Recursive form of general limited memory variable metric methods
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Vlček, Jan
2013-01-01
Roč. 49, č. 2 (2013), s. 224-235 ISSN 0023-5954 Institutional support: RVO:67985807 Keywords : unconstrained optimization * large scale optimization * limited memory methods * variable metric updates * recursive matrix formulation * algorithms Subject RIV: BA - General Mathematics Impact factor: 0.563, year: 2013 http://dml.cz/handle/10338.dmlcz/143365
International Nuclear Information System (INIS)
Nazareth, J. L.
1979-01-01
1 - Description of problem or function: OCOPTR and DRVOCR are computer programs designed to find minima of non-linear differentiable functions f: R n →R with n dimensional domains. OCOPTR requires that the user only provide function values (i.e. it is a derivative-free routine). DRVOCR requires the user to supply both function and gradient information. 2 - Method of solution: OCOPTR and DRVOCR use the variable metric (or quasi-Newton) method of Davidon (1975). For OCOPTR, the derivatives are estimated by finite differences along a suitable set of linearly independent directions. For DRVOCR, the derivatives are user- supplied. Some features of the codes are the storage of the approximation to the inverse Hessian matrix in lower trapezoidal factored form and the use of an optimally-conditioned updating method. Linear equality constraints are permitted subject to the initial Hessian factor being chosen correctly. 3 - Restrictions on the complexity of the problem: The functions to which the routine is applied are assumed to be differentiable. The routine also requires (n 2 /2) + 0(n) storage locations where n is the problem dimension
International Nuclear Information System (INIS)
Kowsary, F.; Pooladvand, K.; Pourshaghaghy, A.
2007-01-01
In this paper, an appropriate distribution of the heating elements' strengths in a radiation furnace is estimated using inverse methods so that a pre-specified temperature and heat flux distribution is attained on the design surface. Minimization of the sum of the squares of the error function is performed using the variable metric method (VMM), and the results are compared with those obtained by the conjugate gradient method (CGM) established previously in the literature. It is shown via test cases and a well-founded validation procedure that the VMM, when using a 'regularized' estimator, is more accurate and is able to reach at a higher quality final solution as compared to the CGM. The test cases used in this study were two-dimensional furnaces filled with an absorbing, emitting, and scattering gas
KEELE, Minimization of Nonlinear Function with Linear Constraints, Variable Metric Method
International Nuclear Information System (INIS)
Westley, G.W.
1975-01-01
1 - Description of problem or function: KEELE is a linearly constrained nonlinear programming algorithm for locating a local minimum of a function of n variables with the variables subject to linear equality and/or inequality constraints. 2 - Method of solution: A variable metric procedure is used where the direction of search at each iteration is obtained by multiplying the negative of the gradient vector by a positive definite matrix which approximates the inverse of the matrix of second partial derivatives associated with the function. 3 - Restrictions on the complexity of the problem: Array dimensions limit the number of variables to 20 and the number of constraints to 50. These can be changed by the user
Real variables with basic metric space topology
Ash, Robert B
2009-01-01
Designed for a first course in real variables, this text presents the fundamentals for more advanced mathematical work, particularly in the areas of complex variables, measure theory, differential equations, functional analysis, and probability. Geared toward advanced undergraduate and graduate students of mathematics, it is also appropriate for students of engineering, physics, and economics who seek an understanding of real analysis.The author encourages an intuitive approach to problem solving and offers concrete examples, diagrams, and geometric or physical interpretations of results. Deta
Method Points: towards a metric for method complexity
Directory of Open Access Journals (Sweden)
Graham McLeod
1998-11-01
Full Text Available A metric for method complexity is proposed as an aid to choosing between competing methods, as well as in validating the effects of method integration or the products of method engineering work. It is based upon a generic method representation model previously developed by the author and adaptation of concepts used in the popular Function Point metric for system size. The proposed technique is illustrated by comparing two popular I.E. deliverables with counterparts in the object oriented Unified Modeling Language (UML. The paper recommends ways to improve the practical adoption of new methods.
Variable-metric diffraction crystals for x-ray optics
International Nuclear Information System (INIS)
Smither, R.K.; Fernandez, P.B.
1992-01-01
A variable-metric (VM) crystal is one in which the spacing between the crystalline planes changes with position in the crystal. This variation can be either parallel to the crystalline planes or perpendicular to the crystalline planes of interest and can be produced by either introducing a thermal gradient in the crystal or by growing a crystal made of two or more elements and changing the relative percentages of the two elements as the crystal is grown. A series of experiments were performed in the laboratory to demonstrate the principle of the variable-metric crystal and its potential use in synchrotron beam lines. One of the most useful applications of the VM crystal is to increase the number of photons per unit bandwidth in a diffracted beam without losing any of the overall intensity. In a normal synchrotron beam line that uses a two-crystal monochromator, the bandwidth of the diffracted photon beam is determined by the vertical opening angle of the beam which is typically 0.10--0.30 mrad or 20--60 arcsec. When the VM crystal approach is applied, the bandwidth of the beam can be made as narrow as the rocking curve of the diffracting crystal, which is typically 0.005--0.050 mrad or 1--10 arcsec. Thus a very large increase of photons per unit bandwidth (or per unit energy) can be achieved through the use of VM crystals. When the VM principle is used with bent crystals, new kinds of x-ray optical elements can be generated that can focus and defocus x-ray beams much like simple lenses where the focal length of the lens can be changed to match its application. Thus both large magnifications and large demagnifications can be achieved as well as parallel beams with narrow bandwidths
Shoaib, Syed Abu; Marshall, Lucy; Sharma, Ashish
2018-06-01
Every model to characterise a real world process is affected by uncertainty. Selecting a suitable model is a vital aspect of engineering planning and design. Observation or input errors make the prediction of modelled responses more uncertain. By way of a recently developed attribution metric, this study is aimed at developing a method for analysing variability in model inputs together with model structure variability to quantify their relative contributions in typical hydrological modelling applications. The Quantile Flow Deviation (QFD) metric is used to assess these alternate sources of uncertainty. The Australian Water Availability Project (AWAP) precipitation data for four different Australian catchments is used to analyse the impact of spatial rainfall variability on simulated streamflow variability via the QFD. The QFD metric attributes the variability in flow ensembles to uncertainty associated with the selection of a model structure and input time series. For the case study catchments, the relative contribution of input uncertainty due to rainfall is higher than that due to potential evapotranspiration, and overall input uncertainty is significant compared to model structure and parameter uncertainty. Overall, this study investigates the propagation of input uncertainty in a daily streamflow modelling scenario and demonstrates how input errors manifest across different streamflow magnitudes.
An Overview of Heart Rate Variability Metrics and Norms
Directory of Open Access Journals (Sweden)
Fred Shaffer
2017-09-01
Full Text Available Healthy biological systems exhibit complex patterns of variability that can be described by mathematical chaos. Heart rate variability (HRV consists of changes in the time intervals between consecutive heartbeats called interbeat intervals (IBIs. A healthy heart is not a metronome. The oscillations of a healthy heart are complex and constantly changing, which allow the cardiovascular system to rapidly adjust to sudden physical and psychological challenges to homeostasis. This article briefly reviews current perspectives on the mechanisms that generate 24 h, short-term (~5 min, and ultra-short-term (<5 min HRV, the importance of HRV, and its implications for health and performance. The authors provide an overview of widely-used HRV time-domain, frequency-domain, and non-linear metrics. Time-domain indices quantify the amount of HRV observed during monitoring periods that may range from ~2 min to 24 h. Frequency-domain values calculate the absolute or relative amount of signal energy within component bands. Non-linear measurements quantify the unpredictability and complexity of a series of IBIs. The authors survey published normative values for clinical, healthy, and optimal performance populations. They stress the importance of measurement context, including recording period length, subject age, and sex, on baseline HRV values. They caution that 24 h, short-term, and ultra-short-term normative values are not interchangeable. They encourage professionals to supplement published norms with findings from their own specialized populations. Finally, the authors provide an overview of HRV assessment strategies for clinical and optimal performance interventions.
A Practical Method for Collecting Social Media Campaign Metrics
Gharis, Laurie W.; Hightower, Mary F.
2017-01-01
Today's Extension professionals are tasked with more work and fewer resources. Integrating social media campaigns into outreach efforts can be an efficient way to meet work demands. If resources go toward social media, a practical method for collecting metrics is needed. Collecting metrics adds one more task to the workloads of Extension…
Temporal variability of daily personal magnetic field exposure metrics in pregnant women.
Lewis, Ryan C; Evenson, Kelly R; Savitz, David A; Meeker, John D
2015-01-01
Recent epidemiology studies of power-frequency magnetic fields and reproductive health have characterized exposures using data collected from personal exposure monitors over a single day, possibly resulting in exposure misclassification due to temporal variability in daily personal magnetic field exposure metrics, but relevant data in adults are limited. We assessed the temporal variability of daily central tendency (time-weighted average, median) and peak (upper percentiles, maximum) personal magnetic field exposure metrics over 7 consecutive days in 100 pregnant women. When exposure was modeled as a continuous variable, central tendency metrics had substantial reliability, whereas peak metrics had fair (maximum) to moderate (upper percentiles) reliability. The predictive ability of a single-day metric to accurately classify participants into exposure categories based on a weeklong metric depended on the selected exposure threshold, with sensitivity decreasing with increasing exposure threshold. Consistent with the continuous measures analysis, sensitivity was higher for central tendency metrics than for peak metrics. If there is interest in peak metrics, more than 1 day of measurement is needed over the window of disease susceptibility to minimize measurement error, but 1 day may be sufficient for central tendency metrics.
Methods and Metrics for Evaluating Environmental Dredging ...
This report documents the objectives, approach, methodologies, results, and interpretation of a collaborative research study conducted by the National Risk Management Research Laboratory (NRMRL) and the National Exposure Research laboratory (NERL) of the U.S. Environmental Protection Agency’s (U.S. EPA’s) Office of Research and Development (ORD) and the U.S. EPA’s Great Lakes National Program Office (GLNPO). The objectives of the research study were to: 1) evaluate remedy effectiveness of environmental dredging as applied to contaminated sediments in the Ashtabula River in northeastern Ohio, and 2) monitor the recovery of the surrounding ecosystem. The project was carried out over 6 years from 2006 through 2011 and consisted of the development and evaluation of methods and approaches to assess river and ecosystem conditions prior to dredging (2006), during dredging (2006 and 2007), and following dredging, both short term (2008) and long term (2009-2011). This project report summarizes and interprets the results of this 6-year study to develop and assess methods for monitoring pollutant fate and transport and ecosystem recovery through the use of biological, chemical, and physical lines of evidence (LOEs) such as: 1) comprehensive sampling of and chemical analysis of contaminants in surface, suspended, and historic sediments; 2) extensive grab and multi-level real time water sampling and analysis of contaminants in the water column; 3) sampling, chemi
Estimating bacterial diversity for ecological studies: methods, metrics, and assumptions.
Directory of Open Access Journals (Sweden)
Julia Birtel
Full Text Available Methods to estimate microbial diversity have developed rapidly in an effort to understand the distribution and diversity of microorganisms in natural environments. For bacterial communities, the 16S rRNA gene is the phylogenetic marker gene of choice, but most studies select only a specific region of the 16S rRNA to estimate bacterial diversity. Whereas biases derived from from DNA extraction, primer choice and PCR amplification are well documented, we here address how the choice of variable region can influence a wide range of standard ecological metrics, such as species richness, phylogenetic diversity, β-diversity and rank-abundance distributions. We have used Illumina paired-end sequencing to estimate the bacterial diversity of 20 natural lakes across Switzerland derived from three trimmed variable 16S rRNA regions (V3, V4, V5. Species richness, phylogenetic diversity, community composition, β-diversity, and rank-abundance distributions differed significantly between 16S rRNA regions. Overall, patterns of diversity quantified by the V3 and V5 regions were more similar to one another than those assessed by the V4 region. Similar results were obtained when analyzing the datasets with different sequence similarity thresholds used during sequences clustering and when the same analysis was used on a reference dataset of sequences from the Greengenes database. In addition we also measured species richness from the same lake samples using ARISA Fingerprinting, but did not find a strong relationship between species richness estimated by Illumina and ARISA. We conclude that the selection of 16S rRNA region significantly influences the estimation of bacterial diversity and species distributions and that caution is warranted when comparing data from different variable regions as well as when using different sequencing techniques.
Remark on application of the Banach metric method to cosmology
International Nuclear Information System (INIS)
Szydlowski, M.; Heller, M.
1982-01-01
If the cosmological equations can be reduced to the form of a dynamic system, the space of all their solutions is a Banach space. The influence of different parameters on the dynamics of the world models can be easily studied by means of the Banach metric. The method is tested for the Friedman cosmological models perturbed by the bulk viscosity. (author)
Metric-based method of software requirements correctness improvement
Directory of Open Access Journals (Sweden)
Yaremchuk Svitlana
2017-01-01
Full Text Available The work highlights the most important principles of software reliability management (SRM. The SRM concept construes a basis for developing a method of requirements correctness improvement. The method assumes that complicated requirements contain more actual and potential design faults/defects. The method applies a newer metric to evaluate the requirements complexity and double sorting technique evaluating the priority and complexity of a particular requirement. The method enables to improve requirements correctness due to identification of a higher number of defects with restricted resources. Practical application of the proposed method in the course of demands review assured a sensible technical and economic effect.
International Nuclear Information System (INIS)
Szereszewski, A; Sym, A
2015-01-01
The standard method of separation of variables in PDEs called the Stäckel–Robertson–Eisenhart (SRE) approach originated in the papers by Robertson (1928 Math. Ann. 98 749–52) and Eisenhart (1934 Ann. Math. 35 284–305) on separability of variables in the Schrödinger equation defined on a pseudo-Riemannian space equipped with orthogonal coordinates, which in turn were based on the purely classical mechanics results by Paul Stäckel (1891, Habilitation Thesis, Halle). These still fundamental results have been further extended in diverse directions by e.g. Havas (1975 J. Math. Phys. 16 1461–8; J. Math. Phys. 16 2476–89) or Koornwinder (1980 Lecture Notes in Mathematics 810 (Berlin: Springer) pp 240–63). The involved separability is always ordinary (factor R = 1) and regular (maximum number of independent parameters in separation equations). A different approach to separation of variables was initiated by Gaston Darboux (1878 Ann. Sci. E.N.S. 7 275–348) which has been almost completely forgotten in today’s research on the subject. Darboux’s paper was devoted to the so-called R-separability of variables in the standard Laplace equation. At the outset he did not make any specific assumption about the separation equations (this is in sharp contrast to the SRE approach). After impressive calculations Darboux obtained a complete solution of the problem. He found not only eleven cases of ordinary separability Eisenhart (1934 Ann. Math. 35 284–305) but also Darboux–Moutard–cyclidic metrics (Bôcher 1894 Ueber die Reihenentwickelungen der Potentialtheorie (Leipzig: Teubner)) and non-regularly separable Dupin-cyclidic metrics as well. In our previous paper Darboux’s approach was extended to the case of the stationary Schrödinger equation on Riemannian spaces admitting orthogonal coordinates. In particular the class of isothermic metrics was defined (isothermicity of the metric is a necessary condition for its R-separability). An important sub
Temporal Variability of Daily Personal Magnetic Field Exposure Metrics in Pregnant Women
Lewis, Ryan C.; Evenson, Kelly R.; Savitz, David A.; Meeker, John D.
2014-01-01
Recent epidemiology studies of power-frequency magnetic fields and reproductive health have characterized exposures using data collected from personal exposure monitors over a single day, possibly resulting in exposure misclassification due to temporal variability in daily personal magnetic field exposure metrics, but relevant data in adults are limited. We assessed the temporal variability of daily central tendency (time-weighted average, median) and peak (upper percentiles, maximum) persona...
Rawlings, Renata A.; Shi, Hang; Yuan, Lo-Hua; Brehm, William; Pop-Busui, Rodica
2011-01-01
Abstract Background Several metrics of glucose variability have been proposed to date, but an integrated approach that provides a complete and consistent assessment of glycemic variation is missing. As a consequence, and because of the tedious coding necessary during quantification, most investigators and clinicians have not yet adopted the use of multiple glucose variability metrics to evaluate glycemic variation. Methods We compiled the most extensively used statistical techniques and glucose variability metrics, with adjustable hyper- and hypoglycemic limits and metric parameters, to create a user-friendly Continuous Glucose Monitoring Graphical User Interface for Diabetes Evaluation (CGM-GUIDE©). In addition, we introduce and demonstrate a novel transition density profile that emphasizes the dynamics of transitions between defined glucose states. Results Our combined dashboard of numerical statistics and graphical plots support the task of providing an integrated approach to describing glycemic variability. We integrated existing metrics, such as SD, area under the curve, and mean amplitude of glycemic excursion, with novel metrics such as the slopes across critical transitions and the transition density profile to assess the severity and frequency of glucose transitions per day as they move between critical glycemic zones. Conclusions By presenting the above-mentioned metrics and graphics in a concise aggregate format, CGM-GUIDE provides an easy to use tool to compare quantitative measures of glucose variability. This tool can be used by researchers and clinicians to develop new algorithms of insulin delivery for patients with diabetes and to better explore the link between glucose variability and chronic diabetes complications. PMID:21932986
Extraction Methods, Variability Encountered in
Bodelier, P.L.E.; Nelson, K.E.
2014-01-01
Synonyms Bias in DNA extractions methods; Variation in DNA extraction methods Definition The variability in extraction methods is defined as differences in quality and quantity of DNA observed using various extraction protocols, leading to differences in outcome of microbial community composition
Open Problem: Kernel methods on manifolds and metric spaces
DEFF Research Database (Denmark)
Feragen, Aasa; Hauberg, Søren
2016-01-01
Radial kernels are well-suited for machine learning over general geodesic metric spaces, where pairwise distances are often the only computable quantity available. We have recently shown that geodesic exponential kernels are only positive definite for all bandwidths when the input space has strong...... linear properties. This negative result hints that radial kernel are perhaps not suitable over geodesic metric spaces after all. Here, however, we present evidence that large intervals of bandwidths exist where geodesic exponential kernels have high probability of being positive definite over finite...... datasets, while still having significant predictive power. From this we formulate conjectures on the probability of a positive definite kernel matrix for a finite random sample, depending on the geometry of the data space and the spread of the sample....
The application of simple metrics in the assessment of glycaemic variability.
Monnier, L; Colette, C; Owens, D R
2018-03-06
The assessment of glycaemic variability (GV) remains a subject of debate with many indices proposed to represent either short- (acute glucose fluctuations) or long-term GV (variations of HbA 1c ). For the assessment of short-term within-day GV, the coefficient of variation for glucose (%CV) defined as the standard deviation adjusted on the 24-h mean glucose concentration is easy to perform and with a threshold of 36%, recently adopted by the international consensus on use of continuous glucose monitoring, separating stable from labile glycaemic states. More complex metrics such as the Low Blood Glucose Index (LBGI) or High Blood Glucose Index (HBGI) allow the risk of hypo or hyperglycaemic episodes, respectively to be assessed although in clinical practice its application is limited due to the need for more complex computation. This also applies to other indices of short-term intraday GV including the mean amplitude of glycemic excursions (MAGE), Shlichtkrull's M-value and CONGA. GV is important clinically as exaggerated glucose fluctuations are associated with an enhanced risk of adverse cardiovascular outcomes due primarily to hypoglycaemia. In contrast, there is at present no compelling evidence that elevated short-term GV is an independent risk factor of microvascular complications of diabetes. Concerning long-term GV there are numerous studies supporting its association with an enhanced risk of cardiovascular events. However, this association raises the question as to whether the impact of long-term variability is not simply the consequence of repeated exposure to short-term GV or ambient chronic hyperglycaemia. The renewed emphasis on glucose monitoring with the introduction of continuous glucose monitoring technologies can benefit from the introduction and application of simple metrics for describing GV along with supporting recommendations. Copyright © 2018 Elsevier Masson SAS. All rights reserved.
Directory of Open Access Journals (Sweden)
Keshav Kumar
Full Text Available Bacteria cells are protected from osmotic and environmental stresses by an exoskeleton-like polymeric structure called peptidoglycan (PG or murein sacculus. This structure is fundamental for bacteria's viability and thus, the mechanisms underlying cell wall assembly and how it is modulated serve as targets for many of our most successful antibiotics. Therefore, it is now more important than ever to understand the genetics and structural chemistry of the bacterial cell walls in order to find new and effective methods of blocking it for the treatment of disease. In the last decades, liquid chromatography and mass spectrometry have been demonstrated to provide the required resolution and sensitivity to characterize the fine chemical structure of PG. However, the large volume of data sets that can be produced by these instruments today are difficult to handle without a proper data analysis workflow. Here, we present PG-metrics, a chemometric based pipeline that allows fast and easy classification of bacteria according to their muropeptide chromatographic profiles and identification of the subjacent PG chemical variability between e.g. bacterial species, growth conditions and, mutant libraries. The pipeline is successfully validated here using PG samples from different bacterial species and mutants in cell wall proteins. The obtained results clearly demonstrated that PG-metrics pipeline is a valuable bioanalytical tool that can lead us to cell wall classification and biomarker discovery.
Braithwaite, Susan S; Umpierrez, Guillermo E; Chase, J Geoffrey
2013-09-01
Group metrics are described to quantify blood glucose (BG) variability of hospitalized patients. The "multiplicative surrogate standard deviation" (MSSD) is the reverse-transformed group mean of the standard deviations (SDs) of the logarithmically transformed BG data set of each patient. The "geometric group mean" (GGM) is the reverse-transformed group mean of the means of the logarithmically transformed BG data set of each patient. Before reverse transformation is performed, the mean of means and mean of SDs each has its own SD, which becomes a multiplicative standard deviation (MSD) after reverse transformation. Statistical predictions and comparisons of parametric or nonparametric tests remain valid after reverse transformation. A subset of a previously published BG data set of 20 critically ill patients from the first 72 h of treatment under the SPRINT protocol was transformed logarithmically. After rank ordering according to the SD of the logarithmically transformed BG data of each patient, the cohort was divided into two equal groups, those having lower or higher variability. For the entire cohort, the GGM was 106 (÷/× 1.07) mg/dl, and MSSD was 1.24 (÷/× 1.07). For the subgroups having lower and higher variability, respectively, the GGM did not differ, 104 (÷/× 1.07) versus 109 (÷/× 1.07) mg/dl, but the MSSD differed, 1.17 (÷/× 1.03) versus 1.31 (÷/× 1.05), p = .00004. By using the MSSD with its MSD, groups can be characterized and compared according to glycemic variability of individual patient members. © 2013 Diabetes Technology Society.
Bitner-Mathé, Blanche Christine; David, Jean Robert
2015-08-01
Thermal phenotypic plasticity of 5 metric thoracic traits (3 related to size and 2 to pigmentation) was investigated in Zaprionus indianus with an isofemale line design. Three of these traits are investigated for the first time in a drosophilid, i.e. thorax width and width of pigmented longitudinal white and black stripes. The reaction norms of white and black stripes were completely different: white stripes were insensitive to growth temperature while the black stripes exhibited a strong linear decrease with increasing temperatures. Thorax width exhibited a concave reaction norm, analogous but not identical to those of wing length and thorax length: the temperatures of maximum value were different, the highest being for thorax width. All traits exhibited a significant heritable variability and a low evolvability. Sexual dimorphism was very variable among traits, being nil for white stripes and thorax width, and around 1.13 for black stripes. The ratio thorax length to thorax width (an elongation index) was always >1, showing that males have a more rounded thorax at all temperatures. Black stripes revealed a significant increase of sexual dimorphism with increasing temperature. Shape indices, i.e. ratios between size traits all exhibited a linear decrease with temperature, the least sensitive being the elongation index. All these results illustrate the complexity of developmental processes but also the analytical strength of biometrical plasticity studies in an eco-devo perspective.
A new metric method-improved structural holes researches on software networks
Li, Bo; Zhao, Hai; Cai, Wei; Li, Dazhou; Li, Hui
2013-03-01
The scale software systems quickly increase with the rapid development of software technologies. Hence, how to understand, measure, manage and control software structure is a great challenge for software engineering. there are also many researches on software networks metrics: C&K, MOOD, McCabe and etc, the aim of this paper is to propose a new and better method to metric software networks. The metric method structural holes are firstly introduced to in this paper, which can not directly be applied as a result of modular characteristics on software network. Hence, structural holes is redefined in this paper and improved, calculation process and results are described in detail. The results shows that the new method can better reflect bridge role of vertexes on software network and there is a significant correlation between degree and improved structural holes. At last, a hydropower simulation system is taken as an example to show validity of the new metric method.
Eum, H. I.; Cannon, A. J.
2015-12-01
Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the
COMPARISON OF LARGE RIVER SAMPLING METHODS ON ALGAL METRICS
We compared the results of four methods used to assess the algal communities at 60 sites distributed among four rivers. Based on Principle Component Analysis of physical habitat data collected concomitantly with the algal data, sites were separated into those with a mean thalweg...
COMPARISON OF LARGE RIVER SAMPLING METHOD USING DIATOM METRICS
We compared the results of four methods used to assess the algal communities at 60 sites distributed among four rivers. Based on Principle Component Analysis of physical habitat data collected concomitantly with the algal data, sites were separated into those with a mean thalweg...
Copy alert : A method and metric to detect visual copycat brands
Satomura, T.; Wedel, M.; Pieters, R.
The authors propose a method and metric to quantify the consumer confusion between leading brands and copycat brands that results from the visual similarity of their packaging designs. The method has three components. First, image processing techniques establish the objective similarity of the
Methods and metrics challenges of delivery-system research
Directory of Open Access Journals (Sweden)
Alexander Jeffrey A
2012-03-01
Full Text Available Abstract Background Many delivery-system interventions are fundamentally about change in social systems (both planned and unplanned. This systems perspective raises a number of methodological challenges for studying the effects of delivery-system change--particularly for answering questions related to whether the change will work under different conditions and how the change is integrated (or not into the operating context of the delivery system. Methods The purpose of this paper is to describe the methodological and measurement challenges posed by five key issues in delivery-system research: (1 modeling intervention context; (2 measuring readiness for change; (3 assessing intervention fidelity and sustainability; (4 assessing complex, multicomponent interventions; and (5 incorporating time in delivery-system models to discuss recommendations for addressing these issues. For each issue, we provide recommendations for how research may be designed and implemented to overcome these challenges. Results and conclusions We suggest that a more refined understanding of the mechanisms underlying delivery-system interventions (treatment theory and the ways in which outcomes for different classes of individuals change over time are fundamental starting points for capturing the heterogeneity in samples of individuals exposed to delivery-system interventions. To support the research recommendations outlined in this paper and to advance understanding of the "why" and "how" questions of delivery-system change and their effects, funding agencies should consider supporting studies with larger organizational sample sizes; longer duration; and nontraditional, mixed-methods designs. A version of this paper was prepared under contract with the Agency for Healthcare Research and Quality (AHRQ, US Department of Health and Human Services for presentation and discussion at a meeting on "The Challenge and Promise of Delivery System Research," held in Sterling, VA, on
Madison, Guy
2014-03-01
Timing performance becomes less precise for longer intervals, which makes it difficult to achieve simultaneity in synchronisation with a rhythm. The metrical structure of music, characterised by hierarchical levels of binary or ternary subdivisions of time, may function to increase precision by providing additional timing information when the subdivisions are explicit. This hypothesis was tested by comparing synchronisation performance across different numbers of metrical levels conveyed by loudness of sounds, such that the slowest level was loudest and the fastest was softest. Fifteen participants moved their hand with one of 9 inter-beat intervals (IBIs) ranging from 524 to 3,125 ms in 4 metrical level (ML) conditions ranging from 1 (one movement for each sound) to 4 (one movement for every 8th sound). The lowest relative variability (SD/IBI<1.5%) was obtained for the 3 longest IBIs (1600-3,125 ms) and MLs 3-4, significantly less than the smallest value (4-5% at 524-1024 ms) for any ML 1 condition in which all sounds are identical. Asynchronies were also more negative with higher ML. In conclusion, metrical subdivision provides information that facilitates temporal performance, which suggests an underlying neural multi-level mechanism capable of integrating information across levels. © 2013.
Energy Technology Data Exchange (ETDEWEB)
Cessenat, M.; Genta, P.
1996-12-31
We use a method based on a separation of variables for solving a system of first order partial differential equations, in a very simple modelling of MHD. The method consists in introducing three unknown variables {phi}1, {phi}2, {phi}3 in addition of the time variable {tau} and then searching a solution which is separated with respect to {phi}1 and {tau} only. This is allowed by a very simple relation, called a `metric separation equation`, which governs the type of solutions with respect to time. The families of solutions for the system of equations thus obtained, correspond to a radial evolution of the fluid. Solving the MHD equations is then reduced to find the transverse component H{sub {Sigma}} of the magnetic field on the unit sphere {Sigma} by solving a non linear partial differential equation on {Sigma}. Thus we generalize ideas due to Courant-Friedrichs and to Sedov on dimensional analysis and self-similar solutions. (authors).
Rawlings, Renata A; Shi, Hang; Yuan, Lo-Hua; Brehm, William; Pop-Busui, Rodica; Nelson, Patrick W
2011-12-01
Several metrics of glucose variability have been proposed to date, but an integrated approach that provides a complete and consistent assessment of glycemic variation is missing. As a consequence, and because of the tedious coding necessary during quantification, most investigators and clinicians have not yet adopted the use of multiple glucose variability metrics to evaluate glycemic variation. We compiled the most extensively used statistical techniques and glucose variability metrics, with adjustable hyper- and hypoglycemic limits and metric parameters, to create a user-friendly Continuous Glucose Monitoring Graphical User Interface for Diabetes Evaluation (CGM-GUIDE©). In addition, we introduce and demonstrate a novel transition density profile that emphasizes the dynamics of transitions between defined glucose states. Our combined dashboard of numerical statistics and graphical plots support the task of providing an integrated approach to describing glycemic variability. We integrated existing metrics, such as SD, area under the curve, and mean amplitude of glycemic excursion, with novel metrics such as the slopes across critical transitions and the transition density profile to assess the severity and frequency of glucose transitions per day as they move between critical glycemic zones. By presenting the above-mentioned metrics and graphics in a concise aggregate format, CGM-GUIDE provides an easy to use tool to compare quantitative measures of glucose variability. This tool can be used by researchers and clinicians to develop new algorithms of insulin delivery for patients with diabetes and to better explore the link between glucose variability and chronic diabetes complications.
Osetrin, Evgeny; Osetrin, Konstantin
2017-11-01
We consider space-time models with pure radiation, which admit integration of the eikonal equation by the method of separation of variables. For all types of these models, the equations of the energy-momentum conservation law are integrated. The resulting form of metric, energy density, and wave vectors of radiation as functions of metric for all types of spaces under consideration is presented. The solutions obtained can be used for any metric theories of gravitation.
Link Prediction Methods and Their Accuracy for Different Social Networks and Network Metrics
Directory of Open Access Journals (Sweden)
Fei Gao
2015-01-01
Full Text Available Currently, we are experiencing a rapid growth of the number of social-based online systems. The availability of the vast amounts of data gathered in those systems brings new challenges that we face when trying to analyse it. One of the intensively researched topics is the prediction of social connections between users. Although a lot of effort has been made to develop new prediction approaches, the existing methods are not comprehensively analysed. In this paper we investigate the correlation between network metrics and accuracy of different prediction methods. We selected six time-stamped real-world social networks and ten most widely used link prediction methods. The results of the experiments show that the performance of some methods has a strong correlation with certain network metrics. We managed to distinguish “prediction friendly” networks, for which most of the prediction methods give good performance, as well as “prediction unfriendly” networks, for which most of the methods result in high prediction error. Correlation analysis between network metrics and prediction accuracy of prediction methods may form the basis of a metalearning system where based on network characteristics it will be able to recommend the right prediction method for a given network.
