discussed. PMID:24163752

Statechart-based design controllers for FPGA partial reconfiguration

NASA Astrophysics Data System (ADS)

Łabiak, Grzegorz; Wegrzyn, Marek; Rosado Muñoz, Alfredo

2015-09-01

Statechart diagram and UML technique can be a vital part of early conceptual modeling. At the present time there is no much support in hardware design methodologies for reconfiguration features of reprogrammable devices. Authors try to bridge the gap between imprecise UML model and formal HDL description. The key concept in author's proposal is to describe the behavior of the digital controller by statechart diagrams and to map some parts of the behavior into reprogrammable logic by means of group of states which forms sequential automaton. The whole process is illustrated by the example with experimental results.

Theoretical and Methodological Considerations in Cross-Generational Research on Parenting and Child Aggressive Behavior

PubMed Central

Dubow, Eric F.; Huesmann, L. Rowell; Boxer, Paul

2015-01-01

The four studies in this special issue represent important advances in research on the intergenerational transmission of aggressive behavior. In this commentary, we review the key features and findings of these studies, as well as our own cross-generational study of aggression, the Columbia County Longitudinal Study. Next, we consider important theoretical issues (e.g., defining and operationalizing “aggression” and “parenting”; assessing reciprocal effects of parenting and child aggression; identifying the ages at which aggression should be assessed across generations; broadening the investigation of contextual and individual factors). We then discuss several methodological issues (e.g., determining the most informative measurement intervals for assessing prospective effects; sampling considerations; measuring potential moderating and mediating variables that might explain cross-generational continuities and discontinuities in parenting and aggression). Finally, we raise implications of cross-generational research for designing interventions targeting the reduction and prevention of child aggression. PMID:12735400

Evaluating the trade-off between mechanical and electrochemical performance of separators for lithium-ion batteries: Methodology and application

NASA Astrophysics Data System (ADS)

Plaimer, Martin; Breitfuß, Christoph; Sinz, Wolfgang; Heindl, Simon F.; Ellersdorfer, Christian; Steffan, Hermann; Wilkening, Martin; Hennige, Volker; Tatschl, Reinhard; Geier, Alexander; Schramm, Christian; Freunberger, Stefan A.

2016-02-01

Lithium-ion batteries are in widespread use in electric vehicles and hybrid vehicles. Besides features like energy density, cost, lifetime, and recyclability the safety of a battery system is of prime importance. The separator material impacts all these properties and requires therefore an informed selection. The interplay between the mechanical and electrochemical properties as key selection criteria is investigated. Mechanical properties were investigated using tensile and puncture penetration tests at abuse relevant conditions. To investigate the electrochemical performance in terms of effective conductivity a method based on impedance spectroscopy was introduced. This methodology is applied to evaluate ten commercial separators which allows for a trade-off analysis of mechanical versus electrochemical performance. Based on the results, and in combination with other factors, this offers an effective approach to select suitable separators for automotive applications.

Mining Stable Roles in RBAC

NASA Astrophysics Data System (ADS)

Colantonio, Alessandro; di Pietro, Roberto; Ocello, Alberto; Verde, Nino Vincenzo

In this paper we address the problem of generating a candidate role-set for an RBAC configuration that enjoys the following two key features: it minimizes the administration cost; and, it is a stable candidate role-set. To achieve these goals, we implement a three steps methodology: first, we associate a weight to roles; second, we identify and remove the user-permission assignments that cannot belong to a role that have a weight exceeding a given threshold; third, we restrict the problem of finding a candidate role-set for the given system configuration using only the user-permission assignments that have not been removed in the second step—that is, user-permission assignments that belong to roles with a weight exceeding the given threshold. We formally show—proof of our results are rooted in graph theory—that this methodology achieves the intended goals. Finally, we discuss practical applications of our approach to the role mining problem.

A data mining methodology for predicting early stage Parkinson’s disease using non-invasive, high-dimensional gait sensor data

PubMed Central

Tucker, Conrad; Han, Yixiang; Nembhard, Harriet Black; Lewis, Mechelle; Lee, Wang-Chien; Sterling, Nicholas W; Huang, Xuemei

2017-01-01

Parkinson’s disease (PD) is the second most common neurological disorder after Alzheimer’s disease. Key clinical features of PD are motor-related and are typically assessed by healthcare providers based on qualitative visual inspection of a patient’s movement/gait/posture. More advanced diagnostic techniques such as computed tomography scans that measure brain function, can be cost prohibitive and may expose patients to radiation and other harmful effects. To mitigate these challenges, and open a pathway to remote patient-physician assessment, the authors of this work propose a data mining driven methodology that uses low cost, non-invasive sensors to model and predict the presence (or lack therefore) of PD movement abnormalities and model clinical subtypes. The study presented here evaluates the discriminative ability of non-invasive hardware and data mining algorithms to classify PD cases and controls. A 10-fold cross validation approach is used to compare several data mining algorithms in order to determine that which provides the most consistent results when varying the subject gait data. Next, the predictive accuracy of the data mining model is quantified by testing it against unseen data captured from a test pool of subjects. The proposed methodology demonstrates the feasibility of using non-invasive, low cost, hardware and data mining models to monitor the progression of gait features outside of the traditional healthcare facility, which may ultimately lead to earlier diagnosis of emerging neurological diseases. PMID:29541376

A general gridding, discretization, and coarsening methodology for modeling flow in porous formations with discrete geological features

NASA Astrophysics Data System (ADS)

Karimi-Fard, M.; Durlofsky, L. J.

2016-10-01

A comprehensive framework for modeling flow in porous media containing thin, discrete features, which could be high-permeability fractures or low-permeability deformation bands, is presented. The key steps of the methodology are mesh generation, fine-grid discretization, upscaling, and coarse-grid discretization. Our specialized gridding technique combines a set of intersecting triangulated surfaces by constructing approximate intersections using existing edges. This procedure creates a conforming mesh of all surfaces, which defines the internal boundaries for the volumetric mesh. The flow equations are discretized on this conforming fine mesh using an optimized two-point flux finite-volume approximation. The resulting discrete model is represented by a list of control-volumes with associated positions and pore-volumes, and a list of cell-to-cell connections with associated transmissibilities. Coarse models are then constructed by the aggregation of fine-grid cells, and the transmissibilities between adjacent coarse cells are obtained using flow-based upscaling procedures. Through appropriate computation of fracture-matrix transmissibilities, a dual-continuum representation is obtained on the coarse scale in regions with connected fracture networks. The fine and coarse discrete models generated within the framework are compatible with any connectivity-based simulator. The applicability of the methodology is illustrated for several two- and three-dimensional examples. In particular, we consider gas production from naturally fractured low-permeability formations, and transport through complex fracture networks. In all cases, highly accurate solutions are obtained with significant model reduction.

Institutions and national development in Latin America: a comparative study

PubMed Central

Portes, Alejandro; Smith, Lori D.

2013-01-01

We review the theoretical and empirical literatures on the role of institutions on national development as a prelude to present a more rigorous and measurable definition of the concept and a methodology to study this relationship at the national and subnational levels. The existing research literature features conflicting definitions of the concept of “institutions” and empirical tests based mostly on reputational indices, with countries as units of analysis. The present study’s methodology is based on a set of five strategic organizations studied comparatively in five Latin American countries. These include key federal agencies, public administrative organizations, and stock exchanges. Systematic analysis of results show a pattern of differences between economically-oriented institutions and those entrusted with providing basic services to the general population. Consistent differences in institutional quality also emerge across countries, despite similar levels of economic development. Using the algebraic methods developed by Ragin, we test six hypotheses about factors determining the developmental character of particular institutions. Implications of results for theory and for methodological practices of future studies in this field are discussed. PMID:26543407

A Guide to the Application of Probability Risk Assessment Methodology and Hazard Risk Frequency Criteria as a Hazard Control for the Use of the Mobile Servicing System on the International Space Station

NASA Astrophysics Data System (ADS)

D'silva, Oneil; Kerrison, Roger

2013-09-01

A key feature for the increased utilization of space robotics is to automate Extra-Vehicular manned space activities and thus significantly reduce the potential for catastrophic hazards while simultaneously minimizing the overall costs associated with manned space. The principal scope of the paper is to evaluate the use of industry standard accepted Probability risk/safety assessment (PRA/PSA) methodologies and Hazard Risk frequency Criteria as a hazard control. This paper illustrates the applicability of combining the selected Probability risk assessment methodology and hazard risk frequency criteria, in order to apply the necessary safety controls that allow for the increased use of the Mobile Servicing system (MSS) robotic system on the International Space Station. This document will consider factors such as component failure rate reliability, software reliability, and periods of operation and dormancy, fault tree analyses and their effects on the probability risk assessments. The paper concludes with suggestions for the incorporation of existing industry Risk/Safety plans to create an applicable safety process for future activities/programs

Dynamic Assessment and Response to Intervention

PubMed Central

Grigorenko, Elena L.

2013-01-01

This article compares and contrasts the main features of dynamic testing and assessment (DT/A) and response to intervention (RTI). The comparison is carried out along the following lines: (a) historical and empirical roots of both concepts, (b) premises underlying DT/A and RTI, (c) terms used in these concepts, (d) use of these concepts, (e) evidence in support of DT/A and RTI, and (f) expectations associated with each of the concepts. The main outcome of this comparison is a conclusion that both approaches belong to one family of methodologies in psychology and education whose key feature is in blending assessment and intervention in one holistic activity. Because DT/A has been around much longer than RTI, it makes sense for the proponents of RTI to consider both the accomplishments and frustrations that have accumulated in the field of DT/A. PMID:19073895

Current trends in the design of scaffolds for computer-aided tissue engineering.

PubMed

Giannitelli, S M; Accoto, D; Trombetta, M; Rainer, A

2014-02-01

Advances introduced by additive manufacturing have significantly improved the ability to tailor scaffold architecture, enhancing the control over microstructural features. This has led to a growing interest in the development of innovative scaffold designs, as testified by the increasing amount of research activities devoted to the understanding of the correlation between topological features of scaffolds and their resulting properties, in order to find architectures capable of optimal trade-off between often conflicting requirements (such as biological and mechanical ones). The main aim of this paper is to provide a review and propose a classification of existing methodologies for scaffold design and optimization in order to address key issues and help in deciphering the complex link between design criteria and resulting scaffold properties. Copyright © 2013 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Message Variability and Heterogeneity: A Core Challenge for Communication Research

PubMed Central

Slater, Michael D.; Peter, Jochen; Valkenberg, Patti

2015-01-01

Messages are central to human social experience, and pose key conceptual and methodological challenges in the study of communication. In response to these challenges, we outline a systematic approach to conceptualizing, operationalizing, and analyzing messages. At the conceptual level, we distinguish between two core aspects of messages: message variability (the defined and operationalized features of messages) and message heterogeneity (the undefined and unmeasured features of messages), and suggest preferred approaches to defining message variables. At the operational level, we identify message sampling, selection, and research design strategies responsive to issues of message variability and heterogeneity in experimental and survey research. At the analytical level, we highlight effective techniques to deal with message variability and heterogeneity. We conclude with seven recommendations to increase rigor in the study of communication through appropriately addressing the challenges presented by messages. PMID:26681816

MUSIC-Expected maximization gaussian mixture methodology for clustering and detection of task-related neuronal firing rates.

PubMed

Ortiz-Rosario, Alexis; Adeli, Hojjat; Buford, John A

2017-01-15

Researchers often rely on simple methods to identify involvement of neurons in a particular motor task. The historical approach has been to inspect large groups of neurons and subjectively separate neurons into groups based on the expertise of the investigator. In cases where neuron populations are small it is reasonable to inspect these neuronal recordings and their firing rates carefully to avoid data omissions. In this paper, a new methodology is presented for automatic objective classification of neurons recorded in association with behavioral tasks into groups. By identifying characteristics of neurons in a particular group, the investigator can then identify functional classes of neurons based on their relationship to the task. The methodology is based on integration of a multiple signal classification (MUSIC) algorithm to extract relevant features from the firing rate and an expectation-maximization Gaussian mixture algorithm (EM-GMM) to cluster the extracted features. The methodology is capable of identifying and clustering similar firing rate profiles automatically based on specific signal features. An empirical wavelet transform (EWT) was used to validate the features found in the MUSIC pseudospectrum and the resulting signal features captured by the methodology. Additionally, this methodology was used to inspect behavioral elements of neurons to physiologically validate the model. This methodology was tested using a set of data collected from awake behaving non-human primates. Copyright © 2016 Elsevier B.V. All rights reserved.

[Prediction of ETA oligopeptides antagonists from Glycine max based on in silico proteolysis].

PubMed

Qiao, Lian-Sheng; Jiang, Lu-di; Luo, Gang-Gang; Lu, Fang; Chen, Yan-Kun; Wang, Ling-Zhi; Li, Gong-Yu; Zhang, Yan-Ling

2017-02-01

Oligopeptides are one of the the key pharmaceutical effective constituents of traditional Chinese medicine(TCM). Systematic study on composition and efficacy of TCM oligopeptides is essential for the analysis of material basis and mechanism of TCM. In this study, the potential anti-hypertensive oligopeptides from Glycine max and their endothelin receptor A (ETA) antagonistic activity were discovered and predicted based on in silico technologies.Main protein sequences of G. max were collected and oligopeptides were obtained using in silico gastrointestinal tract proteolysis. Then, the pharmacophore of ETA antagonistic peptides was constructed and included one hydrophobic feature, one ionizable negative feature, one ring aromatic feature and five excluded volumes. Meanwhile, three-dimensional structure of ETA was developed by homology modeling methods for further docking studies. According to docking analysis and consensus score, the key amino acid of GLN165 was identified for ETA antagonistic activity. And 27 oligopeptides from G. max were predicted as the potential ETA antagonists by pharmacophore and docking studies.In silico proteolysis could be used to analyze the protein sequences from TCM. According to combination of in silico proteolysis and molecular simulation, the biological activities of oligopeptides could be predicted rapidly based on the known TCM protein sequence. It might provide the methodology basis for rapidly and efficiently implementing the mechanism analysis of TCM oligopeptides. Copyright© by the Chinese Pharmaceutical Association.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

FY17 Status Report on Testing Supporting the Inclusion of Grade 91 Steel as an Acceptable Material for Application of the EPP Methodology

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

Messner, Mark C.; Sham, Sam; Wang, Yanli

This report summarizes the experiments performed in FY17 on Gr. 91 steels. The testing of Gr. 91 has technical significance because, currently, it is the only approved material for Class A construction that is strongly cyclic softening. Specific FY17 testing includes the following activities for Gr. 91 steel. First, two types of key feature testing have been initiated, including two-bar thermal ratcheting and Simplified Model Testing (SMT). The goal is to qualify the Elastic – Perfectly Plastic (EPP) design methodologies and to support incorporation of these rules for Gr. 91 into the ASME Division 5 Code. The preliminary SMT testmore » results show that Gr. 91 is most damaging when tested with compression hold mode under the SMT creep fatigue testing condition. Two-bar thermal ratcheting test results at a temperature range between 350 to 650o C were compared with the EPP strain limits code case evaluation, and the results show that the EPP strain limits code case is conservative. The material information obtained from these key feature tests can also be used to verify its material model. Second, to provide experimental data in support of the viscoplastic material model development at Argonne National Laboratory, selective tests were performed to evaluate the effect of cyclic softening on strain rate sensitivity and creep rates. The results show the prior cyclic loading history decreases the strain rate sensitivity and increases creep rates. In addition, isothermal cyclic stress-strain curves were generated at six different temperatures, and a nonisothermal thermomechanical testing was also performed to provide data to calibrate the viscoplastic material model.« less

A machine learning approach for the identification of key markers involved in brain development from single-cell transcriptomic data.

PubMed

Hu, Yongli; Hase, Takeshi; Li, Hui Peng; Prabhakar, Shyam; Kitano, Hiroaki; Ng, See Kiong; Ghosh, Samik; Wee, Lawrence Jin Kiat

2016-12-22

The ability to sequence the transcriptomes of single cells using single-cell RNA-seq sequencing technologies presents a shift in the scientific paradigm where scientists, now, are able to concurrently investigate the complex biology of a heterogeneous population of cells, one at a time. However, till date, there has not been a suitable computational methodology for the analysis of such intricate deluge of data, in particular techniques which will aid the identification of the unique transcriptomic profiles difference between the different cellular subtypes. In this paper, we describe the novel methodology for the analysis of single-cell RNA-seq data, obtained from neocortical cells and neural progenitor cells, using machine learning algorithms (Support Vector machine (SVM) and Random Forest (RF)). Thirty-eight key transcripts were identified, using the SVM-based recursive feature elimination (SVM-RFE) method of feature selection, to best differentiate developing neocortical cells from neural progenitor cells in the SVM and RF classifiers built. Also, these genes possessed a higher discriminative power (enhanced prediction accuracy) as compared commonly used statistical techniques or geneset-based approaches. Further downstream network reconstruction analysis was carried out to unravel hidden general regulatory networks where novel interactions could be further validated in web-lab experimentation and be useful candidates to be targeted for the treatment of neuronal developmental diseases. This novel approach reported for is able to identify transcripts, with reported neuronal involvement, which optimally differentiate neocortical cells and neural progenitor cells. It is believed to be extensible and applicable to other single-cell RNA-seq expression profiles like that of the study of the cancer progression and treatment within a highly heterogeneous tumour.

'Setting the guinea pigs free': towards a new model of community-led social marketing.

PubMed

Smith, A J; Henry, L

2009-09-01

To offer the opportunity to discuss the positive contribution of co-production approaches in the field of social marketing. Recognizing the ever-evolving theoretical base for social marketing, this article offers a brief commentary on the positive contribution of co-production approaches in this field. The authors outline their own move towards conceptualizing a community-led social marketing approach and describe some key features. This developing framework has been influenced by, and tested through, the Early Presentation of Cancer Symptoms Programme, a community-led social marketing approach to tackle health inequalities across priority neighbourhoods in North East Lincolnshire, UK. A blend of social marketing, community involvement and rapid improvement science methodologies are drawn upon. The approach involves not just a strong focus on involving communities in insight and consultation, but also adopts methods where they are in charge of the process of generating solutions. A series of monthly and pre/post measures have demonstrated improvements in awareness of symptoms, reported willingness to act and increases in presentation measured through service referrals. Key features of the approach involve shared ownership and a shift away from service-instigated change by enabling communities 'to do' through developing skills and confidence and the conditions to 'try out'. The approach highlights the contribution that co-production approaches have to offer social marketing activity. In order to maximize potential, it is important to consider ways of engaging communities effectively. Successful approaches include translating social marketing methodology into easy-to-use frameworks, involving communities in gathering and interpreting local data, and supporting communities to act as change agents by planning and carrying out activity. The range of impacts across organisational, health and social capital measures demonstrates that multiple and longer-lasting improvements can be achieved with successful approaches.

Testing earthquake source inversion methodologies

USGS Publications Warehouse

Page, M.; Mai, P.M.; Schorlemmer, D.

2011-01-01

Source Inversion Validation Workshop; Palm Springs, California, 11-12 September 2010; Nowadays earthquake source inversions are routinely performed after large earthquakes and represent a key connection between recorded seismic and geodetic data and the complex rupture process at depth. The resulting earthquake source models quantify the spatiotemporal evolution of ruptures. They are also used to provide a rapid assessment of the severity of an earthquake and to estimate losses. However, because of uncertainties in the data, assumed fault geometry and velocity structure, and chosen rupture parameterization, it is not clear which features of these source models are robust. Improved understanding of the uncertainty and reliability of earthquake source inversions will allow the scientific community to use the robust features of kinematic inversions to more thoroughly investigate the complexity of the rupture process and to better constrain other earthquakerelated computations, such as ground motion simulations and static stress change calculations.

Hypothesis-Testing Demands Trustworthy Data—A Simulation Approach to Inferential Statistics Advocating the Research Program Strategy

PubMed Central

Krefeld-Schwalb, Antonia; Witte, Erich H.; Zenker, Frank

2018-01-01

In psychology as elsewhere, the main statistical inference strategy to establish empirical effects is null-hypothesis significance testing (NHST). The recent failure to replicate allegedly well-established NHST-results, however, implies that such results lack sufficient statistical power, and thus feature unacceptably high error-rates. Using data-simulation to estimate the error-rates of NHST-results, we advocate the research program strategy (RPS) as a superior methodology. RPS integrates Frequentist with Bayesian inference elements, and leads from a preliminary discovery against a (random) H0-hypothesis to a statistical H1-verification. Not only do RPS-results feature significantly lower error-rates than NHST-results, RPS also addresses key-deficits of a “pure” Frequentist and a standard Bayesian approach. In particular, RPS aggregates underpowered results safely. RPS therefore provides a tool to regain the trust the discipline had lost during the ongoing replicability-crisis. PMID:29740363

Using Geographic Information Systems (GIS) to assess the role of the built environment in influencing obesity: a glossary.

PubMed

Thornton, Lukar E; Pearce, Jamie R; Kavanagh, Anne M

2011-07-01

Features of the built environment are increasingly being recognised as potentially important determinants of obesity. This has come about, in part, because of advances in methodological tools such as Geographic Information Systems (GIS). GIS has made the procurement of data related to the built environment easier and given researchers the flexibility to create a new generation of environmental exposure measures such as the travel time to the nearest supermarket or calculations of the amount of neighbourhood greenspace. Given the rapid advances in the availability of GIS data and the relative ease of use of GIS software, a glossary on the use of GIS to assess the built environment is timely. As a case study, we draw on aspects the food and physical activity environments as they might apply to obesity, to define key GIS terms related to data collection, concepts, and the measurement of environmental features.

Hypothesis-Testing Demands Trustworthy Data-A Simulation Approach to Inferential Statistics Advocating the Research Program Strategy.

PubMed

Krefeld-Schwalb, Antonia; Witte, Erich H; Zenker, Frank

2018-01-01

In psychology as elsewhere, the main statistical inference strategy to establish empirical effects is null-hypothesis significance testing (NHST). The recent failure to replicate allegedly well-established NHST-results, however, implies that such results lack sufficient statistical power, and thus feature unacceptably high error-rates. Using data-simulation to estimate the error-rates of NHST-results, we advocate the research program strategy (RPS) as a superior methodology. RPS integrates Frequentist with Bayesian inference elements, and leads from a preliminary discovery against a (random) H 0 -hypothesis to a statistical H 1 -verification. Not only do RPS-results feature significantly lower error-rates than NHST-results, RPS also addresses key-deficits of a "pure" Frequentist and a standard Bayesian approach. In particular, RPS aggregates underpowered results safely. RPS therefore provides a tool to regain the trust the discipline had lost during the ongoing replicability-crisis.