Wang, Chao; Ding, Mingzhou; Kluger, Benzi M
2014-03-01
Cognitive fatigability is conventionally quantified as the increase over time in either mean reaction time (RT) or error rate from two or more time periods during sustained performance of a prolonged cognitive task. There is evidence indicating that these mean performance measures may not sufficiently reflect the response characteristics of cognitive fatigue. We hypothesized that changes in intraindividual variability over time would be a more sensitive and ecologically meaningful metric for investigations of fatigability of cognitive performance. To test the hypothesis fifteen young adults were recruited. Trait fatigue perceptions in various domains were assessed with the Multidimensional Fatigue Index (MFI). Behavioral data were then recorded during performance of a three-hour continuous cued Stroop task. Results showed that intraindividual variability, as quantified by the coefficient of variation of RT, increased linearly over the course of three hours and demonstrated a significantly greater effect size than mean RT or accuracy. Change in intraindividual RT variability over time was significantly correlated with relevant subscores of the MFI including reduced activity, reduced motivation and mental fatigue. While change in mean RT over time was also correlated with reduced motivation and mental fatigue, these correlations were significantly smaller than those associated with intraindividual RT variability. RT distribution analysis using an ex-Gaussian model further revealed that change in intraindividual variability over time reflects an increase in the exponential component of variance and may reflect attentional lapses or other breakdowns in cognitive control. These results suggest that intraindividual variability and its change over time provide important metrics for measuring cognitive fatigability and may prove useful for inferring the underlying neuronal mechanisms of both perceptions of fatigue and objective changes in performance. Copyright © 2014
Accounting for no net loss: A critical assessment of biodiversity offsetting metrics and methods.
Carreras Gamarra, Maria Jose; Lassoie, James Philip; Milder, Jeffrey
2018-08-15
Biodiversity offset strategies are based on the explicit calculation of both losses and gains necessary to establish ecological equivalence between impact and offset areas. Given the importance of quantifying biodiversity values, various accounting methods and metrics are continuously being developed and tested for this purpose. Considering the wide array of alternatives, selecting an appropriate one for a specific project can be not only challenging, but also crucial; accounting methods can strongly influence the biodiversity outcomes of an offsetting strategy, and if not well-suited to the context and values being offset, a no net loss outcome might not be delivered. To date there has been no systematic review or comparative classification of the available biodiversity accounting alternatives that aim at facilitating metric selection, and no tools that guide decision-makers throughout such a complex process. We fill this gap by developing a set of analyses to support (i) identifying the spectrum of available alternatives, (ii) understanding the characteristics of each and, ultimately (iii) making the most sensible and sound decision about which one to implement. The metric menu, scoring matrix, and decision tree developed can be used by biodiversity offsetting practitioners to help select an existing metric, and thus achieve successful outcomes that advance the goal of no net loss of biodiversity. Copyright © 2018 Elsevier Ltd. All rights reserved.
Metric Learning Method Aided Data-Driven Design of Fault Detection Systems
Directory of Open Access Journals (Sweden)
Guoyang Yan
2014-01-01
Full Text Available Fault detection is fundamental to many industrial applications. With the development of system complexity, the number of sensors is increasing, which makes traditional fault detection methods lose efficiency. Metric learning is an efficient way to build the relationship between feature vectors with the categories of instances. In this paper, we firstly propose a metric learning-based fault detection framework in fault detection. Meanwhile, a novel feature extraction method based on wavelet transform is used to obtain the feature vector from detection signals. Experiments on Tennessee Eastman (TE chemical process datasets demonstrate that the proposed method has a better performance when comparing with existing methods, for example, principal component analysis (PCA and fisher discriminate analysis (FDA.
Spangler, Derek P; Williams, DeWayne P; Speller, Lassiter F; Brooks, Justin R; Thayer, Julian F
2018-03-01
The relationships between vagally mediated heart rate variability (vmHRV) and the cognitive mechanisms underlying performance can be elucidated with ex-Gaussian modeling-an approach that quantifies two different forms of intra-individual variability (IIV) in reaction time (RT). To this end, the current study examined relations of resting vmHRV to whole-distribution and ex-Gaussian IIV. Subjects (N = 83) completed a 5-minute baseline while vmHRV (root mean square of successive differences; RMSSD) was measured. Ex-Gaussian (sigma, tau) and whole-distribution (standard deviation) estimates of IIV were derived from reaction times on a Stroop task. Resting vmHRV was found to be inversely related to tau (exponential IIV) but not to sigma (Gaussian IIV) or the whole-distribution standard deviation of RTs. Findings suggest that individuals with high vmHRV can better prevent attentional lapses but not difficulties with motor control. These findings inform the differential relationships of cardiac vagal control to the cognitive processes underlying human performance. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Mahajan, Ruhi; Viangteeravat, Teeradache; Akbilgic, Oguz
2017-12-01
A timely diagnosis of congestive heart failure (CHF) is crucial to evade a life-threatening event. This paper presents a novel probabilistic symbol pattern recognition (PSPR) approach to detect CHF in subjects from their cardiac interbeat (R-R) intervals. PSPR discretizes each continuous R-R interval time series by mapping them onto an eight-symbol alphabet and then models the pattern transition behavior in the symbolic representation of the series. The PSPR-based analysis of the discretized series from 107 subjects (69 normal and 38 CHF subjects) yielded discernible features to distinguish normal subjects and subjects with CHF. In addition to PSPR features, we also extracted features using the time-domain heart rate variability measures such as average and standard deviation of R-R intervals. An ensemble of bagged decision trees was used to classify two groups resulting in a five-fold cross-validation accuracy, specificity, and sensitivity of 98.1%, 100%, and 94.7%, respectively. However, a 20% holdout validation yielded an accuracy, specificity, and sensitivity of 99.5%, 100%, and 98.57%, respectively. Results from this study suggest that features obtained with the combination of PSPR and long-term heart rate variability measures can be used in developing automated CHF diagnosis tools. Copyright © 2017 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Zharkova, N.Ya.; Martynenko, L.I.; Dzyubenko, N.G.
1989-01-01
Interaction of zirconium oxychloride with acetylacetone (NA) was studied by the method of pH-metric titration using KOH and NH 4 OH as neutralizing agents. It is shown that processes of hydrolysis and complexation complete in the system. It was established that decrease of hydrolysis of Zr-containing complex forms and ZrA 4 · 10H 2 O isolation takes place in relatively concentrated solutions of ZrOCl 2 and NA mixture, taken with 1:4 molar ratio when using NH 4 OH as neutralizing agent
Variable selection by lasso-type methods
Directory of Open Access Journals (Sweden)
Sohail Chand
2011-09-01
Full Text Available Variable selection is an important property of shrinkage methods. The adaptive lasso is an oracle procedure and can do consistent variable selection. In this paper, we provide an explanation that how use of adaptive weights make it possible for the adaptive lasso to satisfy the necessary and almost sufcient condition for consistent variable selection. We suggest a novel algorithm and give an important result that for the adaptive lasso if predictors are normalised after the introduction of adaptive weights, it makes the adaptive lasso performance identical to the lasso.
Gait variability: methods, modeling and meaning
Directory of Open Access Journals (Sweden)
Hausdorff Jeffrey M
2005-07-01
Full Text Available Abstract The study of gait variability, the stride-to-stride fluctuations in walking, offers a complementary way of quantifying locomotion and its changes with aging and disease as well as a means of monitoring the effects of therapeutic interventions and rehabilitation. Previous work has suggested that measures of gait variability may be more closely related to falls, a serious consequence of many gait disorders, than are measures based on the mean values of other walking parameters. The Current JNER series presents nine reports on the results of recent investigations into gait variability. One novel method for collecting unconstrained, ambulatory data is reviewed, and a primer on analysis methods is presented along with a heuristic approach to summarizing variability measures. In addition, the first studies of gait variability in animal models of neurodegenerative disease are described, as is a mathematical model of human walking that characterizes certain complex (multifractal features of the motor control's pattern generator. Another investigation demonstrates that, whereas both healthy older controls and patients with a higher-level gait disorder walk more slowly in reduced lighting, only the latter's stride variability increases. Studies of the effects of dual tasks suggest that the regulation of the stride-to-stride fluctuations in stride width and stride time may be influenced by attention loading and may require cognitive input. Finally, a report of gait variability in over 500 subjects, probably the largest study of this kind, suggests how step width variability may relate to fall risk. Together, these studies provide new insights into the factors that regulate the stride-to-stride fluctuations in walking and pave the way for expanded research into the control of gait and the practical application of measures of gait variability in the clinical setting.
Harmonizing exposure metrics and methods for sustainability assessments of food contact materials
DEFF Research Database (Denmark)
Ernstoff, Alexi; Jolliet, Olivier; Niero, Monia
2016-01-01
) and Cradle to Cradle to support packaging design. Each assessment has distinct context and goals, but can help manage exposure to toxic chemicals and other environmental impacts. Metrics a nd methods to quantify and characterize exposure to potentially toxic chemicals specifically in food packaging are......, however, notably lacking from such assessments. Furthermore, previous case studies demonstrated that sustainable packaging design focuses, such as decreasing greenhouse gas emissions or resource consumption, can increase exposure to toxic chemicals through packaging. Thereby, developing harmonized methods...... for quantifying exposure to chemicals in food packaging is critical to ensure ‘sustainable packages’ do not increase exposure to toxic chemicals. Therefore we developed modelling methods suitable for first-tier risk screening and environmental assessments. The modelling framework was based on the new product...
Helmer, K G; Chou, M-C; Preciado, R I; Gimi, B; Rollins, N K; Song, A; Turner, J; Mori, S
2016-02-27
It is now common for magnetic-resonance-imaging (MRI) based multi-site trials to include diffusion-weighted imaging (DWI) as part of the protocol. It is also common for these sites to possess MR scanners of different manufacturers, different software and hardware, and different software licenses. These differences mean that scanners may not be able to acquire data with the same number of gradient amplitude values and number of available gradient directions. Variability can also occur in achievable b-values and minimum echo times. The challenge of a multi-site study then, is to create a common protocol by understanding and then minimizing the effects of scanner variability and identifying reliable and accurate diffusion metrics. This study describes the effect of site, scanner vendor, field strength, and TE on two diffusion metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA) using two common analyses (region-of-interest and mean-bin value of whole brain histograms). The goal of the study was to identify sources of variability in diffusion-sensitized imaging and their influence on commonly reported metrics. The results demonstrate that the site, vendor, field strength, and echo time all contribute to variability in FA and MD, though to different extent. We conclude that characterization of the variability of DTI metrics due to site, vendor, field strength, and echo time is a worthwhile step in the construction of multi-center trials.
Bellet, Aurelien; Sebban, Marc
2015-01-01
Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learnin
Helmer, K. G.; Chou, M-C.; Preciado, R. I.; Gimi, B.; Rollins, N. K.; Song, A.; Turner, J.; Mori, S.
2016-01-01
MRI-based multi-site trials now routinely include some form of diffusion-weighted imaging (DWI) in their protocol. These studies can include data originating from scanners built by different vendors, each with their own set of unique protocol restrictions, including restrictions on the number of available gradient directions, whether an externally-generated list of gradient directions can be used, and restrictions on the echo time (TE). One challenge of multi-site studies is to create a common imaging protocol that will result in a reliable and accurate set of diffusion metrics. The present study describes the effect of site, scanner vendor, field strength, and TE on two common metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA). We have shown in earlier work that ROI metrics and the mean of MD and FA histograms are not sufficiently sensitive for use in site characterization. Here we use the distance between whole brain histograms of FA and MD to investigate within- and between-site effects. We concluded that the variability of DTI metrics due to site, vendor, field strength, and echo time could influence the results in multi-center trials and that histogram distance is sensitive metrics for each of these variables. PMID:27350723
Helmer, K G; Chou, M-C; Preciado, R I; Gimi, B; Rollins, N K; Song, A; Turner, J; Mori, S
2016-02-27
MRI-based multi-site trials now routinely include some form of diffusion-weighted imaging (DWI) in their protocol. These studies can include data originating from scanners built by different vendors, each with their own set of unique protocol restrictions, including restrictions on the number of available gradient directions, whether an externally-generated list of gradient directions can be used, and restrictions on the echo time (TE). One challenge of multi-site studies is to create a common imaging protocol that will result in a reliable and accurate set of diffusion metrics. The present study describes the effect of site, scanner vendor, field strength, and TE on two common metrics: the first moment of the diffusion tensor field (mean diffusivity, MD), and the fractional anisotropy (FA). We have shown in earlier work that ROI metrics and the mean of MD and FA histograms are not sufficiently sensitive for use in site characterization. Here we use the distance between whole brain histograms of FA and MD to investigate within- and between-site effects. We concluded that the variability of DTI metrics due to site, vendor, field strength, and echo time could influence the results in multi-center trials and that histogram distance is sensitive metrics for each of these variables.
Novel Clustering Method Based on K-Medoids and Mobility Metric
Directory of Open Access Journals (Sweden)
Y. Hamzaoui
2018-06-01
Full Text Available The structure and constraint of MANETS influence negatively the performance of QoS, moreover the main routing protocols proposed generally operate in flat routing. Hence, this structure gives the bad results of QoS when the network becomes larger and denser. To solve this problem we use one of the most popular methods named clustering. The present paper comes within the frameworks of research to improve the QoS in MANETs. In this paper we propose a new algorithm of clustering based on the new mobility metric and K-Medoid to distribute the nodes into several clusters. Intuitively our algorithm can give good results in terms of stability of the cluster, and can also extend life time of cluster head.
Karnowski, Thomas P [Knoxville, TN; Tobin, Jr., Kenneth W.; Muthusamy Govindasamy, Vijaya Priya [Knoxville, TN; Chaum, Edward [Memphis, TN
2012-07-10
A method for assigning a confidence metric for automated determination of optic disc location that includes analyzing a retinal image and determining at least two sets of coordinates locating an optic disc in the retinal image. The sets of coordinates can be determined using first and second image analysis techniques that are different from one another. An accuracy parameter can be calculated and compared to a primary risk cut-off value. A high confidence level can be assigned to the retinal image if the accuracy parameter is less than the primary risk cut-off value and a low confidence level can be assigned to the retinal image if the accuracy parameter is greater than the primary risk cut-off value. The primary risk cut-off value being selected to represent an acceptable risk of misdiagnosis of a disease having retinal manifestations by the automated technique.
Directory of Open Access Journals (Sweden)
Jochen eSchubert
2015-11-01
Full Text Available Metric resolution digital terrain models (DTMs of rivers now make it possible for multi-dimensional fluid mechanics models to be applied to characterize flow at fine scales that are relevant to studies of river morphology and ecological habitat, or microscales. These developments are important for managing rivers because of the potential to better understand system dynamics, anthropogenic impacts, and the consequences of proposed interventions. However, the data volumes and computational demands of microscale river modeling have largely constrained applications to small multiples of the channel width, or the mesoscale. This report presents computational methods to extend a microscale river model beyond the mesoscale to the macroscale, defined as large multiples of the channel width. A method of automated unstructured grid generation is presented that automatically clusters fine resolution cells in areas of curvature (e.g., channel banks, and places relatively coarse cells in areas lacking topographic variability. This overcomes the need to manually generate breaklines to constrain the grid, which is painstaking at the mesoscale and virtually impossible at the macroscale. The method is applied to a braided river with an extremely complex channel network configuration and shown to yield an efficient fine resolution model. The sensitivity of model output to grid design and resistance parameters is also examined as it relates to analysis of hydrology, hydraulic geometry and river habitats and the findings reiterate the importance of model calibration and validation.
Local cell metrics: a novel method for analysis of cell-cell interactions.
Su, Jing; Zapata, Pedro J; Chen, Chien-Chiang; Meredith, J Carson
2009-10-23
The regulation of many cell functions is inherently linked to cell-cell contact interactions. However, effects of contact interactions among adherent cells can be difficult to detect with global summary statistics due to the localized nature and noise inherent to cell-cell interactions. The lack of informatics approaches specific for detecting cell-cell interactions is a limitation in the analysis of large sets of cell image data, including traditional and combinatorial or high-throughput studies. Here we introduce a novel histogram-based data analysis strategy, termed local cell metrics (LCMs), which addresses this shortcoming. The new LCM method is demonstrated via a study of contact inhibition of proliferation of MC3T3-E1 osteoblasts. We describe how LCMs can be used to quantify the local environment of cells and how LCMs are decomposed mathematically into metrics specific to each cell type in a culture, e.g., differently-labelled cells in fluorescence imaging. Using this approach, a quantitative, probabilistic description of the contact inhibition effects in MC3T3-E1 cultures has been achieved. We also show how LCMs are related to the naïve Bayes model. Namely, LCMs are Bayes class-conditional probability functions, suggesting their use for data mining and classification. LCMs are successful in robust detection of cell contact inhibition in situations where conventional global statistics fail to do so. The noise due to the random features of cell behavior was suppressed significantly as a result of the focus on local distances, providing sensitive detection of cell-cell contact effects. The methodology can be extended to any quantifiable feature that can be obtained from imaging of cell cultures or tissue samples, including optical, fluorescent, and confocal microscopy. This approach may prove useful in interpreting culture and histological data in fields where cell-cell interactions play a critical role in determining cell fate, e.g., cancer, developmental
Constrained variable projection method for blind deconvolution
International Nuclear Information System (INIS)
Cornelio, A; Piccolomini, E Loli; Nagy, J G
2012-01-01
This paper is focused on the solution of the blind deconvolution problem, here modeled as a separable nonlinear least squares problem. The well known ill-posedness, both on recovering the blurring operator and the true image, makes the problem really difficult to handle. We show that, by imposing appropriate constraints on the variables and with well chosen regularization parameters, it is possible to obtain an objective function that is fairly well behaved. Hence, the resulting nonlinear minimization problem can be effectively solved by classical methods, such as the Gauss-Newton algorithm.
Local cell metrics: a novel method for analysis of cell-cell interactions
Directory of Open Access Journals (Sweden)
Chen Chien-Chiang
2009-10-01
Full Text Available Abstract Background The regulation of many cell functions is inherently linked to cell-cell contact interactions. However, effects of contact interactions among adherent cells can be difficult to detect with global summary statistics due to the localized nature and noise inherent to cell-cell interactions. The lack of informatics approaches specific for detecting cell-cell interactions is a limitation in the analysis of large sets of cell image data, including traditional and combinatorial or high-throughput studies. Here we introduce a novel histogram-based data analysis strategy, termed local cell metrics (LCMs, which addresses this shortcoming. Results The new LCM method is demonstrated via a study of contact inhibition of proliferation of MC3T3-E1 osteoblasts. We describe how LCMs can be used to quantify the local environment of cells and how LCMs are decomposed mathematically into metrics specific to each cell type in a culture, e.g., differently-labelled cells in fluorescence imaging. Using this approach, a quantitative, probabilistic description of the contact inhibition effects in MC3T3-E1 cultures has been achieved. We also show how LCMs are related to the naïve Bayes model. Namely, LCMs are Bayes class-conditional probability functions, suggesting their use for data mining and classification. Conclusion LCMs are successful in robust detection of cell contact inhibition in situations where conventional global statistics fail to do so. The noise due to the random features of cell behavior was suppressed significantly as a result of the focus on local distances, providing sensitive detection of cell-cell contact effects. The methodology can be extended to any quantifiable feature that can be obtained from imaging of cell cultures or tissue samples, including optical, fluorescent, and confocal microscopy. This approach may prove useful in interpreting culture and histological data in fields where cell-cell interactions play a critical
Standard metrics and methods for conducting Avian/wind energy interaction studies
Energy Technology Data Exchange (ETDEWEB)
Anderson, R.L. [California Energy Commission, Sacramento, CA (United States); Davis, H. [National Renewable Energy Lab., Golden, CO (United States); Kendall, W. [National Biological Service, Laurel, MD (United States)] [and others
1997-12-31
The awareness of the problem of avian fatalities at large scale wind energy developments first emerged in the late 1980`s at the Altamont Pass Wind Resource Area (WRA) in Central California. Observations of dead raptors at the Altamont Pass WRA triggered concern on the part of regulatory agencies, environmental/conservation groups, resource agencies, and wind and electric utility industries. This led the California Energy Commission staff, along with the planning departments of Alameda, Contra Costa, and Solano counties, to commission a study of bird mortality at the Altamont Pass WRA. In addition to the Altamont Pass WRA, other studies and observations have established that windplants kill birds. Depending upon the specific factors, this may or may not be a serious problem. The current level of scrutiny and caution exhibited during the permitting of a new windplant development in the United States results in costly delays and studies. This is occurring during a highly competitive period for electrical production companies in the USA. Clarification of the bird fatality issue is needed to bring it into perspective. This means standardizing metrics, defining terms, and recommending methods to be used in addressing or studying wind energy/bird interactions.
A metric space for Type Ia supernova spectra: a new method to assess explosion scenarios
Sasdelli, Michele; Hillebrandt, W.; Kromer, M.; Ishida, E. E. O.; Röpke, F. K.; Sim, S. A.; Pakmor, R.; Seitenzahl, I. R.; Fink, M.
2017-04-01
Over the past years, Type Ia supernovae (SNe Ia) have become a major tool to determine the expansion history of the Universe, and considerable attention has been given to, both, observations and models of these events. However, until now, their progenitors are not known. The observed diversity of light curves and spectra seems to point at different progenitor channels and explosion mechanisms. Here, we present a new way to compare model predictions with observations in a systematic way. Our method is based on the construction of a metric space for SN Ia spectra by means of linear principal component analysis, taking care of missing and/or noisy data, and making use of partial least-squares regression to find correlations between spectral properties and photometric data. We investigate realizations of the three major classes of explosion models that are presently discussed: delayed-detonation Chandrasekhar-mass explosions, sub-Chandrasekhar-mass detonations and double-degenerate mergers, and compare them with data. We show that in the principal component space, all scenarios have observed counterparts, supporting the idea that different progenitors are likely. However, all classes of models face problems in reproducing the observed correlations between spectral properties and light curves and colours. Possible reasons are briefly discussed.
Risk assessment of groundwater level variability using variable Kriging methods
Spanoudaki, Katerina; Kampanis, Nikolaos A.
2015-04-01
Assessment of the water table level spatial variability in aquifers provides useful information regarding optimal groundwater management. This information becomes more important in basins where the water table level has fallen significantly. The spatial variability of the water table level in this work is estimated based on hydraulic head measured during the wet period of the hydrological year 2007-2008, in a sparsely monitored basin in Crete, Greece, which is of high socioeconomic and agricultural interest. Three Kriging-based methodologies are elaborated in Matlab environment to estimate the spatial variability of the water table level in the basin. The first methodology is based on the Ordinary Kriging approach, the second involves auxiliary information from a Digital Elevation Model in terms of Residual Kriging and the third methodology calculates the probability of the groundwater level to fall below a predefined minimum value that could cause significant problems in groundwater resources availability, by means of Indicator Kriging. The Box-Cox methodology is applied to normalize both the data and the residuals for improved prediction results. In addition, various classical variogram models are applied to determine the spatial dependence of the measurements. The Matérn model proves to be the optimal, which in combination with Kriging methodologies provides the most accurate cross validation estimations. Groundwater level and probability maps are constructed to examine the spatial variability of the groundwater level in the basin and the associated risk that certain locations exhibit regarding a predefined minimum value that has been set for the sustainability of the basin's groundwater resources. Acknowledgement The work presented in this paper has been funded by the Greek State Scholarships Foundation (IKY), Fellowships of Excellence for Postdoctoral Studies (Siemens Program), 'A simulation-optimization model for assessing the best practices for the
Methods for detrending success metrics to account for inflationary and deflationary factors*
Petersen, A. M.; Penner, O.; Stanley, H. E.
2011-01-01
Time-dependent economic, technological, and social factors can artificially inflate or deflate quantitative measures for career success. Here we develop and test a statistical method for normalizing career success metrics across time dependent factors. In particular, this method addresses the long standing question: how do we compare the career achievements of professional athletes from different historical eras? Developing an objective approach will be of particular importance over the next decade as major league baseball (MLB) players from the "steroids era" become eligible for Hall of Fame induction. Some experts are calling for asterisks (*) to be placed next to the career statistics of athletes found guilty of using performance enhancing drugs (PED). Here we address this issue, as well as the general problem of comparing statistics from distinct eras, by detrending the seasonal statistics of professional baseball players. We detrend player statistics by normalizing achievements to seasonal averages, which accounts for changes in relative player ability resulting from a range of factors. Our methods are general, and can be extended to various arenas of competition where time-dependent factors play a key role. For five statistical categories, we compare the probability density function (pdf) of detrended career statistics to the pdf of raw career statistics calculated for all player careers in the 90-year period 1920-2009. We find that the functional form of these pdfs is stationary under detrending. This stationarity implies that the statistical regularity observed in the right-skewed distributions for longevity and success in professional sports arises from both the wide range of intrinsic talent among athletes and the underlying nature of competition. We fit the pdfs for career success by the Gamma distribution in order to calculate objective benchmarks based on extreme statistics which can be used for the identification of extraordinary careers.
Assessing the metrics of climate change. Current methods and future possibilities
Energy Technology Data Exchange (ETDEWEB)
Fuglestveit, Jan S.; Berntsen, Terje K.; Godal, Odd; Sausen, Robert; Shine, Keith P.; Skodvin, Tora
2001-07-01
With the principle of comprehensiveness embedded in the UN Framework Convention on Climate Change (Art. 3), a multi-gas abatement strategy with emphasis also on non-CO2 greenhouse gases as targets for reduction and control measures has been adopted in the international climate regime. In the Kyoto Protocol, the comprehensive approach is made operative as the aggregate anthropogenic carbon dioxide equivalent emissions of six specified greenhouse gases or groups of gases (Art. 3). With this operationalisation, the emissions of a set of greenhouse gases with very different atmospheric lifetimes and radiative properties are transformed into one common unit - CO2 equivalents. This transformation is based on the Global Warming Potential (GWP) index, which in turn is based on the concept of radiative forcing. The GWP metric and its application in policy making has been debated, and several other alternative concepts have been suggested. In this paper, we review existing and alternative metrics of climate change, with particular emphasis on radiative forcing and GWPs, in terms of their scientific performance. This assessment focuses on questions such as the climate impact (end point) against which gases are weighted; the extent to which and how temporality is included, both with regard to emission control and with regard to climate impact; how cost issues are dealt with; and the sensitivity of the metrics to various assumptions. It is concluded that the radiative forcing concept is a robust and useful metric of the potential climatic impact of various agents and that there are prospects for improvement by weighing different forcings according to their effectiveness. We also find that although the GWP concept is associated with serious shortcomings, it retains advantages over any of the proposed alternatives in terms of political feasibility. Alternative metrics, however, make a significant contribution to addressing important issues, and this contribution should be taken
Assessing the metrics of climate change. Current methods and future possibilities
International Nuclear Information System (INIS)
Fuglestveit, Jan S.; Berntsen, Terje K.; Godal, Odd; Sausen, Robert; Shine, Keith P.; Skodvin, Tora
2001-01-01
With the principle of comprehensiveness embedded in the UN Framework Convention on Climate Change (Art. 3), a multi-gas abatement strategy with emphasis also on non-CO2 greenhouse gases as targets for reduction and control measures has been adopted in the international climate regime. In the Kyoto Protocol, the comprehensive approach is made operative as the aggregate anthropogenic carbon dioxide equivalent emissions of six specified greenhouse gases or groups of gases (Art. 3). With this operationalisation, the emissions of a set of greenhouse gases with very different atmospheric lifetimes and radiative properties are transformed into one common unit - CO2 equivalents. This transformation is based on the Global Warming Potential (GWP) index, which in turn is based on the concept of radiative forcing. The GWP metric and its application in policy making has been debated, and several other alternative concepts have been suggested. In this paper, we review existing and alternative metrics of climate change, with particular emphasis on radiative forcing and GWPs, in terms of their scientific performance. This assessment focuses on questions such as the climate impact (end point) against which gases are weighted; the extent to which and how temporality is included, both with regard to emission control and with regard to climate impact; how cost issues are dealt with; and the sensitivity of the metrics to various assumptions. It is concluded that the radiative forcing concept is a robust and useful metric of the potential climatic impact of various agents and that there are prospects for improvement by weighing different forcings according to their effectiveness. We also find that although the GWP concept is associated with serious shortcomings, it retains advantages over any of the proposed alternatives in terms of political feasibility. Alternative metrics, however, make a significant contribution to addressing important issues, and this contribution should be taken
Comparison of image sharpness metrics and real-time sharpening methods with GPU implementations
CSIR Research Space (South Africa)
De Villiers, Johan P
2010-06-01
Full Text Available , and not in trying to adjust the image to some fixed sharpness value. With the advent of the increased progammability of Graphics Pro- cessing Units (GPU) and their seemingly ever increasing number of processor cores (the dual-GPU NVidia GTX295 has 480 cores...) Quadro MDS 140M 16 400 64 700 ATI HD 2400XT 40 800 64 700 NVidia 9600GT 64 650 256 900 NVidia GTX280 240 602 512 1107 2 Metric descriptions Three metrics are used to evaluate images for sharpness. The first two are a measure of how much information...
Collective variables method in relativistic theory
International Nuclear Information System (INIS)
Shurgaya, A.V.
1983-01-01
Classical theory of N-component field is considered. The method of collective variables accurately accounting for conservation laws proceeding from invariance theory under homogeneous Lorentz group is developed within the frames of generalized hamiltonian dynamics. Hyperboloids are invariant surfaces Under the homogeneous Lorentz group. Proceeding from this, field transformation is introduced, and the surface is parametrized so that generators of the homogeneous Lorentz group do not include components dependent on interaction and their effect on the field function is reduced to geometrical. The interaction is completely included in the expression for the energy-momentum vector of the system which is a dynamical value. Gauge is chosen where parameters of four-dimensional translations and their canonically-conjugated pulses are non-physical and thus phase space is determined by parameters of the homogeneous Lorentz group, field function and their canonically-conjugated pulses. So it is managed to accurately account for conservation laws proceeding from the requirement of lorentz-invariance
Prognostic Performance Metrics
National Aeronautics and Space Administration — This chapter presents several performance metrics for offline evaluation of prognostics algorithms. A brief overview of different methods employed for performance...
A multiple decision support metrics method for effective risk-informed asset management
International Nuclear Information System (INIS)
Liming, J.K.; Salter, J.E.
2004-01-01
The objective of this paper is to provide electric utilities with a concept for developing and applying effective decision support metrics via integrated risk-informed asset management (RIAM) programs for power stations and generating companies. RIAM is a process by which analysts review historical performance and develop predictive logic models and data analyses to predict critical decision support figures-of-merit (or metrics) for generating station managers and electric utility company executives. These metrics include, but are not limited to, the following: profitability, net benefit, benefit-to-cost ratio, projected return on investment, projected revenue, projected costs, asset value, safety (catastrophic facility damage frequency and consequences, etc.), power production availability (capacity factor, etc.), efficiency (heat rate), and others. RIAM applies probabilistic safety assessment (PSA) techniques and generates predictions in a probabilistic way so that metrics information can be supplied to managers in terms of probability distributions as well as point estimates. This enables the managers to apply the concept of 'confidence levels' in their critical decision-making processes. (authors)
DATA COLLECTION METHOD FOR PEDESTRIAN MOVEMENT VARIABLES
Directory of Open Access Journals (Sweden)
Hajime Inamura
2000-01-01
Full Text Available The need of tools for design and evaluation of pedestrian areas, subways stations, entrance hall, shopping mall, escape routes, stadium etc lead to the necessity of a pedestrian model. One approach pedestrian model is Microscopic Pedestrian Simulation Model. To be able to develop and calibrate a microscopic pedestrian simulation model, a number of variables need to be considered. As the first step of model development, some data was collected using video and the coordinate of the head path through image processing were also taken. Several numbers of variables can be gathered to describe the behavior of pedestrian from a different point of view. This paper describes how to obtain variables from video taking and simple image processing that can represent the movement of pedestrians and its variables
A method based on a separation of variables in magnetohydrodynamics (MHD)
International Nuclear Information System (INIS)
Cessenat, M.; Genta, P.
1996-01-01
We use a method based on a separation of variables for solving a system of first order partial differential equations, in a very simple modelling of MHD. The method consists in introducing three unknown variables φ1, φ2, φ3 in addition of the time variable τ and then searching a solution which is separated with respect to φ1 and τ only. This is allowed by a very simple relation, called a 'metric separation equation', which governs the type of solutions with respect to time. The families of solutions for the system of equations thus obtained, correspond to a radial evolution of the fluid. Solving the MHD equations is then reduced to find the transverse component H Σ of the magnetic field on the unit sphere Σ by solving a non linear partial differential equation on Σ. Thus we generalize ideas due to Courant-Friedrichs and to Sedov on dimensional analysis and self-similar solutions. (authors)
Chernozhukov, Victor; Hansen, Christian; Spindler, Martin
2016-01-01
In this article the package High-dimensional Metrics (\\texttt{hdm}) is introduced. It is a collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e...
Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean
2017-12-04
Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further
Hu, Bo; Kalfoglou, Yannis; Dupplaw, David; Alani, Harith; Lewis, Paul; Shadbolt, Nigel
2006-01-01
In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can be boiled down to one fundamental operation: computing the similarity and/or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a...
Emittance measurements by variable quadrupole method
International Nuclear Information System (INIS)
Toprek, D.
2005-01-01
The beam emittance is a measure of both the beam size and beam divergence, we cannot directly measure its value. If the beam size is measured at different locations or under different focusing conditions such that different parts of the phase space ellipse will be probed by the beam size monitor, the beam emittance can be determined. An emittance measurement can be performed by different methods. Here we will consider the varying quadrupole setting method.
Russell, J. L.; Sarmiento, J. L.
2017-12-01
The Southern Ocean is central to the climate's response to increasing levels of atmospheric greenhouse gases as it ventilates a large fraction of the global ocean volume. Global coupled climate models and earth system models, however, vary widely in their simulations of the Southern Ocean and its role in, and response to, the ongoing anthropogenic forcing. Due to its complex water-mass structure and dynamics, Southern Ocean carbon and heat uptake depend on a combination of winds, eddies, mixing, buoyancy fluxes and topography. Understanding how the ocean carries heat and carbon into its interior and how the observed wind changes are affecting this uptake is essential to accurately projecting transient climate sensitivity. Observationally-based metrics are critical for discerning processes and mechanisms, and for validating and comparing climate models. As the community shifts toward Earth system models with explicit carbon simulations, more direct observations of important biogeochemical parameters, like those obtained from the biogeochemically-sensored floats that are part of the Southern Ocean Carbon and Climate Observations and Modeling project, are essential. One goal of future observing systems should be to create observationally-based benchmarks that will lead to reducing uncertainties in climate projections, and especially uncertainties related to oceanic heat and carbon uptake.
Sheridan, Robert P
2008-02-01
We introduce two ways of testing the robustness of conclusions from studies comparing virtual screening methods: alternative "global goodness" metrics and sensitivity analysis. While the robustness tests cannot eliminate all biases in virtual screening comparisons, they are useful as a "reality check" for any given study. To illustrate this, we apply them to a set of enrichments published in McGaughey et al. (J. Chem. Inf. Model. 2007, 47, 1504-1519) where 11 target protein/ligand combinations are tested on 2D and 3D similarity methods, plus docking. The major conclusions in that paper, for instance, that ligand-based methods are better than docking methods, hold up. However, some minor conclusions, such as Glide being the best docking method, do not.
Directory of Open Access Journals (Sweden)
Miroslav Kališnik
2011-05-01
Full Text Available In the introduction the evolution of methods for numerical density estimation of particles is presented shortly. Three pairs of methods have been analysed and compared: (1 classical methods for particles counting in thin and thick sections, (2 original and modified differential counting methods and (3 physical and optical disector methods. Metric characteristics such as accuracy, efficiency, robustness, and feasibility of methods have been estimated and compared. Logical, geometrical and mathematical analysis as well as computer simulations have been applied. In computer simulations a model of randomly distributed equal spheres with maximal contrast against surroundings has been used. According to our computer simulation all methods give accurate results provided that the sample is representative and sufficiently large. However, there are differences in their efficiency, robustness and feasibility. Efficiency and robustness increase with increasing slice thickness in all three pairs of methods. Robustness is superior in both differential and both disector methods compared to both classical methods. Feasibility can be judged according to the additional equipment as well as to the histotechnical and counting procedures necessary for performing individual counting methods. However, it is evident that not all practical problems can efficiently be solved with models.
Probabilistic Power Flow Method Considering Continuous and Discrete Variables
Directory of Open Access Journals (Sweden)
Xuexia Zhang
2017-04-01
Full Text Available This paper proposes a probabilistic power flow (PPF method considering continuous and discrete variables (continuous and discrete power flow, CDPF for power systems. The proposed method—based on the cumulant method (CM and multiple deterministic power flow (MDPF calculations—can deal with continuous variables such as wind power generation (WPG and loads, and discrete variables such as fuel cell generation (FCG. In this paper, continuous variables follow a normal distribution (loads or a non-normal distribution (WPG, and discrete variables follow a binomial distribution (FCG. Through testing on IEEE 14-bus and IEEE 118-bus power systems, the proposed method (CDPF has better accuracy compared with the CM, and higher efficiency compared with the Monte Carlo simulation method (MCSM.
A Streamlined Artificial Variable Free Version of Simplex Method
Inayatullah, Syed; Touheed, Nasir; Imtiaz, Muhammad
2015-01-01
This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new ...
Tarle, Stephanie J; Alderson, R Matt; Patros, Connor H G; Lea, Sarah E; Hudec, Kristen L; Arrington, Elaine F
2017-05-01
Despite promising findings in extant research that suggest impaired working memory (WM) serves as a central neurocognitive deficit or candidate endophenotype of attention-deficit/hyperactivity disorder (ADHD), findings from translational research have been relatively underwhelming. This study aimed to explicate previous equivocal findings by systematically examining the effect of methodological variability on WM performance estimates across experimental and clinical WM measures. Age-matched boys (ages 8-12 years) with (n = 20) and without (n = 20) ADHD completed 1 experimental (phonological) and 2 clinical (digit span, letter-number sequencing) WM measures. The use of partial scoring procedures, administration of greater trial numbers, and high central executive demands yielded moderate-to-large between-groups effect sizes. Moreover, the combination of these best-case procedures, compared to worst-case procedures (i.e., absolute scoring, administration of few trials, use of discontinue rules, and low central executive demands), resulted in a 12.5% increase in correct group classification. Collectively, these findings explain inconsistent ADHD-related WM deficits in previous reports, and highlight the need for revised clinical measures that utilize best-case procedures. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Two methods for studying the X-ray variability
Yan, Shu-Ping; Ji, Li; Méndez, Mariano; Wang, Na; Liu, Siming; Li, Xiang-Dong
2016-01-01
The X-ray aperiodic variability and quasi-periodic oscillation (QPO) are the important tools to study the structure of the accretion flow of X-ray binaries. However, the origin of the complex X-ray variability from X-ray binaries remains yet unsolved. We proposed two methods for studying the X-ray
The functional variable method for solving the fractional Korteweg ...
Indian Academy of Sciences (India)
The physical and engineering processes have been modelled by means of fractional ... very important role in various fields such as economics, chemistry, notably control the- .... In §3, the functional variable method is applied for finding exact.
Extensions of von Neumann's method for generating random variables
International Nuclear Information System (INIS)
Monahan, J.F.
1979-01-01
Von Neumann's method of generating random variables with the exponential distribution and Forsythe's method for obtaining distributions with densities of the form e/sup -G//sup( x/) are generalized to apply to certain power series representations. The flexibility of the power series methods is illustrated by algorithms for the Cauchy and geometric distributions
Variable identification in group method of data handling methodology
Energy Technology Data Exchange (ETDEWEB)
Pereira, Iraci Martinez, E-mail: martinez@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia, Guarulhos, SP (Brazil)
2011-07-01
The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a preselected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and Artificial Neural Network - ANN methodologies, and applied to the IPEN research Reactor IEA-R1. The GMDH was used to study the best set of variables to be used to train an ANN, resulting in a best monitoring variable estimative. The system performs the monitoring by comparing these estimative calculated values with measured ones. The IPEN Reactor Data Acquisition System is composed of 58 variables (process and nuclear variables). As the GMDH is a self-organizing methodology, the input variables choice is made automatically, and the real input variables used in the Monitoring and Diagnosis System were not showed in the final result. This work presents a study of variable identification of GMDH methodology by means of an algorithm that works in parallel with the GMDH algorithm and traces the initial variables paths, resulting in an identification of the variables that composes the best Monitoring and Diagnosis Model. (author)
Variable identification in group method of data handling methodology
International Nuclear Information System (INIS)
Pereira, Iraci Martinez; Bueno, Elaine Inacio
2011-01-01
The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a preselected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and Artificial Neural Network - ANN methodologies, and applied to the IPEN research Reactor IEA-R1. The GMDH was used to study the best set of variables to be used to train an ANN, resulting in a best monitoring variable estimative. The system performs the monitoring by comparing these estimative calculated values with measured ones. The IPEN Reactor Data Acquisition System is composed of 58 variables (process and nuclear variables). As the GMDH is a self-organizing methodology, the input variables choice is made automatically, and the real input variables used in the Monitoring and Diagnosis System were not showed in the final result. This work presents a study of variable identification of GMDH methodology by means of an algorithm that works in parallel with the GMDH algorithm and traces the initial variables paths, resulting in an identification of the variables that composes the best Monitoring and Diagnosis Model. (author)
Metrics for Probabilistic Geometries
DEFF Research Database (Denmark)
Tosi, Alessandra; Hauberg, Søren; Vellido, Alfredo
2014-01-01
the distribution over mappings is given by a Gaussian process. We treat the corresponding latent variable model as a Riemannian manifold and we use the expectation of the metric under the Gaussian process prior to define interpolating paths and measure distance between latent points. We show how distances...
ICT support for measuring customer metrics defined by the Balanced Scorecard method
Directory of Open Access Journals (Sweden)
František Dařena
2006-01-01
Full Text Available In the paper an approach to support of strategic management process using the Balanced Scorecard method is discussed. The main focus is primarily directed to the customer perspective as the most important determining factor of today‘s strategic management. The article suggests general framework for construction of individual performance indicators from this field independently on particular implementation of existing information system in the organization. Methods of gaining necessary information from organization‘s database and from organization‘s environment using customer research are considered.
Timothy G. Wade; James D. Wickham; Maliha S. Nash; Anne C. Neale; Kurt H. Riitters; K. Bruce Jones
2003-01-01
AbstractGIS-based measurements that combine native raster and native vector data are commonly used in environmental assessments. Most of these measurements can be calculated using either raster or vector data formats and processing methods. Raster processes are more commonly used because they can be significantly faster computationally...
pH-metric solubility. 3. Dissolution titration template method for solubility determination.
Avdeef, A; Berger, C M
2001-12-01
The main objective of this study was to develop an effective potentiometric saturation titration protocol for determining the aqueous intrinsic solubility and the solubility-pH profile of ionizable molecules, with the specific aim of overcoming incomplete dissolution conditions, while attempting to shorten the data collection time. A modern theory of dissolution kinetics (an extension of the Noyes-Whitney approach) was applied to acid-base titration experiments. A thermodynamic method was developed, based on a three-component model, to calculate interfacial, diffusion-layer, and bulk-water reactant concentrations in saturated solutions of ionizable compounds perturbed by additions of acid/base titrant, leading to partial dissolution of the solid material. Ten commercial drugs (cimetidine, diltiazem hydrochloride, enalapril maleate, metoprolol tartrate, nadolol, propoxyphene hydrochloride, quinine hydrochloride, terfenadine, trovafloxacin mesylate, and benzoic acid) were chosen to illustrate the new titration methodology. It was shown that the new method is about 10 times faster in determining equilibrium solubility constants, compared to the traditional saturation shake-flask methods.
Directory of Open Access Journals (Sweden)
В. С. Білоус
2017-10-01
Full Text Available Subject. Theme. The aim of the work. The level of development of science and technology is crucial to the progress of society. The need to increase the presence of science in the global scientific information space, increase its influence in the world. The use of metric methods of research in the library of a higher school. Methods. The use of scientific methods of analysis, synthesis, analogy, comparison, forecasting allowed us to examine the results of implementation of innovative communications initiatives in the library of the university Results. Current and future activities of the library of the higher school in integration of scientific publications to international information space are highlighted. The practical implementation of these activities are discussed on the example of the libraries of Vinnitsa State M. Kotsiubynskyi Pedagogical University. Scientific novelty. The role of the university library in the process of increasing the representation of the Ukrainian science in the world of scholarly communication. The proposed strategy, the implementation of which should characterize a modern librarian as a «role model» for the community of the university in the implementation of electronic models of scientific communication. Conclusions. Innovative transformations in the content, forms and methods of library activities, using metric measurements affect the improvement of scientific activities of the institution, give significant social results. Introduction to the practice of library activities certain areas will prevent the «dissipation» of documentary scientific information resources of the university, will contribute to their consolidating, will increase the importance of scientific publications and the authority of the Ukrainian science in General. The article reflects the innovative activities of libraries inVinnytsiaMykhailoKotsiubynskyiStatePedagogicalUniversity, development of library service in using research work of the
Falsification Testing of Instrumental Variables Methods for Comparative Effectiveness Research.
Pizer, Steven D
2016-04-01
To demonstrate how falsification tests can be used to evaluate instrumental variables methods applicable to a wide variety of comparative effectiveness research questions. Brief conceptual review of instrumental variables and falsification testing principles and techniques accompanied by an empirical application. Sample STATA code related to the empirical application is provided in the Appendix. Comparative long-term risks of sulfonylureas and thiazolidinediones for management of type 2 diabetes. Outcomes include mortality and hospitalization for an ambulatory care-sensitive condition. Prescribing pattern variations are used as instrumental variables. Falsification testing is an easily computed and powerful way to evaluate the validity of the key assumption underlying instrumental variables analysis. If falsification tests are used, instrumental variables techniques can help answer a multitude of important clinical questions. © Health Research and Educational Trust.
Adaptive metric kernel regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
2000-01-01
Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...
Adaptive Metric Kernel Regression
DEFF Research Database (Denmark)
Goutte, Cyril; Larsen, Jan
1998-01-01
Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...
The functional variable method for finding exact solutions of some ...
Indian Academy of Sciences (India)
Abstract. In this paper, we implemented the functional variable method and the modified. Riemann–Liouville derivative for the exact solitary wave solutions and periodic wave solutions of the time-fractional Klein–Gordon equation, and the time-fractional Hirota–Satsuma coupled. KdV system. This method is extremely simple ...
International Nuclear Information System (INIS)
Yu, Dequan; Cong, Shu-Lin; Sun, Zhigang
2015-01-01
Highlights: • An optimised finite element discrete variable representation method is proposed. • The method is tested by solving one and two dimensional Schrödinger equations. • The method is quite efficient in solving the molecular Schrödinger equation. • It is very easy to generalise the method to multidimensional problems. - Abstract: The Lobatto discrete variable representation (LDVR) proposed by Manoloupolos and Wyatt (1988) has unique features but has not been generally applied in the field of chemical dynamics. Instead, it has popular application in solving atomic physics problems, in combining with the finite element method (FE-DVR), due to its inherent abilities for treating the Coulomb singularity in spherical coordinates. In this work, an efficient phase optimisation and variable mapping procedure is proposed to improve the grid efficiency of the LDVR/FE-DVR method, which makes it not only be competing with the popular DVR methods, such as the Sinc-DVR, but also keep its advantages for treating with the Coulomb singularity. The method is illustrated by calculations for one-dimensional Coulomb potential, and the vibrational states of one-dimensional Morse potential, two-dimensional Morse potential and two-dimensional Henon–Heiles potential, which prove the efficiency of the proposed scheme and promise more general applications of the LDVR/FE-DVR method
Energy Technology Data Exchange (ETDEWEB)
Yu, Dequan [School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024 (China); State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023 (China); Cong, Shu-Lin, E-mail: shlcong@dlut.edu.cn [School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024 (China); Sun, Zhigang, E-mail: zsun@dicp.ac.cn [State Key Laboratory of Molecular Reaction Dynamics and Center for Theoretical and Computational Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023 (China); Center for Advanced Chemical Physics and 2011 Frontier Center for Quantum Science and Technology, University of Science and Technology of China, 96 Jinzhai Road, Hefei 230026 (China)
2015-09-08
Highlights: • An optimised finite element discrete variable representation method is proposed. • The method is tested by solving one and two dimensional Schrödinger equations. • The method is quite efficient in solving the molecular Schrödinger equation. • It is very easy to generalise the method to multidimensional problems. - Abstract: The Lobatto discrete variable representation (LDVR) proposed by Manoloupolos and Wyatt (1988) has unique features but has not been generally applied in the field of chemical dynamics. Instead, it has popular application in solving atomic physics problems, in combining with the finite element method (FE-DVR), due to its inherent abilities for treating the Coulomb singularity in spherical coordinates. In this work, an efficient phase optimisation and variable mapping procedure is proposed to improve the grid efficiency of the LDVR/FE-DVR method, which makes it not only be competing with the popular DVR methods, such as the Sinc-DVR, but also keep its advantages for treating with the Coulomb singularity. The method is illustrated by calculations for one-dimensional Coulomb potential, and the vibrational states of one-dimensional Morse potential, two-dimensional Morse potential and two-dimensional Henon–Heiles potential, which prove the efficiency of the proposed scheme and promise more general applications of the LDVR/FE-DVR method.
Deep Transfer Metric Learning.
Junlin Hu; Jiwen Lu; Yap-Peng Tan; Jie Zhou
2016-12-01
Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption does not hold in many real visual recognition applications, especially when samples are captured across different data sets. In this paper, we propose a new deep transfer metric learning (DTML) method to learn a set of hierarchical nonlinear transformations for cross-domain visual recognition by transferring discriminative knowledge from the labeled source domain to the unlabeled target domain. Specifically, our DTML learns a deep metric network by maximizing the inter-class variations and minimizing the intra-class variations, and minimizing the distribution divergence between the source domain and the target domain at the top layer of the network. To better exploit the discriminative information from the source domain, we further develop a deeply supervised transfer metric learning (DSTML) method by including an additional objective on DTML, where the output of both the hidden layers and the top layer are optimized jointly. To preserve the local manifold of input data points in the metric space, we present two new methods, DTML with autoencoder regularization and DSTML with autoencoder regularization. Experimental results on face verification, person re-identification, and handwritten digit recognition validate the effectiveness of the proposed methods.
International Nuclear Information System (INIS)
Harper, A.F.A.; Digby, R.B.; Thong, S.P.; Lacey, F.
1978-04-01
In April 1978 a meeting of senior metrication officers convened by the Commonwealth Science Council of the Commonwealth Secretariat, was held in London. The participants were drawn from Australia, Bangladesh, Britain, Canada, Ghana, Guyana, India, Jamaica, Papua New Guinea, Solomon Islands and Trinidad and Tobago. Among other things, the meeting resolved to develop a set of guidelines to assist countries to change to SI and to compile such guidelines in the form of a working manual
Variable Camber Continuous Aerodynamic Control Surfaces and Methods for Active Wing Shaping Control
Nguyen, Nhan T. (Inventor)
2016-01-01
An aerodynamic control apparatus for an air vehicle improves various aerodynamic performance metrics by employing multiple spanwise flap segments that jointly form a continuous or a piecewise continuous trailing edge to minimize drag induced by lift or vortices. At least one of the multiple spanwise flap segments includes a variable camber flap subsystem having multiple chordwise flap segments that may be independently actuated. Some embodiments also employ a continuous leading edge slat system that includes multiple spanwise slat segments, each of which has one or more chordwise slat segment. A method and an apparatus for implementing active control of a wing shape are also described and include the determination of desired lift distribution to determine the improved aerodynamic deflection of the wings. Flap deflections are determined and control signals are generated to actively control the wing shape to approximate the desired deflection.
Measuring the surgical 'learning curve': methods, variables and competency.
Khan, Nuzhath; Abboudi, Hamid; Khan, Mohammed Shamim; Dasgupta, Prokar; Ahmed, Kamran
2014-03-01
To describe how learning curves are measured and what procedural variables are used to establish a 'learning curve' (LC). To assess whether LCs are a valuable measure of competency. A review of the surgical literature pertaining to LCs was conducted using the Medline and OVID databases. Variables should be fully defined and when possible, patient-specific variables should be used. Trainee's prior experience and level of supervision should be quantified; the case mix and complexity should ideally be constant. Logistic regression may be used to control for confounding variables. Ideally, a learning plateau should reach a predefined/expert-derived competency level, which should be fully defined. When the group splitting method is used, smaller cohorts should be used in order to narrow the range of the LC. Simulation technology and competence-based objective assessments may be used in training and assessment in LC studies. Measuring the surgical LC has potential benefits for patient safety and surgical education. However, standardisation in the methods and variables used to measure LCs is required. Confounding variables, such as participant's prior experience, case mix, difficulty of procedures and level of supervision, should be controlled. Competency and expert performance should be fully defined. © 2013 The Authors. BJU International © 2013 BJU International.
New complex variable meshless method for advection—diffusion problems
International Nuclear Information System (INIS)
Wang Jian-Fei; Cheng Yu-Min
2013-01-01
In this paper, an improved complex variable meshless method (ICVMM) for two-dimensional advection—diffusion problems is developed based on improved complex variable moving least-square (ICVMLS) approximation. The equivalent functional of two-dimensional advection—diffusion problems is formed, the variation method is used to obtain the equation system, and the penalty method is employed to impose the essential boundary conditions. The difference method for two-point boundary value problems is used to obtain the discrete equations. Then the corresponding formulas of the ICVMM for advection—diffusion problems are presented. Two numerical examples with different node distributions are used to validate and inestigate the accuracy and efficiency of the new method in this paper. It is shown that ICVMM is very effective for advection—diffusion problems, and has a good convergent character, accuracy, and computational efficiency
Error response test system and method using test mask variable
Gender, Thomas K. (Inventor)
2006-01-01
An error response test system and method with increased functionality and improved performance is provided. The error response test system provides the ability to inject errors into the application under test to test the error response of the application under test in an automated and efficient manner. The error response system injects errors into the application through a test mask variable. The test mask variable is added to the application under test. During normal operation, the test mask variable is set to allow the application under test to operate normally. During testing, the error response test system can change the test mask variable to introduce an error into the application under test. The error response system can then monitor the application under test to determine whether the application has the correct response to the error.
Assessing Mucoadhesion in Polymer Gels: The Effect of Method Type and Instrument Variables
Directory of Open Access Journals (Sweden)
Jéssica Bassi da Silva
2018-03-01
Full Text Available The process of mucoadhesion has been widely studied using a wide variety of methods, which are influenced by instrumental variables and experiment design, making the comparison between the results of different studies difficult. The aim of this work was to standardize the conditions of the detachment test and the rheological methods of mucoadhesion assessment for semisolids, and introduce a texture profile analysis (TPA method. A factorial design was developed to suggest standard conditions for performing the detachment force method. To evaluate the method, binary polymeric systems were prepared containing poloxamer 407 and Carbopol 971P®, Carbopol 974P®, or Noveon® Polycarbophil. The mucoadhesion of systems was evaluated, and the reproducibility of these measurements investigated. This detachment force method was demonstrated to be reproduceable, and gave different adhesion when mucin disk or ex vivo oral mucosa was used. The factorial design demonstrated that all evaluated parameters had an effect on measurements of mucoadhesive force, but the same was not observed for the work of adhesion. It was suggested that the work of adhesion is a more appropriate metric for evaluating mucoadhesion. Oscillatory rheology was more capable of investigating adhesive interactions than flow rheology. TPA method was demonstrated to be reproducible and can evaluate the adhesiveness interaction parameter. This investigation demonstrates the need for standardized methods to evaluate mucoadhesion and makes suggestions for a standard study design.
Improvement of the variable storage coefficient method with water surface gradient as a variable
The variable storage coefficient (VSC) method has been used for streamflow routing in continuous hydrological simulation models such as the Agricultural Policy/Environmental eXtender (APEX) and the Soil and Water Assessment Tool (SWAT) for more than 30 years. APEX operates on a daily time step and ...
The variability of piezoelectric measurements. Material and measurement method contributions
International Nuclear Information System (INIS)
Stewart, M.; Cain, M.
2002-01-01
The variability of piezoelectric materials measurements has been investigated in order to separate the contributions from intrinsic instrumental variability, and the contributions from the variability in materials. The work has pinpointed several areas where weaknesses in the measurement methods result in high variability, and also show that good correlation between piezoelectric parameters allow simpler measurement methods to be used. The Berlincourt method has been shown to be unreliable when testing thin discs, however when testing thicker samples there is a good correlation between this and other methods. The high field permittivity and low field permittivity correlate well, so tolerances on low field measurements would predict high field performance. In trying to identify microstructural origins of samples that behave differently to others within a batch, no direct evidence was found to suggest that outliers originate from either differences in microstructure or crystallography. Some of the samples chosen as maximum outliers showed pin-holes, probably from electrical breakdown during poling, even though these defects would ordinarily be detrimental to piezoelectric output. (author)
Variable Lifting Index (VLI): A New Method for Evaluating Variable Lifting Tasks.
Waters, Thomas; Occhipinti, Enrico; Colombini, Daniela; Alvarez-Casado, Enrique; Fox, Robert
2016-08-01
We seek to develop a new approach for analyzing the physical demands of highly variable lifting tasks through an adaptation of the Revised NIOSH (National Institute for Occupational Safety and Health) Lifting Equation (RNLE) into a Variable Lifting Index (VLI). There are many jobs that contain individual lifts that vary from lift to lift due to the task requirements. The NIOSH Lifting Equation is not suitable in its present form to analyze variable lifting tasks. In extending the prior work on the VLI, two procedures are presented to allow users to analyze variable lifting tasks. One approach involves the sampling of lifting tasks performed by a worker over a shift and the calculation of the Frequency Independent Lift Index (FILI) for each sampled lift and the aggregation of the FILI values into six categories. The Composite Lift Index (CLI) equation is used with lifting index (LI) category frequency data to calculate the VLI. The second approach employs a detailed systematic collection of lifting task data from production and/or organizational sources. The data are organized into simplified task parameter categories and further aggregated into six FILI categories, which also use the CLI equation to calculate the VLI. The two procedures will allow practitioners to systematically employ the VLI method to a variety of work situations where highly variable lifting tasks are performed. The scientific basis for the VLI procedure is similar to that for the CLI originally presented by NIOSH; however, the VLI method remains to be validated. The VLI method allows an analyst to assess highly variable manual lifting jobs in which the task characteristics vary from lift to lift during a shift. © 2015, Human Factors and Ergonomics Society.
Assessment of hip dysplasia and osteoarthritis: Variability of different methods
International Nuclear Information System (INIS)
Troelsen, Anders; Elmengaard, Brian; Soeballe, Kjeld; Roemer, Lone; Kring, Soeren
2010-01-01
Background: Reliable assessment of hip dysplasia and osteoarthritis is crucial in young adults who may benefit from joint-preserving surgery. Purpose: To investigate the variability of different methods for diagnostic assessment of hip dysplasia and osteoarthritis. Material and Methods: By each of four observers, two assessments were done by vision and two by angle construction. For both methods, the intra- and interobserver variability of center-edge and acetabular index angle assessment were analyzed. The observers' ability to diagnose hip dysplasia and osteoarthritis were assessed. All measures were compared to those made on computed tomography scan. Results: Intra- and interobserver variability of angle assessment was less when angles were drawn compared with assessment by vision, and the observers' ability to diagnose hip dysplasia improved when angles were drawn. Assessment of osteoarthritis in general showed poor agreement with findings on computed tomography scan. Conclusion: We recommend that angles always should be drawn for assessment of hip dysplasia on pelvic radiographs. Given the inherent variability of diagnostic assessment of hip dysplasia, a computed tomography scan could be considered in patients with relevant hip symptoms and a center-edge angle between 20 deg and 30 deg. Osteoarthritis should be assessed by measuring the joint space width or by classifying the Toennis grade as either 0-1 or 2-3
Assessment of hip dysplasia and osteoarthritis: Variability of different methods
Energy Technology Data Exchange (ETDEWEB)
Troelsen, Anders; Elmengaard, Brian; Soeballe, Kjeld (Orthopedic Research Unit, Univ. Hospital of Aarhus, Aarhus (Denmark)), e-mail: a_troelsen@hotmail.com; Roemer, Lone (Dept. of Radiology, Univ. Hospital of Aarhus, Aarhus (Denmark)); Kring, Soeren (Dept. of Orthopedic Surgery, Aabenraa Hospital, Aabenraa (Denmark))
2010-03-15
Background: Reliable assessment of hip dysplasia and osteoarthritis is crucial in young adults who may benefit from joint-preserving surgery. Purpose: To investigate the variability of different methods for diagnostic assessment of hip dysplasia and osteoarthritis. Material and Methods: By each of four observers, two assessments were done by vision and two by angle construction. For both methods, the intra- and interobserver variability of center-edge and acetabular index angle assessment were analyzed. The observers' ability to diagnose hip dysplasia and osteoarthritis were assessed. All measures were compared to those made on computed tomography scan. Results: Intra- and interobserver variability of angle assessment was less when angles were drawn compared with assessment by vision, and the observers' ability to diagnose hip dysplasia improved when angles were drawn. Assessment of osteoarthritis in general showed poor agreement with findings on computed tomography scan. Conclusion: We recommend that angles always should be drawn for assessment of hip dysplasia on pelvic radiographs. Given the inherent variability of diagnostic assessment of hip dysplasia, a computed tomography scan could be considered in patients with relevant hip symptoms and a center-edge angle between 20 deg and 30 deg. Osteoarthritis should be assessed by measuring the joint space width or by classifying the Toennis grade as either 0-1 or 2-3
International Nuclear Information System (INIS)
Douglas, Michael R.; Karp, Robert L.; Lukic, Sergio; Reinbacher, Rene
2008-01-01
We develop numerical methods for approximating Ricci flat metrics on Calabi-Yau hypersurfaces in projective spaces. Our approach is based on finding balanced metrics and builds on recent theoretical work by Donaldson. We illustrate our methods in detail for a one parameter family of quintics. We also suggest several ways to extend our results
Chernozhukov, Victor; Hansen, Chris; Spindler, Martin
2016-01-01
The package High-dimensional Metrics (\\Rpackage{hdm}) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment or poli...