Functional equivalency inferred from "authoritative sources" in networks of homologous proteins.

PubMed

Natarajan, Shreedhar; Jakobsson, Eric

2009-06-12

A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods.

Functional Equivalency Inferred from “Authoritative Sources” in Networks of Homologous Proteins

PubMed Central

Natarajan, Shreedhar; Jakobsson, Eric

2009-01-01

A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods. PMID:19521530

Predicting the constitutive behavior of semi-solids via a direct finite element simulation: application to AA5182

NASA Astrophysics Data System (ADS)

Phillion, A. B.; Cockcroft, S. L.; Lee, P. D.

2009-07-01

The methodology of direct finite element (FE) simulation was used to predict the semi-solid constitutive behavior of an industrially important aluminum-magnesium alloy, AA5182. Model microstructures were generated that detail key features of the as-cast semi-solid: equiaxed-globular grains of random size and shape, interconnected liquid films, and pores at the triple-junctions. Based on the results of over fifty different simulations, a model-based constitutive relationship which includes the effects of the key microstructure features—fraction solid, grain size and fraction porosity—was derived using regression analysis. This novel constitutive equation was then validated via comparison with both the FE simulations and experimental stress/strain data. Such an equation can now be used to incorporate the effects of microstructure on the bulk semi-solid flow stress within a macro- scale process model.

Methodological Features of Educational System Modernization in the Context of the "Economy of Knowledge"

ERIC Educational Resources Information Center

Karpova, Natalia Konstantinovna; Uvarovsky, Alexander Pavlovich; Mareev, Vladimir Ivanovich; Petrova, Nina Petrovna; Borzilov, Yuri Petrovich

2016-01-01

The article is devoted to some methodological features of modernization in modern education in the context of "the knowledge economy" development which is aimed at shaping new mental potential of the modern state. Features and prerequisites for the emergence of the knowledge economy, the priorities of which include the development and…

System perspectives for mobile platform design in m-Health

NASA Astrophysics Data System (ADS)

Roveda, Janet M.; Fink, Wolfgang

2016-05-01

Advances in integrated circuit technologies have led to the integration of medical sensor front ends with data processing circuits, i.e., mobile platform design for wearable sensors. We discuss design methodologies for wearable sensor nodes and their applications in m-Health. From the user perspective, flexibility, comfort, appearance, fashion, ease-of-use, and visibility are key form factors. From the technology development point of view, high accuracy, low power consumption, and high signal to noise ratio are desirable features. From the embedded software design standpoint, real time data analysis algorithms, application and database interfaces are the critical components to create successful wearable sensor-based products.

Classification of electroencephalograph signals using time-frequency decomposition and linear discriminant analysis

NASA Astrophysics Data System (ADS)

Szuflitowska, B.; Orlowski, P.

2017-08-01

Automated detection system consists of two key steps: extraction of features from EEG signals and classification for detection of pathology activity. The EEG sequences were analyzed using Short-Time Fourier Transform and the classification was performed using Linear Discriminant Analysis. The accuracy of the technique was tested on three sets of EEG signals: epilepsy, healthy and Alzheimer's Disease. The classification error below 10% has been considered a success. The higher accuracy are obtained for new data of unknown classes than testing data. The methodology can be helpful in differentiation epilepsy seizure and disturbances in the EEG signal in Alzheimer's Disease.

Ultrasonic characterization of the fiber-matrix interfacial bond in aerospace composites.

PubMed

Aggelis, D G; Kleitsa, D; Matikas, T E

2013-01-01

The properties of advanced composites rely on the quality of the fiber-matrix bonding. Service-induced damage results in deterioration of bonding quality, seriously compromising the load-bearing capacity of the structure. While traditional methods to assess bonding are destructive, herein a nondestructive methodology based on shear wave reflection is numerically investigated. Reflection relies on the bonding quality and results in discernable changes in the received waveform. The key element is the "interphase" model material with varying stiffness. The study is an example of how computational methods enhance the understanding of delicate features concerning the nondestructive evaluation of materials used in advanced structures.

Improving applied roughness measurement of involute helical gears

NASA Astrophysics Data System (ADS)

Koulin, G.; Zhang, J.; Frazer, R. C.; Wilson, S. J.; Shaw, B. A.

2017-12-01

With improving gear design and manufacturing technology, improvement in metrology is necessary to provide reliable feedback to the designer and manufacturer. A recommended gear roughness measurement method is applied to a micropitting contact fatigue test gear. The development of wear and micropitting is reliably characterised at the sub-micron roughness level. Changes to the features of the localised surface texture are revealed and are related to key gear meshing positions. The application of the recommended methodology is shown to provide informative feedback to the gear designer in reference to the fundamental gear coordinate system, which is used in gear performance simulations such as tooth contact analysis.

Deterministic nonlinear phase gates induced by a single qubit

NASA Astrophysics Data System (ADS)

Park, Kimin; Marek, Petr; Filip, Radim

2018-05-01

We propose deterministic realizations of nonlinear phase gates by repeating a finite sequence of non-commuting Rabi interactions between a harmonic oscillator and only a single two-level ancillary qubit. We show explicitly that the key nonclassical features of the ideal cubic phase gate and the quartic phase gate are generated in the harmonic oscillator faithfully by our method. We numerically analyzed the performance of our scheme under realistic imperfections of the oscillator and the two-level system. The methodology is extended further to higher-order nonlinear phase gates. This theoretical proposal completes the set of operations required for continuous-variable quantum computation.

Health impact assessment of industrial development projects: a spatio-temporal visualization.

PubMed

Winkler, Mirko S; Krieger, Gary R; Divall, Mark J; Singer, Burton H; Utzinger, Jürg

2012-05-01

Development and implementation of large-scale industrial projects in complex eco-epidemiological settings typically require combined environmental, social and health impact assessments. We present a generic, spatio-temporal health impact assessment (HIA) visualization, which can be readily adapted to specific projects and key stakeholders, including poorly literate communities that might be affected by consequences of a project. We illustrate how the occurrence of a variety of complex events can be utilized for stakeholder communication, awareness creation, interactive learning as well as formulating HIA research and implementation questions. Methodological features are highlighted in the context of an iron ore development in a rural part of Africa.

Iris recognition based on key image feature extraction.

PubMed

Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

2008-01-01

In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

Accuracy and Calibration of Computational Approaches for Inpatient Mortality Predictive Modeling.

PubMed

Nakas, Christos T; Schütz, Narayan; Werners, Marcus; Leichtle, Alexander B

2016-01-01

Electronic Health Record (EHR) data can be a key resource for decision-making support in clinical practice in the "big data" era. The complete database from early 2012 to late 2015 involving hospital admissions to Inselspital Bern, the largest Swiss University Hospital, was used in this study, involving over 100,000 admissions. Age, sex, and initial laboratory test results were the features/variables of interest for each admission, the outcome being inpatient mortality. Computational decision support systems were utilized for the calculation of the risk of inpatient mortality. We assessed the recently proposed Acute Laboratory Risk of Mortality Score (ALaRMS) model, and further built generalized linear models, generalized estimating equations, artificial neural networks, and decision tree systems for the predictive modeling of the risk of inpatient mortality. The Area Under the ROC Curve (AUC) for ALaRMS marginally corresponded to the anticipated accuracy (AUC = 0.858). Penalized logistic regression methodology provided a better result (AUC = 0.872). Decision tree and neural network-based methodology provided even higher predictive performance (up to AUC = 0.912 and 0.906, respectively). Additionally, decision tree-based methods can efficiently handle Electronic Health Record (EHR) data that have a significant amount of missing records (in up to >50% of the studied features) eliminating the need for imputation in order to have complete data. In conclusion, we show that statistical learning methodology can provide superior predictive performance in comparison to existing methods and can also be production ready. Statistical modeling procedures provided unbiased, well-calibrated models that can be efficient decision support tools for predicting inpatient mortality and assigning preventive measures.

Nuclear thermal propulsion engine system design analysis code development

NASA Astrophysics Data System (ADS)

Pelaccio, Dennis G.; Scheil, Christine M.; Petrosky, Lyman J.; Ivanenok, Joseph F.

1992-01-01

A Nuclear Thermal Propulsion (NTP) Engine System Design Analyis Code has recently been developed to characterize key NTP engine system design features. Such a versatile, standalone NTP system performance and engine design code is required to support ongoing and future engine system and vehicle design efforts associated with proposed Space Exploration Initiative (SEI) missions of interest. Key areas of interest in the engine system modeling effort were the reactor, shielding, and inclusion of an engine multi-redundant propellant pump feed system design option. A solid-core nuclear thermal reactor and internal shielding code model was developed to estimate the reactor's thermal-hydraulic and physical parameters based on a prescribed thermal output which was integrated into a state-of-the-art engine system design model. The reactor code module has the capability to model graphite, composite, or carbide fuels. Key output from the model consists of reactor parameters such as thermal power, pressure drop, thermal profile, and heat generation in cooled structures (reflector, shield, and core supports), as well as the engine system parameters such as weight, dimensions, pressures, temperatures, mass flows, and performance. The model's overall analysis methodology and its key assumptions and capabilities are summarized in this paper.

BATSE gamma-ray burst line search. 2: Bayesian consistency methodology

NASA Technical Reports Server (NTRS)

Band, D. L.; Ford, L. A.; Matteson, J. L.; Briggs, M.; Paciesas, W.; Pendleton, G.; Preece, R.; Palmer, D.; Teegarden, B.; Schaefer, B.

1994-01-01

We describe a Bayesian methodology to evaluate the consistency between the reported Ginga and Burst and Transient Source Experiment (BATSE) detections of absorption features in gamma-ray burst spectra. Currently no features have been detected by BATSE, but this methodology will still be applicable if and when such features are discovered. The Bayesian methodology permits the comparison of hypotheses regarding the two detectors' observations and makes explicit the subjective aspects of our analysis (e.g., the quantification of our confidence in detector performance). We also present non-Bayesian consistency statistics. Based on preliminary calculations of line detectability, we find that both the Bayesian and non-Bayesian techniques show that the BATSE and Ginga observations are consistent given our understanding of these detectors.

From LCAs to simplified models: a generic methodology applied to wind power electricity.

PubMed

Padey, Pierryves; Girard, Robin; le Boulch, Denis; Blanc, Isabelle

2013-02-05

This study presents a generic methodology to produce simplified models able to provide a comprehensive life cycle impact assessment of energy pathways. The methodology relies on the application of global sensitivity analysis to identify key parameters explaining the impact variability of systems over their life cycle. Simplified models are built upon the identification of such key parameters. The methodology is applied to one energy pathway: onshore wind turbines of medium size considering a large sample of possible configurations representative of European conditions. Among several technological, geographical, and methodological parameters, we identified the turbine load factor and the wind turbine lifetime as the most influent parameters. Greenhouse Gas (GHG) performances have been plotted as a function of these key parameters identified. Using these curves, GHG performances of a specific wind turbine can be estimated, thus avoiding the undertaking of an extensive Life Cycle Assessment (LCA). This methodology should be useful for decisions makers, providing them a robust but simple support tool for assessing the environmental performance of energy systems.

Reliability in content analysis: The case of semantic feature norms classification.

PubMed

Bolognesi, Marianna; Pilgram, Roosmaryn; van den Heerik, Romy

2017-12-01

Semantic feature norms (e.g., STIMULUS: car → RESPONSE: ) are commonly used in cognitive psychology to look into salient aspects of given concepts. Semantic features are typically collected in experimental settings and then manually annotated by the researchers into feature types (e.g., perceptual features, taxonomic features, etc.) by means of content analyses-that is, by using taxonomies of feature types and having independent coders perform the annotation task. However, the ways in which such content analyses are typically performed and reported are not consistent across the literature. This constitutes a serious methodological problem that might undermine the theoretical claims based on such annotations. In this study, we first offer a review of some of the released datasets of annotated semantic feature norms and the related taxonomies used for content analysis. We then provide theoretical and methodological insights in relation to the content analysis methodology. Finally, we apply content analysis to a new dataset of semantic features and show how the method should be applied in order to deliver reliable annotations and replicable coding schemes. We tackle the following issues: (1) taxonomy structure, (2) the description of categories, (3) coder training, and (4) sustainability of the coding scheme-that is, comparison of the annotations provided by trained versus novice coders. The outcomes of the project are threefold: We provide methodological guidelines for semantic feature classification; we provide a revised and adapted taxonomy that can (arguably) be applied to both concrete and abstract concepts; and we provide a dataset of annotated semantic feature norms.

Methodology for Generating Conflict Scenarios by Time Shifting Recorded Traffic Data

NASA Technical Reports Server (NTRS)

Paglione, Mike; Oaks, Robert; Bilimoria, Karl D.

2003-01-01

A methodology is presented for generating conflict scenarios that can be used as test cases to estimate the operational performance of a conflict probe. Recorded air traffic data is time shifted to create traffic scenarios featuring conflicts with characteristic properties similar to those encountered in typical air traffic operations. First, a reference set of conflicts is obtained from trajectories that are computed using birth points and nominal flight plans extracted from recorded traffic data. Distributions are obtained for several primary properties (e.g., encounter angle) that are most likely to affect the performance of a conflict probe. A genetic algorithm is then utilized to determine the values of time shifts for the recorded track data so that the primary properties of conflicts generated by the time shifted data match those of the reference set. This methodology is successfully demonstrated using recorded traffic data for the Memphis Air Route Traffic Control Center; a key result is that the required time shifts are less than 5 min for 99% of the tracks. It is also observed that close matching of the primary properties used in this study additionally provides a good match for some other secondary properties.

A quantitative metric to identify critical elements within seafood supply networks.

PubMed

Plagányi, Éva E; van Putten, Ingrid; Thébaud, Olivier; Hobday, Alistair J; Innes, James; Lim-Camacho, Lilly; Norman-López, Ana; Bustamante, Rodrigo H; Farmery, Anna; Fleming, Aysha; Frusher, Stewart; Green, Bridget; Hoshino, Eriko; Jennings, Sarah; Pecl, Gretta; Pascoe, Sean; Schrobback, Peggy; Thomas, Linda

2014-01-01

A theoretical basis is required for comparing key features and critical elements in wild fisheries and aquaculture supply chains under a changing climate. Here we develop a new quantitative metric that is analogous to indices used to analyse food-webs and identify key species. The Supply Chain Index (SCI) identifies critical elements as those elements with large throughput rates, as well as greater connectivity. The sum of the scores for a supply chain provides a single metric that roughly captures both the resilience and connectedness of a supply chain. Standardised scores can facilitate cross-comparisons both under current conditions as well as under a changing climate. Identification of key elements along the supply chain may assist in informing adaptation strategies to reduce anticipated future risks posed by climate change. The SCI also provides information on the relative stability of different supply chains based on whether there is a fairly even spread in the individual scores of the top few key elements, compared with a more critical dependence on a few key individual supply chain elements. We use as a case study the Australian southern rock lobster Jasus edwardsii fishery, which is challenged by a number of climate change drivers such as impacts on recruitment and growth due to changes in large-scale and local oceanographic features. The SCI identifies airports, processors and Chinese consumers as the key elements in the lobster supply chain that merit attention to enhance stability and potentially enable growth. We also apply the index to an additional four real-world Australian commercial fishery and two aquaculture industry supply chains to highlight the utility of a systematic method for describing supply chains. Overall, our simple methodological approach to empirically-based supply chain research provides an objective method for comparing the resilience of supply chains and highlighting components that may be critical.

A Quantitative Metric to Identify Critical Elements within Seafood Supply Networks

PubMed Central

Plagányi, Éva E.; van Putten, Ingrid; Thébaud, Olivier; Hobday, Alistair J.; Innes, James; Lim-Camacho, Lilly; Norman-López, Ana; Bustamante, Rodrigo H.; Farmery, Anna; Fleming, Aysha; Frusher, Stewart; Green, Bridget; Hoshino, Eriko; Jennings, Sarah; Pecl, Gretta; Pascoe, Sean; Schrobback, Peggy; Thomas, Linda

2014-01-01

A theoretical basis is required for comparing key features and critical elements in wild fisheries and aquaculture supply chains under a changing climate. Here we develop a new quantitative metric that is analogous to indices used to analyse food-webs and identify key species. The Supply Chain Index (SCI) identifies critical elements as those elements with large throughput rates, as well as greater connectivity. The sum of the scores for a supply chain provides a single metric that roughly captures both the resilience and connectedness of a supply chain. Standardised scores can facilitate cross-comparisons both under current conditions as well as under a changing climate. Identification of key elements along the supply chain may assist in informing adaptation strategies to reduce anticipated future risks posed by climate change. The SCI also provides information on the relative stability of different supply chains based on whether there is a fairly even spread in the individual scores of the top few key elements, compared with a more critical dependence on a few key individual supply chain elements. We use as a case study the Australian southern rock lobster Jasus edwardsii fishery, which is challenged by a number of climate change drivers such as impacts on recruitment and growth due to changes in large-scale and local oceanographic features. The SCI identifies airports, processors and Chinese consumers as the key elements in the lobster supply chain that merit attention to enhance stability and potentially enable growth. We also apply the index to an additional four real-world Australian commercial fishery and two aquaculture industry supply chains to highlight the utility of a systematic method for describing supply chains. Overall, our simple methodological approach to empirically-based supply chain research provides an objective method for comparing the resilience of supply chains and highlighting components that may be critical. PMID:24633147

Design and development of a virtual reality simulator for advanced cardiac life support training.

PubMed

Vankipuram, Akshay; Khanal, Prabal; Ashby, Aaron; Vankipuram, Mithra; Gupta, Ashish; DrummGurnee, Denise; Josey, Karen; Smith, Marshall

2014-07-01

The use of virtual reality (VR) training tools for medical education could lead to improvements in the skills of clinicians while providing economic incentives for healthcare institutions. The use of VR tools can also mitigate some of the drawbacks currently associated with providing medical training in a traditional clinical environment such as scheduling conflicts and the need for specialized equipment (e.g., high-fidelity manikins). This paper presents the details of the framework and the development methodology associated with a VR-based training simulator for advanced cardiac life support, a time critical, team-based medical scenario. In addition, we also report the key findings of a usability study conducted to assess the efficacy of various features of this VR simulator through a postuse questionnaire administered to various care providers. The usability questionnaires were completed by two groups that used two different versions of the VR simulator. One version consisted of the VR trainer with it all its features and a minified version with certain immersive features disabled. We found an increase in usability scores from the minified group to the full VR group.

Automatic Feature Selection and Improved Classification in SICADA Counterfeit Electronics Detection

DTIC Science & Technology

2017-03-20

The SICADA methodology was developed to detect such counterfeit microelectronics by collecting power side channel data and applying machine learning...to identify counterfeits. This methodology has been extended to include a two-step automated feature selection process and now uses a one-class SVM...classifier. We describe this methodology and show results for empirical data collected from several types of Microchip dsPIC33F microcontrollers

The colloquial approach: An active learning technique

NASA Astrophysics Data System (ADS)

Arce, Pedro

1994-09-01

This paper addresses the very important problem of the effectiveness of teaching methodologies in fundamental engineering courses such as transport phenomena. An active learning strategy, termed the colloquial approach, is proposed in order to increase student involvement in the learning process. This methodology is a considerable departure from traditional methods that use solo lecturing. It is based on guided discussions, and it promotes student understanding of new concepts by directing the student to construct new ideas by building upon the current knowledge and by focusing on key cases that capture the essential aspects of new concepts. The colloquial approach motivates the student to participate in discussions, to develop detailed notes, and to design (or construct) his or her own explanation for a given problem. This paper discusses the main features of the colloquial approach within the framework of other current and previous techniques. Problem-solving strategies and the need for new textbooks and for future investigations based on the colloquial approach are also outlined.

Technological advancements and their importance for nematode identification

NASA Astrophysics Data System (ADS)

Ahmed, Mohammed; Sapp, Melanie; Prior, Thomas; Karssen, Gerrit; Back, Matthew Alan

2016-06-01

Nematodes represent a species-rich and morphologically diverse group of metazoans known to inhabit both aquatic and terrestrial environments. Their role as biological indicators and as key players in nutrient cycling has been well documented. Some plant-parasitic species are also known to cause significant losses to crop production. In spite of this, there still exists a huge gap in our knowledge of their diversity due to the enormity of time and expertise often involved in characterising species using phenotypic features. Molecular methodology provides useful means of complementing the limited number of reliable diagnostic characters available for morphology-based identification. We discuss herein some of the limitations of traditional taxonomy and how molecular methodologies, especially the use of high-throughput sequencing, have assisted in carrying out large-scale nematode community studies and characterisation of phytonematodes through rapid identification of multiple taxa. We also provide brief descriptions of some the current and almost-outdated high-throughput sequencing platforms and their applications in both plant nematology and soil ecology.

A 3D model retrieval approach based on Bayesian networks lightfield descriptor

NASA Astrophysics Data System (ADS)

Xiao, Qinhan; Li, Yanjun

2009-12-01

A new 3D model retrieval methodology is proposed by exploiting a novel Bayesian networks lightfield descriptor (BNLD). There are two key novelties in our approach: (1) a BN-based method for building lightfield descriptor; and (2) a 3D model retrieval scheme based on the proposed BNLD. To overcome the disadvantages of the existing 3D model retrieval methods, we explore BN for building a new lightfield descriptor. Firstly, 3D model is put into lightfield, about 300 binary-views can be obtained along a sphere, then Fourier descriptors and Zernike moments descriptors can be calculated out from binaryviews. Then shape feature sequence would be learned into a BN model based on BN learning algorithm; Secondly, we propose a new 3D model retrieval method by calculating Kullback-Leibler Divergence (KLD) between BNLDs. Beneficial from the statistical learning, our BNLD is noise robustness as compared to the existing methods. The comparison between our method and the lightfield descriptor-based approach is conducted to demonstrate the effectiveness of our proposed methodology.

Celluloid devils: a research study of male nurses in feature films.