Chaos synchronization using single variable feedback based on backstepping method
International Nuclear Information System (INIS)
Zhang Jian; Li Chunguang; Zhang Hongbin; Yu Juebang
2004-01-01
In recent years, backstepping method has been developed in the field of nonlinear control, such as controller, observer and output regulation. In this paper, an effective backstepping design is applied to chaos synchronization. There are some advantages in this method for synchronizing chaotic systems, such as (a) the synchronization error is exponential convergent; (b) only one variable information of the master system is needed; (c) it presents a systematic procedure for selecting a proper controller. Numerical simulations for the Chua's circuit and the Roessler system demonstrate that this method is very effective
SU-F-E-07: Web-Based Training for Radiosurgery: Methods and Metrics for Global Reach
International Nuclear Information System (INIS)
Schulz, R; Thomas, E; Popple, R; Fiveash, J; Jacobsen, E
2016-01-01
Purpose: Webinars have become an evolving tool with greater or lesser success in reaching health care providers (HCPs). This study seeks to assess best practices and metrics for success in webinar deployment for optimal global reach. Methods: Webinars have been developed and launched to reach practicing health care providers in the field of radiation oncology and radiosurgery. One such webinar was launched in early February 2016. “Multiple Brain Metastases & Volumetric Modulated Arc Radiosurgery: Refining the Single-Isocenter Technique to Benefit Surgeons and Patients” presented by Drs. Fiveash and Thomas from UAB was submitted to and accredited by the Institute for Medical Education as qualifying for CME as well as MDCB for educational credit for dosimetrists, in order to encourage participation. MedicalPhysicsWeb was chosen as the platform to inform attendees regarding the webinar. Further IME accredited the activity for 1 AMA PRA Category 1 credit for physicians & medical physicists. The program was qualified by the ABR in meeting the criteria for self-assessment towards fulfilling MOC requirements. Free SAMs credits were underwritten by an educational grant from Varian Medical Systems. Results: The webinar in question attracted 992 pre-registrants from 66 countries. Outside the US and Canada; 11 were from the Americas; 32 were from Europe; 9 from the Middle East and Africa. Australasia and the Indian subcontinent represented the remaining 14 countries. Pre-registrants included 423 Medical Physicists, 225 Medical Dosimetrists, 24 Radiation Therapists, 66 Radiation Oncologists & other. Conclusion: The effectiveness of CME and SAM-CME programs such as this can be gauged by the high rate of respondents who state an intention to change practice habits, a primary goal of continuing medical education and self-assessment. This webinar succeeded in being the most successful webinar on Medical Physics Web as measured by pre-registration, participation and
SU-F-E-07: Web-Based Training for Radiosurgery: Methods and Metrics for Global Reach
Energy Technology Data Exchange (ETDEWEB)
Schulz, R [Varian Medical Systems, Palo Alto, CA (United States); Thomas, E [University of Alabama - Birmingham, Birmingham, AL (United States); Popple, R [The University of Alabama at Birmingham, Birmingham, AL (United States); Fiveash, J [University Alabama Birmingham, Birmingham, AL (United States); Jacobsen, E [Univesity of California, Los Angeles, Los Angeles, CA (United States)
2016-06-15
Purpose: Webinars have become an evolving tool with greater or lesser success in reaching health care providers (HCPs). This study seeks to assess best practices and metrics for success in webinar deployment for optimal global reach. Methods: Webinars have been developed and launched to reach practicing health care providers in the field of radiation oncology and radiosurgery. One such webinar was launched in early February 2016. “Multiple Brain Metastases & Volumetric Modulated Arc Radiosurgery: Refining the Single-Isocenter Technique to Benefit Surgeons and Patients” presented by Drs. Fiveash and Thomas from UAB was submitted to and accredited by the Institute for Medical Education as qualifying for CME as well as MDCB for educational credit for dosimetrists, in order to encourage participation. MedicalPhysicsWeb was chosen as the platform to inform attendees regarding the webinar. Further IME accredited the activity for 1 AMA PRA Category 1 credit for physicians & medical physicists. The program was qualified by the ABR in meeting the criteria for self-assessment towards fulfilling MOC requirements. Free SAMs credits were underwritten by an educational grant from Varian Medical Systems. Results: The webinar in question attracted 992 pre-registrants from 66 countries. Outside the US and Canada; 11 were from the Americas; 32 were from Europe; 9 from the Middle East and Africa. Australasia and the Indian subcontinent represented the remaining 14 countries. Pre-registrants included 423 Medical Physicists, 225 Medical Dosimetrists, 24 Radiation Therapists, 66 Radiation Oncologists & other. Conclusion: The effectiveness of CME and SAM-CME programs such as this can be gauged by the high rate of respondents who state an intention to change practice habits, a primary goal of continuing medical education and self-assessment. This webinar succeeded in being the most successful webinar on Medical Physics Web as measured by pre-registration, participation and
A streamlined artificial variable free version of simplex method.
Directory of Open Access Journals (Sweden)
Syed Inayatullah
Full Text Available This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new method has also been presented which provides a way to easily implement the phase 1 of traditional dual simplex method. For a problem having an initial basis which is both primal and dual infeasible, our methods provide full freedom to the user, that whether to start with primal artificial free version or dual artificial free version without making any reformulation to the LP structure. Last but not the least, it provides a teaching aid for the teachers who want to teach feasibility achievement as a separate topic before teaching optimality achievement.
A streamlined artificial variable free version of simplex method.
Inayatullah, Syed; Touheed, Nasir; Imtiaz, Muhammad
2015-01-01
This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new method has also been presented which provides a way to easily implement the phase 1 of traditional dual simplex method. For a problem having an initial basis which is both primal and dual infeasible, our methods provide full freedom to the user, that whether to start with primal artificial free version or dual artificial free version without making any reformulation to the LP structure. Last but not the least, it provides a teaching aid for the teachers who want to teach feasibility achievement as a separate topic before teaching optimality achievement.
Variable scaling method and Stark effect in hydrogen atom
International Nuclear Information System (INIS)
Choudhury, R.K.R.; Ghosh, B.
1983-09-01
By relating the Stark effect problem in hydrogen-like atoms to that of the spherical anharmonic oscillator we have found simple formulas for energy eigenvalues for the Stark effect. Matrix elements have been calculated using 0(2,1) algebra technique after Armstrong and then the variable scaling method has been used to find optimal solutions. Our numerical results are compared with those of Hioe and Yoo and also with the results obtained by Lanczos. (author)
2014-01-01
Background Verbal Autopsy (VA) is widely viewed as the only immediate strategy for registering cause of death in much of Africa and Asia, where routine physician certification of deaths is not widely practiced. VA involves a lay interview with family or friends after a death, to record essential details of the circumstances. These data can then be processed automatically to arrive at standardized cause of death information. Methods The Population Health Metrics Research Consortium (PHMRC) undertook a study at six tertiary hospitals in low- and middle-income countries which documented over 12,000 deaths clinically and subsequently undertook VA interviews. This dataset, now in the public domain, was compared with the WHO 2012 VA standard and the InterVA-4 interpretative model. Results The PHMRC data covered 70% of the WHO 2012 VA input indicators, and categorized cause of death according to PHMRC definitions. After eliminating some problematic or incomplete records, 11,984 VAs were compared. Some of the PHMRC cause definitions, such as ‘preterm delivery’, differed substantially from the International Classification of Diseases, version 10 equivalent. There were some appreciable inconsistencies between the hospital and VA data, including 20% of the hospital maternal deaths being described as non-pregnant in the VA data. A high proportion of VA cases (66%) reported respiratory symptoms, but only 18% of assigned hospital causes were respiratory-related. Despite these issues, the concordance correlation coefficient between hospital and InterVA-4 cause of death categories was 0.61. Conclusions The PHMRC dataset is a valuable reference source for VA methods, but has to be interpreted with care. Inherently inconsistent cases should not be included when using these data to build other VA models. Conversely, models built from these data should be independently evaluated. It is important to distinguish between the internal and external validity of VA models. The effects of
Variable importance and prediction methods for longitudinal problems with missing variables.
Directory of Open Access Journals (Sweden)
Iván Díaz
Full Text Available We present prediction and variable importance (VIM methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patients, a field in which current medical practice involves rules of thumb and scoring methods that only use a few variables and ignore the dynamic and high-dimensional nature of trauma recovery. Well-principled prediction and VIM methods can provide a tool to make care decisions informed by the high-dimensional patient's physiological and clinical history. Our VIM parameters are analogous to slope coefficients in adjusted regressions, but are not dependent on a specific statistical model, nor require a certain functional form of the prediction regression to be estimated. In addition, they can be causally interpreted under causal and statistical assumptions as the expected outcome under time-specific clinical interventions, related to changes in the mean of the outcome if each individual experiences a specified change in the variable (keeping other variables in the model fixed. Better yet, the targeted MLE used is doubly robust and locally efficient. Because the proposed VIM does not constrain the prediction model fit, we use a very flexible ensemble learner (the SuperLearner, which returns a linear combination of a list of user-given algorithms. Not only is such a prediction algorithm intuitive appealing, it has theoretical justification as being asymptotically equivalent to the oracle selector. The results of the analysis show effects whose size and significance would have been not been found using a parametric approach (such as stepwise regression or LASSO. In addition, the procedure is even more compelling as the predictor on which it is based showed significant improvements in cross-validated fit, for instance area under the curve (AUC for a receiver-operator curve (ROC. Thus, given that 1 our VIM
Evans, Garrett Nolan
In this work, I present two projects that both contribute to the aim of discovering how intelligence manifests in the brain. The first project is a method for analyzing recorded neural signals, which takes the form of a convolution-based metric on neural membrane potential recordings. Relying only on integral and algebraic operations, the metric compares the timing and number of spikes within recordings as well as the recordings' subthreshold features: summarizing differences in these with a single "distance" between the recordings. Like van Rossum's (2001) metric for spike trains, the metric is based on a convolution operation that it performs on the input data. The kernel used for the convolution is carefully chosen such that it produces a desirable frequency space response and, unlike van Rossum's kernel, causes the metric to be first order both in differences between nearby spike times and in differences between same-time membrane potential values: an important trait. The second project is a combinatorial syntax method for connectionist semantic network encoding. Combinatorial syntax has been a point on which those who support a symbol-processing view of intelligent processing and those who favor a connectionist view have had difficulty seeing eye-to-eye. Symbol-processing theorists have persuasively argued that combinatorial syntax is necessary for certain intelligent mental operations, such as reasoning by analogy. Connectionists have focused on the versatility and adaptability offered by self-organizing networks of simple processing units. With this project, I show that there is a way to reconcile the two perspectives and to ascribe a combinatorial syntax to a connectionist network. The critical principle is to interpret nodes, or units, in the connectionist network as bound integrations of the interpretations for nodes that they share links with. Nodes need not correspond exactly to neurons and may correspond instead to distributed sets, or assemblies, of
Instrumental variable methods in comparative safety and effectiveness research.
Brookhart, M Alan; Rassen, Jeremy A; Schneeweiss, Sebastian
2010-06-01
Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial.
Instrumental variable methods in comparative safety and effectiveness research†
Brookhart, M. Alan; Rassen, Jeremy A.; Schneeweiss, Sebastian
2010-01-01
Summary Instrumental variable (IV) methods have been proposed as a potential approach to the common problem of uncontrolled confounding in comparative studies of medical interventions, but IV methods are unfamiliar to many researchers. The goal of this article is to provide a non-technical, practical introduction to IV methods for comparative safety and effectiveness research. We outline the principles and basic assumptions necessary for valid IV estimation, discuss how to interpret the results of an IV study, provide a review of instruments that have been used in comparative effectiveness research, and suggest some minimal reporting standards for an IV analysis. Finally, we offer our perspective of the role of IV estimation vis-à-vis more traditional approaches based on statistical modeling of the exposure or outcome. We anticipate that IV methods will be often underpowered for drug safety studies of very rare outcomes, but may be potentially useful in studies of intended effects where uncontrolled confounding may be substantial. PMID:20354968
Wind resource in metropolitan France: assessment methods, variability and trends
International Nuclear Information System (INIS)
Jourdier, Benedicte
2015-01-01
France has one of the largest wind potentials in Europe, yet far from being fully exploited. The wind resource and energy yield assessment is a key step before building a wind farm, aiming at predicting the future electricity production. Any over-estimation in the assessment process puts in jeopardy the project's profitability. This has been the case in the recent years, when wind farm managers have noticed that they produced less than expected. The under-production problem leads to questioning both the validity of the assessment methods and the inter-annual wind variability. This thesis tackles these two issues. In a first part are investigated the errors linked to the assessment methods, especially in two steps: the vertical extrapolation of wind measurements and the statistical modelling of wind-speed data by a Weibull distribution. The second part investigates the inter-annual to decadal variability of wind speeds, in order to understand how this variability may have contributed to the under-production and so that it is better taken into account in the future. (author) [fr
Selman, Delon; And Others
1976-01-01
The relationships among measures of quantitative thinking in first through fifth grade children assigned either to an experimental math program emphasizing tactile, manipulative, or individual activity in learning metric and decimal concepts, or to a control group, were examined. Tables are presented and conclusions discussed. (Author/JKS)
Modeling intraindividual variability with repeated measures data methods and applications
Hershberger, Scott L
2013-01-01
This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable.It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a ""user-friendly"" style such that even the ""novice"" data analyst can easily apply the techniques.Each chapter features:a minimum discussion of mathematical detail;an empirical examp
Viscoelastic Earthquake Cycle Simulation with Memory Variable Method
Hirahara, K.; Ohtani, M.
2017-12-01
There have so far been no EQ (earthquake) cycle simulations, based on RSF (rate and state friction) laws, in viscoelastic media, except for Kato (2002), who simulated cycles on a 2-D vertical strike-slip fault, and showed nearly the same cycles as those in elastic cases. The viscoelasticity could, however, give more effects on large dip-slip EQ cycles. In a boundary element approach, stress is calculated using a hereditary integral of stress relaxation function and slip deficit rate, where we need the past slip rates, leading to huge computational costs. This is a cause for almost no simulations in viscoelastic media. We have investigated the memory variable method utilized in numerical computation of wave propagation in dissipative media (e.g., Moczo and Kristek, 2005). In this method, introducing memory variables satisfying 1st order differential equations, we need no hereditary integrals in stress calculation and the computational costs are the same order of those in elastic cases. Further, Hirahara et al. (2012) developed the iterative memory variable method, referring to Taylor et al. (1970), in EQ cycle simulations in linear viscoelastic media. In this presentation, first, we introduce our method in EQ cycle simulations and show the effect of the linear viscoelasticity on stick-slip cycles in a 1-DOF block-SLS (standard linear solid) model, where the elastic spring of the traditional block-spring model is replaced by SLS element and we pull, in a constant rate, the block obeying RSF law. In this model, the memory variable stands for the displacement of the dash-pot in SLS element. The use of smaller viscosity reduces the recurrence time to a minimum value. The smaller viscosity means the smaller relaxation time, which makes the stress recovery quicker, leading to the smaller recurrence time. Second, we show EQ cycles on a 2-D dip-slip fault with the dip angel of 20 degrees in an elastic layer with thickness of 40 km overriding a Maxwell viscoelastic half
Directory of Open Access Journals (Sweden)
Corey Sparks
2009-07-01
Full Text Available This paper presents an analysis of the differential growth rates of the farming and non-farming segments of a rural Scottish community during the 19th and early 20th centuries using the variable-r method allowing for net migration. Using this method, I find that the farming population of Orkney, Scotland, showed less variability in their reproduction and growth rates than the non-farming population during a period of net population decline. I conclude by suggesting that the variable-r method can be used in general cases where the relative growth of subpopulations or subpopulation reproduction is of interest.
International Nuclear Information System (INIS)
Gareis, Iván; Atum, Yanina; Gentiletti, Gerardo; Acevedo, Rubén; Bañuelos, Verónica Medina; Rufiner, Leonardo
2011-01-01
Brain computer interfaces (BCIs) translate brain activity into computer commands. To enhance the performance of a BCI, it is necessary to improve the feature extraction techniques being applied to decode the users' intentions. Objective comparison methods are needed to analyze different feature extraction techniques. One possibility is to use the classifier performance as a comparative measure. In this work the effect of several variables that affect the behaviour of linear discriminant analysis (LDA) has been studied when used to distinguish between electroencephalographic signals with and without the presence of event related potentials (ERPs). The error rate (ER) and the area under the receiver operating characteristic curve (AUC) were used as performance estimators of LDA. The results show that the number of characteristics, the degree of balance of the training patterns set and the number of averaged trials affect the classifier's performance and therefore, must be considered in the design of the integrated system.
Directory of Open Access Journals (Sweden)
Marius POPA
2011-01-01
Full Text Available The paper presents how an assessment system is implemented to evaluate the IT&C audit process quality. Issues regarding theoretical and practical terms are presented together with a brief presentation of the metrics and indicators developed in previous researches. The implementation process of an indicator system is highlighted and linked to specification stated in international standards regarding the measurement process. Also, the effects of an assessment system on the IT&C audit process quality are emphasized to demonstrate the importance of such assessment system. The audit process quality is an iterative process consisting of repetitive improvements based on objective measures established on analytical models of the indicators.
Daylight metrics and energy savings
Energy Technology Data Exchange (ETDEWEB)
Mardaljevic, John; Heschong, Lisa; Lee, Eleanor
2009-12-31
The drive towards sustainable, low-energy buildings has increased the need for simple, yet accurate methods to evaluate whether a daylit building meets minimum standards for energy and human comfort performance. Current metrics do not account for the temporal and spatial aspects of daylight, nor of occupants comfort or interventions. This paper reviews the historical basis of current compliance methods for achieving daylit buildings, proposes a technical basis for development of better metrics, and provides two case study examples to stimulate dialogue on how metrics can be applied in a practical, real-world context.
International Nuclear Information System (INIS)
Roege, Paul E.; Collier, Zachary A.; Mancillas, James; McDonagh, John A.; Linkov, Igor
2014-01-01
Energy lies at the backbone of any advanced society and constitutes an essential prerequisite for economic growth, social order and national defense. However there is an Achilles heel to today's energy and technology relationship; namely a precarious intimacy between energy and the fiscal, social, and technical systems it supports. Recently, widespread and persistent disruptions in energy systems have highlighted the extent of this dependence and the vulnerability of increasingly optimized systems to changing conditions. Resilience is an emerging concept that offers to reconcile considerations of performance under dynamic environments and across multiple time frames by supplementing traditionally static system performance measures to consider behaviors under changing conditions and complex interactions among physical, information and human domains. This paper identifies metrics useful to implement guidance for energy-related planning, design, investment, and operation. Recommendations are presented using a matrix format to provide a structured and comprehensive framework of metrics relevant to a system's energy resilience. The study synthesizes previously proposed metrics and emergent resilience literature to provide a multi-dimensional model intended for use by leaders and practitioners as they transform our energy posture from one of stasis and reaction to one that is proactive and which fosters sustainable growth. - Highlights: • Resilience is the ability of a system to recover from adversity. • There is a need for methods to quantify and measure system resilience. • We developed a matrix-based approach to generate energy resilience metrics. • These metrics can be used in energy planning, system design, and operations
Software Quality Assurance Metrics
McRae, Kalindra A.
2004-01-01
Software Quality Assurance (SQA) is a planned and systematic set of activities that ensures conformance of software life cycle processes and products conform to requirements, standards and procedures. In software development, software quality means meeting requirements and a degree of excellence and refinement of a project or product. Software Quality is a set of attributes of a software product by which its quality is described and evaluated. The set of attributes includes functionality, reliability, usability, efficiency, maintainability, and portability. Software Metrics help us understand the technical process that is used to develop a product. The process is measured to improve it and the product is measured to increase quality throughout the life cycle of software. Software Metrics are measurements of the quality of software. Software is measured to indicate the quality of the product, to assess the productivity of the people who produce the product, to assess the benefits derived from new software engineering methods and tools, to form a baseline for estimation, and to help justify requests for new tools or additional training. Any part of the software development can be measured. If Software Metrics are implemented in software development, it can save time, money, and allow the organization to identify the caused of defects which have the greatest effect on software development. The summer of 2004, I worked with Cynthia Calhoun and Frank Robinson in the Software Assurance/Risk Management department. My task was to research and collect, compile, and analyze SQA Metrics that have been used in other projects that are not currently being used by the SA team and report them to the Software Assurance team to see if any metrics can be implemented in their software assurance life cycle process.
Directory of Open Access Journals (Sweden)
Sandvik Leiv
2011-04-01
Full Text Available Abstract Background The number of events per individual is a widely reported variable in medical research papers. Such variables are the most common representation of the general variable type called discrete numerical. There is currently no consensus on how to compare and present such variables, and recommendations are lacking. The objective of this paper is to present recommendations for analysis and presentation of results for discrete numerical variables. Methods Two simulation studies were used to investigate the performance of hypothesis tests and confidence interval methods for variables with outcomes {0, 1, 2}, {0, 1, 2, 3}, {0, 1, 2, 3, 4}, and {0, 1, 2, 3, 4, 5}, using the difference between the means as an effect measure. Results The Welch U test (the T test with adjustment for unequal variances and its associated confidence interval performed well for almost all situations considered. The Brunner-Munzel test also performed well, except for small sample sizes (10 in each group. The ordinary T test, the Wilcoxon-Mann-Whitney test, the percentile bootstrap interval, and the bootstrap-t interval did not perform satisfactorily. Conclusions The difference between the means is an appropriate effect measure for comparing two independent discrete numerical variables that has both lower and upper bounds. To analyze this problem, we encourage more frequent use of parametric hypothesis tests and confidence intervals.
International Nuclear Information System (INIS)
1987-08-01
A proposed method is described for assigning an equivalent metric ton heavy metal (eMTHM) value to defense high-level waste forms to be disposed of in a geologic repository. This method for establishing a curie equivalency between defense high-level waste and irradiated commercial fuel is based on the ratio of defense fuel exposure to the typical commercial fuel exposure, MWd/MTHM. application of this technique to defense high-level wastes is described. Additionally, this proposed technique is compared to several alternate calculations for eMTHM. 15 refs., 2 figs., 10 tabs
Variable aperture-based ptychographical iterative engine method.
Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng
2018-02-01
A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
Variable aperture-based ptychographical iterative engine method
Sun, Aihui; Kong, Yan; Meng, Xin; He, Xiaoliang; Du, Ruijun; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng
2018-02-01
A variable aperture-based ptychographical iterative engine (vaPIE) is demonstrated both numerically and experimentally to reconstruct the sample phase and amplitude rapidly. By adjusting the size of a tiny aperture under the illumination of a parallel light beam to change the illumination on the sample step by step and recording the corresponding diffraction patterns sequentially, both the sample phase and amplitude can be faithfully reconstructed with a modified ptychographical iterative engine (PIE) algorithm. Since many fewer diffraction patterns are required than in common PIE and the shape, the size, and the position of the aperture need not to be known exactly, this proposed vaPIE method remarkably reduces the data acquisition time and makes PIE less dependent on the mechanical accuracy of the translation stage; therefore, the proposed technique can be potentially applied for various scientific researches.
Method for curing polymers using variable-frequency microwave heating
Lauf, Robert J.; Bible, Don W.; Paulauskas, Felix L.
1998-01-01
A method for curing polymers (11) incorporating a variable frequency microwave furnace system (10) designed to allow modulation of the frequency of the microwaves introduced into a furnace cavity (34). By varying the frequency of the microwave signal, non-uniformities within the cavity (34) are minimized, thereby achieving a more uniform cure throughout the workpiece (36). A directional coupler (24) is provided for detecting the direction of a signal and further directing the signal depending on the detected direction. A first power meter (30) is provided for measuring the power delivered to the microwave furnace (32). A second power meter (26) detects the magnitude of reflected power. The furnace cavity (34) may be adapted to be used to cure materials defining a continuous sheet or which require compressive forces during curing.
Wang, Zhiguo; Liang, Yingchun; Chen, Mingjun; Tong, Zhen; Chen, Jiaxuan
2010-10-01
Tool wear not only changes its geometry accuracy and integrity, but also decrease machining precision and surface integrity of workpiece that affect using performance and service life of workpiece in ultra-precision machining. Scholars made a lot of experimental researches and stimulant analyses, but there is a great difference on the wear mechanism, especially on the nano-scale wear mechanism. In this paper, the three-dimensional simulation model is built to simulate nano-metric cutting of a single crystal silicon with a non-rigid right-angle diamond tool with 0 rake angle and 0 clearance angle by the molecular dynamics (MD) simulation approach, which is used to investigate the diamond tool wear during the nano-metric cutting process. A Tersoff potential is employed for the interaction between carbon-carbon atoms, silicon-silicon atoms and carbon-silicon atoms. The tool gets the high alternating shear stress, the tool wear firstly presents at the cutting edge where intension is low. At the corner the tool is splitted along the {1 1 1} crystal plane, which forms the tipping. The wear at the flank face is the structure transformation of diamond that the diamond structure transforms into the sheet graphite structure. Owing to the tool wear the cutting force increases.
Interpolation decoding method with variable parameters for fractal image compression
International Nuclear Information System (INIS)
He Chuanjiang; Li Gaoping; Shen Xiaona
2007-01-01
The interpolation fractal decoding method, which is introduced by [He C, Yang SX, Huang X. Progressive decoding method for fractal image compression. IEE Proc Vis Image Signal Process 2004;3:207-13], involves generating progressively the decoded image by means of an interpolation iterative procedure with a constant parameter. It is well-known that the majority of image details are added at the first steps of iterations in the conventional fractal decoding; hence the constant parameter for the interpolation decoding method must be set as a smaller value in order to achieve a better progressive decoding. However, it needs to take an extremely large number of iterations to converge. It is thus reasonable for some applications to slow down the iterative process at the first stages of decoding and then to accelerate it afterwards (e.g., at some iteration as we need). To achieve the goal, this paper proposed an interpolation decoding scheme with variable (iteration-dependent) parameters and proved the convergence of the decoding process mathematically. Experimental results demonstrate that the proposed scheme has really achieved the above-mentioned goal
Measures of agreement between computation and experiment:validation metrics.
Energy Technology Data Exchange (ETDEWEB)
Barone, Matthew Franklin; Oberkampf, William Louis
2005-08-01
With the increasing role of computational modeling in engineering design, performance estimation, and safety assessment, improved methods are needed for comparing computational results and experimental measurements. Traditional methods of graphically comparing computational and experimental results, though valuable, are essentially qualitative. Computable measures are needed that can quantitatively compare computational and experimental results over a range of input, or control, variables and sharpen assessment of computational accuracy. This type of measure has been recently referred to as a validation metric. We discuss various features that we believe should be incorporated in a validation metric and also features that should be excluded. We develop a new validation metric that is based on the statistical concept of confidence intervals. Using this fundamental concept, we construct two specific metrics: one that requires interpolation of experimental data and one that requires regression (curve fitting) of experimental data. We apply the metrics to three example problems: thermal decomposition of a polyurethane foam, a turbulent buoyant plume of helium, and compressibility effects on the growth rate of a turbulent free-shear layer. We discuss how the present metrics are easily interpretable for assessing computational model accuracy, as well as the impact of experimental measurement uncertainty on the accuracy assessment.
Variable threshold method for ECG R-peak detection.
Kew, Hsein-Ping; Jeong, Do-Un
2011-10-01
In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.
Feasibility of wavelet expansion methods to treat the energy variable
International Nuclear Information System (INIS)
Van Rooijen, W. F. G.
2012-01-01
This paper discusses the use of the Discrete Wavelet Transform (DWT) to implement a functional expansion of the energy variable in neutron transport. The motivation of the work is to investigate the possibility of adapting the expansion level of the neutron flux in a material region to the complexity of the cross section in that region. If such an adaptive treatment is possible, 'simple' material regions (e.g., moderator regions) require little effort, while a detailed treatment is used for 'complex' regions (e.g., fuel regions). Our investigations show that in fact adaptivity cannot be achieved. The most fundamental reason is that in a multi-region system, the energy dependence of the cross section in a material region does not imply that the neutron flux in that region has a similar energy dependence. If it is chosen to sacrifice adaptivity, then the DWT method can be very accurate, but the complexity of such a method is higher than that of an equivalent hyper-fine group calculation. The conclusion is thus that, unfortunately, the DWT approach is not very practical. (authors)
International Nuclear Information System (INIS)
Muratova, N.M.; Martynenko, L.I.
1979-01-01
The pH-metric titration technique was used to study the possibility of formation of higher complexes between rare earth elements of the whole series and ethylenediaminedisuccinic acid (L). The logarithms of stability constants were determined for LaL - (10.95), PrL - (11.30), NdL - (11.35), ErL 2 5- (4.10), TuL 2 5- (4.00), YbL 2 5- (4.25) and LnL 2 5- (4.8). In the concentrations studied only heavy lanthanides were forming unstable bis-ethylenediaminedisuccinates. Lighter rare earth elements did not form higher complexes even when the ligand was in four-fold excess; however, the complexes did appear in more concentrated solutions
International Nuclear Information System (INIS)
Ma Zhihao; Chen Jingling
2011-01-01
In this work we study metrics of quantum states, which are natural generalizations of the usual trace metric and Bures metric. Some useful properties of the metrics are proved, such as the joint convexity and contractivity under quantum operations. Our result has a potential application in studying the geometry of quantum states as well as the entanglement detection.
Separable metrics and radiating stars
Indian Academy of Sciences (India)
We study the junction condition relating the pressure to heat flux at the boundary of an accelerating and expanding spherically symmetric radiating star. We transform the junction condition to an ordinary differential equation by making a separability assumption on the metric functions in the space–time variables.
Gaba, Yaé Ulrich
2017-01-01
In this paper, we discuss recent results about generalized metric spaces and fixed point theory. We introduce the notion of $\\eta$-cone metric spaces, give some topological properties and prove some fixed point theorems for contractive type maps on these spaces. In particular we show that theses $\\eta$-cone metric spaces are natural generalizations of both cone metric spaces and metric type spaces.
Candelas, Philip; de la Ossa, Xenia; McOrist, Jock
2017-12-01
Heterotic vacua of string theory are realised, at large radius, by a compact threefold with vanishing first Chern class together with a choice of stable holomorphic vector bundle. These form a wide class of potentially realistic four-dimensional vacua of string theory. Despite all their phenomenological promise, there is little understanding of the metric on the moduli space of these. What is sought is the analogue of special geometry for these vacua. The metric on the moduli space is important in phenomenology as it normalises D-terms and Yukawa couplings. It is also of interest in mathematics, since it generalises the metric, first found by Kobayashi, on the space of gauge field connections, to a more general context. Here we construct this metric, correct to first order in {α^{\\backprime}}, in two ways: first by postulating a metric that is invariant under background gauge transformations of the gauge field, and also by dimensionally reducing heterotic supergravity. These methods agree and the resulting metric is Kähler, as is required by supersymmetry. Checking the metric is Kähler is intricate and the anomaly cancellation equation for the H field plays an essential role. The Kähler potential nevertheless takes a remarkably simple form: it is the Kähler potential of special geometry with the Kähler form replaced by the {α^{\\backprime}}-corrected hermitian form.
Electromagnetic variable degrees of freedom actuator systems and methods
Montesanti, Richard C [Pleasanton, CA; Trumper, David L [Plaistow, NH; Kirtley, Jr., James L.
2009-02-17
The present invention provides a variable reluctance actuator system and method that can be adapted for simultaneous rotation and translation of a moving element by applying a normal-direction magnetic flux on the moving element. In a beneficial example arrangement, the moving element includes a swing arm that carries a cutting tool at a set radius from an axis of rotation so as to produce a rotary fast tool servo that provides a tool motion in a direction substantially parallel to the surface-normal of a workpiece at the point of contact between the cutting tool and workpiece. An actuator rotates a swing arm such that a cutting tool moves toward and away from a mounted rotating workpiece in a controlled manner in order to machine the workpiece. Position sensors provide rotation and displacement information for a swing arm to a control system. A control system commands and coordinates motion of the fast tool servo with the motion of a spindle, rotating table, cross-feed slide, and in feed slide of a precision lathe.
Bigus, Paulina; Tsakovski, Stefan; Simeonov, Vasil; Namieśnik, Jacek; Tobiszewski, Marek
2016-05-01
This study presents an application of the Hasse diagram technique (HDT) as the assessment tool to select the most appropriate analytical procedures according to their greenness or the best analytical performance. The dataset consists of analytical procedures for benzo[a]pyrene determination in sediment samples, which were described by 11 variables concerning their greenness and analytical performance. Two analyses with the HDT were performed-the first one with metrological variables and the second one with "green" variables as input data. Both HDT analyses ranked different analytical procedures as the most valuable, suggesting that green analytical chemistry is not in accordance with metrology when benzo[a]pyrene in sediment samples is determined. The HDT can be used as a good decision support tool to choose the proper analytical procedure concerning green analytical chemistry principles and analytical performance merits.
Invariant metrics for Hamiltonian systems
International Nuclear Information System (INIS)
Rangarajan, G.; Dragt, A.J.; Neri, F.
1991-05-01
In this paper, invariant metrics are constructed for Hamiltonian systems. These metrics give rise to norms on the space of homeogeneous polynomials of phase-space variables. For an accelerator lattice described by a Hamiltonian, these norms characterize the nonlinear content of the lattice. Therefore, the performance of the lattice can be improved by minimizing the norm as a function of parameters describing the beam-line elements in the lattice. A four-fold increase in the dynamic aperture of a model FODO cell is obtained using this procedure. 7 refs
Generalization of Vaidya's radiation metric
Energy Technology Data Exchange (ETDEWEB)
Gleiser, R J; Kozameh, C N [Universidad Nacional de Cordoba (Argentina). Instituto de Matematica, Astronomia y Fisica
1981-11-01
In this paper it is shown that if Vaidya's radiation metric is considered from the point of view of kinetic theory in general relativity, the corresponding phase space distribution function can be generalized in a particular way. The new family of spherically symmetric radiation metrics obtained contains Vaidya's as a limiting situation. The Einstein field equations are solved in a ''comoving'' coordinate system. Two arbitrary functions of a single variable are introduced in the process of solving these equations. Particular examples considered are a stationary solution, a nonvacuum solution depending on a single parameter, and several limiting situations.
Parrish, Donna; Butryn, Ryan S.; Rizzo, Donna M.
2012-01-01
We developed a methodology to predict brook trout (Salvelinus fontinalis) distribution using summer temperature metrics as predictor variables. Our analysis used long-term fish and hourly water temperature data from the Dog River, Vermont (USA). Commonly used metrics (e.g., mean, maximum, maximum 7-day maximum) tend to smooth the data so information on temperature variation is lost. Therefore, we developed a new set of metrics (called event metrics) to capture temperature variation by describing the frequency, area, duration, and magnitude of events that exceeded a user-defined temperature threshold. We used 16, 18, 20, and 22°C. We built linear discriminant models and tested and compared the event metrics against the commonly used metrics. Correct classification of the observations was 66% with event metrics and 87% with commonly used metrics. However, combined event and commonly used metrics correctly classified 92%. Of the four individual temperature thresholds, it was difficult to assess which threshold had the “best” accuracy. The 16°C threshold had slightly fewer misclassifications; however, the 20°C threshold had the fewest extreme misclassifications. Our method leveraged the volumes of existing long-term data and provided a simple, systematic, and adaptable framework for monitoring changes in fish distribution, specifically in the case of irregular, extreme temperature events.
A condition metric for Eucalyptus woodland derived from expert evaluations.
Sinclair, Steve J; Bruce, Matthew J; Griffioen, Peter; Dodd, Amanda; White, Matthew D
2018-02-01
The evaluation of ecosystem quality is important for land-management and land-use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert-evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers' evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data-driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real-world contexts. We believe our approach is applicable to any ecosystem. © 2017 State of Victoria.
Bachegowda, Lohith S; Cheng, Yan H; Long, Thomas; Shaz, Beth H
2017-01-01
-Substantial variability between different antibody titration methods prompted development and introduction of uniform methods in 2008. -To determine whether uniform methods consistently decrease interlaboratory variation in proficiency testing. -Proficiency testing data for antibody titration between 2009 and 2013 were obtained from the College of American Pathologists. Each laboratory was supplied plasma and red cells to determine anti-A and anti-D antibody titers by their standard method: gel or tube by uniform or other methods at different testing phases (immediate spin and/or room temperature [anti-A], and/or anti-human globulin [AHG: anti-A and anti-D]) with different additives. Interlaboratory variations were compared by analyzing the distribution of titer results by method and phase. -A median of 574 and 1100 responses were reported for anti-A and anti-D antibody titers, respectively, during a 5-year period. The 3 most frequent (median) methods performed for anti-A antibody were uniform tube room temperature (147.5; range, 119-159), uniform tube AHG (143.5; range, 134-150), and other tube AHG (97; range, 82-116); for anti-D antibody, the methods were other tube (451; range, 431-465), uniform tube (404; range, 382-462), and uniform gel (137; range, 121-153). Of the larger reported methods, uniform gel AHG phase for anti-A and anti-D antibodies had the most participants with the same result (mode). For anti-A antibody, 0 of 8 (uniform versus other tube room temperature) and 1 of 8 (uniform versus other tube AHG), and for anti-D antibody, 0 of 8 (uniform versus other tube) and 0 of 8 (uniform versus other gel) proficiency tests showed significant titer variability reduction. -Uniform methods harmonize laboratory techniques but rarely reduce interlaboratory titer variance in comparison with other methods.
Field calculations. Part I: Choice of variables and methods
International Nuclear Information System (INIS)
Turner, L.R.
1981-01-01
Magnetostatic calculations can involve (in order of increasing complexity) conductors only, material with constant or infinite permeability, or material with variable permeability. We consider here only the most general case, calculations involving ferritic material with variable permeability. Variables suitable for magnetostatic calculations are the magnetic field, the magnetic vector potential, and the magnetic scalar potential. For two-dimensional calculations the potentials, which each have only one component, have advantages over the field, which has two components. Because it is a single-valued variable, the vector potential is perhaps the best variable for two-dimensional calculations. In three dimensions, both the field and the vector potential have three components; the scalar potential, with only one component,provides a much smaller system of equations to be solved. However the scalar potential is not single-valued. To circumvent this problem, a calculation with two scalar potentials can be performed. The scalar potential whose source is the conductors can be calculated directly by the Biot-Savart law, and the scalar potential whose source is the magnetized material is single valued. However in some situations, the fields from the two potentials nearly cancel; and the numerical accuracy is lost. The 3-D magnetostatic program TOSCA employs a single total scalar potential; the program GFUN uses the magnetic field as its variable
Active Metric Learning for Supervised Classification
Kumaran, Krishnan; Papageorgiou, Dimitri; Chang, Yutong; Li, Minhan; Takáč, Martin
2018-01-01
Clustering and classification critically rely on distance metrics that provide meaningful comparisons between data points. We present mixed-integer optimization approaches to find optimal distance metrics that generalize the Mahalanobis metric extensively studied in the literature. Additionally, we generalize and improve upon leading methods by removing reliance on pre-designated "target neighbors," "triplets," and "similarity pairs." Another salient feature of our method is its ability to en...
A moving mesh method with variable relaxation time
Soheili, Ali Reza; Stockie, John M.
2006-01-01
We propose a moving mesh adaptive approach for solving time-dependent partial differential equations. The motion of spatial grid points is governed by a moving mesh PDE (MMPDE) in which a mesh relaxation time \\tau is employed as a regularization parameter. Previously reported results on MMPDEs have invariably employed a constant value of the parameter \\tau. We extend this standard approach by incorporating a variable relaxation time that is calculated adaptively alongside the solution in orde...
Muntlin Athlin, Åsa
2018-06-01
To examine and map research on minimum data sets linked to nursing practice and the fundamentals of care. Another aim was to identify gaps in the evidence to suggest future research questions to highlight the need for standardisation of terminology around nursing practice and fundamental care. Addressing fundamental care has been highlighted internationally as a response to missed nursing care. Systematic performance measurements are needed to capture nursing practice outcomes. Overview of the literature framed by the scoping study methodology. PubMed and CINAHL were searched using the following inclusion criteria: peer-reviewed empirical quantitative and qualitative studies related to minimum data sets and nursing practice published in English. No time restrictions were set. Exclusion criteria were as follows: no available full text, reviews and methodological and discursive studies. Data were categorised into one of the fundamentals of care elements. The review included 20 studies published in 1999-2016. Settings were mainly nursing homes or hospitals. Of 14 elements of the fundamentals of care, 11 were identified as measures in the included studies, but their frequency varied. The most commonly identified elements concerned safety, prevention and medication (n = 11), comfort (n = 6) and eating and drinking (n = 5). Studies have used minimum data sets and included variables linked to nursing practices and fundamentals of care. However, the relations of these variables to nursing practice were not always clearly described and the main purpose of the studies was seldom to measure the outcomes of nursing interventions. More robust studies focusing on nursing practice and patient outcomes are warranted. Using minimum data sets can highlight the nurses' work and what impact it has on direct patient care. Appropriate models, systems and standardised terminology are needed to facilitate the documentation of nursing activities. © 2017 John Wiley & Sons Ltd.
METRIC context unit architecture
Energy Technology Data Exchange (ETDEWEB)
Simpson, R.O.
1988-01-01
METRIC is an architecture for a simple but powerful Reduced Instruction Set Computer (RISC). Its speed comes from the simultaneous processing of several instruction streams, with instructions from the various streams being dispatched into METRIC's execution pipeline as they become available for execution. The pipeline is thus kept full, with a mix of instructions for several contexts in execution at the same time. True parallel programming is supported within a single execution unit, the METRIC Context Unit. METRIC's architecture provides for expansion through the addition of multiple Context Units and of specialized Functional Units. The architecture thus spans a range of size and performance from a single-chip microcomputer up through large and powerful multiprocessors. This research concentrates on the specification of the METRIC Context Unit at the architectural level. Performance tradeoffs made during METRIC's design are discussed, and projections of METRIC's performance are made based on simulation studies.
Avdeef, A; Berger, C M; Brownell, C
2000-01-01
The objective of this study was to compare the results of a normal saturation shake-flask method to a new potentiometric acid-base titration method for determining the intrinsic solubility and the solubility-pH profiles of ionizable molecules, and to report the solubility constants determined by the latter technique. The solubility-pH profiles of twelve generic drugs (atenolol, diclofenac.Na, famotidine, flurbiprofen, furosemide, hydrochlorothiazide, ibuprofen, ketoprofen, labetolol.HCl, naproxen, phenytoin, and propranolol.HCl), with solubilities spanning over six orders of magnitude, were determined both by the new pH-metric method and by a traditional approach (24 hr shaking of saturated solutions, followed by filtration, then HPLC assaying with UV detection). The 212 separate saturation shake-flask solubility measurements and those derived from 65 potentiometric titrations agreed well. The analysis produced the correlation equation: log(1/S)titration = -0.063(+/- 0.032) + 1.025(+/- 0.011) log(1/S)shake-flask, s = 0.20, r2 = 0.978. The potentiometrically-derived intrinsic solubilities of the drugs were: atenolol 13.5 mg/mL, diclofenac.Na 0.82 microg/mL, famotidine 1.1 mg/ mL, flurbiprofen 10.6 microg/mL, furosemide 5.9 microg/mL, hydrochlorothiazide 0.70 mg/mL, ibuprofen 49 microg/mL, ketoprofen 118 microg/mL, labetolol.HCl 128 microg/mL, naproxen 14 microg/mL, phenytoin 19 microg/mL, and propranolol.HCl 70 microg/mL. The new potentiometric method was shown to be reliable for determining the solubility-pH profiles of uncharged ionizable drug substances. Its speed compared to conventional equilibrium measurements, its sound theoretical basis, its ability to generate the full solubility-pH profile from a single titration, and its dynamic range (currently estimated to be seven orders of magnitude) make the new pH-metric method an attractive addition to traditional approaches used by preformulation and development scientists. It may be useful even to discovery
Design Method of Active Disturbance Rejection Variable Structure Control System
Directory of Open Access Journals (Sweden)
Yun-jie Wu
2015-01-01
Full Text Available Based on lines cluster approaching theory and inspired by the traditional exponent reaching law method, a new control method, lines cluster approaching mode control (LCAMC method, is designed to improve the parameter simplicity and structure optimization of the control system. The design guidelines and mathematical proofs are also given. To further improve the tracking performance and the inhibition of the white noise, connect the active disturbance rejection control (ADRC method with the LCAMC method and create the extended state observer based lines cluster approaching mode control (ESO-LCAMC method. Taking traditional servo control system as example, two control schemes are constructed and two kinds of comparison are carried out. Computer simulation results show that LCAMC method, having better tracking performance than the traditional sliding mode control (SMC system, makes the servo system track command signal quickly and accurately in spite of the persistent equivalent disturbances and ESO-LCAMC method further reduces the tracking error and filters the white noise added on the system states. Simulation results verify the robust property and comprehensive performance of control schemes.
Variable-mesh method of solving differential equations
Van Wyk, R.
1969-01-01
Multistep predictor-corrector method for numerical solution of ordinary differential equations retains high local accuracy and convergence properties. In addition, the method was developed in a form conducive to the generation of effective criteria for the selection of subsequent step sizes in step-by-step solution of differential equations.
Generally covariant Hamilton-Jacobi equation and rotated liquid sphere metrics
International Nuclear Information System (INIS)
Abdil'din, M.M.; Abdulgafarov, M.K.; Abishev, M.E.
2005-01-01
In the work Lense-Thirring problem on corrected Fock's first approximation metrics by Hamilton-Jacobi method considered. Generally covariant Hamilton-Jacobi equation had been sold by separation of variable method. Path equation of probe particle motion in rotated liquid sphere field is obtained. (author)
Sarvari, S. M. Hosseini
2017-09-01
The traditional form of discrete ordinates method is applied to solve the radiative transfer equation in plane-parallel semi-transparent media with variable refractive index through using the variable discrete ordinate directions and the concept of refracted radiative intensity. The refractive index are taken as constant in each control volume, such that the direction cosines of radiative rays remain non-variant through each control volume, and then, the directions of discrete ordinates are changed locally by passing each control volume, according to the Snell's law of refraction. The results are compared by the previous studies in this field. Despite simplicity, the results show that the variable discrete ordinate method has a good accuracy in solving the radiative transfer equation in the semi-transparent media with arbitrary distribution of refractive index.
Apparatus and method for variable angle slant hole collimator
Lee, Seung Joon; Kross, Brian J.; McKisson, John E.
2017-07-18
A variable angle slant hole (VASH) collimator for providing collimation of high energy photons such as gamma rays during radiological imaging of humans. The VASH collimator includes a stack of multiple collimator leaves and a means of quickly aligning each leaf to provide various projection angles. Rather than rotate the detector around the subject, the VASH collimator enables the detector to remain stationary while the projection angle of the collimator is varied for tomographic acquisition. High collimator efficiency is achieved by maintaining the leaves in accurate alignment through the various projection angles. Individual leaves include unique angled cuts to maintain a precise target collimation angle. Matching wedge blocks driven by two actuators with twin-lead screws accurately position each leaf in the stack resulting in the precise target collimation angle. A computer interface with the actuators enables precise control of the projection angle of the collimator.
Combustion engine variable compression ratio apparatus and method
Lawrence,; Keith, E [Peoria, IL; Strawbridge, Bryan E [Dunlap, IL; Dutart, Charles H [Washington, IL
2006-06-06
An apparatus and method for varying a compression ratio of an engine having a block and a head mounted thereto. The apparatus and method includes a cylinder having a block portion and a head portion, a piston linearly movable in the block portion of the cylinder, a cylinder plug linearly movable in the head portion of the cylinder, and a valve located in the cylinder plug and operable to provide controlled fluid communication with the block portion of the cylinder.
DeJournett, Jeremy; DeJournett, Leon
2017-11-01
Effective glucose control in the intensive care unit (ICU) setting has the potential to decrease morbidity and mortality rates and thereby decrease health care expenditures. To evaluate what constitutes effective glucose control, typically several metrics are reported, including time in range, time in mild and severe hypoglycemia, coefficient of variation, and others. To date, there is no one metric that combines all of these individual metrics to give a number indicative of overall performance. We proposed a composite metric that combines 5 commonly reported metrics, and we used this composite metric to compare 6 glucose controllers. We evaluated the following controllers: Ideal Medical Technologies (IMT) artificial-intelligence-based controller, Yale protocol, Glucommander, Wintergerst et al PID controller, GRIP, and NICE-SUGAR. We evaluated each controller across 80 simulated patients, 4 clinically relevant exogenous dextrose infusions, and one nonclinical infusion as a test of the controller's ability to handle difficult situations. This gave a total of 2400 5-day simulations, and 585 604 individual glucose values for analysis. We used a random walk sensor error model that gave a 10% MARD. For each controller, we calculated severe hypoglycemia (140 mg/dL), and coefficient of variation (CV), as well as our novel controller metric. For the controllers tested, we achieved the following median values for our novel controller scoring metric: IMT: 88.1, YALE: 46.7, GLUC: 47.2, PID: 50, GRIP: 48.2, NICE: 46.4. The novel scoring metric employed in this study shows promise as a means for evaluating new and existing ICU-based glucose controllers, and it could be used in the future to compare results of glucose control studies in critical care. The IMT AI-based glucose controller demonstrated the most consistent performance results based on this new metric.
Metric diffusion along foliations
Walczak, Szymon M
2017-01-01
Up-to-date research in metric diffusion along compact foliations is presented in this book. Beginning with fundamentals from the optimal transportation theory and the theory of foliations; this book moves on to cover Wasserstein distance, Kantorovich Duality Theorem, and the metrization of the weak topology by the Wasserstein distance. Metric diffusion is defined, the topology of the metric space is studied and the limits of diffused metrics along compact foliations are discussed. Essentials on foliations, holonomy, heat diffusion, and compact foliations are detailed and vital technical lemmas are proved to aide understanding. Graduate students and researchers in geometry, topology and dynamics of foliations and laminations will find this supplement useful as it presents facts about the metric diffusion along non-compact foliation and provides a full description of the limit for metrics diffused along foliation with at least one compact leaf on the two dimensions.
Chistyakov, Vyacheslav
2015-01-01
Aimed toward researchers and graduate students familiar with elements of functional analysis, linear algebra, and general topology; this book contains a general study of modulars, modular spaces, and metric modular spaces. Modulars may be thought of as generalized velocity fields and serve two important purposes: generate metric spaces in a unified manner and provide a weaker convergence, the modular convergence, whose topology is non-metrizable in general. Metric modular spaces are extensions of metric spaces, metric linear spaces, and classical modular linear spaces. The topics covered include the classification of modulars, metrizability of modular spaces, modular transforms and duality between modular spaces, metric and modular topologies. Applications illustrated in this book include: the description of superposition operators acting in modular spaces, the existence of regular selections of set-valued mappings, new interpretations of spaces of Lipschitzian and absolutely continuous mappings, the existe...
Fast analytical method for the addition of random variables
International Nuclear Information System (INIS)
Senna, V.; Milidiu, R.L.; Fleming, P.V.; Salles, M.R.; Oliveria, L.F.S.
1983-01-01
Using the minimal cut sets representation of a fault tree, a new approach to the method of moments is proposed in order to estimate confidence bounds to the top event probability. The method utilizes two or three moments either to fit a distribution (the normal and lognormal families) or to evaluate bounds from standard inequalities (e.g. Markov, Tchebycheff, etc.) Examples indicate that the results obtained by the log-normal family are in good agreement with those obtained by Monte Carlo simulation
A Latent Variable Clustering Method for Wireless Sensor Networks
DEFF Research Database (Denmark)
Vasilev, Vladislav; Iliev, Georgi; Poulkov, Vladimir
2016-01-01
In this paper we derive a clustering method based on the Hidden Conditional Random Field (HCRF) model in order to maximizes the performance of a wireless sensor. Our novel approach to clustering in this paper is in the application of an index invariant graph that we defined in a previous work and...
Directory of Open Access Journals (Sweden)
Kihong Kim
2018-02-01
Full Text Available Various kinds of metrics used for the quantitative evaluation of scholarly journals are reviewed. The impact factor and related metrics including the immediacy index and the aggregate impact factor, which are provided by the Journal Citation Reports, are explained in detail. The Eigenfactor score and the article influence score are also reviewed. In addition, journal metrics such as CiteScore, Source Normalized Impact per Paper, SCImago Journal Rank, h-index, and g-index are discussed. Limitations and problems that these metrics have are pointed out. We should be cautious to rely on those quantitative measures too much when we evaluate journals or researchers.
Variational method for objective analysis of scalar variable and its ...
Indian Academy of Sciences (India)
e-mail: sinha@tropmet.res.in. In this study real time data have been used to compare the standard and triangle method by ... The work presented in this paper is about a vari- ... But when the balance is needed ..... tred at 17:30h IST of 11 June within half a degree of ..... Ogura Y and Chen Y L 1977 A life history of an intense.
Comparing Resource Adequacy Metrics and Their Influence on Capacity Value: Preprint
Energy Technology Data Exchange (ETDEWEB)
Ibanez, E.; Milligan, M.
2014-04-01
Traditional probabilistic methods have been used to evaluate resource adequacy. The increasing presence of variable renewable generation in power systems presents a challenge to these methods because, unlike thermal units, variable renewable generation levels change over time because they are driven by meteorological events. Thus, capacity value calculations for these resources are often performed to simple rules of thumb. This paper follows the recommendations of the North American Electric Reliability Corporation?s Integration of Variable Generation Task Force to include variable generation in the calculation of resource adequacy and compares different reliability metrics. Examples are provided using the Western Interconnection footprint under different variable generation penetrations.
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
Methods for Analyzing Electric Load Shape and its Variability
Energy Technology Data Exchange (ETDEWEB)
Price, Philip
2010-05-12
Current methods of summarizing and analyzing electric load shape are discussed briefly and compared. Simple rules of thumb for graphical display of load shapes are suggested. We propose a set of parameters that quantitatively describe the load shape in many buildings. Using the example of a linear regression model to predict load shape from time and temperature, we show how quantities such as the load?s sensitivity to outdoor temperature, and the effectiveness of demand response (DR), can be quantified. Examples are presented using real building data.
The Variability and Evaluation Method of Recycled Concrete Aggregate Properties
Directory of Open Access Journals (Sweden)
Zhiqing Zhang
2017-01-01
Full Text Available With the same sources and regeneration techniques, given RA’s properties may display large variations. The same single property index of different sets maybe has a large difference of the whole property. How shall we accurately evaluate the whole property of RA? 8 groups of RAs from pavement and building were used to research the method of evaluating the holistic characteristics of RA. After testing and investigating, the parameters of aggregates were analyzed. The data of physical and mechanical properties show a distinct dispersion and instability; thus, it has been difficult to express the whole characteristics in any single property parameter. The Euclidean distance can express the similarity of samples. The closer the distance, the more similar the property. The standard variance of the whole property Euclidean distances for two types of RA is Sk=7.341 and Sk=2.208, respectively, which shows that the property of building RA has great fluctuation, while pavement RA is more stable. There are certain correlations among the apparent density, water absorption, and crushed value of RAs, and the Mahalanobis distance method can directly evaluate the whole property by using its parameters: mean, variance, and covariance, and it can provide a grade evaluation model for RAs.
Bernhardt, Jase; Carleton, Andrew M.
2018-05-01
The two main methods for determining the average daily near-surface air temperature, twice-daily averaging (i.e., [Tmax+Tmin]/2) and hourly averaging (i.e., the average of 24 hourly temperature measurements), typically show differences associated with the asymmetry of the daily temperature curve. To quantify the relative influence of several land surface and atmosphere variables on the two temperature averaging methods, we correlate data for 215 weather stations across the Contiguous United States (CONUS) for the period 1981-2010 with the differences between the two temperature-averaging methods. The variables are land use-land cover (LULC) type, soil moisture, snow cover, cloud cover, atmospheric moisture (i.e., specific humidity, dew point temperature), and precipitation. Multiple linear regression models explain the spatial and monthly variations in the difference between the two temperature-averaging methods. We find statistically significant correlations between both the land surface and atmosphere variables studied with the difference between temperature-averaging methods, especially for the extreme (i.e., summer, winter) seasons (adjusted R2 > 0.50). Models considering stations with certain LULC types, particularly forest and developed land, have adjusted R2 values > 0.70, indicating that both surface and atmosphere variables control the daily temperature curve and its asymmetry. This study improves our understanding of the role of surface and near-surface conditions in modifying thermal climates of the CONUS for a wide range of environments, and their likely importance as anthropogenic forcings—notably LULC changes and greenhouse gas emissions—continues.
Partial differential equations with variable exponents variational methods and qualitative analysis
Radulescu, Vicentiu D
2015-01-01
Partial Differential Equations with Variable Exponents: Variational Methods and Qualitative Analysis provides researchers and graduate students with a thorough introduction to the theory of nonlinear partial differential equations (PDEs) with a variable exponent, particularly those of elliptic type. The book presents the most important variational methods for elliptic PDEs described by nonhomogeneous differential operators and containing one or more power-type nonlinearities with a variable exponent. The authors give a systematic treatment of the basic mathematical theory and constructive meth
Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, e...
Area Regge calculus and discontinuous metrics
International Nuclear Information System (INIS)
Wainwright, Chris; Williams, Ruth M
2004-01-01
Taking the triangle areas as independent variables in the theory of Regge calculus can lead to ambiguities in the edge lengths, which can be interpreted as discontinuities in the metric. We construct solutions to area Regge calculus using a triangulated lattice and find that on a spacelike or timelike hypersurface no such discontinuity can arise. On a null hypersurface however, we can have such a situation and the resulting metric can be interpreted as a so-called refractive wave
Muntinga, D.; Bernritter, S.
2017-01-01
Het merk staat steeds meer centraal in de organisatie. Het is daarom essentieel om de gezondheid, prestaties en ontwikkelingen van het merk te meten. Het is echter een uitdaging om de juiste brand metrics te selecteren. Een enorme hoeveelheid metrics vraagt de aandacht van merkbeheerders. Maar welke
Privacy Metrics and Boundaries
L-F. Pau (Louis-François)
2005-01-01
textabstractThis paper aims at defining a set of privacy metrics (quantitative and qualitative) in the case of the relation between a privacy protector ,and an information gatherer .The aims with such metrics are: -to allow to assess and compare different user scenarios and their differences; for
International Nuclear Information System (INIS)
Millwater, Harry; Singh, Gulshan; Cortina, Miguel
2012-01-01
There are many methods to identify the important variable out of a set of random variables, i.e., “inter-variable” importance; however, to date there are no comparable methods to identify the “region” of importance within a random variable, i.e., “intra-variable” importance. Knowledge of the critical region of an input random variable (tail, near-tail, and central region) can provide valuable information towards characterizing, understanding, and improving a model through additional modeling or testing. As a result, an intra-variable probabilistic sensitivity method was developed and demonstrated for independent random variables that computes the partial derivative of a probabilistic response with respect to a localized perturbation in the CDF values of each random variable. These sensitivities are then normalized in absolute value with respect to the largest sensitivity within a distribution to indicate the region of importance. The methodology is implemented using the Score Function kernel-based method such that existing samples can be used to compute sensitivities for negligible cost. Numerical examples demonstrate the accuracy of the method through comparisons with finite difference and numerical integration quadrature estimates. - Highlights: ► Probabilistic sensitivity methodology. ► Determines the “region” of importance within random variables such as left tail, near tail, center, right tail, etc. ► Uses the Score Function approach to reuse the samples, hence, negligible cost. ► No restrictions on the random variable types or limit states.
Group field theory with noncommutative metric variables.
Baratin, Aristide; Oriti, Daniele
2010-11-26
We introduce a dual formulation of group field theories as a type of noncommutative field theories, making their simplicial geometry manifest. For Ooguri-type models, the Feynman amplitudes are simplicial path integrals for BF theories. We give a new definition of the Barrett-Crane model for gravity by imposing the simplicity constraints directly at the level of the group field theory action.
Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.
2008-04-01
Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.
Holographic Spherically Symmetric Metrics
Petri, Michael
The holographic principle (HP) conjectures, that the maximum number of degrees of freedom of any realistic physical system is proportional to the system's boundary area. The HP has its roots in the study of black holes. It has recently been applied to cosmological solutions. In this article we apply the HP to spherically symmetric static space-times. We find that any regular spherically symmetric object saturating the HP is subject to tight constraints on the (interior) metric, energy-density, temperature and entropy-density. Whenever gravity can be described by a metric theory, gravity is macroscopically scale invariant and the laws of thermodynamics hold locally and globally, the (interior) metric of a regular holographic object is uniquely determined up to a constant factor and the interior matter-state must follow well defined scaling relations. When the metric theory of gravity is general relativity, the interior matter has an overall string equation of state (EOS) and a unique total energy-density. Thus the holographic metric derived in this article can serve as simple interior 4D realization of Mathur's string fuzzball proposal. Some properties of the holographic metric and its possible experimental verification are discussed. The geodesics of the holographic metric describe an isotropically expanding (or contracting) universe with a nearly homogeneous matter-distribution within the local Hubble volume. Due to the overall string EOS the active gravitational mass-density is zero, resulting in a coasting expansion with Ht = 1, which is compatible with the recent GRB-data.
A New Metric for Land-Atmosphere Coupling Strength: Applications on Observations and Modeling
Tang, Q.; Xie, S.; Zhang, Y.; Phillips, T. J.; Santanello, J. A., Jr.; Cook, D. R.; Riihimaki, L.; Gaustad, K.
2017-12-01
A new metric is proposed to quantify the land-atmosphere (LA) coupling strength and is elaborated by correlating the surface evaporative fraction and impacting land and atmosphere variables (e.g., soil moisture, vegetation, and radiation). Based upon multiple linear regression, this approach simultaneously considers multiple factors and thus represents complex LA coupling mechanisms better than existing single variable metrics. The standardized regression coefficients quantify the relative contributions from individual drivers in a consistent manner, avoiding the potential inconsistency in relative influence of conventional metrics. Moreover, the unique expendable feature of the new method allows us to verify and explore potentially important coupling mechanisms. Our observation-based application of the new metric shows moderate coupling with large spatial variations at the U.S. Southern Great Plains. The relative importance of soil moisture vs. vegetation varies by location. We also show that LA coupling strength is generally underestimated by single variable methods due to their incompleteness. We also apply this new metric to evaluate the representation of LA coupling in the Accelerated Climate Modeling for Energy (ACME) V1 Contiguous United States (CONUS) regionally refined model (RRM). This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-734201
Metrics for image segmentation
Rees, Gareth; Greenway, Phil; Morray, Denise
1998-07-01
An important challenge in mapping image-processing techniques onto applications is the lack of quantitative performance measures. From a systems engineering perspective these are essential if system level requirements are to be decomposed into sub-system requirements which can be understood in terms of algorithm selection and performance optimization. Nowhere in computer vision is this more evident than in the area of image segmentation. This is a vigorous and innovative research activity, but even after nearly two decades of progress, it remains almost impossible to answer the question 'what would the performance of this segmentation algorithm be under these new conditions?' To begin to address this shortcoming, we have devised a well-principled metric for assessing the relative performance of two segmentation algorithms. This allows meaningful objective comparisons to be made between their outputs. It also estimates the absolute performance of an algorithm given ground truth. Our approach is an information theoretic one. In this paper, we describe the theory and motivation of our method, and present practical results obtained from a range of state of the art segmentation methods. We demonstrate that it is possible to measure the objective performance of these algorithms, and to use the information so gained to provide clues about how their performance might be improved.
International Nuclear Information System (INIS)
Le Coq, G.; Boudsocq, G.; Raymond, P.
1983-03-01
The Control Variable Method is extended to multidimensional fluid flow transient computations. In this paper basic principles of the method are given. The method uses a fully implicit space discretization and is based on the decomposition of the momentum flux tensor into scalar, vectorial, and tensorial, terms. Finally some computations about viscous-driven flow and buoyancy-driven flow in cavity are presented
Variable selection methods in PLS regression - a comparison study on metabolomics data
DEFF Research Database (Denmark)
Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach
. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using LC-MS based metabolomic approach. References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse PLS for Variable Selection when...... integrated approach. Due to the high number of variables in data sets (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need to be related. Variable selection (or removal of irrelevant...... different strategies for variable selection on PLSR method were considered and compared with respect to selected subset of variables and the possibility for biological validation. Sparse PLSR [1] as well as PLSR with Jack-knifing [2] was applied to data in order to achieve variable selection prior...
Harris, John Richardson; Caporaso, George J; Sampayan, Stephen E
2013-10-22
A system and method for producing modulated electrical signals. The system uses a variable resistor having a photoconductive wide bandgap semiconductor material construction whose conduction response to changes in amplitude of incident radiation is substantially linear throughout a non-saturation region to enable operation in non-avalanche mode. The system also includes a modulated radiation source, such as a modulated laser, for producing amplitude-modulated radiation with which to direct upon the variable resistor and modulate its conduction response. A voltage source and an output port, are both operably connected to the variable resistor so that an electrical signal may be produced at the output port by way of the variable resistor, either generated by activation of the variable resistor or propagating through the variable resistor. In this manner, the electrical signal is modulated by the variable resistor so as to have a waveform substantially similar to the amplitude-modulated radiation.
The relationship between glass ceiling and power distance as a cultural variable by a new method
Naide Jahangirov; Guler Saglam Ari; Seymur Jahangirov; Nuray Guneri Tosunoglu
2015-01-01
Glass ceiling symbolizes a variety of barriers and obstacles that arise from gender inequality at business life. With this mind, culture influences gender dynamics. The purpose of this research was to examine the relationship between the glass ceiling and the power distance as a cultural variable within organizations. Gender variable is taken as a moderator variable in relationship between the concepts. In addition to conventional correlation analysis, we employed a new method to investigate ...