PubMed

Stanley, David

2012-11-01

To report a study of how male nurses are portrayed in feature films. It was hypothesized that male nurses are frequently portrayed negatively or stereotypically in the film media, potentially having a negative impact on male nurse recruitment and the public's perception of male nurses. An interpretive, qualitative methodology guided by insights into hegemonic masculinity and structured around a set of collective case studies (films) was used to examine the portrayal of male nurses in feature films made in the Western world from 1900 to 2007. Over 36,000 feature film synopses were reviewed (via CINAHL, ProQuest and relevant movie-specific literature) for the keyword 'nurse' and 'nursing' with an additional search for films from 1900 to 2010 for the word 'male nurse'. Identified films were labelled as 'cases' and analysed collectively to determine key attributes related to men in nursing and explore them for the emergence of concepts and themes related to the image of male nurses in films. A total of 13 relevant cases (feature films) were identified with 12 being made in the USA. Most films portrayed male nurses negatively and in ways opposed to hegemonic masculinity, as effeminate, homosexual, homicidal, corrupt or incompetent. Few film images of male nurses show them in traditional masculine roles or as clinically competent or self-confident professionals.   Feature films predominantly portray male nurses negatively. Given the popularity of feature films, there may be negative effects on recruitment and on the public's perception of male nurses. © 2012 Blackwell Publishing Ltd.

A new approach for minimum phase output definition

NASA Astrophysics Data System (ADS)

Jahangiri, Fatemeh; Talebi, Heidar Ali; Menhaj, Mohammad Bagher; Ebenbauer, Christian

2017-01-01

This paper presents a novel method for output redefinition for linear systems. The approach also determines possible relative degrees for the systems corresponding to any new output vector. To guarantee the minimum phase property with a prescribed relative degree, a set of new conditions is introduced. A key feature of these conditions is that there is no need to any form of transformations which make the scheme suitable for optimisation problems in control to ensure the minimum phase property. Moreover, the results are useful for sensor placement problems and for obtaining minimum phase approximations of non-minimum phase systems. Numerical examples including an example of unmanned aerial vehicle systems are given to demonstrate the effectiveness of the methodology.

Standards for the user interface - Developing a user consensus. [for Space Station Information System

NASA Technical Reports Server (NTRS)

Moe, Karen L.; Perkins, Dorothy C.; Szczur, Martha R.

1987-01-01

The user support environment (USE) which is a set of software tools for a flexible standard interactive user interface to the Space Station systems, platforms, and payloads is described in detail. Included in the USE concept are a user interface language, a run time environment and user interface management system, support tools, and standards for human interaction methods. The goals and challenges of the USE are discussed as well as a methodology based on prototype demonstrations for involving users in the process of validating the USE concepts. By prototyping the key concepts and salient features of the proposed user interface standards, the user's ability to respond is greatly enhanced.

How Methodological Features Affect Effect Sizes in Education

ERIC Educational Resources Information Center

Cheung, Alan; Slavin, Robert

2016-01-01

As evidence-based reform becomes increasingly important in educational policy, it is becoming essential to understand how research design might contribute to reported effect sizes in experiments evaluating educational programs. The purpose of this study was to examine how methodological features such as types of publication, sample sizes, and…

Qualitative Research in PBL in Health Sciences Education: A Review

ERIC Educational Resources Information Center

Jin, Jun; Bridges, Susan

2016-01-01

Context: Qualitative methodologies are relatively new in health sciences education research, especially in the area of problem-based learning (PBL). A key advantage of qualitative approaches is the ability to gain in-depth, textured insights into educational phenomena. Key methodological issues arise, however, in terms of the strategies of…

The impact of feature selection on one and two-class classification performance for plant microRNAs.

PubMed

Khalifa, Waleed; Yousef, Malik; Saçar Demirci, Müşerref Duygu; Allmer, Jens

2016-01-01

MicroRNAs (miRNAs) are short nucleotide sequences that form a typical hairpin structure which is recognized by a complex enzyme machinery. It ultimately leads to the incorporation of 18-24 nt long mature miRNAs into RISC where they act as recognition keys to aid in regulation of target mRNAs. It is involved to determine miRNAs experimentally and, therefore, machine learning is used to complement such endeavors. The success of machine learning mostly depends on proper input data and appropriate features for parameterization of the data. Although, in general, two-class classification (TCC) is used in the field; because negative examples are hard to come by, one-class classification (OCC) has been tried for pre-miRNA detection. Since both positive and negative examples are currently somewhat limited, feature selection can prove to be vital for furthering the field of pre-miRNA detection. In this study, we compare the performance of OCC and TCC using eight feature selection methods and seven different plant species providing positive pre-miRNA examples. Feature selection was very successful for OCC where the best feature selection method achieved an average accuracy of 95.6%, thereby being ∼29% better than the worst method which achieved 66.9% accuracy. While the performance is comparable to TCC, which performs up to 3% better than OCC, TCC is much less affected by feature selection and its largest performance gap is ∼13% which only occurs for two of the feature selection methodologies. We conclude that feature selection is crucially important for OCC and that it can perform on par with TCC given the proper set of features.

Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption.

PubMed

Chandrasekaran, Jeyamala; Thiruvengadam, S J

2015-01-01

Owing to the growth of high performance network technologies, multimedia applications over the Internet are increasing exponentially. Applications like video conferencing, video-on-demand, and pay-per-view depend upon encryption algorithms for providing confidentiality. Video communication is characterized by distinct features such as large volume, high redundancy between adjacent frames, video codec compliance, syntax compliance, and application specific requirements. Naive approaches for video encryption encrypt the entire video stream with conventional text based cryptographic algorithms. Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. This research work aims at enhancing the speed of naive approaches through chaos based S-box design. Chaotic equations are popularly known for randomness, extreme sensitivity to initial conditions, and ergodicity. The proposed methodology employs two-dimensional discrete Henon map for (i) generation of dynamic and key-dependent S-box that could be integrated with symmetric algorithms like Blowfish and Data Encryption Standard (DES) and (ii) generation of one-time keys for simple substitution ciphers. The proposed design is tested for randomness, nonlinearity, avalanche effect, bit independence criterion, and key sensitivity. Experimental results confirm that chaos based S-box design and key generation significantly reduce the computational cost of video encryption with no compromise in security.

Ensemble of Chaotic and Naive Approaches for Performance Enhancement in Video Encryption

PubMed Central

Chandrasekaran, Jeyamala; Thiruvengadam, S. J.

2015-01-01

Owing to the growth of high performance network technologies, multimedia applications over the Internet are increasing exponentially. Applications like video conferencing, video-on-demand, and pay-per-view depend upon encryption algorithms for providing confidentiality. Video communication is characterized by distinct features such as large volume, high redundancy between adjacent frames, video codec compliance, syntax compliance, and application specific requirements. Naive approaches for video encryption encrypt the entire video stream with conventional text based cryptographic algorithms. Although naive approaches are the most secure for video encryption, the computational cost associated with them is very high. This research work aims at enhancing the speed of naive approaches through chaos based S-box design. Chaotic equations are popularly known for randomness, extreme sensitivity to initial conditions, and ergodicity. The proposed methodology employs two-dimensional discrete Henon map for (i) generation of dynamic and key-dependent S-box that could be integrated with symmetric algorithms like Blowfish and Data Encryption Standard (DES) and (ii) generation of one-time keys for simple substitution ciphers. The proposed design is tested for randomness, nonlinearity, avalanche effect, bit independence criterion, and key sensitivity. Experimental results confirm that chaos based S-box design and key generation significantly reduce the computational cost of video encryption with no compromise in security. PMID:26550603

Secure image retrieval with multiple keys

NASA Astrophysics Data System (ADS)

Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

2018-03-01

This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

A practical guide to assessing clinical decision-making skills using the key features approach.

PubMed

Farmer, Elizabeth A; Page, Gordon

2005-12-01

This paper in the series on professional assessment provides a practical guide to writing key features problems (KFPs). Key features problems test clinical decision-making skills in written or computer-based formats. They are based on the concept of critical steps or 'key features' in decision making and represent an advance on the older, less reliable patient management problem (PMP) formats. The practical steps in writing these problems are discussed and illustrated by examples. Steps include assembling problem-writing groups, selecting a suitable clinical scenario or problem and defining its key features, writing the questions, selecting question response formats, preparing scoring keys, reviewing item quality and item banking. The KFP format provides educators with a flexible approach to testing clinical decision-making skills with demonstrated validity and reliability when constructed according to the guidelines provided.

Ghost Hunting as a Means to Illustrate Scientific Methodology and Enhance Critical Thinking

ERIC Educational Resources Information Center

Rockwell, Steven C.

2012-01-01

The increasing popularity of television shows featuring paranormal investigations has led to a renewed enthusiasm in ghost hunting activities, and belief in the paranormal in general. These shows typically feature a group of investigators who, while claiming to utilize proper scientifically correct methodologies, violate many core scientific…

Eye-gaze and intent: Application in 3D interface control

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

Schryver, J.C.; Goldberg, J.H.

1993-06-01

Computer interface control is typically accomplished with an input ``device`` such as keyboard, mouse, trackball, etc. An input device translates a users input actions, such as mouse clicks and key presses, into appropriate computer commands. To control the interface, the user must first convert intent into the syntax of the input device. A more natural means of computer control is possible when the computer can directly infer user intent, without need of intervening input devices. We describe an application of eye-gaze-contingent control of an interactive three-dimensional (3D) user interface. A salient feature of the user interface is natural input, withmore » a heightened impression of controlling the computer directly by the mind. With this interface, input of rotation and translation are intuitive, whereas other abstract features, such as zoom, are more problematic to match with user intent. This paper describes successes with implementation to date, and ongoing efforts to develop a more sophisticated intent inferencing methodology.« less

Eye-gaze and intent: Application in 3D interface control

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

Schryver, J.C.; Goldberg, J.H.

1993-01-01

Computer interface control is typically accomplished with an input device'' such as keyboard, mouse, trackball, etc. An input device translates a users input actions, such as mouse clicks and key presses, into appropriate computer commands. To control the interface, the user must first convert intent into the syntax of the input device. A more natural means of computer control is possible when the computer can directly infer user intent, without need of intervening input devices. We describe an application of eye-gaze-contingent control of an interactive three-dimensional (3D) user interface. A salient feature of the user interface is natural input, withmore » a heightened impression of controlling the computer directly by the mind. With this interface, input of rotation and translation are intuitive, whereas other abstract features, such as zoom, are more problematic to match with user intent. This paper describes successes with implementation to date, and ongoing efforts to develop a more sophisticated intent inferencing methodology.« less

Mapping cattle trade routes in southern Somalia: a method for mobile livestock keeping systems.

PubMed

Tempia, S; Braidotti, F; Aden, H H; Abdulle, M H; Costagli, R; Otieno, F T

2010-12-01

The Somali economy is the only one in the world in which more than half the population is dependent on nomadic pastoralism. Trade typically involves drovers trekking animals over long distances to markets. A pilot approach for mapping trade routes was undertaken, using the Afmadow to Garissa routes in southern Somalia. The methodology included conducting a workshop with traders to gather preliminary information about the most-used routes and general husbandry practices and training selected drovers to collect data about key features along the routes, using hand-held global positioning system (GPS) devices, radio collar GPS and pictorial data forms. Collected data were then integrated into geographic information systems for analysis. The resultant spatial maps describe the Afmadow to Garissa routes, the speed of livestock movement along these routes and relevant environmental and social features affecting this speed. These data are useful for identifying critical control points for health screening along the routes, which may enable the establishment of a livestock certification system in nomadic pastoral environments.

Electromyogenic Artifacts and Electroencephalographic Inferences Revisited

PubMed Central

McMenamin, Brenton W.; Shackman, Alexander J.; Greischar, Lawrence L.; Davidson, Richard J.

2010-01-01

Recent years have witnessed a renewed interest in using oscillatory brain electrical activity to understand the neural bases of cognition and emotion. Electrical signals originating from pericranial muscles represent a profound threat to the validity of such research. Recently, McMenamin et al (2010) examined whether independent component analysis (ICA) provides a sensitive and specific means of correcting electromyogenic (EMG) artifacts. This report sparked the accompanying commentary (Olbrich, Jödicke, Sander, Himmerich & Hegerl, in press), and here we revisit the question of how EMG can alter inferences drawn from the EEG and what can be done to minimize its pernicious effects. Accordingly, we briefly summarize salient features of the EMG problem and review recent research investigating the utility of ICA for correcting EMG and other artifacts. We then directly address the key concerns articulated by Olbrich and provide a critique of their efforts at validating ICA. We conclude by identifying key areas for future methodological work and offer some practical recommendations for intelligently addressing EMG artifact. PMID:20981275

Evidence-based development and evaluation of mobile cognitive support apps for people on the autism spectrum: methodological conclusions from two R+D projects.

PubMed

Gyori, Miklos; Stefanik, Krisztina; Kanizsai-Nagy, Ildikó

2015-01-01

A growing body of evidence confirms that mobile digital devices have key potentials as assistive/educational tools for people with autism spectrum disorders. The aim of this paper is to outline key aspects of development and evaluation methodologies that build on, and provide systematic evidence on effects of using such apps. We rely on the results of two R+D projects, both using quantitative and qualitative methods to support development and to evaluate developed apps (n=54 and n=22). Analyzing methodological conclusions from these studies we outline some guidelines for an 'ideal' R+D methodology but we also point to important trade-offs between the need for best systematic evidence and the limitations on development time and costs. We see these trade-offs as a key issue to be resolved in this field.

Key topics in surgical research and methodology Thanos Athanasiou Key topics in surgical research and methodology , Haile Debas and Ara Darzi Springer Pages: 1090 £180 9783540719144 3540719148 [Formula: see text].

PubMed

2011-01-21

If the editors' intention was to produce a comprehensive text book that will be of value to healthcare professionals interested in surgical research and improvements in health care, they have succeeded.

Self-adaptive MOEA feature selection for classification of bankruptcy prediction data.

PubMed

Gaspar-Cunha, A; Recio, G; Costa, L; Estébanez, C

2014-01-01

Bankruptcy prediction is a vast area of finance and accounting whose importance lies in the relevance for creditors and investors in evaluating the likelihood of getting into bankrupt. As companies become complex, they develop sophisticated schemes to hide their real situation. In turn, making an estimation of the credit risks associated with counterparts or predicting bankruptcy becomes harder. Evolutionary algorithms have shown to be an excellent tool to deal with complex problems in finances and economics where a large number of irrelevant features are involved. This paper provides a methodology for feature selection in classification of bankruptcy data sets using an evolutionary multiobjective approach that simultaneously minimise the number of features and maximise the classifier quality measure (e.g., accuracy). The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. The methodology was applied to four different sets of data. The obtained results showed the utility of using the self-adaptation of the classifier.

Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data

PubMed Central

Gaspar-Cunha, A.; Recio, G.; Costa, L.; Estébanez, C.

2014-01-01

Bankruptcy prediction is a vast area of finance and accounting whose importance lies in the relevance for creditors and investors in evaluating the likelihood of getting into bankrupt. As companies become complex, they develop sophisticated schemes to hide their real situation. In turn, making an estimation of the credit risks associated with counterparts or predicting bankruptcy becomes harder. Evolutionary algorithms have shown to be an excellent tool to deal with complex problems in finances and economics where a large number of irrelevant features are involved. This paper provides a methodology for feature selection in classification of bankruptcy data sets using an evolutionary multiobjective approach that simultaneously minimise the number of features and maximise the classifier quality measure (e.g., accuracy). The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. The methodology was applied to four different sets of data. The obtained results showed the utility of using the self-adaptation of the classifier. PMID:24707201

Combining familiarity and landscape features helps break down the barriers between movements and home ranges in a non-territorial large herbivore.

PubMed

Marchand, Pascal; Garel, Mathieu; Bourgoin, Gilles; Duparc, Antoine; Dubray, Dominique; Maillard, Daniel; Loison, Anne

2017-03-01

Recent advances in animal ecology have enabled identification of certain mechanisms that lead to the emergence of territories and home ranges from movements considered as unbounded. Among them, memory and familiarity have been identified as key parameters in cognitive maps driving animal navigation, but have been only recently used in empirical analyses of animal movements. At the same time, the influence of landscape features on movements of numerous species and on space division in territorial animals has been highlighted. Despite their potential as exocentric information in cognitive maps and as boundaries for home ranges, few studies have investigated their role in the design of home ranges of non-territorial species. Using step selection analyses, we assessed the relative contribution of habitat characteristics, familiarity preferences and linear landscape features in movement step selection of 60 GPS-collared Mediterranean mouflon Ovis gmelini musimon × Ovis sp. monitored in southern France. Then, we evaluated the influence of these movement-impeding landscape features on the design of home ranges by testing for a non-random distribution of these behavioural barriers within sections of space differentially used by mouflon. We reveal that familiarity and landscape features are key determinants of movements, relegating to a lower level certain habitat constraints (e.g. food/cover trade-off) that we had previously identified as important for this species. Mouflon generally avoid crossing both anthropogenic (i.e. roads, tracks and hiking trails) and natural landscape features (i.e. ridges, talwegs and forest edges) while moving in the opposite direction, preferentially toward familiar areas. These specific behaviours largely depend on the relative position of each movement step regarding distance to the landscape features or level of familiarity in the surroundings. We also revealed cascading consequences on the design of home ranges in which most landscape features were excluded from cores and relegated to the peripheral areas. These results provide crucial information on landscape connectivity in a context of marked habitat fragmentation. They also call for more research on the role of landscape features in the emergence of home ranges in non-territorial species using recent methodological developments bridging the gap between movements and space use patterns. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Chemometric strategy for modeling metabolic biological space along the gastrointestinal tract and assessing microbial influences.

PubMed

Martin, François-Pierre J; Montoliu, Ivan; Kochhar, Sunil; Rezzi, Serge

2010-12-01

Over the past decade, the analysis of metabolic data with advanced chemometric techniques has offered the potential to explore functional relationships among biological compartments in relation to the structure and function of the intestine. However, the employed methodologies, generally based on regression modeling techniques, have given emphasis to region-specific metabolic patterns, while providing only limited insights into the spatiotemporal metabolic features of the complex gastrointestinal system. Hence, novel approaches are needed to analyze metabolic data to reconstruct the metabolic biological space associated with the evolving structures and functions of an organ such as the gastrointestinal tract. Here, we report the application of multivariate curve resolution (MCR) methodology to model metabolic relationships along the gastrointestinal compartments in relation to its structure and function using data from our previous metabonomic analysis. The method simultaneously summarizes metabolite occurrence and contribution to continuous metabolic signatures of the different biological compartments of the gut tract. This methodology sheds new light onto the complex web of metabolic interactions with gut symbionts that modulate host cell metabolism in surrounding gut tissues. In the future, such an approach will be key to provide new insights into the dynamic onset of metabolic deregulations involved in region-specific gastrointestinal disorders, such as Crohn's disease or ulcerative colitis.

A novel MALDI–TOF based methodology for genotyping single nucleotide polymorphisms

PubMed Central

Blondal, Thorarinn; Waage, Benedikt G.; Smarason, Sigurdur V.; Jonsson, Frosti; Fjalldal, Sigridur B.; Stefansson, Kari; Gulcher, Jeffery; Smith, Albert V.

2003-01-01

A new MALDI–TOF based detection assay was developed for analysis of single nucleotide polymorphisms (SNPs). It is a significant modification on the classic three-step minisequencing method, which includes a polymerase chain reaction (PCR), removal of excess nucleotides and primers, followed by primer extension in the presence of dideoxynucleotides using modified thermostable DNA polymerase. The key feature of this novel assay is reliance upon deoxynucleotide mixes, lacking one of the nucleotides at the polymorphic position. During primer extension in the presence of depleted nucleotide mixes, standard thermostable DNA polymerases dissociate from the template at positions requiring a depleted nucleotide; this principal was harnessed to create a genotyping assay. The assay design requires a primer- extension primer having its 3′-end one nucleotide upstream from the interrogated site. The assay further utilizes the same DNA polymerase in both PCR and the primer extension step. This not only simplifies the assay but also greatly reduces the cost per genotype compared to minisequencing methodology. We demonstrate accurate genotyping using this methodology for two SNPs run in both singleplex and duplex reactions. We term this assay nucleotide depletion genotyping (NUDGE). Nucleotide depletion genotyping could be extended to other genotyping assays based on primer extension such as detection by gel or capillary electrophoresis. PMID:14654708

Design for dependability: A simulation-based approach. Ph.D. Thesis, 1993

NASA Technical Reports Server (NTRS)

Goswami, Kumar K.

1994-01-01

This research addresses issues in simulation-based system level dependability analysis of fault-tolerant computer systems. The issues and difficulties of providing a general simulation-based approach for system level analysis are discussed and a methodology that address and tackle these issues is presented. The proposed methodology is designed to permit the study of a wide variety of architectures under various fault conditions. It permits detailed functional modeling of architectural features such as sparing policies, repair schemes, routing algorithms as well as other fault-tolerant mechanisms, and it allows the execution of actual application software. One key benefit of this approach is that the behavior of a system under faults does not have to be pre-defined as it is normally done. Instead, a system can be simulated in detail and injected with faults to determine its failure modes. The thesis describes how object-oriented design is used to incorporate this methodology into a general purpose design and fault injection package called DEPEND. A software model is presented that uses abstractions of application programs to study the behavior and effect of software on hardware faults in the early design stage when actual code is not available. Finally, an acceleration technique that combines hierarchical simulation, time acceleration algorithms and hybrid simulation to reduce simulation time is introduced.

Results of a Demonstration Assessment of Passive System Reliability Utilizing the Reliability Method for Passive Systems (RMPS)

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

Bucknor, Matthew; Grabaskas, David; Brunett, Acacia

2015-04-26

Advanced small modular reactor designs include many advantageous design features such as passively driven safety systems that are arguably more reliable and cost effective relative to conventional active systems. Despite their attractiveness, a reliability assessment of passive systems can be difficult using conventional reliability methods due to the nature of passive systems. Simple deviations in boundary conditions can induce functional failures in a passive system, and intermediate or unexpected operating modes can also occur. As part of an ongoing project, Argonne National Laboratory is investigating various methodologies to address passive system reliability. The Reliability Method for Passive Systems (RMPS), amore » systematic approach for examining reliability, is one technique chosen for this analysis. This methodology is combined with the Risk-Informed Safety Margin Characterization (RISMC) approach to assess the reliability of a passive system and the impact of its associated uncertainties. For this demonstration problem, an integrated plant model of an advanced small modular pool-type sodium fast reactor with a passive reactor cavity cooling system is subjected to a station blackout using RELAP5-3D. This paper discusses important aspects of the reliability assessment, including deployment of the methodology, the uncertainty identification and quantification process, and identification of key risk metrics.« less

Development and application of a new grey dynamic hierarchy analysis system (GDHAS) for evaluating urban ecological security.