Directory of Open Access Journals (Sweden)
Said Broumi
2015-03-01
Full Text Available The interval neutrosophic uncertain linguistic variables can easily express the indeterminate and inconsistent information in real world, and TOPSIS is a very effective decision making method more and more extensive applications. In this paper, we will extend the TOPSIS method to deal with the interval neutrosophic uncertain linguistic information, and propose an extended TOPSIS method to solve the multiple attribute decision making problems in which the attribute value takes the form of the interval neutrosophic uncertain linguistic variables and attribute weight is unknown. Firstly, the operational rules and properties for the interval neutrosophic variables are introduced. Then the distance between two interval neutrosophic uncertain linguistic variables is proposed and the attribute weight is calculated by the maximizing deviation method, and the closeness coefficients to the ideal solution for each alternatives. Finally, an illustrative example is given to illustrate the decision making steps and the effectiveness of the proposed method.
Azmi, Nur Iffah Mohamed; Arifin Mat Piah, Kamal; Yusoff, Wan Azhar Wan; Romlay, Fadhlur Rahman Mohd
2018-03-01
Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey- Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the particle velocity limit and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO- PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Furthermore, the physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning method responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a tuning method in the hydraulic positioning system.
A Comparison of Methods to Test Mediation and Other Intervening Variable Effects
MacKinnon, David P.; Lockwood, Chondra M.; Hoffman, Jeanne M.; West, Stephen G.; Sheets, Virgil
2010-01-01
A Monte Carlo study compared 14 methods to test the statistical significance of the intervening variable effect. An intervening variable (mediator) transmits the effect of an independent variable to a dependent variable. The commonly used R. M. Baron and D. A. Kenny (1986) approach has low statistical power. Two methods based on the distribution of the product and 2 difference-in-coefficients methods have the most accurate Type I error rates and greatest statistical power except in 1 important case in which Type I error rates are too high. The best balance of Type I error and statistical power across all cases is the test of the joint significance of the two effects comprising the intervening variable effect. PMID:11928892
Propulsion and launching analysis of variable-mass rockets by analytical methods
D.D. Ganji; M. Gorji; M. Hatami; A. Hasanpour; N. Khademzadeh
2013-01-01
In this study, applications of some analytical methods on nonlinear equation of the launching of a rocket with variable mass are investigated. Differential transformation method (DTM), homotopy perturbation method (HPM) and least square method (LSM) were applied and their results are compared with numerical solution. An excellent agreement with analytical methods and numerical ones is observed in the results and this reveals that analytical methods are effective and convenient. Also a paramet...
Schweizer, B
2005-01-01
Topics include special classes of probabilistic metric spaces, topologies, and several related structures, such as probabilistic normed and inner-product spaces. 1983 edition, updated with 3 new appendixes. Includes 17 illustrations.
National Research Council Canada - National Science Library
Olson, Teresa; Lee, Harry; Sanders, Johnnie
2002-01-01
.... We have developed the Tracker Performance Metric (TPM) specifically for this purpose. It was designed to measure the output performance, on a frame-by-frame basis, using its output position and quality...
Energy Technology Data Exchange (ETDEWEB)
Romero, Vicente [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bonney, Matthew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Schroeder, Benjamin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Weirs, V. Gregory [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-11-01
When very few samples of a random quantity are available from a source distribution of unknown shape, it is usually not possible to accurately infer the exact distribution from which the data samples come. Under-estimation of important quantities such as response variance and failure probabilities can result. For many engineering purposes, including design and risk analysis, we attempt to avoid under-estimation with a strategy to conservatively estimate (bound) these types of quantities -- without being overly conservative -- when only a few samples of a random quantity are available from model predictions or replicate experiments. This report examines a class of related sparse-data uncertainty representation and inference approaches that are relatively simple, inexpensive, and effective. Tradeoffs between the methods' conservatism, reliability, and risk versus number of data samples (cost) are quantified with multi-attribute metrics use d to assess method performance for conservative estimation of two representative quantities: central 95% of response; and 10^{-4} probability of exceeding a response threshold in a tail of the distribution. Each method's performance is characterized with 10,000 random trials on a large number of diverse and challenging distributions. The best method and number of samples to use in a given circumstance depends on the uncertainty quantity to be estimated, the PDF character, and the desired reliability of bounding the true value. On the basis of this large data base and study, a strategy is proposed for selecting the method and number of samples for attaining reasonable credibility levels in bounding these types of quantities when sparse samples of random variables or functions are available from experiments or simulations.
Theoretical investigations of the new Cokriging method for variable-fidelity surrogate modeling
DEFF Research Database (Denmark)
Zimmermann, Ralf; Bertram, Anna
2018-01-01
Cokriging is a variable-fidelity surrogate modeling technique which emulates a target process based on the spatial correlation of sampled data of different levels of fidelity. In this work, we address two theoretical questions associated with the so-called new Cokriging method for variable fidelity...
DEFF Research Database (Denmark)
Burgess, Stephen; Thompson, Simon G; Thompson, Grahame
2010-01-01
Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context o...
Comparison of Sparse and Jack-knife partial least squares regression methods for variable selection
DEFF Research Database (Denmark)
Karaman, Ibrahim; Qannari, El Mostafa; Martens, Harald
2013-01-01
The objective of this study was to compare two different techniques of variable selection, Sparse PLSR and Jack-knife PLSR, with respect to their predictive ability and their ability to identify relevant variables. Sparse PLSR is a method that is frequently used in genomics, whereas Jack-knife PL...
P-Link: A method for generating multicomponent cytochrome P450 fusions with variable linker length
DEFF Research Database (Denmark)
Belsare, Ketaki D.; Ruff, Anna Joelle; Martinez, Ronny
2014-01-01
Fusion protein construction is a widely employed biochemical technique, especially when it comes to multi-component enzymes such as cytochrome P450s. Here we describe a novel method for generating fusion proteins with variable linker lengths, protein fusion with variable linker insertion (P...
Directory of Open Access Journals (Sweden)
2007-01-01
Full Text Available Many software and IT projects fail in completing theirs objectives because different causes of which the management of the projects has a high weight. In order to have successfully projects, lessons learned have to be used, historical data to be collected and metrics and indicators have to be computed and used to compare them with past projects and avoid failure to happen. This paper presents some metrics that can be used for the IT project management.
Mass Customization Measurements Metrics
DEFF Research Database (Denmark)
Nielsen, Kjeld; Brunø, Thomas Ditlev; Jørgensen, Kaj Asbjørn
2014-01-01
A recent survey has indicated that 17 % of companies have ceased mass customizing less than 1 year after initiating the effort. This paper presents measurement for a company’s mass customization performance, utilizing metrics within the three fundamental capabilities: robust process design, choice...... navigation, and solution space development. A mass customizer when assessing performance with these metrics can identify within which areas improvement would increase competitiveness the most and enable more efficient transition to mass customization....
Metric inhomogeneous Diophantine approximation in positive characteristic
DEFF Research Database (Denmark)
Kristensen, Simon
2011-01-01
We obtain asymptotic formulae for the number of solutions to systems of inhomogeneous linear Diophantine inequalities over the field of formal Laurent series with coefficients from a finite fields, which are valid for almost every such system. Here `almost every' is with respect to Haar measure...... of the coefficients of the homogeneous part when the number of variables is at least two (singly metric case), and with respect to the Haar measure of all coefficients for any number of variables (doubly metric case). As consequences, we derive zero-one laws in the spirit of the Khintchine-Groshev Theorem and zero...
Metric inhomogeneous Diophantine approximation in positive characteristic
DEFF Research Database (Denmark)
Kristensen, S.
We obtain asymptotic formulae for the number of solutions to systems of inhomogeneous linear Diophantine inequalities over the field of formal Laurent series with coefficients from a finite fields, which are valid for almost every such system. Here 'almost every' is with respect to Haar measure...... of the coefficients of the homogeneous part when the number of variables is at least two (singly metric case), and with respect to the Haar measure of all coefficients for any number of variables (doubly metric case). As consequences, we derive zero-one laws in the spirit of the Khintchine--Groshev Theorem and zero...
International Nuclear Information System (INIS)
Qin Maochang; Fan Guihong
2008-01-01
There are many interesting methods can be utilized to construct special solutions of nonlinear differential equations with constant coefficients. However, most of these methods are not applicable to nonlinear differential equations with variable coefficients. A new method is presented in this Letter, which can be used to find special solutions of nonlinear differential equations with variable coefficients. This method is based on seeking appropriate Bernoulli equation corresponding to the equation studied. Many well-known equations are chosen to illustrate the application of this method
Comparison of different calibration methods suited for calibration problems with many variables
DEFF Research Database (Denmark)
Holst, Helle
1992-01-01
This paper describes and compares different kinds of statistical methods proposed in the literature as suited for solving calibration problems with many variables. These are: principal component regression, partial least-squares, and ridge regression. The statistical techniques themselves do...
Using traditional methods and indigenous technologies for coping with climate variability
Stigter, C.J.; Zheng Dawei,; Onyewotu, L.O.Z.; Mei Xurong,
2005-01-01
In agrometeorology and management of meteorology related natural resources, many traditional methods and indigenous technologies are still in use or being revived for managing low external inputs sustainable agriculture (LEISA) under conditions of climate variability. This paper starts with the
International Nuclear Information System (INIS)
Bosevski, T.
1971-01-01
The polynomial interpolation of neutron flux between the chosen space and energy variables enabled transformation of the integral transport equation into a system of linear equations with constant coefficients. Solutions of this system are the needed values of flux for chosen values of space and energy variables. The proposed improved method for solving the neutron transport problem including the mathematical formalism is simple and efficient since the number of needed input data is decreased both in treating the spatial and energy variables. Mathematical method based on this approach gives more stable solutions with significantly decreased probability of numerical errors. Computer code based on the proposed method was used for calculations of one heavy water and one light water reactor cell, and the results were compared to results of other very precise calculations. The proposed method was better concerning convergence rate, decreased computing time and needed computer memory. Discretization of variables enabled direct comparison of theoretical and experimental results
Term Based Comparison Metrics for Controlled and Uncontrolled Indexing Languages
Good, B. M.; Tennis, J. T.
2009-01-01
Introduction: We define a collection of metrics for describing and comparing sets of terms in controlled and uncontrolled indexing languages and then show how these metrics can be used to characterize a set of languages spanning folksonomies, ontologies and thesauri. Method: Metrics for term set characterization and comparison were identified and…
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.
Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan
2017-01-01
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method
Directory of Open Access Journals (Sweden)
Jun-He Yang
2017-01-01
Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.
Model reduction method using variable-separation for stochastic saddle point problems
Jiang, Lijian; Li, Qiuqi
2018-02-01
In this paper, we consider a variable-separation (VS) method to solve the stochastic saddle point (SSP) problems. The VS method is applied to obtain the solution in tensor product structure for stochastic partial differential equations (SPDEs) in a mixed formulation. The aim of such a technique is to construct a reduced basis approximation of the solution of the SSP problems. The VS method attempts to get a low rank separated representation of the solution for SSP in a systematic enrichment manner. No iteration is performed at each enrichment step. In order to satisfy the inf-sup condition in the mixed formulation, we enrich the separated terms for the primal system variable at each enrichment step. For the SSP problems by regularization or penalty, we propose a more efficient variable-separation (VS) method, i.e., the variable-separation by penalty method. This can avoid further enrichment of the separated terms in the original mixed formulation. The computation of the variable-separation method decomposes into offline phase and online phase. Sparse low rank tensor approximation method is used to significantly improve the online computation efficiency when the number of separated terms is large. For the applications of SSP problems, we present three numerical examples to illustrate the performance of the proposed methods.
Latent variable method for automatic adaptation to background states in motor imagery BCI
Dagaev, Nikolay; Volkova, Ksenia; Ossadtchi, Alexei
2018-02-01
Objective. Brain-computer interface (BCI) systems are known to be vulnerable to variabilities in background states of a user. Usually, no detailed information on these states is available even during the training stage. Thus there is a need in a method which is capable of taking background states into account in an unsupervised way. Approach. We propose a latent variable method that is based on a probabilistic model with a discrete latent variable. In order to estimate the model’s parameters, we suggest to use the expectation maximization algorithm. The proposed method is aimed at assessing characteristics of background states without any corresponding data labeling. In the context of asynchronous motor imagery paradigm, we applied this method to the real data from twelve able-bodied subjects with open/closed eyes serving as background states. Main results. We found that the latent variable method improved classification of target states compared to the baseline method (in seven of twelve subjects). In addition, we found that our method was also capable of background states recognition (in six of twelve subjects). Significance. Without any supervised information on background states, the latent variable method provides a way to improve classification in BCI by taking background states into account at the training stage and then by making decisions on target states weighted by posterior probabilities of background states at the prediction stage.
International Nuclear Information System (INIS)
Proriol, J.
1994-01-01
Five different methods are compared for selecting the most important variables with a view to classifying high energy physics events with neural networks. The different methods are: the F-test, Principal Component Analysis (PCA), a decision tree method: CART, weight evaluation, and Optimal Cell Damage (OCD). The neural networks use the variables selected with the different methods. We compare the percentages of events properly classified by each neural network. The learning set and the test set are the same for all the neural networks. (author)
Energy functionals for Calabi-Yau metrics
International Nuclear Information System (INIS)
Headrick, M; Nassar, A
2013-01-01
We identify a set of ''energy'' functionals on the space of metrics in a given Kähler class on a Calabi-Yau manifold, which are bounded below and minimized uniquely on the Ricci-flat metric in that class. Using these functionals, we recast the problem of numerically solving the Einstein equation as an optimization problem. We apply this strategy, using the ''algebraic'' metrics (metrics for which the Kähler potential is given in terms of a polynomial in the projective coordinates), to the Fermat quartic and to a one-parameter family of quintics that includes the Fermat and conifold quintics. We show that this method yields approximations to the Ricci-flat metric that are exponentially accurate in the degree of the polynomial (except at the conifold point, where the convergence is polynomial), and therefore orders of magnitude more accurate than the balanced metrics, previously studied as approximations to the Ricci-flat metric. The method is relatively fast and easy to implement. On the theoretical side, we also show that the functionals can be used to give a heuristic proof of Yau's theorem
International Nuclear Information System (INIS)
Tang, Bo; He, Yinnian; Wei, Leilei; Zhang, Xindong
2012-01-01
In this Letter, a generalized fractional sub-equation method is proposed for solving fractional differential equations with variable coefficients. Being concise and straightforward, this method is applied to the space–time fractional Gardner equation with variable coefficients. As a result, many exact solutions are obtained including hyperbolic function solutions, trigonometric function solutions and rational solutions. It is shown that the considered method provides a very effective, convenient and powerful mathematical tool for solving many other fractional differential equations in mathematical physics. -- Highlights: ► Study of fractional differential equations with variable coefficients plays a role in applied physical sciences. ► It is shown that the proposed algorithm is effective for solving fractional differential equations with variable coefficients. ► The obtained solutions may give insight into many considerable physical processes.
Aygunes, Gunes
2017-07-01
The objective of this paper is to survey and determine the macroeconomic factors affecting the level of venture capital (VC) investments in a country. The literary depends on venture capitalists' quality and countries' venture capital investments. The aim of this paper is to give relationship between venture capital investment and macro economic variables via statistical computation method. We investigate the countries and macro economic variables. By using statistical computation method, we derive correlation between venture capital investments and macro economic variables. According to method of logistic regression model (logit regression or logit model), macro economic variables are correlated with each other in three group. Venture capitalists regard correlations as a indicator. Finally, we give correlation matrix of our results.
Partner Symmetries, Group Foliation and ASD Ricci-Flat Metrics without Killing Vectors
Directory of Open Access Journals (Sweden)
Andrei A. Malykh
2013-11-01
Full Text Available We demonstrate how a combination of our recently developed methods of partner symmetries, symmetry reduction in group parameters and a new version of the group foliation method can produce noninvariant solutions of complex Monge-Ampère equation (CMA and provide a lift from invariant solutions of CMA satisfying Boyer-Finley equation to non-invariant ones. Applying these methods, we obtain a new noninvariant solution of CMA and the corresponding Ricci-flat anti-self-dual Einstein-Kähler metric with Euclidean signature without Killing vectors, together with Riemannian curvature two-forms. There are no singularities of the metric and curvature in a bounded domain if we avoid very special choices of arbitrary functions of a single variable in our solution. This metric does not describe gravitational instantons because the curvature is not concentrated in a bounded domain.
Metrical and dynamical aspects in complex analysis
2017-01-01
The central theme of this reference book is the metric geometry of complex analysis in several variables. Bridging a gap in the current literature, the text focuses on the fine behavior of the Kobayashi metric of complex manifolds and its relationships to dynamical systems, hyperbolicity in the sense of Gromov and operator theory, all very active areas of research. The modern points of view expressed in these notes, collected here for the first time, will be of interest to academics working in the fields of several complex variables and metric geometry. The different topics are treated coherently and include expository presentations of the relevant tools, techniques and objects, which will be particularly useful for graduate and PhD students specializing in the area.
Johnson, Stephen B.; Ghoshal, Sudipto; Haste, Deepak; Moore, Craig
2017-01-01
This paper describes the theory and considerations in the application of metrics to measure the effectiveness of fault management. Fault management refers here to the operational aspect of system health management, and as such is considered as a meta-control loop that operates to preserve or maximize the system's ability to achieve its goals in the face of current or prospective failure. As a suite of control loops, the metrics to estimate and measure the effectiveness of fault management are similar to those of classical control loops in being divided into two major classes: state estimation, and state control. State estimation metrics can be classified into lower-level subdivisions for detection coverage, detection effectiveness, fault isolation and fault identification (diagnostics), and failure prognosis. State control metrics can be classified into response determination effectiveness and response effectiveness. These metrics are applied to each and every fault management control loop in the system, for each failure to which they apply, and probabilistically summed to determine the effectiveness of these fault management control loops to preserve the relevant system goals that they are intended to protect.
Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H
2017-07-01
Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in
A stochastic Galerkin method for the Euler equations with Roe variable transformation
Pettersson, Per; Iaccarino, Gianluca; Nordströ m, Jan
2014-01-01
The Euler equations subject to uncertainty in the initial and boundary conditions are investigated via the stochastic Galerkin approach. We present a new fully intrusive method based on a variable transformation of the continuous equations. Roe variables are employed to get quadratic dependence in the flux function and a well-defined Roe average matrix that can be determined without matrix inversion.In previous formulations based on generalized polynomial chaos expansion of the physical variables, the need to introduce stochastic expansions of inverse quantities, or square roots of stochastic quantities of interest, adds to the number of possible different ways to approximate the original stochastic problem. We present a method where the square roots occur in the choice of variables, resulting in an unambiguous problem formulation.The Roe formulation saves computational cost compared to the formulation based on expansion of conservative variables. Moreover, the Roe formulation is more robust and can handle cases of supersonic flow, for which the conservative variable formulation fails to produce a bounded solution. For certain stochastic basis functions, the proposed method can be made more effective and well-conditioned. This leads to increased robustness for both choices of variables. We use a multi-wavelet basis that can be chosen to include a large number of resolution levels to handle more extreme cases (e.g. strong discontinuities) in a robust way. For smooth cases, the order of the polynomial representation can be increased for increased accuracy. © 2013 Elsevier Inc.
Energy Technology Data Exchange (ETDEWEB)
Frye, Jason Neal; Veitch, Cynthia K.; Mateski, Mark Elliot; Michalski, John T.; Harris, James Mark; Trevino, Cassandra M.; Maruoka, Scott
2012-03-01
Threats are generally much easier to list than to describe, and much easier to describe than to measure. As a result, many organizations list threats. Fewer describe them in useful terms, and still fewer measure them in meaningful ways. This is particularly true in the dynamic and nebulous domain of cyber threats - a domain that tends to resist easy measurement and, in some cases, appears to defy any measurement. We believe the problem is tractable. In this report we describe threat metrics and models for characterizing threats consistently and unambiguously. The purpose of this report is to support the Operational Threat Assessment (OTA) phase of risk and vulnerability assessment. To this end, we focus on the task of characterizing cyber threats using consistent threat metrics and models. In particular, we address threat metrics and models for describing malicious cyber threats to US FCEB agencies and systems.
Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant
Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa
2013-09-17
System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.
VOLUMETRIC METHOD FOR EVALUATION OF BEACHES VARIABILITY BASED ON GIS-TOOLS
Directory of Open Access Journals (Sweden)
V. V. Dolotov
2015-01-01
Full Text Available In frame of cadastral beach evaluation the volumetric method of natural variability index is proposed. It base on spatial calculations with Cut-Fill method and volume accounting ofboththe common beach contour and specific areas for the each time.
Control Method for Variable Speed Wind Turbines to Support Temporary Primary Frequency Control
DEFF Research Database (Denmark)
Wang, Haijiao; Chen, Zhe; Jiang, Quanyuan
2014-01-01
This paper develops a control method for variable speed wind turbines (VSWTs) to support temporary primary frequency control of power system. The control method contains two parts: (1) up-regulate support control when a frequency drop event occurs; (2) down-regulate support control when a frequen...
A design method of compensators for multi-variable control system with PID controllers 'CHARLY'
International Nuclear Information System (INIS)
Fujiwara, Toshitaka; Yamada, Katsumi
1985-01-01
A systematic design method of compensators for a multi-variable control system having usual PID controllers in its loops is presented in this paper. The method itself is able: to determine the main manipulating variable corresponding to each controlled variable with a sensitivity analysis in the frequency domain. to tune PID controllers sufficiently to realize adequate control actions with a searching technique of minimum values of cost functionals. to design compensators improving the control preformance and to simulate a total system for confirming the designed compensators. In the phase of compensator design, the state variable feed-back gain is obtained by means of the OPTIMAL REGULATOR THEORY for the composite system of plant and PID controllers. The transfer function type compensators the configurations of which were previously given are, then, designed to approximate the frequency responces of the above mentioned state feed-back system. An example is illustrated for convenience. (author)
A Novel Flood Forecasting Method Based on Initial State Variable Correction
Directory of Open Access Journals (Sweden)
Kuang Li
2017-12-01
Full Text Available The influence of initial state variables on flood forecasting accuracy by using conceptual hydrological models is analyzed in this paper and a novel flood forecasting method based on correction of initial state variables is proposed. The new method is abbreviated as ISVC (Initial State Variable Correction. The ISVC takes the residual between the measured and forecasted flows during the initial period of the flood event as the objective function, and it uses a particle swarm optimization algorithm to correct the initial state variables, which are then used to drive the flood forecasting model. The historical flood events of 11 watersheds in south China are forecasted and verified, and important issues concerning the ISVC application are then discussed. The study results show that the ISVC is effective and applicable in flood forecasting tasks. It can significantly improve the flood forecasting accuracy in most cases.
Shuler, Robert
2018-04-01
The goal of this paper is to take a completely fresh approach to metric gravity, in which the metric principle is strictly adhered to but its properties in local space-time are derived from conservation principles, not inferred from a global field equation. The global field strength variation then gains some flexibility, but only in the regime of very strong fields (2nd-order terms) whose measurement is now being contemplated. So doing provides a family of similar gravities, differing only in strong fields, which could be developed into meaningful verification targets for strong fields after the manner in which far-field variations were used in the 20th century. General Relativity (GR) is shown to be a member of the family and this is demonstrated by deriving the Schwarzschild metric exactly from a suitable field strength assumption. The method of doing so is interesting in itself because it involves only one differential equation rather than the usual four. Exact static symmetric field solutions are also given for one pedagogical alternative based on potential, and one theoretical alternative based on inertia, and the prospects of experimentally differentiating these are analyzed. Whether the method overturns the conventional wisdom that GR is the only metric theory of gravity and that alternatives must introduce additional interactions and fields is somewhat semantical, depending on whether one views the field strength assumption as a field and whether the assumption that produces GR is considered unique in some way. It is of course possible to have other fields, and the local space-time principle can be applied to field gravities which usually are weak-field approximations having only time dilation, giving them the spatial factor and promoting them to full metric theories. Though usually pedagogical, some of them are interesting from a quantum gravity perspective. Cases are noted where mass measurement errors, or distributions of dark matter, can cause one
International Nuclear Information System (INIS)
Sumer, Kutluk Kagan; Goktas, Ozlem; Hepsag, Aycan
2009-01-01
In this study, we used ARIMA, seasonal ARIMA (SARIMA) and alternatively the regression model with seasonal latent variable in forecasting electricity demand by using data that belongs to 'Kayseri and Vicinity Electricity Joint-Stock Company' over the 1997:1-2005:12 periods. This study tries to examine the advantages of forecasting with ARIMA, SARIMA methods and with the model has seasonal latent variable to each other. The results support that ARIMA and SARIMA models are unsuccessful in forecasting electricity demand. The regression model with seasonal latent variable used in this study gives more successful results than ARIMA and SARIMA models because also this model can consider seasonal fluctuations and structural breaks
Johnson, Kenneth L.; White, K. Preston, Jr.
2012-01-01
The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. In this paper, the results of empirical tests intended to assess the accuracy of acceptance sampling plan calculators implemented for six variable distributions are presented.
A method to forecast quantitative variables relating to nuclear public acceptance
International Nuclear Information System (INIS)
Ohnishi, T.
1992-01-01
A methodology is proposed for forecasting the future trend of quantitative variables profoundly related to the public acceptance (PA) of nuclear energy. The social environment influencing PA is first modeled by breaking it down into a finite number of fundamental elements and then the interactive formulae between the quantitative variables, which are attributed to and characterize each element, are determined by using the actual values of the variables in the past. Inputting the estimated values of exogenous variables into these formulae, the forecast values of endogenous variables can finally be obtained. Using this method, the problem of nuclear PA in Japan is treated as, for example, where the context is considered to comprise a public sector and the general social environment and socio-psychology. The public sector is broken down into three elements of the general public, the inhabitants living around nuclear facilities and the activists of anti-nuclear movements, whereas the social environment and socio-psychological factors are broken down into several elements, such as news media and psychological factors. Twenty-seven endogenous and seven exogenous variables are introduced to quantify these elements. After quantitatively formulating the interactive features between them and extrapolating the exogenous variables into the future estimates are made of the growth or attenuation of the endogenous variables, such as the pro- and anti-nuclear fractions in public opinion polls and the frequency of occurrence of anti-nuclear movements. (author)
Resistance Torque Based Variable Duty-Cycle Control Method for a Stage II Compressor
Zhong, Meipeng; Zheng, Shuiying
2017-07-01
The resistance torque of a piston stage II compressor generates strenuous fluctuations in a rotational period, and this can lead to negative influences on the working performance of the compressor. To restrain the strenuous fluctuations in the piston stage II compressor, a variable duty-cycle control method based on the resistance torque is proposed. A dynamic model of a stage II compressor is set up, and the resistance torque and other characteristic parameters are acquired as the control targets. Then, a variable duty-cycle control method is applied to track the resistance torque, thereby improving the working performance of the compressor. Simulated results show that the compressor, driven by the proposed method, requires lower current, while the rotating speed and the output torque remain comparable to the traditional variable-frequency control methods. A variable duty-cycle control system is developed, and the experimental results prove that the proposed method can help reduce the specific power, input power, and working noise of the compressor to 0.97 kW·m-3·min-1, 0.09 kW and 3.10 dB, respectively, under the same conditions of discharge pressure of 2.00 MPa and a discharge volume of 0.095 m3/min. The proposed variable duty-cycle control method tracks the resistance torque dynamically, and improves the working performance of a Stage II Compressor. The proposed variable duty-cycle control method can be applied to other compressors, and can provide theoretical guidance for the compressor.
A survey of variable selection methods in two Chinese epidemiology journals
Directory of Open Access Journals (Sweden)
Lynn Henry S
2010-09-01
Full Text Available Abstract Background Although much has been written on developing better procedures for variable selection, there is little research on how it is practiced in actual studies. This review surveys the variable selection methods reported in two high-ranking Chinese epidemiology journals. Methods Articles published in 2004, 2006, and 2008 in the Chinese Journal of Epidemiology and the Chinese Journal of Preventive Medicine were reviewed. Five categories of methods were identified whereby variables were selected using: A - bivariate analyses; B - multivariable analysis; e.g. stepwise or individual significance testing of model coefficients; C - first bivariate analyses, followed by multivariable analysis; D - bivariate analyses or multivariable analysis; and E - other criteria like prior knowledge or personal judgment. Results Among the 287 articles that reported using variable selection methods, 6%, 26%, 30%, 21%, and 17% were in categories A through E, respectively. One hundred sixty-three studies selected variables using bivariate analyses, 80% (130/163 via multiple significance testing at the 5% alpha-level. Of the 219 multivariable analyses, 97 (44% used stepwise procedures, 89 (41% tested individual regression coefficients, but 33 (15% did not mention how variables were selected. Sixty percent (58/97 of the stepwise routines also did not specify the algorithm and/or significance levels. Conclusions The variable selection methods reported in the two journals were limited in variety, and details were often missing. Many studies still relied on problematic techniques like stepwise procedures and/or multiple testing of bivariate associations at the 0.05 alpha-level. These deficiencies should be rectified to safeguard the scientific validity of articles published in Chinese epidemiology journals.
Tice, Bradley S.
Metrical phonology, a linguistic process of phonological stress assessment and diagrammatic simplification of sentence and word stress, is discussed as it is found in the English language with the intention that it may be used in second language instruction. Stress is defined by its physical and acoustical correlates, and the principles of…
Engineering performance metrics
Delozier, R.; Snyder, N.
1993-03-01
Implementation of a Total Quality Management (TQM) approach to engineering work required the development of a system of metrics which would serve as a meaningful management tool for evaluating effectiveness in accomplishing project objectives and in achieving improved customer satisfaction. A team effort was chartered with the goal of developing a system of engineering performance metrics which would measure customer satisfaction, quality, cost effectiveness, and timeliness. The approach to developing this system involved normal systems design phases including, conceptual design, detailed design, implementation, and integration. The lessons teamed from this effort will be explored in this paper. These lessons learned may provide a starting point for other large engineering organizations seeking to institute a performance measurement system accomplishing project objectives and in achieving improved customer satisfaction. To facilitate this effort, a team was chartered to assist in the development of the metrics system. This team, consisting of customers and Engineering staff members, was utilized to ensure that the needs and views of the customers were considered in the development of performance measurements. The development of a system of metrics is no different than the development of any type of system. It includes the steps of defining performance measurement requirements, measurement process conceptual design, performance measurement and reporting system detailed design, and system implementation and integration.
Quantification and variability in colonic volume with a novel magnetic resonance imaging method
DEFF Research Database (Denmark)
Nilsson, M; Sandberg, Thomas Holm; Poulsen, Jakob Lykke
2015-01-01
Background: Segmental distribution of colorectal volume is relevant in a number of diseases, but clinical and experimental use demands robust reliability and validity. Using a novel semi-automatic magnetic resonance imaging-based technique, the aims of this study were to describe: (i) inter......-individual and intra-individual variability of segmental colorectal volumes between two observations in healthy subjects and (ii) the change in segmental colorectal volume distribution before and after defecation. Methods: The inter-individual and intra-individual variability of four colorectal volumes (cecum...... (p = 0.02). Conclusions & Inferences: Imaging of segmental colorectal volume, morphology, and fecal accumulation is advantageous to conventional methods in its low variability, high spatial resolution, and its absence of contrast-enhancing agents and irradiation. Hence, the method is suitable...
A sizing method for stand-alone PV installations with variable demand
Energy Technology Data Exchange (ETDEWEB)
Posadillo, R. [Grupo de Investigacion en Energias y Recursos Renovables, Dpto. de Fisica Aplicada, E.P.S., Universidad de Cordoba, Avda. Menendez Pidal s/n, 14004 Cordoba (Spain); Lopez Luque, R. [Grupo de Investigacion de Fisica Para las Energias y Recursos Renovables, Dpto. de Fisica Aplicada, Edificio C2 Campus de Rabanales, 14071 Cordoba (Spain)
2008-05-15
The practical applicability of the considerations made in a previous paper to characterize energy balances in stand-alone photovoltaic systems (SAPV) is presented. Given that energy balances were characterized based on monthly estimations, the method is appropriate for sizing installations with variable monthly demands and variable monthly panel tilt (for seasonal estimations). The method presented is original in that it is the only method proposed for this type of demand. The method is based on the rational utilization of daily solar radiation distribution functions. When exact mathematical expressions are not available, approximate empirical expressions can be used. The more precise the statistical characterization of the solar radiation on the receiver module, the more precise the sizing method given that the characterization will solely depend on the distribution function of the daily global irradiation on the tilted surface H{sub g{beta}}{sub i}. This method, like previous ones, uses the concept of loss of load probability (LLP) as a parameter to characterize system design and includes information on the standard deviation of this parameter ({sigma}{sub LLP}) as well as two new parameters: annual number of system failures (f) and the standard deviation of annual number of system failures ({sigma}{sub f}). This paper therefore provides an analytical method for evaluating and sizing stand-alone PV systems with variable monthly demand and panel inclination. The sizing method has also been applied in a practical manner. (author)
Wegner, Franz
2016-01-01
This text presents the mathematical concepts of Grassmann variables and the method of supersymmetry to a broad audience of physicists interested in applying these tools to disordered and critical systems, as well as related topics in statistical physics. Based on many courses and seminars held by the author, one of the pioneers in this field, the reader is given a systematic and tutorial introduction to the subject matter. The algebra and analysis of Grassmann variables is presented in part I. The mathematics of these variables is applied to a random matrix model, path integrals for fermions, dimer models and the Ising model in two dimensions. Supermathematics - the use of commuting and anticommuting variables on an equal footing - is the subject of part II. The properties of supervectors and supermatrices, which contain both commuting and Grassmann components, are treated in great detail, including the derivation of integral theorems. In part III, supersymmetric physical models are considered. While supersym...
Duan, Fajie; Fu, Xiao; Jiang, Jiajia; Huang, Tingting; Ma, Ling; Zhang, Cong
2018-05-01
In this work, an automatic variable selection method for quantitative analysis of soil samples using laser-induced breakdown spectroscopy (LIBS) is proposed, which is based on full spectrum correction (FSC) and modified iterative predictor weighting-partial least squares (mIPW-PLS). The method features automatic selection without artificial processes. To illustrate the feasibility and effectiveness of the method, a comparison with genetic algorithm (GA) and successive projections algorithm (SPA) for different elements (copper, barium and chromium) detection in soil was implemented. The experimental results showed that all the three methods could accomplish variable selection effectively, among which FSC-mIPW-PLS required significantly shorter computation time (12 s approximately for 40,000 initial variables) than the others. Moreover, improved quantification models were got with variable selection approaches. The root mean square errors of prediction (RMSEP) of models utilizing the new method were 27.47 (copper), 37.15 (barium) and 39.70 (chromium) mg/kg, which showed comparable prediction effect with GA and SPA.
The Leech method for diagnosing constipation: intra- and interobserver variability and accuracy
International Nuclear Information System (INIS)
Lorijn, Fleur de; Voskuijl, Wieger P.; Taminiau, Jan A.; Benninga, Marc A.; Rijn, Rick R. van; Henneman, Onno D.F.; Heijmans, Jarom; Reitsma, Johannes B.
2006-01-01
The data concerning the value of a plain abdominal radiograph in childhood constipation are inconsistent. Recently, positive results have been reported of a new radiographic scoring system, ''the Leech method'', for assessing faecal loading. To assess intra- and interobserver variability and determine diagnostic accuracy of the Leech method in identifying children with functional constipation (FC). A total of 89 children (median age 9.8 years) with functional gastrointestinal disorders were included in the study. Based on clinical parameters, 52 fulfilled the criteria for FC, six fulfilled the criteria for functional abdominal pain (FAP), and 31 for functional non-retentive faecal incontinence (FNRFI); the latter two groups provided the controls. To assess intra- and interobserver variability of the Leech method three scorers scored the same abdominal radiograph twice. A Leech score of 9 or more was considered as suggestive of constipation. ROC analysis was used to determine the diagnostic accuracy of the Leech method in separating patients with FC from control patients. Significant intraobserver variability was found between two scorers (P=0.005 and P<0.0001), whereas there was no systematic difference between the two scores of the other scorer (P=0.89). The scores between scorers differed systematically and displayed large variability. The area under the ROC curve was 0.68 (95% CI 0.58-0.80), indicating poor diagnostic accuracy. The Leech scoring method for assessing faecal loading on a plain abdominal radiograph is of limited value in the diagnosis of FC in children. (orig.)
Defining quality metrics and improving safety and outcome in allergy care.
Lee, Stella; Stachler, Robert J; Ferguson, Berrylin J
2014-04-01
The delivery of allergy immunotherapy in the otolaryngology office is variable and lacks standardization. Quality metrics encompasses the measurement of factors associated with good patient-centered care. These factors have yet to be defined in the delivery of allergy immunotherapy. We developed and applied quality metrics to 6 allergy practices affiliated with an academic otolaryngic allergy center. This work was conducted at a tertiary academic center providing care to over 1500 patients. We evaluated methods and variability between 6 sites. Tracking of errors and anaphylaxis was initiated across all sites. A nationwide survey of academic and private allergists was used to collect data on current practice and use of quality metrics. The most common types of errors recorded were patient identification errors (n = 4), followed by vial mixing errors (n = 3), and dosing errors (n = 2). There were 7 episodes of anaphylaxis of which 2 were secondary to dosing errors for a rate of 0.01% or 1 in every 10,000 injection visits/year. Site visits showed that 86% of key safety measures were followed. Analysis of nationwide survey responses revealed that quality metrics are still not well defined by either medical or otolaryngic allergy practices. Academic practices were statistically more likely to use quality metrics (p = 0.021) and perform systems reviews and audits in comparison to private practices (p = 0.005). Quality metrics in allergy delivery can help improve safety and quality care. These metrics need to be further defined by otolaryngic allergists in the changing health care environment. © 2014 ARS-AAOA, LLC.
Crowdsourcing metrics of digital collections
Directory of Open Access Journals (Sweden)
Tuula Pääkkönen
2015-12-01
Full Text Available In the National Library of Finland (NLF there are millions of digitized newspaper and journal pages, which are openly available via the public website http://digi.kansalliskirjasto.fi. To serve users better, last year the front end was completely overhauled with its main aim in crowdsourcing features, e.g., by giving end-users the opportunity to create digital clippings and a personal scrapbook from the digital collections. But how can you know whether crowdsourcing has had an impact? How much crowdsourcing functionalities have been used so far? Did crowdsourcing work? In this paper the statistics and metrics of a recent crowdsourcing effort are analysed across the different digitized material types (newspapers, journals, ephemera. The subjects, categories and keywords given by the users are analysed to see which topics are the most appealing. Some notable public uses of the crowdsourced article clippings are highlighted. These metrics give us indications on how the end-users, based on their own interests, are investigating and using the digital collections. Therefore, the suggested metrics illustrate the versatility of the information needs of the users, varying from citizen science to research purposes. By analysing the user patterns, we can respond to the new needs of the users by making minor changes to accommodate the most active participants, while still making the service more approachable for those who are trying out the functionalities for the first time. Participation in the clippings and annotations can enrich the materials in unexpected ways and can possibly pave the way for opportunities of using crowdsourcing more also in research contexts. This creates more opportunities for the goals of open science since source data becomes available, making it possible for researchers to reach out to the general public for help. In the long term, utilizing, for example, text mining methods can allow these different end-user segments to
He, Xiaowei; Liang, Jimin; Wang, Xiaorui; Yu, Jingjing; Qu, Xiaochao; Wang, Xiaodong; Hou, Yanbin; Chen, Duofang; Liu, Fang; Tian, Jie
2010-11-22
In this paper, we present an incomplete variables truncated conjugate gradient (IVTCG) method for bioluminescence tomography (BLT). Considering the sparse characteristic of the light source and insufficient surface measurement in the BLT scenarios, we combine a sparseness-inducing (ℓ1 norm) regularization term with a quadratic error term in the IVTCG-based framework for solving the inverse problem. By limiting the number of variables updated at each iterative and combining a variable splitting strategy to find the search direction more efficiently, it obtains fast and stable source reconstruction, even without a priori information of the permissible source region and multispectral measurements. Numerical experiments on a mouse atlas validate the effectiveness of the method. In vivo mouse experimental results further indicate its potential for a practical BLT system.
Approaches for developing a sizing method for stand-alone PV systems with variable demand
Energy Technology Data Exchange (ETDEWEB)
Posadillo, R. [Grupo de Investigacion en Energias y Recursos Renovables, Dpto. de Fisica Aplicada, E.P.S., Universidad de Cordoba, Avda. Menendez Pidal s/n, 14004 Cordoba (Spain); Lopez Luque, R. [Grupo de Investigacion de Fisica para las Energias y Recursos Renovables, Dpto. de Fisica Aplicada. Edificio C2 Campus de Rabanales, 14071 Cordoba (Spain)
2008-05-15
Accurate sizing is one of the most important aspects to take into consideration when designing a stand-alone photovoltaic system (SAPV). Various methods, which differ in terms of their simplicity or reliability, have been developed for this purpose. Analytical methods, which seek functional relationships between variables of interest to the sizing problem, are one of these approaches. A series of rational considerations are presented in this paper with the aim of shedding light upon the basic principles and results of various sizing methods proposed by different authors. These considerations set the basis for a new analytical method that has been designed for systems with variable monthly energy demands. Following previous approaches, the method proposed is based on the concept of loss of load probability (LLP) - a parameter that is used to characterize system design. The method includes information on the standard deviation of loss of load probability ({sigma}{sub LLP}) and on two new parameters: annual number of system failures (f) and standard deviation of annual number of failures ({sigma}{sub f}). The method proves useful for sizing a PV system in a reliable manner and serves to explain the discrepancies found in the research on systems with LLP<10{sup -2}. We demonstrate that reliability depends not only on the sizing variables and on the distribution function of solar radiation, but on the minimum value as well, which in a given location and with a monthly average clearness index, achieves total solar radiation on the receiver surface. (author)
Validation of Metrics as Error Predictors
Mendling, Jan
In this chapter, we test the validity of metrics that were defined in the previous chapter for predicting errors in EPC business process models. In Section 5.1, we provide an overview of how the analysis data is generated. Section 5.2 describes the sample of EPCs from practice that we use for the analysis. Here we discuss a disaggregation by the EPC model group and by error as well as a correlation analysis between metrics and error. Based on this sample, we calculate a logistic regression model for predicting error probability with the metrics as input variables in Section 5.3. In Section 5.4, we then test the regression function for an independent sample of EPC models from textbooks as a cross-validation. Section 5.5 summarizes the findings.
A fast collocation method for a variable-coefficient nonlocal diffusion model
Wang, Che; Wang, Hong
2017-02-01
We develop a fast collocation scheme for a variable-coefficient nonlocal diffusion model, for which a numerical discretization would yield a dense stiffness matrix. The development of the fast method is achieved by carefully handling the variable coefficients appearing inside the singular integral operator and exploiting the structure of the dense stiffness matrix. The resulting fast method reduces the computational work from O (N3) required by a commonly used direct solver to O (Nlog N) per iteration and the memory requirement from O (N2) to O (N). Furthermore, the fast method reduces the computational work of assembling the stiffness matrix from O (N2) to O (N). Numerical results are presented to show the utility of the fast method.
Directory of Open Access Journals (Sweden)
Jovković Biljana
2012-12-01
Full Text Available The aim of this paper is to present the procedure of audit sampling using the variable sampling methods for conducting the tests of income from insurance premiums in insurance company 'Takovo'. Since the incomes from the insurance premiums from vehicle insurance and third-party vehicle insurance have the dominant share of the insurance company's income, the application of this method will be shown in the audit examination of these incomes - incomes from VI and TPVI premiums. For investigating the applicability of these methods in testing the income of other insurance companies, we shall implement the method of variable sampling in the audit testing of the premium income from the three leading insurance companies in Serbia, 'Dunav', 'DDOR' and 'Delta Generali' Insurance.
A method to standardize gait and balance variables for gait velocity.
Iersel, M.B. van; Olde Rikkert, M.G.M.; Borm, G.F.
2007-01-01
Many gait and balance variables depend on gait velocity, which seriously hinders the interpretation of gait and balance data derived from walks at different velocities. However, as far as we know there is no widely accepted method to correct for effects of gait velocity on other gait and balance
Directory of Open Access Journals (Sweden)
Hongwu Zhang
2011-08-01
Full Text Available In this article, we study a Cauchy problem for an elliptic equation with variable coefficients. It is well-known that such a problem is severely ill-posed; i.e., the solution does not depend continuously on the Cauchy data. We propose a modified quasi-boundary value regularization method to solve it. Convergence estimates are established under two a priori assumptions on the exact solution. A numerical example is given to illustrate our proposed method.
Enterprise Sustainment Metrics
2015-06-19
are negatively impacting KPIs” (Parmenter, 2010: 31). In the current state, the Air Force’s AA and PBL metrics are once again split . AA does...must have the authority to “take immediate action to rectify situations that are negatively impacting KPIs” (Parmenter, 2010: 31). 3. Measuring...highest profitability and shareholder value for each company” (2014: 273). By systematically diagraming a process, either through a swim lane flowchart
Symmetries of the dual metrics
International Nuclear Information System (INIS)
Baleanu, D.
1998-01-01
The geometric duality between the metric g μν and a Killing tensor K μν is studied. The conditions were found when the symmetries of the metric g μν and the dual metric K μν are the same. Dual spinning space was constructed without introduction of torsion. The general results are applied to the case of Kerr-Newmann metric
Accuracy and precision in the calculation of phenology metrics
DEFF Research Database (Denmark)
Ferreira, Ana Sofia; Visser, Andre; MacKenzie, Brian
2014-01-01
a phenology metric is first determined from a noise- and gap-free time series, and again once it has been modified. We show that precision is a greater concern than accuracy for many of these metrics, an important point that has been hereto overlooked in the literature. The variability in precision between...... phenology metrics is substantial, but it can be improved by the use of preprocessing techniques (e.g., gap-filling or smoothing). Furthermore, there are important differences in the inherent variability of the metrics that may be crucial in the interpretation of studies based upon them. Of the considered......Phytoplankton phenology (the timing of seasonal events) is a commonly used indicator for evaluating responses of marine ecosystems to climate change. However, phenological metrics are vulnerable to observation-(bloom amplitude, missing data, and observational noise) and analysis-related (temporal...
Strong Stability Preserving Explicit Linear Multistep Methods with Variable Step Size
Hadjimichael, Yiannis
2016-09-08
Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods (of order two and three) with variable step size, and prove their optimality, stability, and convergence. The choice of step size for multistep SSP methods is an interesting problem because the allowable step size depends on the SSP coefficient, which in turn depends on the chosen step sizes. The description of the methods includes an optimal step-size strategy. We prove sharp upper bounds on the allowable step size for explicit SSP linear multistep methods and show the existence of methods with arbitrarily high order of accuracy. The effectiveness of the methods is demonstrated through numerical examples.
Kerr metric in cosmological background
Energy Technology Data Exchange (ETDEWEB)
Vaidya, P C [Gujarat Univ., Ahmedabad (India). Dept. of Mathematics
1977-06-01
A metric satisfying Einstein's equation is given which in the vicinity of the source reduces to the well-known Kerr metric and which at large distances reduces to the Robertson-Walker metric of a nomogeneous cosmological model. The radius of the event horizon of the Kerr black hole in the cosmological background is found out.
Xu, Jun; Cudel, Christophe; Kohler, Sophie; Fontaine, Stéphane; Haeberlé, Olivier; Klotz, Marie-Louise
2012-04-01
Fabric's smoothness is a key factor in determining the quality of finished textile products and has great influence on the functionality of industrial textiles and high-end textile products. With popularization of the zero defect industrial concept, identifying and measuring defective material in the early stage of production is of great interest to the industry. In the current market, many systems are able to achieve automatic monitoring and control of fabric, paper, and nonwoven material during the entire production process, however online measurement of hairiness is still an open topic and highly desirable for industrial applications. We propose a computer vision approach to compute epipole by using variable homography, which can be used to measure emergent fiber length on textile fabrics. The main challenges addressed in this paper are the application of variable homography on textile monitoring and measurement, as well as the accuracy of the estimated calculation. We propose that a fibrous structure can be considered as a two-layer structure, and then we show how variable homography combined with epipolar geometry can estimate the length of the fiber defects. Simulations are carried out to show the effectiveness of this method. The true length of selected fibers is measured precisely using a digital optical microscope, and then the same fibers are tested by our method. Our experimental results suggest that smoothness monitored by variable homography is an accurate and robust method of quality control for important industrial fabrics.
A QSAR Study of Environmental Estrogens Based on a Novel Variable Selection Method
Directory of Open Access Journals (Sweden)
Aiqian Zhang
2012-05-01
Full Text Available A large number of descriptors were employed to characterize the molecular structure of 53 natural, synthetic, and environmental chemicals which are suspected of disrupting endocrine functions by mimicking or antagonizing natural hormones and may thus pose a serious threat to the health of humans and wildlife. In this work, a robust quantitative structure-activity relationship (QSAR model with a novel variable selection method has been proposed for the effective estrogens. The variable selection method is based on variable interaction (VSMVI with leave-multiple-out cross validation (LMOCV to select the best subset. During variable selection, model construction and assessment, the Organization for Economic Co-operation and Development (OECD principles for regulation of QSAR acceptability were fully considered, such as using an unambiguous multiple-linear regression (MLR algorithm to build the model, using several validation methods to assessment the performance of the model, giving the define of applicability domain and analyzing the outliers with the results of molecular docking. The performance of the QSAR model indicates that the VSMVI is an effective, feasible and practical tool for rapid screening of the best subset from large molecular descriptors.
A Method of MPPT Control Based on Power Variable Step-size in Photovoltaic Converter System
Directory of Open Access Journals (Sweden)
Xu Hui-xiang
2016-01-01
Full Text Available Since the disadvantage of traditional MPPT algorithms of variable step-size, proposed power tracking based on variable step-size with the advantage method of the constant-voltage and the perturb-observe (P&O[1-3]. The control strategy modify the problem of voltage fluctuation caused by perturb-observe method, at the same time, introducing the advantage of constant-voltage method and simplify the circuit topology. With the theoretical derivation, control the output power of photovoltaic modules to change the duty cycle of main switch. Achieve the maximum power stabilization output, reduce the volatility of energy loss effectively, and improve the inversion efficiency[3,4]. Given the result of experimental test based theoretical derivation and the curve of MPPT when the prototype work.
International Nuclear Information System (INIS)
Xu, Yuenong; Smooke, M.D.
1993-01-01
In this paper we present a primitive variable Newton-based solution method with a block-line linear equation solver for the calculation of reacting flows. The present approach is compared with the stream function-vorticity Newton's method and the SIMPLER algorithm on the calculation of a system of fully elliptic equations governing an axisymmetric methane-air laminar diffusion flame. The chemical reaction is modeled by the flame sheet approximation. The numerical solution agrees well with experimental data in the major chemical species. The comparison of three sets of numerical results indicates that the stream function-vorticity solution using the approximate boundary conditions reported in the previous calculations predicts a longer flame length and a broader flame shape. With a new set of modified vorticity boundary conditions, we obtain agreement between the primitive variable and stream function-vorticity solutions. The primitive variable Newton's method converges much faster than the other two methods. Because of much less computer memory required for the block-line tridiagonal solver compared to a direct solver, the present approach makes it possible to calculate multidimensional flames with detailed reaction mechanisms. The SIMPLER algorithm shows a slow convergence rate compared to the other two methods in the present calculation
Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose
2018-06-01
An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.
Social Media Metrics Importance and Usage Frequency in Latvia
Directory of Open Access Journals (Sweden)
Ronalds Skulme
2017-12-01
Full Text Available Purpose of the article: The purpose of this paper was to explore which social media marketing metrics are most often used and are most important for marketing experts in Latvia and can be used to evaluate marketing campaign effectiveness. Methodology/methods: In order to achieve the aim of this paper several theoretical and practical research methods were used, such as theoretical literature analysis, surveying and grouping. First of all, theoretical research about social media metrics was conducted. Authors collected information about social media metric grouping methods and the most frequently mentioned social media metrics in the literature. The collected information was used as the foundation for the expert surveys. The expert surveys were used to collect information from Latvian marketing professionals to determine which social media metrics are used most often and which social media metrics are most important in Latvia. Scientific aim: The scientific aim of this paper was to identify if social media metrics importance varies depending on the consumer purchase decision stage. Findings: Information about the most important and most often used social media marketing metrics in Latvia was collected. A new social media grouping framework is proposed. Conclusions: The main conclusion is that the importance and the usage frequency of the social media metrics is changing depending of consumer purchase decisions stage the metric is used to evaluate.
Zwinderman, A. H.; Cleophas, T. J.
2005-01-01
BACKGROUND: Clinical investigators, although they are generally familiar with testing differences between averages, have difficulty testing differences between variabilities. OBJECTIVE: To give examples of situations where variability is more relevant than averages and to describe simple methods for
Selecting minimum dataset soil variables using PLSR as a regressive multivariate method
Stellacci, Anna Maria; Armenise, Elena; Castellini, Mirko; Rossi, Roberta; Vitti, Carolina; Leogrande, Rita; De Benedetto, Daniela; Ferrara, Rossana M.; Vivaldi, Gaetano A.
2017-04-01
Long-term field experiments and science-based tools that characterize soil status (namely the soil quality indices, SQIs) assume a strategic role in assessing the effect of agronomic techniques and thus in improving soil management especially in marginal environments. Selecting key soil variables able to best represent soil status is a critical step for the calculation of SQIs. Current studies show the effectiveness of statistical methods for variable selection to extract relevant information deriving from multivariate datasets. Principal component analysis (PCA) has been mainly used, however supervised multivariate methods and regressive techniques are progressively being evaluated (Armenise et al., 2013; de Paul Obade et al., 2016; Pulido Moncada et al., 2014). The present study explores the effectiveness of partial least square regression (PLSR) in selecting critical soil variables, using a dataset comparing conventional tillage and sod-seeding on durum wheat. The results were compared to those obtained using PCA and stepwise discriminant analysis (SDA). The soil data derived from a long-term field experiment in Southern Italy. On samples collected in April 2015, the following set of variables was quantified: (i) chemical: total organic carbon and nitrogen (TOC and TN), alkali-extractable C (TEC and humic substances - HA-FA), water extractable N and organic C (WEN and WEOC), Olsen extractable P, exchangeable cations, pH and EC; (ii) physical: texture, dry bulk density (BD), macroporosity (Pmac), air capacity (AC), and relative field capacity (RFC); (iii) biological: carbon of the microbial biomass quantified with the fumigation-extraction method. PCA and SDA were previously applied to the multivariate dataset (Stellacci et al., 2016). PLSR was carried out on mean centered and variance scaled data of predictors (soil variables) and response (wheat yield) variables using the PLS procedure of SAS/STAT. In addition, variable importance for projection (VIP
Read margin analysis of crossbar arrays using the cell-variability-aware simulation method
Sun, Wookyung; Choi, Sujin; Shin, Hyungsoon
2018-02-01
This paper proposes a new concept of read margin analysis of crossbar arrays using cell-variability-aware simulation. The size of the crossbar array should be considered to predict the read margin characteristic of the crossbar array because the read margin depends on the number of word lines and bit lines. However, an excessively high-CPU time is required to simulate large arrays using a commercial circuit simulator. A variability-aware MATLAB simulator that considers independent variability sources is developed to analyze the characteristics of the read margin according to the array size. The developed MATLAB simulator provides an effective method for reducing the simulation time while maintaining the accuracy of the read margin estimation in the crossbar array. The simulation is also highly efficient in analyzing the characteristic of the crossbar memory array considering the statistical variations in the cell characteristics.
Biological variables for the site survey of surface ecosystems - existing data and survey methods
International Nuclear Information System (INIS)
Kylaekorpi, Lasse; Berggren, Jens; Larsson, Mats; Liberg, Maria; Rydgren, Bernt
2000-06-01
In the process of selecting a safe and environmentally acceptable location for the deep level repository of nuclear waste, site surveys will be carried out. These site surveys will also include studies of the biota at the site, in order to assure that the chosen site will not conflict with important ecological interests, and to establish a thorough baseline for future impact assessments and monitoring programmes. As a preparation to the site survey programme, a review of the variables that need to be surveyed is conducted. This report contains the review for some of those variables. For each variable, existing data sources and their characteristics are listed. For those variables for which existing data sources are inadequate, suggestions are made for appropriate methods that will enable the establishment of an acceptable baseline. In this report the following variables are reviewed: Fishery, Landscape, Vegetation types, Key biotopes, Species (flora and fauna), Red-listed species (flora and fauna), Biomass (flora and fauna), Water level, water retention time (incl. water body and flow), Nutrients/toxins, Oxygen concentration, Layering, stratification, Light conditions/transparency, Temperature, Sediment transport, (Marine environments are excluded from this review). For a major part of the variables, the existing data coverage is most likely insufficient. Both the temporal and/or the geographical resolution is often limited, which means that complementary surveys must be performed during (or before) the site surveys. It is, however, in general difficult to make exact judgements on the extent of existing data, and also to give suggestions for relevant methods to use in the site surveys. This can be finally decided only when the locations for the sites are decided upon. The relevance of the different variables also depends on the environmental characteristics of the sites. Therefore, we suggest that when the survey sites are selected, an additional review is
Biological variables for the site survey of surface ecosystems - existing data and survey methods
Energy Technology Data Exchange (ETDEWEB)
Kylaekorpi, Lasse; Berggren, Jens; Larsson, Mats; Liberg, Maria; Rydgren, Bernt [SwedPower AB, Stockholm (Sweden)
2000-06-01
In the process of selecting a safe and environmentally acceptable location for the deep level repository of nuclear waste, site surveys will be carried out. These site surveys will also include studies of the biota at the site, in order to assure that the chosen site will not conflict with important ecological interests, and to establish a thorough baseline for future impact assessments and monitoring programmes. As a preparation to the site survey programme, a review of the variables that need to be surveyed is conducted. This report contains the review for some of those variables. For each variable, existing data sources and their characteristics are listed. For those variables for which existing data sources are inadequate, suggestions are made for appropriate methods that will enable the establishment of an acceptable baseline. In this report the following variables are reviewed: Fishery, Landscape, Vegetation types, Key biotopes, Species (flora and fauna), Red-listed species (flora and fauna), Biomass (flora and fauna), Water level, water retention time (incl. water body and flow), Nutrients/toxins, Oxygen concentration, Layering, stratification, Light conditions/transparency, Temperature, Sediment transport, (Marine environments are excluded from this review). For a major part of the variables, the existing data coverage is most likely insufficient. Both the temporal and/or the geographical resolution is often limited, which means that complementary surveys must be performed during (or before) the site surveys. It is, however, in general difficult to make exact judgements on the extent of existing data, and also to give suggestions for relevant methods to use in the site surveys. This can be finally decided only when the locations for the sites are decided upon. The relevance of the different variables also depends on the environmental characteristics of the sites. Therefore, we suggest that when the survey sites are selected, an additional review is
International Nuclear Information System (INIS)
Nanty, Simon
2015-01-01
This work relates to the framework of uncertainty quantification for numerical simulators, and more precisely studies two industrial applications linked to the safety studies of nuclear plants. These two applications have several common features. The first one is that the computer code inputs are functional and scalar variables, functional ones being dependent. The second feature is that the probability distribution of functional variables is known only through a sample of their realizations. The third feature, relative to only one of the two applications, is the high computational cost of the code, which limits the number of possible simulations. The main objective of this work was to propose a complete methodology for the uncertainty analysis of numerical simulators for the two considered cases. First, we have proposed a methodology to quantify the uncertainties of dependent functional random variables from a sample of their realizations. This methodology enables to both model the dependency between variables and their link to another variable, called co-variate, which could be, for instance, the output of the considered code. Then, we have developed an adaptation of a visualization tool for functional data, which enables to simultaneously visualize the uncertainties and features of dependent functional variables. Second, a method to perform the global sensitivity analysis of the codes used in the two studied cases has been proposed. In the case of a computationally demanding code, the direct use of quantitative global sensitivity analysis methods is intractable. To overcome this issue, the retained solution consists in building a surrogate model or meta model, a fast-running model approximating the computationally expensive code. An optimized uniform sampling strategy for scalar and functional variables has been developed to build a learning basis for the meta model. Finally, a new approximation approach for expensive codes with functional outputs has been
Propulsion and launching analysis of variable-mass rockets by analytical methods
Directory of Open Access Journals (Sweden)
D.D. Ganji
2013-09-01
Full Text Available In this study, applications of some analytical methods on nonlinear equation of the launching of a rocket with variable mass are investigated. Differential transformation method (DTM, homotopy perturbation method (HPM and least square method (LSM were applied and their results are compared with numerical solution. An excellent agreement with analytical methods and numerical ones is observed in the results and this reveals that analytical methods are effective and convenient. Also a parametric study is performed here which includes the effect of exhaust velocity (Ce, burn rate (BR of fuel and diameter of cylindrical rocket (d on the motion of a sample rocket, and contours for showing the sensitivity of these parameters are plotted. The main results indicate that the rocket velocity and altitude are increased with increasing the Ce and BR and decreased with increasing the rocket diameter and drag coefficient.
A Review of Spectral Methods for Variable Amplitude Fatigue Prediction and New Results
Larsen, Curtis E.; Irvine, Tom
2013-01-01
A comprehensive review of the available methods for estimating fatigue damage from variable amplitude loading is presented. The dependence of fatigue damage accumulation on power spectral density (psd) is investigated for random processes relevant to real structures such as in offshore or aerospace applications. Beginning with the Rayleigh (or narrow band) approximation, attempts at improved approximations or corrections to the Rayleigh approximation are examined by comparison to rainflow analysis of time histories simulated from psd functions representative of simple theoretical and real world applications. Spectral methods investigated include corrections by Wirsching and Light, Ortiz and Chen, the Dirlik formula, and the Single-Moment method, among other more recent proposed methods. Good agreement is obtained between the spectral methods and the time-domain rainflow identification for most cases, with some limitations. Guidelines are given for using the several spectral methods to increase confidence in the damage estimate.
Learning Low-Dimensional Metrics
Jain, Lalit; Mason, Blake; Nowak, Robert
2017-01-01
This paper investigates the theoretical foundations of metric learning, focused on three key questions that are not fully addressed in prior work: 1) we consider learning general low-dimensional (low-rank) metrics as well as sparse metrics; 2) we develop upper and lower (minimax)bounds on the generalization error; 3) we quantify the sample complexity of metric learning in terms of the dimension of the feature space and the dimension/rank of the underlying metric;4) we also bound the accuracy ...
The Leech method for diagnosing constipation: intra- and interobserver variability and accuracy
Energy Technology Data Exchange (ETDEWEB)
Lorijn, Fleur de; Voskuijl, Wieger P.; Taminiau, Jan A.; Benninga, Marc A. [Emma Children' s Hospital, Department of Paediatric Gastroenterology and Nutrition, Amsterdam (Netherlands); Rijn, Rick R. van; Henneman, Onno D.F. [Academic Medical Centre, Department of Radiology, Amsterdam (Netherlands); Heijmans, Jarom [Emma Children' s Hospital, Department of Paediatric Gastroenterology and Nutrition, Amsterdam (Netherlands); Academic Medical Centre, Department of Radiology, Amsterdam (Netherlands); Reitsma, Johannes B. [Academic Medical Centre, Department of Clinical Epidemiology and Biostatistics, Amsterdam (Netherlands)
2006-01-01
The data concerning the value of a plain abdominal radiograph in childhood constipation are inconsistent. Recently, positive results have been reported of a new radiographic scoring system, ''the Leech method'', for assessing faecal loading. To assess intra- and interobserver variability and determine diagnostic accuracy of the Leech method in identifying children with functional constipation (FC). A total of 89 children (median age 9.8 years) with functional gastrointestinal disorders were included in the study. Based on clinical parameters, 52 fulfilled the criteria for FC, six fulfilled the criteria for functional abdominal pain (FAP), and 31 for functional non-retentive faecal incontinence (FNRFI); the latter two groups provided the controls. To assess intra- and interobserver variability of the Leech method three scorers scored the same abdominal radiograph twice. A Leech score of 9 or more was considered as suggestive of constipation. ROC analysis was used to determine the diagnostic accuracy of the Leech method in separating patients with FC from control patients. Significant intraobserver variability was found between two scorers (P=0.005 and P<0.0001), whereas there was no systematic difference between the two scores of the other scorer (P=0.89). The scores between scorers differed systematically and displayed large variability. The area under the ROC curve was 0.68 (95% CI 0.58-0.80), indicating poor diagnostic accuracy. The Leech scoring method for assessing faecal loading on a plain abdominal radiograph is of limited value in the diagnosis of FC in children. (orig.)