PubMed

Shao, Chaofeng; Tian, Xiaogang; Guan, Yang; Ju, Meiting; Xie, Qiang

2013-05-21

Selecting indicators based on the characteristics and development trends of a given study area is essential for building a framework for assessing urban ecological security. However, few studies have focused on how to select the representative indicators systematically, and quantitative research is lacking. We developed an innovative quantitative modeling approach called the grey dynamic hierarchy analytic system (GDHAS) for both the procedures of indicator selection and quantitative assessment of urban ecological security. Next, a systematic methodology based on the GDHAS is developed to assess urban ecological security comprehensively and dynamically. This assessment includes indicator selection, driving force-pressure-state-impact-response (DPSIR) framework building, and quantitative evaluation. We applied this systematic methodology to assess the urban ecological security of Tianjin, which is a typical coastal super megalopolis and the industry base in China. This case study highlights the key features of our approach. First, 39 representative indicators are selected for the evaluation index system from 62 alternative ones available through the GDHAS. Second, the DPSIR framework is established based on the indicators selected, and the quantitative assessment of the eco-security of Tianjin is conducted. The results illustrate the following: urban ecological security of Tianjin in 2008 was in alert level but not very stable; the driving force and pressure subsystems were in good condition, but the eco-security levels of the remainder of the subsystems were relatively low; the pressure subsystem was the key to urban ecological security; and 10 indicators are defined as the key indicators for five subsystems. These results can be used as the basis for urban eco-environmental management.

Development and Application of a New Grey Dynamic Hierarchy Analysis System (GDHAS) for Evaluating Urban Ecological Security

PubMed Central

Shao, Chaofeng; Tian, Xiaogang; Guan, Yang; Ju, Meiting; Xie, Qiang

2013-01-01

Selecting indicators based on the characteristics and development trends of a given study area is essential for building a framework for assessing urban ecological security. However, few studies have focused on how to select the representative indicators systematically, and quantitative research is lacking. We developed an innovative quantitative modeling approach called the grey dynamic hierarchy analytic system (GDHAS) for both the procedures of indicator selection and quantitative assessment of urban ecological security. Next, a systematic methodology based on the GDHAS is developed to assess urban ecological security comprehensively and dynamically. This assessment includes indicator selection, driving force-pressure-state-impact-response (DPSIR) framework building, and quantitative evaluation. We applied this systematic methodology to assess the urban ecological security of Tianjin, which is a typical coastal super megalopolis and the industry base in China. This case study highlights the key features of our approach. First, 39 representative indicators are selected for the evaluation index system from 62 alternative ones available through the GDHAS. Second, the DPSIR framework is established based on the indicators selected, and the quantitative assessment of the eco-security of Tianjin is conducted. The results illustrate the following: urban ecological security of Tianjin in 2008 was in alert level but not very stable; the driving force and pressure subsystems were in good condition, but the eco-security levels of the remainder of the subsystems were relatively low; the pressure subsystem was the key to urban ecological security; and 10 indicators are defined as the key indicators for five subsystems. These results can be used as the basis for urban eco-environmental management. PMID:23698700

Model-based assist feature insertion for sub-40nm memory device

NASA Astrophysics Data System (ADS)

Suh, Sungsoo; Lee, Suk-joo; Choi, Seong-woon; Lee, Sung-Woo; Park, Chan-hoon

2009-04-01

Many issues need to be resolved for a production-worthy model based assist feature insertion flow for single and double exposure patterning process to extend low k1 process at 193 nm immersion technology. Model based assist feature insertion is not trivial to implement either for single and double exposure patterning compared to rule based methods. As shown in Fig. 1, pixel based mask inversion technology in itself has difficulties in mask writing and inspection although it presents as one of key technology to extend single exposure for contact layer. Thus far, inversion technology is tried as a cooptimization of target mask to simultaneously generate optimized main and sub-resolution assists features for a desired process window. Alternatively, its technology can also be used to optimize for a target feature after an assist feature types are inserted in order to simplify the mask complexity. Simplification of inversion mask is one of major issue with applying inversion technology to device development even if a smaller mask feature can be fabricated since the mask writing time is also a major factor. As shown in Figure 2, mask writing time may be a limiting factor in determining whether or not an inversion solution is viable. It can be reasoned that increased number of shot counts relates to increase in margin for inversion methodology. On the other hand, there is a limit on how complex a mask can be in order to be production worthy. There is also source and mask co-optimization which influences the final mask patterns and assist feature sizes and positions for a given target. In this study, we will discuss assist feature insertion methods for sub 40-nm technology.

The role of health informatics in clinical audit: part of the problem or key to the solution?

PubMed

Georgiou, Andrew; Pearson, Michael

2002-05-01

The concepts of quality assurance (for which clinical audit is an essential part), evaluation and clinical governance each depend on the ability to derive and record measurements that describe clinical performance. Rapid IT developments have raised many new possibilities for managing health care. They have allowed for easier collection and processing of data in greater quantities. These developments have encouraged the growth of quality assurance as a key feature of health care delivery. In the past most of the emphasis has been on hospital information systems designed predominantly for the administration of patients and the management of financial performance. Large, hi-tech information system capacity does not guarantee quality information. The task of producing information that can be confidently used to monitor the quality of clinical care requires attention to key aspects of the design and operation of the audit. The Myocardial Infarction National Audit Project (MINAP) utilizes an IT-based system to collect and process data on large numbers of patients and make them readily available to contributing hospitals. The project shows that IT systems that employ rigorous health informatics methodologies can do much to improve the monitoring and provision of health care.

Multi-modal image registration: matching MRI with histology

NASA Astrophysics Data System (ADS)

Alic, Lejla; Haeck, Joost C.; Klein, Stefan; Bol, Karin; van Tiel, Sandra T.; Wielopolski, Piotr A.; Bijster, Magda; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.; de Jong, Marion

2010-03-01

Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co registration of MR images with histological sections. This work proposes a methodology to establish a detailed 3D relation between histology sections and in vivo MRI tumor data. The key features of the methodology are a very dense histological sampling (up to 100 histology slices per tumor), mutual information based non-rigid B-spline registration, the utilization of the whole 3D data sets, and the exploitation of an intermediate ex vivo MRI. In this proof of concept paper, the methodology was applied to one tumor. We found that, after registration, the visual alignment of tumor borders and internal structures was fairly accurate. Utilizing the intermediate ex vivo MRI, it was possible to account for changes caused by the excision of the tumor: we observed a tumor expansion of 20%. Also the effects of fixation, dehydration and histological sectioning could be determined: 26% shrinkage of the tumor was found. The annotation of viable tissue, performed in histology and transformed to the in vivo MRI, matched clearly with high intensity regions in MRI. With this methodology, histological annotation can be directly related to the corresponding in vivo MRI. This is a vital step for the evaluation of the feasibility of multi-spectral MRI to depict histological groundtruth.

Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.

PubMed

Pereira, Sérgio; Meier, Raphael; McKinley, Richard; Wiest, Roland; Alves, Victor; Silva, Carlos A; Reyes, Mauricio

2018-02-01

Machine learning systems are achieving better performances at the cost of becoming increasingly complex. However, because of that, they become less interpretable, which may cause some distrust by the end-user of the system. This is especially important as these systems are pervasively being introduced to critical domains, such as the medical field. Representation Learning techniques are general methods for automatic feature computation. Nevertheless, these techniques are regarded as uninterpretable "black boxes". In this paper, we propose a methodology to enhance the interpretability of automatically extracted machine learning features. The proposed system is composed of a Restricted Boltzmann Machine for unsupervised feature learning, and a Random Forest classifier, which are combined to jointly consider existing correlations between imaging data, features, and target variables. We define two levels of interpretation: global and local. The former is devoted to understanding if the system learned the relevant relations in the data correctly, while the later is focused on predictions performed on a voxel- and patient-level. In addition, we propose a novel feature importance strategy that considers both imaging data and target variables, and we demonstrate the ability of the approach to leverage the interpretability of the obtained representation for the task at hand. We evaluated the proposed methodology in brain tumor segmentation and penumbra estimation in ischemic stroke lesions. We show the ability of the proposed methodology to unveil information regarding relationships between imaging modalities and extracted features and their usefulness for the task at hand. In both clinical scenarios, we demonstrate that the proposed methodology enhances the interpretability of automatically learned features, highlighting specific learning patterns that resemble how an expert extracts relevant data from medical images. Copyright © 2017 Elsevier B.V. All rights reserved.

Improving the adaptability of WHO evidence-informed guidelines for nutrition actions: results of a mixed methods evaluation.

PubMed

Dedios, Maria Cecilia; Esperato, Alexo; De-Regil, Luz Maria; Peña-Rosas, Juan Pablo; Norris, Susan L

2017-03-21

Over the past decade, the World Health Organization (WHO) has implemented a standardized, evidence-informed guideline development process to assure technically sound and policy-relevant guidelines. This study is an independent evaluation of the adaptability of the guidelines produced by the Evidence and Programme Guidance unit, at the Department of Nutrition for Health and Development (NHD). The study systematizes the lessons learned by the NHD group at WHO. We used a mixed methods approach to determine the adaptability of the nutrition guidelines. Adaptability was defined as having two components; methodological quality and implementability of guidelines. Additionally, we gathered recommendations to improve future guideline development in nutrition actions for health and development. Data sources for this evaluation were official documentation and feedback (both qualitative and quantitative) from key stakeholders involved in the development of nutrition guidelines. The qualitative data was collected through a desk review and two waves of semi-structured interviews (n = 12) and was analyzed through axial coding. Guideline adaptability was assessed quantitatively using two standardized instruments completed by key stakeholders. The Appraisal Guideline for Research and Evaluation questionnaire, version II was used to assess guideline quality (n = 6), while implementability was assessed with the electronic version of the GuideLine Implementability Appraisal (n = 7). The nutrition evidence-informed guideline development process has several strengths, among them are the appropriate management of conflicts of interest of guideline developers and the systematic use of high-quality evidence to inform the recommendations. These features contribute to increase the methodological quality of the guidelines. The key areas for improvement are the limited implementability of the recommendations, the lack of explicit and precise implementation advice in the guidelines and challenges related to collaborative work within interdisciplinary groups. Overall, our study found that the nutrition evidence-informed guidelines are of good methodological quality but that the implementability requires improvement. The recommendations to improve guideline adaptability address the guideline content, the dynamics shaping interdisciplinary work, and actions for implementation feasibility. As WHO relies heavily on a standardized procedure to develop guidelines, the lessons learned may be applicable to guideline development across the organization and to other groups developing guidelines.

Common Bolted Joint Analysis Tool

NASA Technical Reports Server (NTRS)

Imtiaz, Kauser

2011-01-01

Common Bolted Joint Analysis Tool (comBAT) is an Excel/VB-based bolted joint analysis/optimization program that lays out a systematic foundation for an inexperienced or seasoned analyst to determine fastener size, material, and assembly torque for a given design. Analysts are able to perform numerous what-if scenarios within minutes to arrive at an optimal solution. The program evaluates input design parameters, performs joint assembly checks, and steps through numerous calculations to arrive at several key margins of safety for each member in a joint. It also checks for joint gapping, provides fatigue calculations, and generates joint diagrams for a visual reference. Optimum fastener size and material, as well as correct torque, can then be provided. Analysis methodology, equations, and guidelines are provided throughout the solution sequence so that this program does not become a "black box:" for the analyst. There are built-in databases that reduce the legwork required by the analyst. Each step is clearly identified and results are provided in number format, as well as color-coded spelled-out words to draw user attention. The three key features of the software are robust technical content, innovative and user friendly I/O, and a large database. The program addresses every aspect of bolted joint analysis and proves to be an instructional tool at the same time. It saves analysis time, has intelligent messaging features, and catches operator errors in real time.

Transfer learning with convolutional neural networks for lesion classification on clinical breast tomosynthesis

NASA Astrophysics Data System (ADS)

Mendel, Kayla R.; Li, Hui; Sheth, Deepa; Giger, Maryellen L.

2018-02-01

With growing adoption of digital breast tomosynthesis (DBT) in breast cancer screening protocols, it is important to compare the performance of computer-aided diagnosis (CAD) in the diagnosis of breast lesions on DBT images compared to conventional full-field digital mammography (FFDM). In this study, we retrospectively collected FFDM and DBT images of 78 lesions from 76 patients, each containing lesions that were biopsy-proven as either malignant or benign. A square region of interest (ROI) was placed to fully cover the lesion on each FFDM, DBT synthesized 2D images, and DBT key slice images in the cranial-caudal (CC) and mediolateral-oblique (MLO) views. Features were extracted on each ROI using a pre-trained convolutional neural network (CNN). These features were then input to a support vector machine (SVM) classifier, and area under the ROC curve (AUC) was used as the figure of merit. We found that in both the CC view and MLO view, the synthesized 2D image performed best (AUC = 0.814, AUC = 0.881 respectively) in the task of lesion characterization. Small database size was a key limitation in this study, and could lead to overfitting in the application of the SVM classifier. In future work, we plan to expand this dataset and to explore more robust deep learning methodology such as fine-tuning.

Medical cost analysis: application to colorectal cancer data from the SEER Medicare database.

PubMed

Bang, Heejung

2005-10-01

Incompleteness is a key feature of most survival data. Numerous well established statistical methodologies and algorithms exist for analyzing life or failure time data. However, induced censorship invalidates the use of those standard analytic tools for some survival-type data such as medical costs. In this paper, some valid methods currently available for analyzing censored medical cost data are reviewed. Some cautionary findings under different assumptions are envisioned through application to medical costs from colorectal cancer patients. Cost analysis should be suitably planned and carefully interpreted under various meaningful scenarios even with judiciously selected statistical methods. This approach would be greatly helpful to policy makers who seek to prioritize health care expenditures and to assess the elements of resource use.

SURF Model Calibration Strategy

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

Menikoff, Ralph

2017-03-10

SURF and SURFplus are high explosive reactive burn models for shock initiation and propagation of detonation waves. They are engineering models motivated by the ignition & growth concept of high spots and for SURFplus a second slow reaction for the energy release from carbon clustering. A key feature of the SURF model is that there is a partial decoupling between model parameters and detonation properties. This enables reduced sets of independent parameters to be calibrated sequentially for the initiation and propagation regimes. Here we focus on a methodology for tting the initiation parameters to Pop plot data based on 1-Dmore » simulations to compute a numerical Pop plot. In addition, the strategy for tting the remaining parameters for the propagation regime and failure diameter is discussed.« less

Advanced Propulsion and TPS for a Rapidly-Prototyped CEV

NASA Astrophysics Data System (ADS)

Hudson, Gary C.

2005-02-01

Transformational Space Corporation (t/Space) is developing for NASA the initial designs for the Crew Exploration Vehicle family, focusing on a Launch CEV for transporting NASA and civilian passengers from Earth to orbit. The t/Space methodology is rapid prototyping of major vehicle systems, and deriving detailed specifications from the resulting hardware, avoiding "written-in-advance" specs that can force the costly invention of new capabilities simply to meet such specs. A key technology shared by the CEV family is Vapor Pressurized propulsion (Vapak) for simplicity and reliability, which provides electrical power, life support gas and a heat sink in addition to propulsion. The CEV family also features active transpiration cooling of re-entry surfaces (for reusability) backed up by passive thermal protection.

Multiagent robotic systems' ambient light sensor

NASA Astrophysics Data System (ADS)

Iureva, Radda A.; Maslennikov, Oleg S.; Komarov, Igor I.

2017-05-01

Swarm robotics is one of the fastest growing areas of modern technology. Being subclass of multi-agent systems it inherits the main part of scientific-methodological apparatus of construction and functioning of practically useful complexes, which consist of rather autonomous independent agents. Ambient light sensors (ALS) are widely used in robotics. But speaking about swarm robotics, the technology which has great number of specific features and is developing, we can't help mentioning that its important to use sensors on each robot not only in order to help it to get directionally oriented, but also to follow light emitted by robot-chief or to help to find the goal easier. Key words: ambient light sensor, swarm system, multiagent system, robotic system, robotic complexes, simulation modelling

I am going to make the most out of it! Italian university Credit Mobility Students' social representations of alcohol use during study abroad experiences.

PubMed

Aresi, Giovanni; Fattori, Francesco; Pozzi, Maura; Moore, Simon C

2016-09-01

The aim was to explore shared representations of alcohol use in students who were to travel abroad to study. Focus group data from Italian students ( N = 69) were collected. Analyses used Grounded Theory Methodology and were informed by the four key components of Social Representation Theory (cognition, emotion, attitude and behavioural intentions). The study abroad experience was described as one that would involve an increase in alcohol consumption compared to pre-departure levels. Reasons given included greater social and leisure opportunities involving alcohol, reduced social control and features of the host country environment. Opportunities to intervene and address risky alcohol use in this group are discussed.

Structural zeros in high-dimensional data with applications to microbiome studies.

PubMed

Kaul, Abhishek; Davidov, Ori; Peddada, Shyamal D

2017-07-01

This paper is motivated by the recent interest in the analysis of high-dimensional microbiome data. A key feature of these data is the presence of "structural zeros" which are microbes missing from an observation vector due to an underlying biological process and not due to error in measurement. Typical notions of missingness are unable to model these structural zeros. We define a general framework which allows for structural zeros in the model and propose methods of estimating sparse high-dimensional covariance and precision matrices under this setup. We establish error bounds in the spectral and Frobenius norms for the proposed estimators and empirically verify them with a simulation study. The proposed methodology is illustrated by applying it to the global gut microbiome data of Yatsunenko and others (2012. Human gut microbiome viewed across age and geography. Nature 486, 222-227). Using our methodology we classify subjects according to the geographical location on the basis of their gut microbiome. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The need for data science in epidemic modelling. Comment on: "Mathematical models to characterize early epidemic growth: A review" by Gerardo Chowell et al.

NASA Astrophysics Data System (ADS)

Danon, Leon; Brooks-Pollock, Ellen

2016-09-01

In their review, Chowell et al. consider the ability of mathematical models to predict early epidemic growth [1]. In particular, they question the central prediction of classical differential equation models that the number of cases grows exponentially during the early stages of an epidemic. Using examples including HIV and Ebola, they argue that classical models fail to capture key qualitative features of early growth and describe a selection of models that do capture non-exponential epidemic growth. An implication of this failure is that predictions may be inaccurate and unusable, highlighting the need for care when embarking upon modelling using classical methodology. There remains a lack of understanding of the mechanisms driving many observed epidemic patterns; we argue that data science should form a fundamental component of epidemic modelling, providing a rigorous methodology for data-driven approaches, rather than trying to enforce established frameworks. The need for refinement of classical models provides a strong argument for the use of data science, to identify qualitative characteristics and pinpoint the mechanisms responsible for the observed epidemic patterns.

Supplement to a Methodology for Succession Planning for Technical Experts

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

Kirk, Bernadette Lugue; Cain, Ronald A.; Agreda, Carla L.

This report complements A Methodology for Succession Planning for Technical Experts (Ron Cain, Shaheen Dewji, Carla Agreda, Bernadette Kirk, July 2017), which describes a draft methodology for identifying and evaluating the loss of key technical skills at nuclear operations facilities. This report targets the methodology for identifying critical skills, and the methodology is tested through interviews with selected subject matter experts.

Pedestrian detection in thermal images: An automated scale based region extraction with curvelet space validation

NASA Astrophysics Data System (ADS)

Lakshmi, A.; Faheema, A. G. J.; Deodhare, Dipti

2016-05-01

Pedestrian detection is a key problem in night vision processing with a dozen of applications that will positively impact the performance of autonomous systems. Despite significant progress, our study shows that performance of state-of-the-art thermal image pedestrian detectors still has much room for improvement. The purpose of this paper is to overcome the challenge faced by the thermal image pedestrian detectors, which employ intensity based Region Of Interest (ROI) extraction followed by feature based validation. The most striking disadvantage faced by the first module, ROI extraction, is the failed detection of cloth insulted parts. To overcome this setback, this paper employs an algorithm and a principle of region growing pursuit tuned to the scale of the pedestrian. The statistics subtended by the pedestrian drastically vary with the scale and deviation from normality approach facilitates scale detection. Further, the paper offers an adaptive mathematical threshold to resolve the problem of subtracting the background while extracting cloth insulated parts as well. The inherent false positives of the ROI extraction module are limited by the choice of good features in pedestrian validation step. One such feature is curvelet feature, which has found its use extensively in optical images, but has as yet no reported results in thermal images. This has been used to arrive at a pedestrian detector with a reduced false positive rate. This work is the first venture made to scrutinize the utility of curvelet for characterizing pedestrians in thermal images. Attempt has also been made to improve the speed of curvelet transform computation. The classification task is realized through the use of the well known methodology of Support Vector Machines (SVMs). The proposed method is substantiated with qualified evaluation methodologies that permits us to carry out probing and informative comparisons across state-of-the-art features, including deep learning methods, with six standard and in-house databases. With reference to deep learning, our algorithm exhibits comparable performance. More important is that it has significant lower requirements in terms of compute power and memory, thus making it more relevant for depolyment in resource constrained platforms with significant size, weight and power constraints.

Key-Aspects of Scientific Modeling Exemplified by School Science Models: Some Units for Teaching Contextualized Scientific Methodology

ERIC Educational Resources Information Center

Develaki, Maria

2016-01-01

Models and modeling are core elements of scientific methods and consequently also are of key importance for the conception and teaching of scientific methodology. The epistemology of models and its transfer and adaption to nature of science education are not, however, simple themes. We present some conceptual units in which school science models…

Second Language Listening Strategy Research: Methodological Challenges and Perspectives

ERIC Educational Resources Information Center

Santos, Denise; Graham, Suzanne; Vanderplank, Robert

2008-01-01

This paper explores methodological issues related to research into second language listening strategies. We argue that a number of central questions regarding research methodology in this line of enquiry are underexamined, and we engage in the discussion of three key methodological questions: (1) To what extent is a verbal report a valid and…

Automatic Road Sign Inventory Using Mobile Mapping Systems

NASA Astrophysics Data System (ADS)

Soilán, M.; Riveiro, B.; Martínez-Sánchez, J.; Arias, P.

2016-06-01

The periodic inspection of certain infrastructure features plays a key role for road network safety and preservation, and for developing optimal maintenance planning that minimize the life-cycle cost of the inspected features. Mobile Mapping Systems (MMS) use laser scanner technology in order to collect dense and precise three-dimensional point clouds that gather both geometric and radiometric information of the road network. Furthermore, time-stamped RGB imagery that is synchronized with the MMS trajectory is also available. In this paper a methodology for the automatic detection and classification of road signs from point cloud and imagery data provided by a LYNX Mobile Mapper System is presented. First, road signs are detected in the point cloud. Subsequently, the inventory is enriched with geometrical and contextual data such as orientation or distance to the trajectory. Finally, semantic content is given to the detected road signs. As point cloud resolution is insufficient, RGB imagery is used projecting the 3D points in the corresponding images and analysing the RGB data within the bounding box defined by the projected points. The methodology was tested in urban and road environments in Spain, obtaining global recall results greater than 95%, and F-score greater than 90%. In this way, inventory data is obtained in a fast, reliable manner, and it can be applied to improve the maintenance planning of the road network, or to feed a Spatial Information System (SIS), thus, road sign information can be available to be used in a Smart City context.

A sensitivity analysis for missing outcomes due to truncation by death under the matched-pairs design.

PubMed

Imai, Kosuke; Jiang, Zhichao

2018-04-29

The matched-pairs design enables researchers to efficiently infer causal effects from randomized experiments. In this paper, we exploit the key feature of the matched-pairs design and develop a sensitivity analysis for missing outcomes due to truncation by death, in which the outcomes of interest (e.g., quality of life measures) are not even well defined for some units (e.g., deceased patients). Our key idea is that if 2 nearly identical observations are paired prior to the randomization of the treatment, the missingness of one unit's outcome is informative about the potential missingness of the other unit's outcome under an alternative treatment condition. We consider the average treatment effect among always-observed pairs (ATOP) whose units exhibit no missing outcome regardless of their treatment status. The naive estimator based on available pairs is unbiased for the ATOP if 2 units of the same pair are identical in terms of their missingness patterns. The proposed sensitivity analysis characterizes how the bounds of the ATOP widen as the degree of the within-pair similarity decreases. We further extend the methodology to the matched-pairs design in observational studies. Our simulation studies show that informative bounds can be obtained under some scenarios when the proportion of missing data is not too large. The proposed methodology is also applied to the randomized evaluation of the Mexican universal health insurance program. An open-source software package is available for implementing the proposed research. Copyright © 2018 John Wiley & Sons, Ltd.

A new methodology for automated diagnosis of mild cognitive impairment (MCI) using magnetoencephalography (MEG).

PubMed

Amezquita-Sanchez, Juan P; Adeli, Anahita; Adeli, Hojjat

2016-05-15

Mild cognitive impairment (MCI) is a cognitive disorder characterized by memory impairment, greater than expected by age. A new methodology is presented to identify MCI patients during a working memory task using MEG signals. The methodology consists of four steps: In step 1, the complete ensemble empirical mode decomposition (CEEMD) is used to decompose the MEG signal into a set of adaptive sub-bands according to its contained frequency information. In step 2, a nonlinear dynamics measure based on permutation entropy (PE) analysis is employed to analyze the sub-bands and detect features to be used for MCI detection. In step 3, an analysis of variation (ANOVA) is used for feature selection. In step 4, the enhanced probabilistic neural network (EPNN) classifier is applied to the selected features to distinguish between MCI and healthy patients. The usefulness and effectiveness of the proposed methodology are validated using the sensed MEG data obtained experimentally from 18 MCI and 19 control patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Key Program Features to Enhance the School-to-Career Transition for Youth with Disabilities

ERIC Educational Resources Information Center

Doren, Bonnie; Yan, Min-Chi; Tu, Wei-Mo

2013-01-01

The purpose of the article was to identify key features within research-based school-to-career programs that were linked to positive employment outcomes for youth disabilities. Three key program features were identified and discussed that could be incorporated into the practices and programs of schools and communities to support the employment…

Methodological reviews of economic evaluations in health care: what do they target?

PubMed

Hutter, Maria-Florencia; Rodríguez-Ibeas, Roberto; Antonanzas, Fernando

2014-11-01

An increasing number of published studies of economic evaluations of health technologies have been reviewed and summarized with different purposes, among them to facilitate decision-making processes. These reviews have covered different aspects of economic evaluations, using a variety of methodological approaches. The aim of this study is to analyze the methodological characteristics of the reviews of economic evaluations in health care, published during the period 1990-2010, to identify their main features and the potential missing elements. This may help to develop a common procedure for elaborating these kinds of reviews. We performed systematic searches in electronic databases (Scopus, Medline and PubMed) of methodological reviews published in English, period 1990-2010. We selected the articles whose main purpose was to review and assess the methodology applied in the economic evaluation studies. We classified the data according to the study objectives, period of the review, number of reviewed studies, methodological and non-methodological items assessed, medical specialty, type of disease and technology, databases used for the review and their main conclusions. We performed a descriptive statistical analysis and checked how generalizability issues were considered in the reviews. We identified 76 methodological reviews, 42 published in the period 1990-2001 and 34 during 2002-2010. The items assessed most frequently (by 70% of the reviews) were perspective, type of economic study, uncertainty and discounting. The reviews also described the type of intervention and disease, funding sources, country in which the evaluation took place, type of journal and author's characteristics. Regarding the intertemporal comparison, higher frequencies were found in the second period for two key methodological items: the source of effectiveness data and the models used in the studies. However, the generalizability issues that apparently are creating a growing interest in the economic evaluation literature did not receive as much attention in the reviews of the second period. The remaining items showed similar frequencies in both periods. Increasingly more reviews of economic evaluation studies aim to analyze the application of methodological principles, and offer summaries of papers classified by either diseases or health technologies. These reviews are useful for finding literature trends, aims of studies and possible deficiencies in the implementation of methods of specific health interventions. As no significant methodological improvement was clearly detected in the two periods analyzed, it would be convenient to pay more attention to the methodological aspects of the reviews.

Extension of Companion Modeling Using Classification Learning

NASA Astrophysics Data System (ADS)

Torii, Daisuke; Bousquet, François; Ishida, Toru

Companion Modeling is a methodology of refining initial models for understanding reality through a role-playing game (RPG) and a multiagent simulation. In this research, we propose a novel agent model construction methodology in which classification learning is applied to the RPG log data in Companion Modeling. This methodology enables a systematic model construction that handles multi-parameters, independent of the modelers ability. There are three problems in applying classification learning to the RPG log data: 1) It is difficult to gather enough data for the number of features because the cost of gathering data is high. 2) Noise data can affect the learning results because the amount of data may be insufficient. 3) The learning results should be explained as a human decision making model and should be recognized by the expert as being the result that reflects reality. We realized an agent model construction system using the following two approaches: 1) Using a feature selction method, the feature subset that has the best prediction accuracy is identified. In this process, the important features chosen by the expert are always included. 2) The expert eliminates irrelevant features from the learning results after evaluating the learning model through a visualization of the results. Finally, using the RPG log data from the Companion Modeling of agricultural economics in northeastern Thailand, we confirm the capability of this methodology.

Fitting methods to paradigms: are ergonomics methods fit for systems thinking?

PubMed

Salmon, Paul M; Walker, Guy H; M Read, Gemma J; Goode, Natassia; Stanton, Neville A

2017-02-01

The issues being tackled within ergonomics problem spaces are shifting. Although existing paradigms appear relevant for modern day systems, it is worth questioning whether our methods are. This paper asks whether the complexities of systems thinking, a currently ubiquitous ergonomics paradigm, are outpacing the capabilities of our methodological toolkit. This is achieved through examining the contemporary ergonomics problem space and the extent to which ergonomics methods can meet the challenges posed. Specifically, five key areas within the ergonomics paradigm of systems thinking are focused on: normal performance as a cause of accidents, accident prediction, system migration, systems concepts and ergonomics in design. The methods available for pursuing each line of inquiry are discussed, along with their ability to respond to key requirements. In doing so, a series of new methodological requirements and capabilities are identified. It is argued that further methodological development is required to provide researchers and practitioners with appropriate tools to explore both contemporary and future problems. Practitioner Summary: Ergonomics methods are the cornerstone of our discipline. This paper examines whether our current methodological toolkit is fit for purpose given the changing nature of ergonomics problems. The findings provide key research and practice requirements for methodological development.

Transitioning Domain Analysis: An Industry Experience.

DTIC Science & Technology

1996-06-01

References 6 Implementation 6.1 Analysis of Operator Services’ Requirements Process 21 6.2 Preliminary Planning for FODA Training by SEI 21...an academic and industry partnership took feature oriented domain analysis ( FODA ) from a methodology that is still being defined to a well-documented...to pilot the use of the Software Engineering Institute (SEI) domain analysis methodology known as feature-oriented domain analysis ( FODA ). Supported

A time-responsive tool for informing policy making: rapid realist review.

PubMed

Saul, Jessie E; Willis, Cameron D; Bitz, Jennifer; Best, Allan

2013-09-05

A realist synthesis attempts to provide policy makers with a transferable theory that suggests a certain program is more or less likely to work in certain respects, for particular subjects, in specific kinds of situations. Yet realist reviews can require considerable and sustained investment over time, which does not always suit the time-sensitive demands of many policy decisions. 'Rapid Realist Review' methodology (RRR) has been developed as a tool for applying a realist approach to a knowledge synthesis process in order to produce a product that is useful to policy makers in responding to time-sensitive and/or emerging issues, while preserving the core elements of realist methodology. Using examples from completed RRRs, we describe key features of the RRR methodology, the resources required, and the strengths and limitations of the process. All aspects of an RRR are guided by both a local reference group, and a group of content experts. Involvement of knowledge users and external experts ensures both the usability of the review products, as well as their links to current practice. RRRs have proven useful in providing evidence for and making explicit what is known on a given topic, as well as articulating where knowledge gaps may exist. From the RRRs completed to date, findings broadly adhere to four (often overlapping) classifications: guiding rules for policy-making; knowledge quantification (i.e., the amount of literature available that identifies context, mechanisms, and outcomes for a given topic); understanding tensions/paradoxes in the evidence base; and, reinforcing or refuting beliefs and decisions taken. 'Traditional' realist reviews and RRRs have some key differences, which allow policy makers to apply each type of methodology strategically to maximize its utility within a particular local constellation of history, goals, resources, politics and environment. In particular, the RRR methodology is explicitly designed to engage knowledge users and review stakeholders to define the research questions, and to streamline the review process. In addition, results are presented with a focus on context-specific explanations for what works within a particular set of parameters rather than producing explanations that are potentially transferrable across contexts and populations. For policy makers faced with making difficult decisions in short time frames for which there is sufficient (if limited) published/research and practice-based evidence available, RRR provides a practical, outcomes-focused knowledge synthesis method.

Comprehensive Genetic Characterization of Intraprostatic Chronic Inflammation and Prostate Cancer in African American Men

DTIC Science & Technology

2017-09-01

with new methodologies of intratumoral phylogenetic analyses, will yield pivotal information in elucidating the key genes involved evolution of PCa...combined with both clinical and experimental genetic data produced by this study may empower patients and doctors to make personalized treatment decisions...sequencing, paired with new methodologies of intratumoral phylogenetic analyses, will yield pivotal information in elucidating the key genes involved

Analysis of the Source Physics Experiment SPE4 Prime Using State-Of Parallel Numerical Tools.

NASA Astrophysics Data System (ADS)

Vorobiev, O.; Ezzedine, S. M.; Antoun, T.; Glenn, L.

2015-12-01

This work describes a methodology used for large scale modeling of wave propagation from underground chemical explosions conducted at the Nevada National Security Site (NNSS) fractured granitic rock. We show that the discrete natures of rock masses as well as the spatial variability of the fabric of rock properties are very important to understand ground motions induced by underground explosions. In order to build a credible conceptual model of the subsurface we integrated the geological, geomechanical and geophysical characterizations conducted during recent test at the NNSS as well as historical data from the characterization during the underground nuclear test conducted at the NNSS. Because detailed site characterization is limited, expensive and, in some instances, impossible we have numerically investigated the effects of the characterization gaps on the overall response of the system. We performed several computational studies to identify the key important geologic features specific to fractured media mainly the joints characterized at the NNSS. We have also explored common key features to both geological environments such as saturation and topography and assess which characteristics affect the most the ground motion in the near-field and in the far-field. Stochastic representation of these features based on the field characterizations has been implemented into LLNL's Geodyn-L hydrocode. Simulations were used to guide site characterization efforts in order to provide the essential data to the modeling community. We validate our computational results by comparing the measured and computed ground motion at various ranges for the recently executed SPE4 prime experiment. We have also conducted a comparative study between SPE4 prime and previous experiments SPE1 and SPE3 to assess similarities and differences and draw conclusions on designing SPE5.

Single Channel EEG Artifact Identification Using Two-Dimensional Multi-Resolution Analysis.

PubMed

Taherisadr, Mojtaba; Dehzangi, Omid; Parsaei, Hossein

2017-12-13

As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and ocular artifacts generated by the user. This is specifically an issue during continuous EEG recording sessions, and is therefore a key step in using EEG signals for either physiological monitoring and diagnosis or brain-computer interface to identify such artifacts from useful EEG components. In this study, we aim to design a new generic framework in order to process and characterize EEG recording as a multi-component and non-stationary signal with the aim of localizing and identifying its component (e.g., artifact). In the proposed method, we gather three complementary algorithms together to enhance the efficiency of the system. Algorithms include time-frequency (TF) analysis and representation, two-dimensional multi-resolution analysis (2D MRA), and feature extraction and classification. Then, a combination of spectro-temporal and geometric features are extracted by combining key instantaneous TF space descriptors, which enables the system to characterize the non-stationarities in the EEG dynamics. We fit a curvelet transform (as a MRA method) to 2D TF representation of EEG segments to decompose the given space to various levels of resolution. Such a decomposition efficiently improves the analysis of the TF spaces with different characteristics (e.g., resolution). Our experimental results demonstrate that the combination of expansion to TF space, analysis using MRA, and extracting a set of suitable features and applying a proper predictive model is effective in enhancing the EEG artifact identification performance. We also compare the performance of the designed system with another common EEG signal processing technique-namely, 1D wavelet transform. Our experimental results reveal that the proposed method outperforms 1D wavelet.

CLAHRCs in practice: combined knowledge transfer and exchange strategies, cultural change, and experimentation.

PubMed

Soper, Bryony; Yaqub, Ohid; Hinrichs, Saba; Marjanovich, Sonja; Drabble, Samuel; Hanney, Stephen; Nolte, Ellen

2013-10-01

The nine NIHR CLAHRCs are collaborations between universities and local NHS organizations that seek to improve patient outcomes through the conduct and application of applied health research. The theoretical and practical context within which the CLAHRCs were set up was characterized by a considerable degree of uncertainty, and the CLAHRCs were established as a natural experiment. We adopted a formative and emergent evaluation approach. Drawing on in-depth, multi-method case studies of two CLAHRCs we explored how they pursued their remit by supporting efforts to increase the relevance and use of health research, and building relationships. Both CLAHRCs: strengthened local networks and relationships; built capacity in their local academic and NHS communities to undertake and use research that meets the needs of the service; developed research and implementation methodologies; and added to understanding of the complex relation between research and implementation. There was evidence of impact of CLAHRC projects on health and social care services. Informed by the literature on implementing collaborative research initiatives, knowledge transfer and exchange and cultural change, some key lessons can be drawn. The CLAHRCs pursued a strategy that can be categorized as one of flexible comprehensiveness; i.e. their programmes have been flexible and responsive and they have used a range of approaches that seek to match the diverse aspects of the complex issues they face. Key features include their work on combining a range of knowledge transfer and exchange strategies, their efforts to promote cultural change, and the freedom to experiment, learn and adapt. Although the CLAHRCs do not, by themselves, have the remit or resources to bring about wholesale service improvement in health care, they do have features that would allow them to play a key role in some of the wider initiatives that encourage innovation.

Improving the performance of univariate control charts for abnormal detection and classification

NASA Astrophysics Data System (ADS)

Yiakopoulos, Christos; Koutsoudaki, Maria; Gryllias, Konstantinos; Antoniadis, Ioannis

2017-03-01

Bearing failures in rotating machinery can cause machine breakdown and economical loss, if no effective actions are taken on time. Therefore, it is of prime importance to detect accurately the presence of faults, especially at their early stage, to prevent sequent damage and reduce costly downtime. The machinery fault diagnosis follows a roadmap of data acquisition, feature extraction and diagnostic decision making, in which mechanical vibration fault feature extraction is the foundation and the key to obtain an accurate diagnostic result. A challenge in this area is the selection of the most sensitive features for various types of fault, especially when the characteristics of failures are difficult to be extracted. Thus, a plethora of complex data-driven fault diagnosis methods are fed by prominent features, which are extracted and reduced through traditional or modern algorithms. Since most of the available datasets are captured during normal operating conditions, the last decade a number of novelty detection methods, able to work when only normal data are available, have been developed. In this study, a hybrid method combining univariate control charts and a feature extraction scheme is introduced focusing towards an abnormal change detection and classification, under the assumption that measurements under normal operating conditions of the machinery are available. The feature extraction method integrates the morphological operators and the Morlet wavelets. The effectiveness of the proposed methodology is validated on two different experimental cases with bearing faults, demonstrating that the proposed approach can improve the fault detection and classification performance of conventional control charts.

Randomized clinical trials in implant therapy: relationships among methodological, statistical, clinical, paratextual features and number of citations.

PubMed

Nieri, Michele; Clauser, Carlo; Franceschi, Debora; Pagliaro, Umberto; Saletta, Daniele; Pini-Prato, Giovanpaolo

2007-08-01

The aim of the present study was to investigate the relationships among reported methodological, statistical, clinical and paratextual variables of randomized clinical trials (RCTs) in implant therapy, and their influence on subsequent research. The material consisted of the RCTs in implant therapy published through the end of the year 2000. Methodological, statistical, clinical and paratextual features of the articles were assessed and recorded. The perceived clinical relevance was subjectively evaluated by an experienced clinician on anonymous abstracts. The impact on research was measured by the number of citations found in the Science Citation Index. A new statistical technique (Structural learning of Bayesian Networks) was used to assess the relationships among the considered variables. Descriptive statistics revealed that the reported methodology and statistics of RCTs in implant therapy were defective. Follow-up of the studies was generally short. The perceived clinical relevance appeared to be associated with the objectives of the studies and with the number of published images in the original articles. The impact on research was related to the nationality of the involved institutions and to the number of published images. RCTs in implant therapy (until 2000) show important methodological and statistical flaws and may not be appropriate for guiding clinicians in their practice. The methodological and statistical quality of the studies did not appear to affect their impact on practice and research. Bayesian Networks suggest new and unexpected relationships among the methodological, statistical, clinical and paratextual features of RCTs.

Impact and Crashworthiness Characteristics of Venera Type Landers for Future Venus Missions

NASA Technical Reports Server (NTRS)

Schroeder, Kevin; Bayandor, Javid; Samareh, Jamshid

2016-01-01

In this paper an in-depth investigation of the structural design of the Venera 9-14 landers is explored. A complete reverse engineering of the Venera lander was required. The lander was broken down into its fundamental components and analyzed. This provided in-sights into the hidden features of the design. A trade study was performed to find the sensitivity of the lander's overall mass to the variation of several key parameters. For the lander's legs, the location, length, configuration, and number are all parameterized. The size of the impact ring, the radius of the drag plate, and other design features are also parameterized, and all of these features were correlated to the change of mass of the lander. A multi-fidelity design tool used for further investigation of the parameterized lander was developed. As a design was passed down from one level to the next, the fidelity, complexity, accuracy, and run time of the model increased. The low-fidelity model was a highly nonlinear analytical model developed to rapidly predict the mass of each design. The medium and high fidelity models utilized an explicit finite element framework to investigate the performance of various landers upon impact with the surface under a range of landing conditions. This methodology allowed for a large variety of designs to be investigated by the analytical model, which identified designs with the optimum structural mass to payload ratio. As promising designs emerged, investigations in the following higher fidelity models were focused on establishing their reliability and crashworthiness. The developed design tool efficiently modelled and tested the best concepts for any scenario based on critical Venusian mission requirements and constraints. Through this program, the strengths and weaknesses inherent in the Venera-Type landers were thoroughly investigated. Key features identified for the design of robust landers will be used as foundations for the development of the next generation of landers for future exploration missions to Venus.

A neuromorphic approach to satellite image understanding

NASA Astrophysics Data System (ADS)

Partsinevelos, Panagiotis; Perakakis, Manolis

2014-05-01

Remote sensing satellite imagery provides high altitude, top viewing aspects of large geographic regions and as such the depicted features are not always easily recognizable. Nevertheless, geoscientists familiar to remote sensing data, gradually gain experience and enhance their satellite image interpretation skills. The aim of this study is to devise a novel computational neuro-centered classification approach for feature extraction and image understanding. Object recognition through image processing practices is related to a series of known image/feature based attributes including size, shape, association, texture, etc. The objective of the study is to weight these attribute values towards the enhancement of feature recognition. The key cognitive experimentation concern is to define the point when a user recognizes a feature as it varies in terms of the above mentioned attributes and relate it with their corresponding values. Towards this end, we have set up an experimentation methodology that utilizes cognitive data from brain signals (EEG) and eye gaze data (eye tracking) of subjects watching satellite images of varying attributes; this allows the collection of rich real-time data that will be used for designing the image classifier. Since the data are already labeled by users (using an input device) a first step is to compare the performance of various machine-learning algorithms on the collected data. On the long-run, the aim of this work would be to investigate the automatic classification of unlabeled images (unsupervised learning) based purely on image attributes. The outcome of this innovative process is twofold: First, in an abundance of remote sensing image datasets we may define the essential image specifications in order to collect the appropriate data for each application and improve processing and resource efficiency. E.g. for a fault extraction application in a given scale a medium resolution 4-band image, may be more effective than costly, multispectral, very high resolution imagery. Second, we attempt to relate the experienced against the non-experienced user understanding in order to indirectly assess the possible limits of purely computational systems. In other words, obtain the conceptual limits of computation vs human cognition concerning feature recognition from satellite imagery. Preliminary results of this pilot study show relations between collected data and differentiation of the image attributes which indicates that our methodology can lead to important results.

Effective Information Systems: What's the Secret?

ERIC Educational Resources Information Center

Kirkham, Sandi

1994-01-01

Argues that false assumptions about user needs implicit in methodologies for building information systems have resulted in inadequate and inflexible systems. Checkland's Soft Systems Methodology is examined as a useful alternative. Its fundamental features are described, and examples of models demonstrate how the methodology can facilitate…

Understanding Participatory Action Research: A Qualitative Research Methodology Option

ERIC Educational Resources Information Center

MacDonald, Cathy

2012-01-01

Participatory Action Research (PAR) is a qualitative research methodology option that requires further understanding and consideration. PAR is considered democratic, equitable, liberating, and life-enhancing qualitative inquiry that remains distinct from other qualitative methodologies (Kach & Kralik, 2006). Using PAR, qualitative features of an…

Mammographic phenotypes of breast cancer risk driven by breast anatomy

NASA Astrophysics Data System (ADS)

Gastounioti, Aimilia; Oustimov, Andrew; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

2017-03-01

Image-derived features of breast parenchymal texture patterns have emerged as promising risk factors for breast cancer, paving the way towards personalized recommendations regarding women's cancer risk evaluation and screening. The main steps to extract texture features of the breast parenchyma are the selection of regions of interest (ROIs) where texture analysis is performed, the texture feature calculation and the texture feature summarization in case of multiple ROIs. In this study, we incorporate breast anatomy in these three key steps by (a) introducing breast anatomical sampling for the definition of ROIs, (b) texture feature calculation aligned with the structure of the breast and (c) weighted texture feature summarization considering the spatial position and the underlying tissue composition of each ROI. We systematically optimize this novel framework for parenchymal tissue characterization in a case-control study with digital mammograms from 424 women. We also compare the proposed approach with a conventional methodology, not considering breast anatomy, recently shown to enhance the case-control discriminatory capacity of parenchymal texture analysis. The case-control classification performance is assessed using elastic-net regression with 5-fold cross validation, where the evaluation measure is the area under the curve (AUC) of the receiver operating characteristic. Upon optimization, the proposed breast-anatomy-driven approach demonstrated a promising case-control classification performance (AUC=0.87). In the same dataset, the performance of conventional texture characterization was found to be significantly lower (AUC=0.80, DeLong's test p-value<0.05). Our results suggest that breast anatomy may further leverage the associations of parenchymal texture features with breast cancer, and may therefore be a valuable addition in pipelines aiming to elucidate quantitative mammographic phenotypes of breast cancer risk.

Epidemiologic evidence on mobile phones and tumor risk: a review.

PubMed

Ahlbom, Anders; Feychting, Maria; Green, Adele; Kheifets, Leeka; Savitz, David A; Swerdlow, Anthony J

2009-09-01

This review summarizes and interprets epidemiologic evidence bearing on a possible causal relation between radiofrequency field exposure from mobile phone use and tumor risk. In the last few years, epidemiologic evidence on mobile phone use and the risk of brain and other tumors of the head in adults has grown in volume, geographic diversity of study settings, and the amount of data on longer-term users. However, some key methodologic problems remain, particularly with regard to selective nonresponse and inaccuracy and bias in recall of phone use. Most studies of glioma show small increased or decreased risks among users, although a subset of studies show appreciably elevated risks. We considered methodologic features that might explain the deviant results, but found no clear explanation. Overall the studies published to date do not demonstrate an increased risk within approximately 10 years of use for any tumor of the brain or any other head tumor. Despite the methodologic shortcomings and the limited data on long latency and long-term use, the available data do not suggest a causal association between mobile phone use and fast-growing tumors such as malignant glioma in adults (at least for tumors with short induction periods). For slow-growing tumors such as meningioma and acoustic neuroma, as well as for glioma among long-term users, the absence of association reported thus far is less conclusive because the observation period has been too short.

Traditional chinese medicine: an update on clinical evidence.

PubMed

Xue, Charlie C L; Zhang, Anthony L; Greenwood, Kenneth M; Lin, Vivian; Story, David F

2010-03-01

As an alternative medical system, Traditional Chinese Medicine (TCM) has been increasingly used over the last several decades. Such a consumer-driven development has resulted in introduction of education programs for practitioner training, development of product and practitioner regulation systems, and generation of an increasing interest in research. Significant efforts have been made in validating the quality, effectiveness, and safety of TCM interventions evidenced by a growing number of published trials and systematic reviews. Commonly, the results of these studies were inconclusive due to the lack of quality and quantity of the trials to answer specific and answerable clinical questions. The methodology of a randomized clinical trial (RCT) is not free from bias, and the unique features of TCM (such as individualization and holism) further complicate effective execution of RCTs in TCM therapies. Thus, data from limited RCTs and systematic reviews need to be interpreted with great caution. Nevertheless, until new and specific methodology is developed that can adequately address these methodology challenges for RCTs in TCM, evidence from quality RCTs and systematic reviews still holds the credibility of TCM in the scientific community. This article summarizes studies on TCM utilization, and regulatory and educational development with a focus on updating the TCM clinical evidence from RCTs and systematic reviews over the last decade. The key issues and challenges associated with evidence-based TCM developments are also explored.

Modeling Operations Other Than War: Non-Combatants in Combat Modeling

DTIC Science & Technology

1994-09-01

supposition that non-combatants are an essential feature in OOTW. The model proposal includes a methodology for civilian unit decision making . The model...combatants are an essential feature in OOTW. The model proposal includes a methodology for civilian unit decision making . Thi- model also includes...numerical example demonstrated that the model appeared to perform in an acceptable manner, in that it produced output within a reasonable range. During the

Summarizing Monte Carlo Results in Methodological Research.

ERIC Educational Resources Information Center

Harwell, Michael R.

Monte Carlo studies of statistical tests are prominently featured in the methodological research literature. Unfortunately, the information from these studies does not appear to have significantly influenced methodological practice in educational and psychological research. One reason is that Monte Carlo studies lack an overarching theory to guide…

Feature extraction through parallel Probabilistic Principal Component Analysis for heart disease diagnosis

NASA Astrophysics Data System (ADS)

Shah, Syed Muhammad Saqlain; Batool, Safeera; Khan, Imran; Ashraf, Muhammad Usman; Abbas, Syed Hussnain; Hussain, Syed Adnan

2017-09-01

Automatic diagnosis of human diseases are mostly achieved through decision support systems. The performance of these systems is mainly dependent on the selection of the most relevant features. This becomes harder when the dataset contains missing values for the different features. Probabilistic Principal Component Analysis (PPCA) has reputation to deal with the problem of missing values of attributes. This research presents a methodology which uses the results of medical tests as input, extracts a reduced dimensional feature subset and provides diagnosis of heart disease. The proposed methodology extracts high impact features in new projection by using Probabilistic Principal Component Analysis (PPCA). PPCA extracts projection vectors which contribute in highest covariance and these projection vectors are used to reduce feature dimension. The selection of projection vectors is done through Parallel Analysis (PA). The feature subset with the reduced dimension is provided to radial basis function (RBF) kernel based Support Vector Machines (SVM). The RBF based SVM serves the purpose of classification into two categories i.e., Heart Patient (HP) and Normal Subject (NS). The proposed methodology is evaluated through accuracy, specificity and sensitivity over the three datasets of UCI i.e., Cleveland, Switzerland and Hungarian. The statistical results achieved through the proposed technique are presented in comparison to the existing research showing its impact. The proposed technique achieved an accuracy of 82.18%, 85.82% and 91.30% for Cleveland, Hungarian and Switzerland dataset respectively.

Towards a taxonomy for integrated care: a mixed-methods study

PubMed Central

Valentijn, Pim P.; Boesveld, Inge C.; van der Klauw, Denise M.; Ruwaard, Dirk; Struijs, Jeroen N.; Molema, Johanna J.W.; Bruijnzeels, Marc A.; Vrijhoef, Hubertus JM.

2015-01-01

Introduction Building integrated services in a primary care setting is considered an essential important strategy for establishing a high-quality and affordable health care system. The theoretical foundations of such integrated service models are described by the Rainbow Model of Integrated Care, which distinguishes six integration dimensions (clinical, professional, organisational, system, functional and normative integration). The aim of the present study is to refine the Rainbow Model of Integrated Care by developing a taxonomy that specifies the underlying key features of the six dimensions. Methods First, a literature review was conducted to identify features for achieving integrated service delivery. Second, a thematic analysis method was used to develop a taxonomy of key features organised into the dimensions of the Rainbow Model of Integrated Care. Finally, the appropriateness of the key features was tested in a Delphi study among Dutch experts. Results The taxonomy consists of 59 key features distributed across the six integration dimensions of the Rainbow Model of Integrated Care. Key features associated with the clinical, professional, organisational and normative dimensions were considered appropriate by the experts. Key features linked to the functional and system dimensions were considered less appropriate. Discussion This study contributes to the ongoing debate of defining the concept and typology of integrated care. This taxonomy provides a development agenda for establishing an accepted scientific framework of integrated care from an end-user, professional, managerial and policy perspective. PMID:25759607

Towards a taxonomy for integrated care: a mixed-methods study.

PubMed

Valentijn, Pim P; Boesveld, Inge C; van der Klauw, Denise M; Ruwaard, Dirk; Struijs, Jeroen N; Molema, Johanna J W; Bruijnzeels, Marc A; Vrijhoef, Hubertus Jm

2015-01-01

Building integrated services in a primary care setting is considered an essential important strategy for establishing a high-quality and affordable health care system. The theoretical foundations of such integrated service models are described by the Rainbow Model of Integrated Care, which distinguishes six integration dimensions (clinical, professional, organisational, system, functional and normative integration). The aim of the present study is to refine the Rainbow Model of Integrated Care by developing a taxonomy that specifies the underlying key features of the six dimensions. First, a literature review was conducted to identify features for achieving integrated service delivery. Second, a thematic analysis method was used to develop a taxonomy of key features organised into the dimensions of the Rainbow Model of Integrated Care. Finally, the appropriateness of the key features was tested in a Delphi study among Dutch experts. The taxonomy consists of 59 key features distributed across the six integration dimensions of the Rainbow Model of Integrated Care. Key features associated with the clinical, professional, organisational and normative dimensions were considered appropriate by the experts. Key features linked to the functional and system dimensions were considered less appropriate. This study contributes to the ongoing debate of defining the concept and typology of integrated care. This taxonomy provides a development agenda for establishing an accepted scientific framework of integrated care from an end-user, professional, managerial and policy perspective.

FY16 Status Report on Development of Integrated EPP and SMT Design Methods

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

Jetter, R. I.; Sham, T. -L.; Wang, Y.

2016-08-01

The goal of the Elastic-Perfectly Plastic (EPP) combined integrated creep-fatigue damage evaluation approach is to incorporate a Simplified Model Test (SMT) data based approach for creep-fatigue damage evaluation into the EPP methodology to avoid the separate evaluation of creep and fatigue damage and eliminate the requirement for stress classification in current methods; thus greatly simplifying evaluation of elevated temperature cyclic service. The EPP methodology is based on the idea that creep damage and strain accumulation can be bounded by a properly chosen “pseudo” yield strength used in an elastic-perfectly plastic analysis, thus avoiding the need for stress classification. The originalmore » SMT approach is based on the use of elastic analysis. The experimental data, cycles to failure, is correlated using the elastically calculated strain range in the test specimen and the corresponding component strain is also calculated elastically. The advantage of this approach is that it is no longer necessary to use the damage interaction, or D-diagram, because the damage due to the combined effects of creep and fatigue are accounted in the test data by means of a specimen that is designed to replicate or bound the stress and strain redistribution that occurs in actual components when loaded in the creep regime. The reference approach to combining the two methodologies and the corresponding uncertainties and validation plans are presented. Results from recent key feature tests are discussed to illustrate the applicability of the EPP methodology and the behavior of materials at elevated temperature when undergoing stress and strain redistribution due to plasticity and creep.« less

Phosphorylation Reaction in cAPK Protein Kinase - Free Energy Quantum Mechanic/Molecular Mechanics Simulations.

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

Valiev, Marat; Yang, Jie; Adams, Joseph

2007-11-29

Protein kinases catalyze the transfer of the γ-phosphoryl group from ATP, a key regulatory process governing signalling pathways in eukaryotic cells. The structure of the active site in these enzymes is highly conserved implying common catalytic mechanism. In this work we investigate the reaction process in cAPK protein kinase (PKA) using a combined quantum mechanics and molecular mechanics approach. The novel computational features of our work include reaction pathway determination with nudged elastic band methodology and calculation of free energy profiles of the reaction process taking into account finite temperature fluctuations of the protein environment. We find that the transfermore » of the γ-phosphoryl group in the protein environment is an exothermic reaction with the reaction barrier of 15 kcal/mol.« less

SEACAS Theory Manuals: Part III. Finite Element Analysis in Nonlinear Solid Mechanics

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

Laursen, T.A.; Attaway, S.W.; Zadoks, R.I.

1999-03-01

This report outlines the application of finite element methodology to large deformation solid mechanics problems, detailing also some of the key technological issues that effective finite element formulations must address. The presentation is organized into three major portions: first, a discussion of finite element discretization from the global point of view, emphasizing the relationship between a virtual work principle and the associated fully discrete system, second, a discussion of finite element technology, emphasizing the important theoretical and practical features associated with an individual finite element; and third, detailed description of specific elements that enjoy widespread use, providing some examples ofmore » the theoretical ideas already described. Descriptions of problem formulation in nonlinear solid mechanics, nonlinear continuum mechanics, and constitutive modeling are given in three companion reports.« less

Methods for Retrievals of CO2 Mixing Ratios from JPL Laser Absorption Spectrometer Flights During a Summer 2011 Campaign

NASA Technical Reports Server (NTRS)

Menzies, Robert T.; Spiers, Gary D.; Jacob, Joseph C.

2013-01-01

The JPL airborne Laser Absorption Spectrometer instrument has been flown several times in the 2007-2011 time frame for the purpose of measuring CO2 mixing ratios in the lower atmosphere. This instrument employs CW laser transmitters and coherent detection receivers in the 2.05- micro m spectral region. The Integrated Path Differential Absorption (IPDA) method is used to retrieve weighted CO2 column mixing ratios. We present key features of the evolving LAS signal processing and data analysis algorithms and the calibration/validation methodology. Results from 2011 flights in various U.S. locations include observed mid-day CO2 drawdown in the Midwest and high spatial resolution plume detection during a leg downwind of the Four Corners power plant in New Mexico.

A data-driven feature extraction framework for predicting the severity of condition of congestive heart failure patients.

PubMed

Sideris, Costas; Alshurafa, Nabil; Pourhomayoun, Mohammad; Shahmohammadi, Farhad; Samy, Lauren; Sarrafzadeh, Majid

2015-01-01

In this paper, we propose a novel methodology for utilizing disease diagnostic information to predict severity of condition for Congestive Heart Failure (CHF) patients. Our methodology relies on a novel, clustering-based, feature extraction framework using disease diagnostic information. To reduce the dimensionality we identify disease clusters using cooccurence frequencies. We then utilize these clusters as features to predict patient severity of condition. We build our clustering and feature extraction algorithm using the 2012 National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP) which contains 7 million discharge records and ICD-9-CM codes. The proposed framework is tested on Ronald Reagan UCLA Medical Center Electronic Health Records (EHR) from 3041 patients. We compare our cluster-based feature set with another that incorporates the Charlson comorbidity score as a feature and demonstrate an accuracy improvement of up to 14% in the predictability of the severity of condition.

Multithreaded hybrid feature tracking for markerless augmented reality.

PubMed

Lee, Taehee; Höllerer, Tobias

2009-01-01

We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.

How Is This Flower Pollinated? A Polyclave Key to Use in Teaching.

ERIC Educational Resources Information Center

Tyrrell, Lucy

1989-01-01

Presents an identification method which uses the process of elimination to identify pollination systems. Provides the polyclave key, methodology for using the key, a sample worksheet, and abbreviation codes for pollination systems. (MVL)

Remote sensing and GIS techniques for assessment of the soil water content in order to improve agricultural practice and reduce the negative impact on groundwater: case study, agricultural area Ştefan cel Mare, Călăraşi County.

PubMed

Tevi, Giuliano; Tevi, Anca

2012-01-01

Traditional agricultural practices based on non-customized irrigation and soil fertilization are harmful for the environment, and may pose a risk for human health. By continuing the use of these practices, it is not possible to ensure effective land management, which might be acquired by using advanced satellite technology configured for modern agricultural development. The paper presents a methodology based on the correlation between remote sensing data and field observations, aiming to identify the key features and to establish an interpretation pattern for the inhomogeneity highlighted by the remote sensing data. Instead of using classical methods for the evaluation of land features (field analysis, measurements and mapping), the approach is to use high resolution multispectral and hyperspectral methods, in correlation with data processing and geographic information systems (GIS), in order to improve the agricultural practices and mitigate their environmental impact (soil and shallow aquifer).

Nonlinear modeling of wave-topography interactions, shear instabilities and shear induced wave breaking using vortex method

NASA Astrophysics Data System (ADS)

Guha, Anirban

2017-11-01

Theoretical studies on linear shear instabilities as well as different kinds of wave interactions often use simple velocity and/or density profiles (e.g. constant, piecewise) for obtaining good qualitative and quantitative predictions of the initial disturbances. Moreover, such simple profiles provide a minimal model to obtain a mechanistic understanding of shear instabilities. Here we have extended this minimal paradigm into nonlinear domain using vortex method. Making use of unsteady Bernoulli's equation in presence of linear shear, and extending Birkhoff-Rott equation to multiple interfaces, we have numerically simulated the interaction between multiple fully nonlinear waves. This methodology is quite general, and has allowed us to simulate diverse problems that can be essentially reduced to the minimal system with interacting waves, e.g. spilling and plunging breakers, stratified shear instabilities (Holmboe, Taylor-Caulfield, stratified Rayleigh), jet flows, and even wave-topography interaction problem like Bragg resonance. We found that the minimal models capture key nonlinear features (e.g. wave breaking features like cusp formation and roll-ups) which are observed in experiments and/or extensive simulations with smooth, realistic profiles.

Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics.

PubMed

Benedek, C; Descombes, X; Zerubia, J

2012-01-01

In this paper, we introduce a new probabilistic method which integrates building extraction with change detection in remotely sensed image pairs. A global optimization process attempts to find the optimal configuration of buildings, considering the observed data, prior knowledge, and interactions between the neighboring building parts. We present methodological contributions in three key issues: 1) We implement a novel object-change modeling approach based on Multitemporal Marked Point Processes, which simultaneously exploits low-level change information between the time layers and object-level building description to recognize and separate changed and unaltered buildings. 2) To answer the challenges of data heterogeneity in aerial and satellite image repositories, we construct a flexible hierarchical framework which can create various building appearance models from different elementary feature-based modules. 3) To simultaneously ensure the convergence, optimality, and computation complexity constraints raised by the increased data quantity, we adopt the quick Multiple Birth and Death optimization technique for change detection purposes, and propose a novel nonuniform stochastic object birth process which generates relevant objects with higher probability based on low-level image features.

Field Test of the Methodology for Succession Planning for Technical Experts

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

Cain, Ronald A.; Kirk, Bernadette Lugue; Agreda, Carla L.

This report complements A Methodology for Succession Planning for Technical Experts (Ron Cain, Shaheen Dewji, Carla Agreda, Bernadette Kirk, July 2017), which describes a methodology for identifying and evaluating the loss of key technical skills at nuclear operations facilities. This report targets the methodology for identifying critical skills, hereafter referred to as “core competencies”. The methodology has been field tested by interviewing selected retiring subject matter experts (SMEs).

Evolution of regional to global paddy rice mapping methods

NASA Astrophysics Data System (ADS)

Dong, J.; Xiao, X.

2016-12-01

Paddy rice agriculture plays an important role in various environmental issues including food security, water use, climate change, and disease transmission. However, regional and global paddy rice maps are surprisingly scarce and sporadic despite numerous efforts in paddy rice mapping algorithms and applications. In this presentation we would like to review the existing paddy rice mapping methods from the literatures ranging from the 1980s to 2015. In particular, we illustrated the evolution of these paddy rice mapping efforts, looking specifically at the future trajectory of paddy rice mapping methodologies. The biophysical features and growth phases of paddy rice were analyzed first, and feature selections for paddy rice mapping were analyzed from spectral, polarimetric, temporal, spatial, and textural aspects. We sorted out paddy rice mapping algorithms into four categories: 1) Reflectance data and image statistic-based approaches, 2) vegetation index (VI) data and enhanced image statistic-based approaches, 3) VI or RADAR backscatter-based temporal analysis approaches, and 4) phenology-based approaches through remote sensing recognition of key growth phases. The phenology-based approaches using unique features of paddy rice (e.g., transplanting) for mapping have been increasingly used in paddy rice mapping. Based on the literature review, we discussed a series of issues for large scale operational paddy rice mapping.

Contributions to the Characterization and Mitigation of Rotorcraft Brownout

NASA Astrophysics Data System (ADS)

Tritschler, John Kirwin

Rotorcraft brownout, the condition in which the flow field of a rotorcraft mobilizes sediment from the ground to generate a cloud that obscures the pilot's field of view, continues to be a significant hazard to civil and military rotorcraft operations. This dissertation presents methodologies for: (i) the systematic mitigation of rotorcraft brownout through operational and design strategies and (ii) the quantitative characterization of the visual degradation caused by a brownout cloud. In Part I of the dissertation, brownout mitigation strategies are developed through simulation-based brownout studies that are mathematically formulated within a numerical optimization framework. Two optimization studies are presented. The first study involves the determination of approach-to-landing maneuvers that result in reduced brownout severity. The second study presents a potential methodology for the design of helicopter rotors with improved brownout characteristics. The results of both studies indicate that the fundamental mechanisms underlying brownout mitigation are aerodynamic in nature, and the evolution of a ground vortex ahead of the rotor disk is seen to be a key element in the development of a brownout cloud. In Part II of the dissertation, brownout cloud characterizations are based upon the Modulation Transfer Function (MTF), a metric commonly used in the optics community for the characterization of imaging systems. The use of the MTF in experimentation is examined first, and the application of MTF calculation and interpretation methods to actual flight test data is described. The potential for predicting the MTF from numerical simulations is examined second, and an initial methodology is presented for the prediction of the MTF of a brownout cloud. Results from the experimental and analytical studies rigorously quantify the intuitively-known facts that the visual degradation caused by brownout is a space and time-dependent phenomenon, and that high spatial frequency features, i.e., fine-grained detail, are obscured before low spatial frequency features, i.e., large objects. As such, the MTF is a metric that is amenable to Handling Qualities (HQ) analyses.

Optimal design of experiments applied to headspace solid phase microextraction for the quantification of vicinal diketones in beer through gas chromatography-mass spectrometric detection.

PubMed

Leça, João M; Pereira, Ana C; Vieira, Ana C; Reis, Marco S; Marques, José C

2015-08-05

Vicinal diketones, namely diacetyl (DC) and pentanedione (PN), are compounds naturally found in beer that play a key role in the definition of its aroma. In lager beer, they are responsible for off-flavors (buttery flavor) and therefore their presence and quantification is of paramount importance to beer producers. Aiming at developing an accurate quantitative monitoring scheme to follow these off-flavor compounds during beer production and in the final product, the head space solid-phase microextraction (HS-SPME) analytical procedure was tuned through experiments planned in an optimal way and the final settings were fully validated. Optimal design of experiments (O-DOE) is a computational, statistically-oriented approach for designing experiences that are most informative according to a well-defined criterion. This methodology was applied for HS-SPME optimization, leading to the following optimal extraction conditions for the quantification of VDK: use a CAR/PDMS fiber, 5 ml of samples in 20 ml vial, 5 min of pre-incubation time followed by 25 min of extraction at 30 °C, with agitation. The validation of the final analytical methodology was performed using a matrix-matched calibration, in order to minimize matrix effects. The following key features were obtained: linearity (R(2) > 0.999, both for diacetyl and 2,3-pentanedione), high sensitivity (LOD of 0.92 μg L(-1) and 2.80 μg L(-1), and LOQ of 3.30 μg L(-1) and 10.01 μg L(-1), for diacetyl and 2,3-pentanedione, respectively), recoveries of approximately 100% and suitable precision (repeatability and reproducibility lower than 3% and 7.5%, respectively). The applicability of the methodology was fully confirmed through an independent analysis of several beer samples, with analyte concentrations ranging from 4 to 200 g L(-1). Copyright © 2015 Elsevier B.V. All rights reserved.

Development of a standardized training course for laparoscopic procedures using Delphi methodology.

PubMed

Bethlehem, Martijn S; Kramp, Kelvin H; van Det, Marc J; ten Cate Hoedemaker, Henk O; Veeger, Nicolaas J G M; Pierie, Jean Pierre E N

2014-01-01

Content, evaluation, and certification of laparoscopic skills and procedure training lack uniformity among different hospitals in The Netherlands. Within the process of developing a new regional laparoscopic training curriculum, a uniform and transferrable curriculum was constructed for a series of laparoscopic procedures. The aim of this study was to determine regional expert consensus regarding the key steps for laparoscopic appendectomy and cholecystectomy using Delphi methodology. Lists of suggested key steps for laparoscopic appendectomy and cholecystectomy were created using surgical textbooks, available guidelines, and local practice. A total of 22 experts, working for teaching hospitals throughout the region, were asked to rate the suggested key steps for both procedures on a Likert scale from 1-5. Consensus was reached with Crohnbach's α ≥ 0.90. Of the 22 experts, 21 completed and returned the survey (95%). Data analysis already showed consensus after the first round of Delphi on the key steps for laparoscopic appendectomy (Crohnbach's α = 0.92) and laparoscopic cholecystectomy (Crohnbach's α = 0.90). After the second round, 15 proposed key steps for laparoscopic appendectomy and 30 proposed key steps for laparoscopic cholecystectomy were rated as important (≥4 by at least 80% of the expert panel). These key steps were used for the further development of the training curriculum. By using the Delphi methodology, regional consensus was reached on the key steps for laparoscopic appendectomy and cholecystectomy. These key steps are going to be used for standardized training and evaluation purposes in a new regional laparoscopic curriculum. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Characteristics of Smartphone Applications for Nutrition Improvement in Community Settings: A Scoping Review1234

PubMed Central

Brimblecombe, Julie; Wycherley, Thomas Philip

2017-01-01

Smartphone applications are increasingly being used to support nutrition improvement in community settings. However, there is a scarcity of practical literature to support researchers and practitioners in choosing or developing health applications. This work maps the features, key content, theoretical approaches, and methods of consumer testing of applications intended for nutrition improvement in community settings. A systematic, scoping review methodology was used to map published, peer-reviewed literature reporting on applications with a specific nutrition-improvement focus intended for use in the community setting. After screening, articles were grouped into 4 categories: dietary self-monitoring trials, nutrition improvement trials, application description articles, and qualitative application development studies. For mapping, studies were also grouped into categories based on the target population and aim of the application or program. Of the 4818 titles identified from the database search, 64 articles were included. The broad categories of features found to be included in applications generally corresponded to different behavior change support strategies common to many classic behavioral change models. Key content of applications generally focused on food composition, with tailored feedback most commonly used to deliver educational content. Consumer testing before application deployment was reported in just over half of the studies. Collaboration between practitioners and application developers promotes an appropriate balance of evidence-based content and functionality. This work provides a unique resource for program development teams and practitioners seeking to use an application for nutrition improvement in community settings. PMID:28298274

A hierarchical anatomical classification schema for prediction of phenotypic side effects

PubMed Central

Kanji, Rakesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a ‘hierarchical anatomical classification schema’ which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects. PMID:29494708

Characteristics of Smartphone Applications for Nutrition Improvement in Community Settings: A Scoping Review.

PubMed

Tonkin, Emma; Brimblecombe, Julie; Wycherley, Thomas Philip

2017-03-01

Smartphone applications are increasingly being used to support nutrition improvement in community settings. However, there is a scarcity of practical literature to support researchers and practitioners in choosing or developing health applications. This work maps the features, key content, theoretical approaches, and methods of consumer testing of applications intended for nutrition improvement in community settings. A systematic, scoping review methodology was used to map published, peer-reviewed literature reporting on applications with a specific nutrition-improvement focus intended for use in the community setting. After screening, articles were grouped into 4 categories: dietary self-monitoring trials, nutrition improvement trials, application description articles, and qualitative application development studies. For mapping, studies were also grouped into categories based on the target population and aim of the application or program. Of the 4818 titles identified from the database search, 64 articles were included. The broad categories of features found to be included in applications generally corresponded to different behavior change support strategies common to many classic behavioral change models. Key content of applications generally focused on food composition, with tailored feedback most commonly used to deliver educational content. Consumer testing before application deployment was reported in just over half of the studies. Collaboration between practitioners and application developers promotes an appropriate balance of evidence-based content and functionality. This work provides a unique resource for program development teams and practitioners seeking to use an application for nutrition improvement in community settings. © 2017 American Society for Nutrition.

A hierarchical anatomical classification schema for prediction of phenotypic side effects.

PubMed

Wadhwa, Somin; Gupta, Aishwarya; Dokania, Shubham; Kanji, Rakesh; Bagler, Ganesh

2018-01-01

Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a 'hierarchical anatomical classification schema' which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects.

CMOS Active Pixel Sensor Technology and Reliability Characterization Methodology

NASA Technical Reports Server (NTRS)

Chen, Yuan; Guertin, Steven M.; Pain, Bedabrata; Kayaii, Sammy

2006-01-01

This paper describes the technology, design features and reliability characterization methodology of a CMOS Active Pixel Sensor. Both overall chip reliability and pixel reliability are projected for the imagers.

Feature extraction across individual time series observations with spikes using wavelet principal component analysis.

PubMed

Røislien, Jo; Winje, Brita

2013-09-20

Clinical studies frequently include repeated measurements of individuals, often for long periods. We present a methodology for extracting common temporal features across a set of individual time series observations. In particular, the methodology explores extreme observations within the time series, such as spikes, as a possible common temporal phenomenon. Wavelet basis functions are attractive in this sense, as they are localized in both time and frequency domains simultaneously, allowing for localized feature extraction from a time-varying signal. We apply wavelet basis function decomposition of individual time series, with corresponding wavelet shrinkage to remove noise. We then extract common temporal features using linear principal component analysis on the wavelet coefficients, before inverse transformation back to the time domain for clinical interpretation. We demonstrate the methodology on a subset of a large fetal activity study aiming to identify temporal patterns in fetal movement (FM) count data in order to explore formal FM counting as a screening tool for identifying fetal compromise and thus preventing adverse birth outcomes. Copyright © 2013 John Wiley & Sons, Ltd.

Electron-beam lithography with character projection exposure for throughput enhancement with line-edge quality optimization

NASA Astrophysics Data System (ADS)

Ikeno, Rimon; Maruyama, Satoshi; Mita, Yoshio; Ikeda, Makoto; Asada, Kunihiro

2016-03-01

Among various electron-beam lithography (EBL) techniques, variable-shaped beam (VSB) and character projection (CP) methods have attracted many EBL users for their high-throughput feature, but they are considered to be more suited to small-featured VLSI fabrication with regularly-arranged layouts like standard-cell logics and memory arrays. On the other hand, non-VLSI applications like photonics, MEMS, MOEMS, and so on, have not been fully utilized the benefit of CP method due to their wide variety of layout patterns. In addition, the stepwise edge shapes by VSB method often causes intolerable edge roughness to degrade device characteristics from its intended performance with smooth edges. We proposed an overall EBL methodology applicable to wade-variety of EBL applications utilizing VSB and CP methods. Its key idea is in our layout data conversion algorithm that decomposes curved or oblique edges of arbitrary layout patterns into CP shots. We expect significant reduction in EB shot count with a CP-bordered exposure data compared to the corresponding VSB-alone conversion result. Several CP conversion parameters are used to optimize EB exposure throughput, edge quality, and resultant device characteristics. We demonstrated out methodology using the leading-edge VSB/CP EBL tool, ADVANTEST F7000S-VD02, with high resolution Hydrogen Silsesquioxane (HSQ) resist. Through our experiments of curved and oblique edge lithography under various data conversion conditions, we learned correspondence of the conversion parameters to the resultant edge roughness and other conditions. They will be utilized as the fundamental data for further enhancement of our EBL strategy for optimized EB exposure.

The Device Centric Communication System for 5G Networks

NASA Astrophysics Data System (ADS)

Biswash, S. K.; Jayakody, D. N. K.

2017-01-01

The Fifth Generation Communication (5G) networks have several functional features such as: Massive Multiple Input and Multiple Output (MIMO), Device centric data and voice support, Smarter-device communications, etc. The objective for 5G networks is to gain the 1000x more throughput, 10x spectral efficiency, 100 x more energy efficiency than existing technologies. The 5G system will provide the balance between the Quality of Experience (QoE) and the Quality of Service (QoS), without compromising the user benefit. The data rate has been the key metric for wireless QoS; QoE deals with the delay and throughput. In order to realize a balance between the QoS and QoE, we propose a cellular Device centric communication methodology for the overlapping network coverage area in the 5G communication system. The multiple beacon signals mobile tower refers to an overlapping network area, and a user must be forwarded to the next location area. To resolve this issue, we suggest the user centric methodology (without Base Station interface) to handover the device in the next area, until the users finalize the communication. The proposed method will reduce the signalling cost and overheads for the communication.

Lifting the veil: a typological survey of the methodological features of Islamic ethical reasoning on biomedical issues.

PubMed

Abdur-Rashid, Khalil; Furber, Steven Woodward; Abdul-Basser, Taha

2013-04-01

We survey the meta-ethical tools and institutional processes that traditional Islamic ethicists apply when deliberating on bioethical issues. We present a typology of these methodological elements, giving particular attention to the meta-ethical techniques and devices that traditional Islamic ethicists employ in the absence of decisive or univocal authoritative texts or in the absence of established transmitted cases. In describing how traditional Islamic ethicists work, we demonstrate that these experts possess a variety of discursive tools. We find that the ethical responsa-i.e., the products of the application of the tools that we describe-are generally characterized by internal consistency. We also conclude that Islamic ethical reasoning on bioethical issues, while clearly scripture-based, is also characterized by strong consequentialist elements and possesses clear principles-based characteristics. The paper contributes to the study of bioethics by familiarizing non-specialists in Islamic ethics with the role, scope, and applicability of key Islamic ethical concepts, such as "aims" (maqāṣid), "universals" (kulliyyāt), "interest" (maṣlaḥa), "maxims" (qawā`id), "controls" (ḍawābit), "differentiators" (furūq), "preponderization" (tarjīḥ), and "extension" (tafrī`).

Key features of an EU health information system: a concept mapping study.

PubMed

Rosenkötter, Nicole; Achterberg, Peter W; van Bon-Martens, Marja J H; Michelsen, Kai; van Oers, Hans A M; Brand, Helmut

2016-02-01

Despite the acknowledged value of an EU health information system (EU-HISys) and the many achievements in this field, the landscape is still heavily fragmented and incomplete. Through a systematic analysis of the opinions and valuations of public health stakeholders, this study aims to conceptualize key features of an EU-HISys. Public health professionals and policymakers were invited to participate in a concept mapping procedure. First, participants (N = 34) formulated statements that reflected their vision of an EU-HISys. Second, participants (N = 28) rated the relative importance of each statement and grouped conceptually similar ones. Principal Component and cluster analyses were used to condense these results to EU-HISys key features in a concept map. The number of key features and the labelling of the concept map were determined by expert consensus. The concept map contains 10 key features that summarize 93 statements. The map consists of a horizontal axis that represents the relevance of an 'organizational strategy', which deals with the 'efforts' to design and develop an EU-HISys and the 'achievements' gained by a functioning EU-HISys. The vertical axis represents the 'professional orientation' of the EU-HISys, ranging from the 'scientific' through to the 'policy' perspective. The top ranking statement expressed the need to establish a system that is permanent and sustainable. The top ranking key feature focuses on data and information quality. This study provides insights into key features of an EU-HISys. The results can be used to guide future planning and to support the development of a health information system for Europe. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Methodological issues associated with preclinical drug development and increased placebo effects in schizophrenia clinical trials.

PubMed

Brown, Matt A; Bishnoi, Ram J; Dholakia, Sara; Velligan, Dawn I

2016-01-20

Recent failures to detect efficacy in clinical trials investigating pharmacological treatments for schizophrenia raise concerns regarding the potential contribution of methodological shortcomings to this research. This review provides an examination of two key methodological issues currently suspected of playing a role in hampering schizophrenia drug development; 1) limitations on the translational utility of preclinical development models, and 2) methodological challenges posed by increased placebo effects. Recommendations for strategies to address these methodological issues are addressed.

Hydro-geomorphic connectivity and landslide features extraction to identifying potential threats and hazardous areas

NASA Astrophysics Data System (ADS)

Tarolli, Paolo; Fuller, Ian C.; Basso, Federica; Cavalli, Marco; Sofia, Giulia

2017-04-01

Hydro-geomorphic connectivity has significantly emerged as a new concept to understand the transfer of surface water and sediment through landscapes. A further scientific challenge is determining how the concept can be used to enable sustainable land and water management. This research proposes an interesting approach to integrating remote sensing techniques, connectivity theory, and geomorphometry based on high-resolution digital terrain model (HR-DTMs) to automatically extract landslides crowns and gully erosion, to determine the different rate of connectivity among the main extracted features and the river network, and thus determine a possible categorization of hazardous areas. The study takes place in two mountainous regions in the Wellington Region (New Zealand). The methodology is a three step approach. Firstly, we performed an automatic detection of the likely landslides crowns through the use of thresholds obtained by the statistical analysis of the variability of landform curvature. After that, the research considered the Connectivity Index to analyse how a complex and rugged topography induces large variations in erosion and sediment delivery in the two catchments. Lastly, the two methods have been integrated to create a unique procedure able to classify the different rate of connectivity among the main features and the river network and thus identifying potential threats and hazardous areas. The methodology is fast, and it can produce a detailed and updated inventory map that could be a key tool for erosional and sediment delivery hazard mitigation. This fast and simple method can be a useful tool to manage emergencies giving priorities to more failure-prone zones. Furthermore, it could be considered to do a preliminary interpretations of geomorphological phenomena and more in general, it could be the base to develop inventory maps. References Cavalli M, Trevisani S, Comiti F, Marchi L. 2013. Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments. Geomorphology 188: 31-41 DOI: 10.1016/j.geomorph.2012.05.007 Sofia G, Dalla Fontana G, Tarolli P. 2014. High-resolution topography and anthropogenic feature extraction: testing geomorphometric parameters in floodplains. Hydrological Processes 28 (4): 2046-2061 DOI: 10.1002/hyp.9727 Tarolli P, Sofia G, Dalla Fontana G. 2012. Geomorphic features extraction from high-resolution topography: landslide crowns and bank erosion. Natural Hazards 61 (1): 65-83 DOI: 10.1007/s11069-010-9695-2

On the effect of model parameters on forecast objects

NASA Astrophysics Data System (ADS)

Marzban, Caren; Jones, Corinne; Li, Ning; Sandgathe, Scott

2018-04-01

Many physics-based numerical models produce a gridded, spatial field of forecasts, e.g., a temperature map. The field for some quantities generally consists of spatially coherent and disconnected objects. Such objects arise in many problems, including precipitation forecasts in atmospheric models, eddy currents in ocean models, and models of forest fires. Certain features of these objects (e.g., location, size, intensity, and shape) are generally of interest. Here, a methodology is developed for assessing the impact of model parameters on the features of forecast objects. The main ingredients of the methodology include the use of (1) Latin hypercube sampling for varying the values of the model parameters, (2) statistical clustering algorithms for identifying objects, (3) multivariate multiple regression for assessing the impact of multiple model parameters on the distribution (across the forecast domain) of object features, and (4) methods for reducing the number of hypothesis tests and controlling the resulting errors. The final output of the methodology is a series of box plots and confidence intervals that visually display the sensitivities. The methodology is demonstrated on precipitation forecasts from a mesoscale numerical weather prediction model.

Review of Research on School Principal Leadership in Mainland China, 1998-2013: Continuity and Change

ERIC Educational Resources Information Center

Walker, Allan; Qian, Haiyan

2015-01-01

Purpose: The purpose of this paper is to review English-language publications about school principalship in China published between 1998 and 2013 and to present an overview of the authorship, topics, methodologies and key findings of these publications. Design/methodology/approach: The methodology includes an exhaustive review of journal articles…

Precipitate statistics in an Al-Mg-Si-Cu alloy from scanning precession electron diffraction data

NASA Astrophysics Data System (ADS)

Sunde, J. K.; Paulsen, Ø.; Wenner, S.; Holmestad, R.

2017-09-01

The key microstructural feature providing strength to age-hardenable Al alloys is nanoscale precipitates. Alloy development requires a reliable statistical assessment of these precipitates, in order to link the microstructure with material properties. Here, it is demonstrated that scanning precession electron diffraction combined with computational analysis enable the semi-automated extraction of precipitate statistics in an Al-Mg-Si-Cu alloy. Among the main findings is the precipitate number density, which agrees well with a conventional method based on manual counting and measurements. By virtue of its data analysis objectivity, our methodology is therefore seen as an advantageous alternative to existing routines, offering reproducibility and efficiency in alloy statistics. Additional results include improved qualitative information on phase distributions. The developed procedure is generic and applicable to any material containing nanoscale precipitates.

Microengineering neocartilage scaffolds.

PubMed

Petersen, Erik F; Spencer, Richard G S; McFarland, Eric W

2002-06-30

Advances in micropatterning methodologies have made it possible to create structures with precise architecture on the surface of cell culture substrata. We applied these techniques to fabricate microfeatures (15-65 microm wide; 40 microm deep) on the surface of a flexible, biocompatible polysaccharide gel. The micropatterned polymer gels were subsequently applied as scaffolds for chondrocyte culture and proved effective in maintaining key aspects of the chondrogenic phenotype. These were rounded cell morphology and a positive and statistically significant (p < 0.0001) immunofluorescence assay for the production of type II collagen throughout the maximum culture time of 10 days after cell seeding. Further, cells housed within individual surface features were observed to proliferate, while serial application of chondrocytes resulted in the formation of cellular aggregates. These methods represent a novel approach to the problem of engineering reparative cartilage in vitro. Copyright 2002 Wiley Periodicals, Inc.

Ablation, Thermal Response, and Chemistry Program for Analysis of Thermal Protection Systems

NASA Technical Reports Server (NTRS)

Milos, Frank S.; Chen, Yih-Kanq

2010-01-01

In previous work, the authors documented the Multicomponent Ablation Thermochemistry (MAT) and Fully Implicit Ablation and Thermal response (FIAT) programs. In this work, key features from MAT and FIAT were combined to create the new Fully Implicit Ablation, Thermal response, and Chemistry (FIATC) program. FIATC is fully compatible with FIAT (version 2.5) but has expanded capabilities to compute the multispecies surface chemistry and ablation rate as part of the surface energy balance. This new methodology eliminates B' tables, provides blown species fractions as a function of time, and enables calculations that would otherwise be impractical (e.g. 4+ dimensional tables) such as pyrolysis and ablation with kinetic rates or unequal diffusion coefficients. Equations and solution procedures are presented, then representative calculations of equilibrium and finite-rate ablation in flight and ground-test environments are discussed.

Helping public sector health systems innovate: the strategic approach to strengthening reproductive health policies and programs.

PubMed

Fajans, Peter; Simmons, Ruth; Ghiron, Laura

2006-03-01

Public sector health systems that provide services to poor and marginalized populations in developing countries face great challenges. Change associated with health sector reform and structural adjustment often leaves these already-strained institutions with fewer resources and insufficient capacity to relieve health burdens. The Strategic Approach to Strengthening Reproductive Health Policies and Programs is a methodological innovation developed by the World Health Organization and its partners to help countries identify and prioritize their reproductive health service needs, test appropriate interventions, and scale up successful innovations to a subnational or national level. The participatory, interdisciplinary, and country-owned process can set in motion much-needed change. We describe key features of this approach, provide illustrations from country experiences, and use insights from the diffusion of innovation literature to explain the approach's dissemination and sustainability.

Transport in Dynamical Astronomy and Multibody Problems

NASA Astrophysics Data System (ADS)

Dellnitz, Michael; Junge, Oliver; Koon, Wang Sang; Lekien, Francois; Lo, Martin W.; Marsden, Jerrold E.; Padberg, Kathrin; Preis, Robert; Ross, Shane D.; Thiere, Bianca

We combine the techniques of almost invariant sets (using tree structured box elimination and graph partitioning algorithms) with invariant manifold and lobe dynamics techniques. The result is a new computational technique for computing key dynamical features, including almost invariant sets, resonance regions as well as transport rates and bottlenecks between regions in dynamical systems. This methodology can be applied to a variety of multibody problems, including those in molecular modeling, chemical reaction rates and dynamical astronomy. In this paper we focus on problems in dynamical astronomy to illustrate the power of the combination of these different numerical tools and their applicability. In particular, we compute transport rates between two resonance regions for the three-body system consisting of the Sun, Jupiter and a third body (such as an asteroid). These resonance regions are appropriate for certain comets and asteroids.

Mixed methods in psychotherapy research: A review of method(ology) integration in psychotherapy science.

PubMed

Bartholomew, Theodore T; Lockard, Allison J

2018-06-13

Mixed methods can foster depth and breadth in psychological research. However, its use remains in development in psychotherapy research. Our purpose was to review the use of mixed methods in psychotherapy research. Thirty-one studies were identified via the PRISMA systematic review method. Using Creswell & Plano Clark's typologies to identify design characteristics, we assessed each study for rigor and how each used mixed methods. Key features of mixed methods designs and these common patterns were identified: (a) integration of clients' perceptions via mixing; (b) understanding group psychotherapy; (c) integrating methods with cases and small samples; (d) analyzing clinical data as qualitative data; and (e) exploring cultural identities in psychotherapy through mixed methods. The review is discussed with respect to the value of integrating multiple data in single studies to enhance psychotherapy research. © 2018 Wiley Periodicals, Inc.

An object-oriented approach to risk and reliability analysis : methodology and aviation safety applications.

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

Dandini, Vincent John; Duran, Felicia Angelica; Wyss, Gregory Dane

2003-09-01

This article describes how features of event tree analysis and Monte Carlo-based discrete event simulation can be combined with concepts from object-oriented analysis to develop a new risk assessment methodology, with some of the best features of each. The resultant object-based event scenario tree (OBEST) methodology enables an analyst to rapidly construct realistic models for scenarios for which an a priori discovery of event ordering is either cumbersome or impossible. Each scenario produced by OBEST is automatically associated with a likelihood estimate because probabilistic branching is integral to the object model definition. The OBEST methodology is then applied to anmore » aviation safety problem that considers mechanisms by which an aircraft might become involved in a runway incursion incident. The resulting OBEST model demonstrates how a close link between human reliability analysis and probabilistic risk assessment methods can provide important insights into aviation safety phenomenology.« less

An economic analysis methodology for project evaluation and programming.

DOT National Transportation Integrated Search

2013-08-01

Economic analysis is a critical component of a comprehensive project or program evaluation methodology that considers all key : quantitative and qualitative impacts of highway investments. It allows highway agencies to identify, quantify, and value t...

New mission requirements methodologies for services provided by the Office of Space Communications

NASA Technical Reports Server (NTRS)

Holmes, Dwight P.; Hall, J. R.; Macoughtry, William; Spearing, Robert

1993-01-01

The Office of Space Communications, NASA Headquarters, has recently revised its methodology for receiving, accepting and responding to customer requests for use of that office's tracking and communications capabilities. This revision is the result of a process which has become over-burdened by the size of the currently active and proposed missions set, requirements reviews that focus on single missions rather than on mission sets, and negotiations most often not completed early enough to effect needed additions to capacity or capability prior to launch. The requirements-coverage methodology described is more responsive to project/program needs and provides integrated input into the NASA budget process early enough to effect change, and describes the mechanisms and tools in place to insure a value-added process which will benefit both NASA and its customers. Key features of the requirements methodology include the establishment of a mechanism for early identification of and systems trades with new customers, and delegates the review and approval of requirements documents to NASA centers in lieu of Headquarters, thus empowering the system design teams to establish and negotiate the detailed requirements with the user. A Mission Requirements Request (MRR) is introduced to facilitate early customer interaction. The expected result is that the time to achieve an approved set of implementation requirements which meet the customer's needs can be greatly reduced. Finally, by increasing the discipline in requirements management, through the use of base lining procedures, a tighter coupling between customer requirements and the budget is provided. A twice-yearly projection of customer requirements accommodation, designated as the Capacity Projection Plan (CPP), provides customer feedback allowing the entire mission set to be serviced.

A novel in vivo receptor occupancy methodology for the glucocorticoid receptor: toward an improved understanding of lung pharmacokinetic/pharmacodynamic relationships.

PubMed

Boger, Elin; Ewing, Pär; Eriksson, Ulf G; Fihn, Britt-Marie; Chappell, Michael; Evans, Neil; Fridén, Markus

2015-05-01

Investigation of pharmacokinetic/pharmacodynamic (PK/PD) relationships for inhaled drugs is challenging because of the limited possibilities of measuring tissue exposure and target engagement in the lung. The aim of this study was to develop a methodology for measuring receptor occupancy in vivo in the rat for the glucocorticoid receptor (GR) to allow more informative inhalation PK/PD studies. From AstraZeneca's chemical library of GR binders, compound 1 [N-(2-amino-2-oxo-ethyl)-3-[5-[(1R,2S)-2-(2,2-difluoropropanoylamino)-1-(2,3-dihydro-1,4-benzodioxin-6-yl)propoxy]indazol-1-yl]-N-methyl-benzamide] was identified to have properties that are useful as a tracer for GR in vitro. When given at an appropriate dose (30 nmol/kg) to rats, compound 1 functioned as a tracer in the lung and spleen in vivo using liquid chromatography-tandem mass spectrometry bioanalysis. The methodology was successfully used to show the dose-receptor occupancy relationship measured at 1.5 hours after intravenous administration of fluticasone propionate (20, 150, and 750 nmol/kg) as well as to characterize the time profile for receptor occupancy after a dose of 90 nmol/kg i.v. The dose giving 50% occupancy was estimated as 47 nmol/kg. The methodology is novel in terms of measuring occupancy strictly in vivo and by using an unlabeled tracer. This feature confers key advantages, including occupancy estimation not being influenced by drug particle dissolution or binding/dissociation taking place postmortem. In addition, the tracer may be labeled for use in positron emission tomography imaging, thus enabling occupancy estimation in humans as a translatable biomarker of target engagement. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

The shape of facial features and the spacing among them generate similar inversion effects: a reply to Rossion (2008).

PubMed

Yovel, Galit

2009-11-01

It is often argued that picture-plane face inversion impairs discrimination of the spacing among face features to a greater extent than the identity of the facial features. However, several recent studies have reported similar inversion effects for both types of face manipulations. In a recent review, Rossion (2008) claimed that similar inversion effects for spacing and features are due to methodological and conceptual shortcomings and that data still support the idea that inversion impairs the discrimination of features less than that of the spacing among them. Here I will claim that when facial features differ primarily in shape, the effect of inversion on features is not smaller than the one on spacing. It is when color/contrast information is added to facial features that the inversion effect on features decreases. This obvious observation accounts for the discrepancy in the literature and suggests that the large inversion effect that was found for features that differ in shape is not a methodological artifact. These findings together with other data that are discussed are consistent with the idea that the shape of facial features and the spacing among them are integrated rather than dissociated in the holistic representation of faces.

An exploratory digital analysis of the early years of G. Stanley Hall's American Journal of Psychology and Pedagogical Seminary.

PubMed

Young, Jacy L; Green, Christopher D

2013-11-01

In this article, we present the results of an exploratory digital analysis of the contents of the two journals founded in the late 19th century by American psychologist G. Stanley Hall. Using the methods of the increasingly popular digital humanities, some key attributes of the American Journal of Psychology (AJP) and the Pedagogical Seminary (PS) are identified. Our analysis reaffirms some of Hall's explicit aims for the two periodicals, while also revealing a number of other features of the journals, as well as of the people who published within their pages, the methodologies they employed, and the institutions at which they worked. Notably, despite Hall's intent that his psychological journal be strictly an outlet for scientific research, the journal-like its sister pedagogically focused publication-included an array of methodologically diverse research. The multiplicity of research styles that characterize the content of Hall's journals in their initial years is, in part, a consequence of individual researchers at times crossing methodological lines and producing a diverse body of research. Along with such variety within each periodical, it is evident that the line between content appropriate to one periodical rather than the other was fluid rather than absolute. The full results of this digitally informed analysis of Hall's two journals suggest a number of novel avenues for future research and demonstrate the utility of digital methods as applied to the history of psychology. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Practical Issues of Conducting a Q Methodology Study: Lessons Learned From a Cross-cultural Study.

PubMed

Stone, Teresa Elizabeth; Maguire, Jane; Kang, Sook Jung; Cha, Chiyoung

This article advances nursing research by presenting the methodological challenges experienced in conducting a multination Q-methodology study. This article critically analyzes the relevance of the methodology for cross-cultural and nursing research and the challenges that led to specific responses by the investigators. The use of focus groups with key stakeholders supplemented the Q-analysis results. The authors discuss practical issues and shared innovative approaches and provide best-practice suggestions on the use of this flexible methodology. Q methodology has the versatility to explore complexities of contemporary nursing practice and cross-cultural health research.

Speech sound classification and detection of articulation disorders with support vector machines and wavelets.

PubMed

Georgoulas, George; Georgopoulos, Voula C; Stylios, Chrysostomos D

2006-01-01

This paper proposes a novel integrated methodology to extract features and classify speech sounds with intent to detect the possible existence of a speech articulation disorder in a speaker. Articulation, in effect, is the specific and characteristic way that an individual produces the speech sounds. A methodology to process the speech signal, extract features and finally classify the signal and detect articulation problems in a speaker is presented. The use of support vector machines (SVMs), for the classification of speech sounds and detection of articulation disorders is introduced. The proposed method is implemented on a data set where different sets of features and different schemes of SVMs are tested leading to satisfactory performance.

A hybrid approach to select features and classify diseases based on medical data

NASA Astrophysics Data System (ADS)

AbdelLatif, Hisham; Luo, Jiawei

2018-03-01

Feature selection is popular problem in the classification of diseases in clinical medicine. Here, we developing a hybrid methodology to classify diseases, based on three medical datasets, Arrhythmia, Breast cancer, and Hepatitis datasets. This methodology called k-means ANOVA Support Vector Machine (K-ANOVA-SVM) uses K-means cluster with ANOVA statistical to preprocessing data and selection the significant features, and Support Vector Machines in the classification process. To compare and evaluate the performance, we choice three classification algorithms, decision tree Naïve Bayes, Support Vector Machines and applied the medical datasets direct to these algorithms. Our methodology was a much better classification accuracy is given of 98% in Arrhythmia datasets, 92% in Breast cancer datasets and 88% in Hepatitis datasets, Compare to use the medical data directly with decision tree Naïve Bayes, and Support Vector Machines. Also, the ROC curve and precision with (K-ANOVA-SVM) Achieved best results than other algorithms

Biosynthesis of Inorganic Nanoparticles: A Fresh Look at the Control of Shape, Size and Composition

PubMed Central

Dahoumane, Si Amar; Jeffryes, Clayton; Mechouet, Mourad; Agathos, Spiros N.

2017-01-01

Several methodologies have been devised for the design of nanomaterials. The “Holy Grail” for materials scientists is the cost-effective, eco-friendly synthesis of nanomaterials with controlled sizes, shapes and compositions, as these features confer to the as-produced nanocrystals unique properties making them appropriate candidates for valuable bio-applications. The present review summarizes published data regarding the production of nanomaterials with special features via sustainable methodologies based on the utilization of natural bioresources. The richness of the latter, the diversity of the routes adopted and the tuned experimental parameters have led to the fabrication of nanomaterials belonging to different chemical families with appropriate compositions and displaying interesting sizes and shapes. It is expected that these outstanding findings will encourage researchers and attract newcomers to continue and extend the exploration of possibilities offered by nature and the design of innovative and safer methodologies towards the synthesis of unique nanomaterials, possessing desired features and exhibiting valuable properties that can be exploited in a profusion of fields. PMID:28952493

Methodology for classification of geographical features with remote sensing images: Application to tidal flats

NASA Astrophysics Data System (ADS)

Revollo Sarmiento, G. N.; Cipolletti, M. P.; Perillo, M. M.; Delrieux, C. A.; Perillo, Gerardo M. E.

2016-03-01

Tidal flats generally exhibit ponds of diverse size, shape, orientation and origin. Studying the genesis, evolution, stability and erosive mechanisms of these geographic features is critical to understand the dynamics of coastal wetlands. However, monitoring these locations through direct access is hard and expensive, not always feasible, and environmentally damaging. Processing remote sensing images is a natural alternative for the extraction of qualitative and quantitative data due to their non-invasive nature. In this work, a robust methodology for automatic classification of ponds and tidal creeks in tidal flats using Google Earth images is proposed. The applicability of our method is tested in nine zones with different morphological settings. Each zone is processed by a segmentation stage, where ponds and tidal creeks are identified. Next, each geographical feature is measured and a set of shape descriptors is calculated. This dataset, together with a-priori classification of each geographical feature, is used to define a regression model, which allows an extensive automatic classification of large volumes of data discriminating ponds and tidal creeks against other various geographical features. In all cases, we identified and automatically classified different geographic features with an average accuracy over 90% (89.7% in the worst case, and 99.4% in the best case). These results show the feasibility of using freely available Google Earth imagery for the automatic identification and classification of complex geographical features. Also, the presented methodology may be easily applied in other wetlands of the world and perhaps employing other remote sensing imagery.

A systematic literature review of the key challenges for developing the structure of public health economic models.

PubMed

Squires, Hazel; Chilcott, James; Akehurst, Ronald; Burr, Jennifer; Kelly, Michael P

2016-04-01

To identify the key methodological challenges for public health economic modelling and set an agenda for future research. An iterative literature search identified papers describing methodological challenges for developing the structure of public health economic models. Additional multidisciplinary literature searches helped expand upon important ideas raised within the review. Fifteen articles were identified within the formal literature search, highlighting three key challenges: inclusion of non-healthcare costs and outcomes; inclusion of equity; and modelling complex systems and multi-component interventions. Based upon these and multidisciplinary searches about dynamic complexity, the social determinants of health, and models of human behaviour, six areas for future research were specified. Future research should focus on: the use of systems approaches within health economic modelling; approaches to assist the systematic consideration of the social determinants of health; methods for incorporating models of behaviour and social interactions; consideration of equity; and methodology to help modellers develop valid, credible and transparent public health economic model structures.

An investigation into creative design methodologies for textiles and fashion

NASA Astrophysics Data System (ADS)

Gault, Alison

2017-10-01

Understanding market intelligence, trends, influences and personal approaches are essential tools for design students to develop their ideas in textiles and fashion. Identifying different personal approaches including, visual, process-led or concept by employing creative methodologies are key to developing a brief. A series of ideas or themes start to emerge and through the design process serve to underpin and inform an entire collection. These investigations ensure that the design collections are able to produce a diverse range of outcomes. Following key structures and coherent stages in the design process creates authentic collections in textiles and fashion. A range of undergraduate students presented their design portfolios (180) and the methodologies employed were mapped against success at module level, industry response and graduate employment.

Assessing Campus Climates for Lesbian, Gay, Bisexual and Transgender (LGBT) Students: Methodological and Political Issues

ERIC Educational Resources Information Center

Brown, Robert D.; Gortmaker, Valerie J.

2009-01-01

Methodological and political issues arise during the designing, conducting, and reporting of campus-climate studies for LGBT students. These issues interact; making a decision about a methodological issue (e.g., sample size) has an impact on a political issue (e.g., how well the findings will be received). Ten key questions that must be addressed…

Speed-Accuracy Tradeoffs in Speech Production

DTIC Science & Technology

2017-06-01

imaging data of speech production. A theoretical framework for considering Fitts’ law in the domain of speech production is elucidated. Methodological ...articulatory kinematics conform to Fitts’ law. A second, associated goal is to address the methodological challenges inherent in performing Fitts-style...analysis on rtMRI data of speech production. Methodological challenges include segmenting continuous speech into specific motor tasks, defining key

Container Surface Evaluation by Function Estimation

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

Wendelberger, James G.

Container images are analyzed for specific surface features, such as, pits, cracks, and corrosion. The detection of these features is confounded with complicating features. These complication features include: shape/curvature, welds, edges, scratches, foreign objects among others. A method is provided to discriminate between the various features. The method consists of estimating the image background, determining a residual image and post processing to determine the features present. The methodology is not finalized but demonstrates the feasibility of a method to determine the kind and size of the features present.

A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data.

PubMed

Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A; Peddada, Shyamal D

2018-01-01

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html.

A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data

PubMed Central

Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A.; Peddada, Shyamal D.

2018-01-01

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html PMID:29456555

Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery.

PubMed

Casado, Monica Rivas; Gonzalez, Rocio Ballesteros; Kriechbaumer, Thomas; Veal, Amanda

2015-11-04

European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management.

Remote sensing of key grassland nutrients using hyperspectral techniques in KwaZulu-Natal, South Africa

NASA Astrophysics Data System (ADS)

Singh, Leeth; Mutanga, Onisimo; Mafongoya, Paramu; Peerbhay, Kabir

2017-07-01

The concentration of forage fiber content is critical in explaining the palatability of forage quality for livestock grazers in tropical grasslands. Traditional methods of determining forage fiber content are usually time consuming, costly, and require specialized laboratory analysis. With the potential of remote sensing technologies, determination of key fiber attributes can be made more accurately. This study aims to determine the effectiveness of known absorption wavelengths for detecting forage fiber biochemicals, neutral detergent fiber, acid detergent fiber, and lignin using hyperspectral data. Hyperspectral reflectance spectral measurements (350 to 2500 nm) of grass were collected and implemented within the random forest (RF) ensemble. Results show successful correlations between the known absorption features and the biochemicals with coefficients of determination (R2) ranging from 0.57 to 0.81 and root mean square errors ranging from 6.97 to 3.03 g/kg. In comparison, using the entire dataset, the study identified additional wavelengths for detecting fiber biochemicals, which contributes to the accurate determination of forage quality in a grassland environment. Overall, the results showed that hyperspectral remote sensing in conjunction with the competent RF ensemble could discriminate each key biochemical evaluated. This study shows the potential to upscale the methodology to a space-borne multispectral platform with similar spectral configurations for an accurate and cost effective mapping analysis of forage quality.

Principles for the formation of an effective concept of multifunctional high-rise construction investment projects

NASA Astrophysics Data System (ADS)

Beliakov, Sergei

2018-03-01

Investment projects of high-rise construction have a number of features that determine specific risks and additional opportunities that require analysis and accounting in the formation of an effective project concept. The most significant features of high-rise construction include long construction time, complexity of technical and technological solutions, complexity of decisions on the organization of construction and operation, high cost of construction and operation, complexity in determining the ratio of areas designed to accommodate different functional areas, when organizing and coordinating the operation of the facility, with internal zoning. Taking into account the specificity of high-rise construction, among the factors determining the effectiveness of projects, it is advisable to consider as key factors: organizational, technological and investment factors. Within the framework of the article, the author singled out key particular functions for each group of factors under consideration, and also developed a system of principles for the formation of an effective concept of multifunctional high-rise construction investment projects, including the principle of logistic efficiency, the principle of optimal functional zoning, the principle of efficiency of equipment use, the principle of optimizing technological processes, the principle maximization of income, the principle of fund management, the principle of risk management . The model of formation of an effective concept of investment projects of multifunctional high-rise construction developed by the author can contribute to the development of methodological tools in the field of managing the implementation of high-rise construction projects, taking into account their specificity in the current economic conditions.

QUALITY ASSURANCE MEASURES ASSOCIATED WITH CORAL REEF MONITORING

EPA Science Inventory

Systematic efforts began in 1997 to assess the incidence of coral diseases in the Florida Keys. Protocols were developed for the selection of permanent stations and for data collection methodology. Permanent stations and for data collection methodology. Permanent stations were es...

Fast Localization in Large-Scale Environments Using Supervised Indexing of Binary Features.

PubMed

Youji Feng; Lixin Fan; Yihong Wu

2016-01-01

The essence of image-based localization lies in matching 2D key points in the query image and 3D points in the database. State-of-the-art methods mostly employ sophisticated key point detectors and feature descriptors, e.g., Difference of Gaussian (DoG) and Scale Invariant Feature Transform (SIFT), to ensure robust matching. While a high registration rate is attained, the registration speed is impeded by the expensive key point detection and the descriptor extraction. In this paper, we propose to use efficient key point detectors along with binary feature descriptors, since the extraction of such binary features is extremely fast. The naive usage of binary features, however, does not lend itself to significant speedup of localization, since existing indexing approaches, such as hierarchical clustering trees and locality sensitive hashing, are not efficient enough in indexing binary features and matching binary features turns out to be much slower than matching SIFT features. To overcome this, we propose a much more efficient indexing approach for approximate nearest neighbor search of binary features. This approach resorts to randomized trees that are constructed in a supervised training process by exploiting the label information derived from that multiple features correspond to a common 3D point. In the tree construction process, node tests are selected in a way such that trees have uniform leaf sizes and low error rates, which are two desired properties for efficient approximate nearest neighbor search. To further improve the search efficiency, a probabilistic priority search strategy is adopted. Apart from the label information, this strategy also uses non-binary pixel intensity differences available in descriptor extraction. By using the proposed indexing approach, matching binary features is no longer much slower but slightly faster than matching SIFT features. Consequently, the overall localization speed is significantly improved due to the much faster key point detection and descriptor extraction. It is empirically demonstrated that the localization speed is improved by an order of magnitude as compared with state-of-the-art methods, while comparable registration rate and localization accuracy are still maintained.

Centimeter-scale subwavelength photolithography using metal-coated elastomeric photomasks with modulated light intensity at the oblique sidewalls.

PubMed

Wu, Jin; Liu, Yayuan; Guo, Yuanyuan; Feng, Shuanglong; Zou, Binghua; Mao, Hui; Yu, Cheng-han; Tian, Danbi; Huang, Wei; Huo, Fengwei

2015-05-05

By coating polydimethylsiloxane (PDMS) relief structures with a layer of opaque metal such as gold, the incident light is strictly allowed to pass through the nanoscopic apertures at the sidewalls of PDMS reliefs to expose underlying photoresist at nanoscale regions, thus producing subwavelength nanopatterns covering centimeter-scale areas. It was found that the sidewalls were a little oblique, which was the key to form the nanoscale apertures. Two-sided and one-sided subwavelength apertures can be constructed by employing vertical and oblique metal evaporation directions, respectively. Consequently, two-line and one-line subwavelength nanopatterns with programmable feature shapes, sizes, and periodicities could be produced using the obtained photomasks. The smallest aperture size and line width of 80 nm were achieved. In contrast to the generation of raised positive photoresist nanopatterns in phase shifting photolithography, the recessed positive photoresist nanopatterns produced in this study provide a convenient route to transfer the resist nanopatterns to metal nanopatterns. This nanolithography methodology possesses the distinctive advantages of simplicity, low cost, high throughput, and nanoscale feature size and shape controllability, making it a potent nanofabrication technique to enable functional nanostructures for various potential applications.

Rolling bearing fault diagnosis and health assessment using EEMD and the adjustment Mahalanobis-Taguchi system

NASA Astrophysics Data System (ADS)

Chen, Junxun; Cheng, Longsheng; Yu, Hui; Hu, Shaolin

2018-01-01