Use of a variable tracer infusion method to determine glucose turnover in humans
International Nuclear Information System (INIS)
Molina, J.M.; Baron, A.D.; Edelman, S.V.; Brechtel, G.; Wallace, P.; Olefsky, J.M.
1990-01-01
The single-compartment pool fraction model, when used with the hyperinsulinemic glucose clamp technique to measure rates of glucose turnover, sometimes underestimates true rates of glucose appearance (Ra) resulting in negative values for hepatic glucose output (HGO). We focused our attention on isotope discrimination and model error as possible explanations for this underestimation. We found no difference in [3-3H] glucose specific activity in samples obtained simultaneously from the femoral artery and vein (2,400 +/- 455 vs. 2,454 +/- 522 dpm/mg) in 6 men during a hyperinsulinemic euglycemic clamp study where insulin was infused at 40 mU.m-2.min-1 for 3 h; therefore, isotope discrimination did not occur. We compared the ability of a constant (0.6 microCi/min) vs. variable tracer infusion method (tracer added to the glucose infusate) to measure non-steady-state Ra during hyperinsulinemic clamp studies. Plasma specific activity fell during the constant tracer infusion studies but did not change from base line during the variable tracer infusion studies. By maintaining a constant plasma specific activity the variable tracer infusion method eliminates uncertainty about changes in glucose pool size. This overcame modeling error and more accurately measures non-steady-state Ra (P less than 0.001 by analysis of variance vs. constant infusion method). In conclusion, underestimation of Ra determined isotopically during hyperinsulinemic clamp studies is largely due to modeling error that can be overcome by use of the variable tracer infusion method. This method allows more accurate determination of Ra and HGO under non-steady-state conditions
The relationship between glass ceiling and power distance as a cultural variable by a new method
Directory of Open Access Journals (Sweden)
Naide Jahangirov
2015-12-01
Full Text Available Glass ceiling symbolizes a variety of barriers and obstacles that arise from gender inequality at business life. With this mind, culture influences gender dynamics. The purpose of this research was to examine the relationship between the glass ceiling and the power distance as a cultural variable within organizations. Gender variable is taken as a moderator variable in relationship between the concepts. In addition to conventional correlation analysis, we employed a new method to investigate this relationship in detail. The survey data were obtained from 109 people working at a research center which operated as a part of the non-profit private university in Ankara, Turkey. The relationship between the variables was revealed by a new method which was developed as an addition to the correlation in survey. The analysis revealed that the female staff perceived the glass ceiling and the power distance more intensely than the male staff. In addition, the medium level relation was determined between the power distance and the glass ceiling perception among female staff.
Improved flux calculations for viscous incompressible flow by the variable penalty method
International Nuclear Information System (INIS)
Kheshgi, H.; Luskin, M.
1985-01-01
The Navier-Stokes system for viscous, incompressible flow is considered, taking into account a replacement of the continuity equation by the perturbed continuity equation. The introduction of the approximation allows the pressure variable to be eliminated to obtain the system of equations for the approximate velocity. The penalty approximation is often applied to numerical discretizations since it provides a reduction in the size and band-width of the system of equations. Attention is given to error estimates, and to two numerical experiments which illustrate the error estimates considered. It is found that the variable penalty method provides an accurate solution for a much wider range of epsilon than the classical penalty method. 8 references
Directory of Open Access Journals (Sweden)
Hongfen Gao
2014-01-01
Full Text Available This paper describes the application of the complex variable meshless manifold method (CVMMM to stress intensity factor analyses of structures containing interface cracks between dissimilar materials. A discontinuous function and the near-tip asymptotic displacement functions are added to the CVMMM approximation using the framework of complex variable moving least-squares (CVMLS approximation. This enables the domain to be modeled by CVMMM without explicitly meshing the crack surfaces. The enriched crack-tip functions are chosen as those that span the asymptotic displacement fields for an interfacial crack. The complex stress intensity factors for bimaterial interfacial cracks were numerically evaluated using the method. Good agreement between the numerical results and the reference solutions for benchmark interfacial crack problems is realized.
A new hydraulic regulation method on district heating system with distributed variable-speed pumps
International Nuclear Information System (INIS)
Wang, Hai; Wang, Haiying; Zhu, Tong
2017-01-01
Highlights: • A hydraulic regulation method was presented for district heating with distributed variable speed pumps. • Information and automation technologies were utilized to support the proposed method. • A new hydraulic model was developed for distributed variable speed pumps. • A new optimization model was developed based on genetic algorithm. • Two scenarios of a multi-source looped system was illustrated to validate the method. - Abstract: Compared with the hydraulic configuration based on the conventional central circulating pump, a district heating system with distributed variable-speed-pumps configuration can often save 30–50% power consumption on circulating pumps with frequency inverters. However, the hydraulic regulations on distributed variable-speed-pumps configuration could be more complicated than ever while all distributed pumps need to be adjusted to their designated flow rates. Especially in a multi-source looped structure heating network where the distributed pumps have strongly coupled and severe non-linear hydraulic connections with each other, it would be rather difficult to maintain the hydraulic balance during the regulations. In this paper, with the help of the advanced automation and information technologies, a new hydraulic regulation method was proposed to achieve on-site hydraulic balance for the district heating systems with distributed variable-speed-pumps configuration. The proposed method was comprised of a new hydraulic model, which was developed to adapt the distributed variable-speed-pumps configuration, and a calibration model with genetic algorithm. By carrying out the proposed method step by step, the flow rates of all distributed pumps can be progressively adjusted to their designated values. A hypothetic district heating system with 2 heat sources and 10 substations was taken as a case study to illustrate the feasibility of the proposed method. Two scenarios were investigated respectively. In Scenario I, the
Yoshida, Yutaka; Yokoyama, Kiyoko; Ishii, Naohiro
It is necessary to monitor the daily health condition for preventing stress syndrome. In this study, it was proposed the method assessing the mental and physiological condition, such as the work stress or the relaxation, using heart rate variability at real time and continuously. The instantanuous heart rate (HR), and the ratio of the number of extreme points (NEP) and the number of heart beats were calculated for assessing mental and physiological condition. In this method, 20 beats heart rate were used to calculate these indexes. These were calculated in one beat interval. Three conditions, which are sitting rest, performing mental arithmetic and watching relaxation movie, were assessed using our proposed algorithm. The assessment accuracies were 71.9% and 55.8%, when performing mental arithmetic and watching relaxation movie respectively. In this method, the mental and physiological condition was assessed using only 20 regressive heart beats, so this method is considered as the real time assessment method.
Directory of Open Access Journals (Sweden)
Mário Mestria
2013-08-01
Full Text Available The Clustered Traveling Salesman Problem (CTSP is a generalization of the Traveling Salesman Problem (TSP in which the set of vertices is partitioned into disjoint clusters and objective is to find a minimum cost Hamiltonian cycle such that the vertices of each cluster are visited contiguously. The CTSP is NP-hard and, in this context, we are proposed heuristic methods for the CTSP using GRASP, Path Relinking and Variable Neighborhood Descent (VND. The heuristic methods were tested using Euclidean instances with up to 2000 vertices and clusters varying between 4 to 150 vertices. The computational tests were performed to compare the performance of the heuristic methods with an exact algorithm using the Parallel CPLEX software. The computational results showed that the hybrid heuristic method using VND outperforms other heuristic methods.
Locating disease genes using Bayesian variable selection with the Haseman-Elston method
Directory of Open Access Journals (Sweden)
He Qimei
2003-12-01
Full Text Available Abstract Background We applied stochastic search variable selection (SSVS, a Bayesian model selection method, to the simulated data of Genetic Analysis Workshop 13. We used SSVS with the revisited Haseman-Elston method to find the markers linked to the loci determining change in cholesterol over time. To study gene-gene interaction (epistasis and gene-environment interaction, we adopted prior structures, which incorporate the relationship among the predictors. This allows SSVS to search in the model space more efficiently and avoid the less likely models. Results In applying SSVS, instead of looking at the posterior distribution of each of the candidate models, which is sensitive to the setting of the prior, we ranked the candidate variables (markers according to their marginal posterior probability, which was shown to be more robust to the prior. Compared with traditional methods that consider one marker at a time, our method considers all markers simultaneously and obtains more favorable results. Conclusions We showed that SSVS is a powerful method for identifying linked markers using the Haseman-Elston method, even for weak effects. SSVS is very effective because it does a smart search over the entire model space.
Method of nuclear reactor control using a variable temperature load dependent set point
International Nuclear Information System (INIS)
Kelly, J.J.; Rambo, G.E.
1982-01-01
A method and apparatus for controlling a nuclear reactor in response to a variable average reactor coolant temperature set point is disclosed. The set point is dependent upon percent of full power load demand. A manually-actuated ''droop mode'' of control is provided whereby the reactor coolant temperature is allowed to drop below the set point temperature a predetermined amount wherein the control is switched from reactor control rods exclusively to feedwater flow
Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis
Directory of Open Access Journals (Sweden)
Ueki Masao
2012-05-01
Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.
Cumulative Mass and NIOSH Variable Lifting Index Method for Risk Assessment: Possible Relations.
Stucchi, Giulia; Battevi, Natale; Pandolfi, Monica; Galinotti, Luca; Iodice, Simona; Favero, Chiara
2018-02-01
Objective The aim of this study was to explore whether the Variable Lifting Index (VLI) can be corrected for cumulative mass and thus test its efficacy in predicting the risk of low-back pain (LBP). Background A validation study of the VLI method was published in this journal reporting promising results. Although several studies highlighted a positive correlation between cumulative load and LBP, cumulative mass has never been considered in any of the studies investigating the relationship between manual material handling and LBP. Method Both VLI and cumulative mass were calculated for 2,374 exposed subjects using a systematic approach. Due to high variability of cumulative mass values, a stratification within VLI categories was employed. Dummy variables (1-4) were assigned to each class and used as a multiplier factor for the VLI, resulting in a new index (VLI_CMM). Data on LBP were collected by occupational physicians at the study sites. Logistic regression was used to estimate the risk of acute LBP within levels of risk exposure when compared with a control group formed by 1,028 unexposed subjects. Results Data showed greatly variable values of cumulative mass across all VLI classes. The potential effect of cumulative mass on damage emerged as not significant ( p value = .6526). Conclusion When comparing VLI_CMM with raw VLI, the former failed to prove itself as a better predictor of LBP risk. Application To recognize cumulative mass as a modifier, especially for lumbar degenerative spine diseases, authors of future studies should investigate potential association between the VLI and other damage variables.
Energy Technology Data Exchange (ETDEWEB)
Price, Phillip N.; Granderson, Jessica; Sohn, Michael; Addy, Nathan; Jump, David
2013-09-01
whose savings can be calculated with least error? 4. What is the state of public domain models, that is, how well do they perform, and what are the associated implications for whole-building measurement and verification (M&V)? Additional project objectives that were addressed as part of this study include: (1) clarification of the use cases and conditions for baseline modeling performance metrics, benchmarks and evaluation criteria, (2) providing guidance for determining customer suitability for baseline modeling, (3) describing the portfolio level effects of baseline model estimation errors, (4) informing PG&E’s development of EMIS technology product specifications, and (5) providing the analytical foundation for future studies about baseline modeling and saving effects of EMIS technologies. A final objective of this project was to demonstrate the application of the methodology, performance metrics, and test protocols with participating EMIS product vendors.
Method of collective variables with reference system for the grand canonical ensemble
International Nuclear Information System (INIS)
Yukhnovskii, I.R.
1989-01-01
A method of collective variables with special reference system for the grand canonical ensemble is presented. An explicit form is obtained for the basis sixth-degree measure density needed to describe the liquid-gas phase transition. Here the author presents the fundamentals of the method, which are as follows: (1) the functional form for the partition function in the grand canonical ensemble; (2) derivation of thermodynamic relations for the coefficients of the Jacobian; (3) transition to the problem on an adequate lattice; and (4) obtaining of the explicit form for the functional of the partition function
Application of Muskingum routing method with variable parameters in ungauged basin
Directory of Open Access Journals (Sweden)
Xiao-meng Song
2011-03-01
Full Text Available This paper describes a flood routing method applied in an ungauged basin, utilizing the Muskingum model with variable parameters of wave travel time K and weight coefficient of discharge x based on the physical characteristics of the river reach and flood, including the reach slope, length, width, and flood discharge. Three formulas for estimating parameters of wide rectangular, triangular, and parabolic cross sections are proposed. The influence of the flood on channel flow routing parameters is taken into account. The HEC-HMS hydrological model and the geospatial hydrologic analysis module HEC-GeoHMS were used to extract channel or watershed characteristics and to divide sub-basins. In addition, the initial and constant-rate method, user synthetic unit hydrograph method, and exponential recession method were used to estimate runoff volumes, the direct runoff hydrograph, and the baseflow hydrograph, respectively. The Muskingum model with variable parameters was then applied in the Louzigou Basin in Henan Province of China, and of the results, the percentages of flood events with a relative error of peak discharge less than 20% and runoff volume less than 10% are both 100%. They also show that the percentages of flood events with coefficients of determination greater than 0.8 are 83.33%, 91.67%, and 87.5%, respectively, for rectangular, triangular, and parabolic cross sections in 24 flood events. Therefore, this method is applicable to ungauged basins.
Metrics with vanishing quantum corrections
International Nuclear Information System (INIS)
Coley, A A; Hervik, S; Gibbons, G W; Pope, C N
2008-01-01
We investigate solutions of the classical Einstein or supergravity equations that solve any set of quantum corrected Einstein equations in which the Einstein tensor plus a multiple of the metric is equated to a symmetric conserved tensor T μν (g αβ , ∂ τ g αβ , ∂ τ ∂ σ g αβ , ...,) constructed from sums of terms, the involving contractions of the metric and powers of arbitrary covariant derivatives of the curvature tensor. A classical solution, such as an Einstein metric, is called universal if, when evaluated on that Einstein metric, T μν is a multiple of the metric. A Ricci flat classical solution is called strongly universal if, when evaluated on that Ricci flat metric, T μν vanishes. It is well known that pp-waves in four spacetime dimensions are strongly universal. We focus attention on a natural generalization; Einstein metrics with holonomy Sim(n - 2) in which all scalar invariants are zero or constant. In four dimensions we demonstrate that the generalized Ghanam-Thompson metric is weakly universal and that the Goldberg-Kerr metric is strongly universal; indeed, we show that universality extends to all four-dimensional Sim(2) Einstein metrics. We also discuss generalizations to higher dimensions
Sharp metric obstructions for quasi-Einstein metrics
Case, Jeffrey S.
2013-02-01
Using the tractor calculus to study smooth metric measure spaces, we adapt results of Gover and Nurowski to give sharp metric obstructions to the existence of quasi-Einstein metrics on suitably generic manifolds. We do this by introducing an analogue of the Weyl tractor W to the setting of smooth metric measure spaces. The obstructions we obtain can be realized as tensorial invariants which are polynomial in the Riemann curvature tensor and its divergence. By taking suitable limits of their tensorial forms, we then find obstructions to the existence of static potentials, generalizing to higher dimensions a result of Bartnik and Tod, and to the existence of potentials for gradient Ricci solitons.
Houston, Lauren; Probst, Yasmine; Martin, Allison
2018-05-18
Data audits within clinical settings are extensively used as a major strategy to identify errors, monitor study operations and ensure high-quality data. However, clinical trial guidelines are non-specific in regards to recommended frequency, timing and nature of data audits. The absence of a well-defined data quality definition and method to measure error undermines the reliability of data quality assessment. This review aimed to assess the variability of source data verification (SDV) auditing methods to monitor data quality in a clinical research setting. The scientific databases MEDLINE, Scopus and Science Direct were searched for English language publications, with no date limits applied. Studies were considered if they included data from a clinical trial or clinical research setting and measured and/or reported data quality using a SDV auditing method. In total 15 publications were included. The nature and extent of SDV audit methods in the articles varied widely, depending upon the complexity of the source document, type of study, variables measured (primary or secondary), data audit proportion (3-100%) and collection frequency (6-24 months). Methods for coding, classifying and calculating error were also inconsistent. Transcription errors and inexperienced personnel were the main source of reported error. Repeated SDV audits using the same dataset demonstrated ∼40% improvement in data accuracy and completeness over time. No description was given in regards to what determines poor data quality in clinical trials. A wide range of SDV auditing methods are reported in the published literature though no uniform SDV auditing method could be determined for "best practice" in clinical trials. Published audit methodology articles are warranted for the development of a standardised SDV auditing method to monitor data quality in clinical research settings. Copyright © 2018. Published by Elsevier Inc.
Objectively Quantifying Radiation Esophagitis With Novel Computed Tomography–Based Metrics
Energy Technology Data Exchange (ETDEWEB)
Niedzielski, Joshua S., E-mail: jsniedzielski@mdanderson.org [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States); Yang, Jinzhong [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States); Stingo, Francesco [Department of Biostatistics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); Martel, Mary K.; Mohan, Radhe [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States); Gomez, Daniel R. [Department of Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); Briere, Tina M. [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States); Liao, Zhongxing [Department of Radiation Oncology, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); Court, Laurence E. [Department of Radiation Physics, The University of Texas M. D. Anderson Cancer Center, Houston, Texas (United States); University of Texas Houston Graduate School of Biomedical Science, Houston, Texas (United States)
2016-02-01
Purpose: To study radiation-induced esophageal expansion as an objective measure of radiation esophagitis in patients with non-small cell lung cancer (NSCLC) treated with intensity modulated radiation therapy. Methods and Materials: Eighty-five patients had weekly intra-treatment CT imaging and esophagitis scoring according to Common Terminlogy Criteria for Adverse Events 4.0, (24 Grade 0, 45 Grade 2, and 16 Grade 3). Nineteen esophageal expansion metrics based on mean, maximum, spatial length, and volume of expansion were calculated as voxel-based relative volume change, using the Jacobian determinant from deformable image registration between the planning and weekly CTs. An anatomic variability correction method was validated and applied to these metrics to reduce uncertainty. An analysis of expansion metrics and radiation esophagitis grade was conducted using normal tissue complication probability from univariate logistic regression and Spearman rank for grade 2 and grade 3 esophagitis endpoints, as well as the timing of expansion and esophagitis grade. Metrics' performance in classifying esophagitis was tested with receiver operating characteristic analysis. Results: Expansion increased with esophagitis grade. Thirteen of 19 expansion metrics had receiver operating characteristic area under the curve values >0.80 for both grade 2 and grade 3 esophagitis endpoints, with the highest performance from maximum axial expansion (MaxExp1) and esophageal length with axial expansion ≥30% (LenExp30%) with area under the curve values of 0.93 and 0.91 for grade 2, 0.90 and 0.90 for grade 3 esophagitis, respectively. Conclusions: Esophageal expansion may be a suitable objective measure of esophagitis, particularly maximum axial esophageal expansion and esophageal length with axial expansion ≥30%, with 2.1 Jacobian value and 98.6 mm as the metric value for 50% probability of grade 3 esophagitis. The uncertainty in esophageal Jacobian calculations can be reduced
Objectively Quantifying Radiation Esophagitis With Novel Computed Tomography–Based Metrics
International Nuclear Information System (INIS)
Niedzielski, Joshua S.; Yang, Jinzhong; Stingo, Francesco; Martel, Mary K.; Mohan, Radhe; Gomez, Daniel R.; Briere, Tina M.; Liao, Zhongxing; Court, Laurence E.
2016-01-01
Purpose: To study radiation-induced esophageal expansion as an objective measure of radiation esophagitis in patients with non-small cell lung cancer (NSCLC) treated with intensity modulated radiation therapy. Methods and Materials: Eighty-five patients had weekly intra-treatment CT imaging and esophagitis scoring according to Common Terminlogy Criteria for Adverse Events 4.0, (24 Grade 0, 45 Grade 2, and 16 Grade 3). Nineteen esophageal expansion metrics based on mean, maximum, spatial length, and volume of expansion were calculated as voxel-based relative volume change, using the Jacobian determinant from deformable image registration between the planning and weekly CTs. An anatomic variability correction method was validated and applied to these metrics to reduce uncertainty. An analysis of expansion metrics and radiation esophagitis grade was conducted using normal tissue complication probability from univariate logistic regression and Spearman rank for grade 2 and grade 3 esophagitis endpoints, as well as the timing of expansion and esophagitis grade. Metrics' performance in classifying esophagitis was tested with receiver operating characteristic analysis. Results: Expansion increased with esophagitis grade. Thirteen of 19 expansion metrics had receiver operating characteristic area under the curve values >0.80 for both grade 2 and grade 3 esophagitis endpoints, with the highest performance from maximum axial expansion (MaxExp1) and esophageal length with axial expansion ≥30% (LenExp30%) with area under the curve values of 0.93 and 0.91 for grade 2, 0.90 and 0.90 for grade 3 esophagitis, respectively. Conclusions: Esophageal expansion may be a suitable objective measure of esophagitis, particularly maximum axial esophageal expansion and esophageal length with axial expansion ≥30%, with 2.1 Jacobian value and 98.6 mm as the metric value for 50% probability of grade 3 esophagitis. The uncertainty in esophageal Jacobian calculations can be reduced
Completion of a Dislocated Metric Space
Directory of Open Access Journals (Sweden)
P. Sumati Kumari
2015-01-01
Full Text Available We provide a construction for the completion of a dislocated metric space (abbreviated d-metric space; we also prove that the completion of the metric associated with a d-metric coincides with the metric associated with the completion of the d-metric.
Evaluation metrics for biostatistical and epidemiological collaborations.
Rubio, Doris McGartland; Del Junco, Deborah J; Bhore, Rafia; Lindsell, Christopher J; Oster, Robert A; Wittkowski, Knut M; Welty, Leah J; Li, Yi-Ju; Demets, Dave
2011-10-15
Increasing demands for evidence-based medicine and for the translation of biomedical research into individual and public health benefit have been accompanied by the proliferation of special units that offer expertise in biostatistics, epidemiology, and research design (BERD) within academic health centers. Objective metrics that can be used to evaluate, track, and improve the performance of these BERD units are critical to their successful establishment and sustainable future. To develop a set of reliable but versatile metrics that can be adapted easily to different environments and evolving needs, we consulted with members of BERD units from the consortium of academic health centers funded by the Clinical and Translational Science Award Program of the National Institutes of Health. Through a systematic process of consensus building and document drafting, we formulated metrics that covered the three identified domains of BERD practices: the development and maintenance of collaborations with clinical and translational science investigators, the application of BERD-related methods to clinical and translational research, and the discovery of novel BERD-related methodologies. In this article, we describe the set of metrics and advocate their use for evaluating BERD practices. The routine application, comparison of findings across diverse BERD units, and ongoing refinement of the metrics will identify trends, facilitate meaningful changes, and ultimately enhance the contribution of BERD activities to biomedical research. Copyright © 2011 John Wiley & Sons, Ltd.
Modeling the solute transport by particle-tracing method with variable weights
Jiang, J.
2016-12-01
Particle-tracing method is usually used to simulate the solute transport in fracture media. In this method, the concentration at one point is proportional to number of particles visiting this point. However, this method is rather inefficient at the points with small concentration. Few particles visit these points, which leads to violent oscillation or gives zero value of concentration. In this paper, we proposed a particle-tracing method with variable weights. The concentration at one point is proportional to the sum of the weights of the particles visiting it. It adjusts the weight factors during simulations according to the estimated probabilities of corresponding walks. If the weight W of a tracking particle is larger than the relative concentration C at the corresponding site, the tracking particle will be splitted into Int(W/C) copies and each copy will be simulated independently with the weight W/Int(W/C) . If the weight W of a tracking particle is less than the relative concentration C at the corresponding site, the tracking particle will be continually tracked with a probability W/C and the weight will be adjusted to be C. By adjusting weights, the number of visiting particles distributes evenly in the whole range. Through this variable weights scheme, we can eliminate the violent oscillation and increase the accuracy of orders of magnitudes.
Metric adjusted skew information
DEFF Research Database (Denmark)
Hansen, Frank
2008-01-01
) that vanishes for observables commuting with the state. We show that the skew information is a convex function on the manifold of states. It also satisfies other requirements, proposed by Wigner and Yanase, for an effective measure-of-information content of a state relative to a conserved observable. We...... establish a connection between the geometrical formulation of quantum statistics as proposed by Chentsov and Morozova and measures of quantum information as introduced by Wigner and Yanase and extended in this article. We show that the set of normalized Morozova-Chentsov functions describing the possible......We extend the concept of Wigner-Yanase-Dyson skew information to something we call "metric adjusted skew information" (of a state with respect to a conserved observable). This "skew information" is intended to be a non-negative quantity bounded by the variance (of an observable in a state...
Directory of Open Access Journals (Sweden)
Mohammad Hadi Jalali
2018-01-01
Full Text Available Elastic stress analysis of rotating variable thickness annular disk made of functionally graded material (FGM is presented. Elasticity modulus, density, and thickness of the disk are assumed to vary radially according to a power-law function. Radial stress, circumferential stress, and radial deformation of the rotating FG annular disk of variable thickness with clamped-clamped (C-C, clamped-free (C-F, and free-free (F-F boundary conditions are obtained using the numerical finite difference method, and the effects of the graded index, thickness variation, and rotating speed on the stresses and deformation are evaluated. It is shown that using FG material could decrease the value of radial stress and increase the radial displacement in a rotating thin disk. It is also demonstrated that increasing the rotating speed can strongly increase the stress in the FG annular disk.
Assessing Software Quality Through Visualised Cohesion Metrics
Directory of Open Access Journals (Sweden)
Timothy Shih
2001-05-01
Full Text Available Cohesion is one of the most important factors for software quality as well as maintainability, reliability and reusability. Module cohesion is defined as a quality attribute that seeks for measuring the singleness of the purpose of a module. The module of poor quality can be a serious obstacle to the system quality. In order to design a good software quality, software managers and engineers need to introduce cohesion metrics to measure and produce desirable software. A highly cohesion software is thought to be a desirable constructing. In this paper, we propose a function-oriented cohesion metrics based on the analysis of live variables, live span and the visualization of processing element dependency graph. We give six typical cohesion examples to be measured as our experiments and justification. Therefore, a well-defined, well-normalized, well-visualized and well-experimented cohesion metrics is proposed to indicate and thus enhance software cohesion strength. Furthermore, this cohesion metrics can be easily incorporated with software CASE tool to help software engineers to improve software quality.
Metric Learning for Hyperspectral Image Segmentation
Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca
2011-01-01
We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.
Software quality metrics aggregation in industry
Mordal, K.; Anquetil, N.; Laval, J.; Serebrenik, A.; Vasilescu, B.N.; Ducasse, S.
2013-01-01
With the growing need for quality assessment of entire software systems in the industry, new issues are emerging. First, because most software quality metrics are defined at the level of individual software components, there is a need for aggregation methods to summarize the results at the system
Metric approach to quantum constraints
International Nuclear Information System (INIS)
Brody, Dorje C; Hughston, Lane P; Gustavsson, Anna C T
2009-01-01
A framework for deriving equations of motion for constrained quantum systems is introduced and a procedure for its implementation is outlined. In special cases, the proposed new method, which takes advantage of the fact that the space of pure states in quantum mechanics has both a symplectic structure and a metric structure, reduces to a quantum analogue of the Dirac theory of constraints in classical mechanics. Explicit examples involving spin-1/2 particles are worked out in detail: in the first example, our approach coincides with a quantum version of the Dirac formalism, while the second example illustrates how a situation that cannot be treated by Dirac's approach can nevertheless be dealt with in the present scheme.
The metric system: An introduction
Energy Technology Data Exchange (ETDEWEB)
Lumley, S.M.
1995-05-01
On July 13, 1992, Deputy Director Duane Sewell restated the Laboratory`s policy on conversion to the metric system which was established in 1974. Sewell`s memo announced the Laboratory`s intention to continue metric conversion on a reasonable and cost effective basis. Copies of the 1974 and 1992 Administrative Memos are contained in the Appendix. There are three primary reasons behind the Laboratory`s conversion to the metric system. First, Public Law 100-418, passed in 1988, states that by the end of fiscal year 1992 the Federal Government must begin using metric units in grants, procurements, and other business transactions. Second, on July 25, 1991, President George Bush signed Executive Order 12770 which urged Federal agencies to expedite conversion to metric units. Third, the contract between the University of California and the Department of Energy calls for the Laboratory to convert to the metric system. Thus, conversion to the metric system is a legal requirement and a contractual mandate with the University of California. Public Law 100-418 and Executive Order 12770 are discussed in more detail later in this section, but first they examine the reasons behind the nation`s conversion to the metric system. The second part of this report is on applying the metric system.
Attack-Resistant Trust Metrics
Levien, Raph
The Internet is an amazingly powerful tool for connecting people together, unmatched in human history. Yet, with that power comes great potential for spam and abuse. Trust metrics are an attempt to compute the set of which people are trustworthy and which are likely attackers. This chapter presents two specific trust metrics developed and deployed on the Advogato Website, which is a community blog for free software developers. This real-world experience demonstrates that the trust metrics fulfilled their goals, but that for good results, it is important to match the assumptions of the abstract trust metric computation to the real-world implementation.
The metric system: An introduction
Lumley, Susan M.
On 13 Jul. 1992, Deputy Director Duane Sewell restated the Laboratory's policy on conversion to the metric system which was established in 1974. Sewell's memo announced the Laboratory's intention to continue metric conversion on a reasonable and cost effective basis. Copies of the 1974 and 1992 Administrative Memos are contained in the Appendix. There are three primary reasons behind the Laboratory's conversion to the metric system. First, Public Law 100-418, passed in 1988, states that by the end of fiscal year 1992 the Federal Government must begin using metric units in grants, procurements, and other business transactions. Second, on 25 Jul. 1991, President George Bush signed Executive Order 12770 which urged Federal agencies to expedite conversion to metric units. Third, the contract between the University of California and the Department of Energy calls for the Laboratory to convert to the metric system. Thus, conversion to the metric system is a legal requirement and a contractual mandate with the University of California. Public Law 100-418 and Executive Order 12770 are discussed in more detail later in this section, but first they examine the reasons behind the nation's conversion to the metric system. The second part of this report is on applying the metric system.
Metric-adjusted skew information
DEFF Research Database (Denmark)
Liang, Cai; Hansen, Frank
2010-01-01
on a bipartite system and proved superadditivity of the Wigner-Yanase-Dyson skew informations for such states. We extend this result to the general metric-adjusted skew information. We finally show that a recently introduced extension to parameter values 1 ...We give a truly elementary proof of the convexity of metric-adjusted skew information following an idea of Effros. We extend earlier results of weak forms of superadditivity to general metric-adjusted skew information. Recently, Luo and Zhang introduced the notion of semi-quantum states...... of (unbounded) metric-adjusted skew information....
Directory of Open Access Journals (Sweden)
Isabel Garrido
2016-04-01
Full Text Available The class of metric spaces (X,d known as small-determined spaces, introduced by Garrido and Jaramillo, are properly defined by means of some type of real-valued Lipschitz functions on X. On the other hand, B-simple metric spaces introduced by Hejcman are defined in terms of some kind of bornologies of bounded subsets of X. In this note we present a common framework where both classes of metric spaces can be studied which allows us to see not only the relationships between them but also to obtain new internal characterizations of these metric properties.
Lung lesion doubling times: values and variability based on method of volume determination
International Nuclear Information System (INIS)
Eisenbud Quint, Leslie; Cheng, Joan; Schipper, Matthew; Chang, Andrew C.; Kalemkerian, Gregory
2008-01-01
Purpose: To determine doubling times (DTs) of lung lesions based on volumetric measurements from thin-section CT imaging. Methods: Previously untreated patients with ≥ two thin-section CT scans showing a focal lung lesion were identified. Lesion volumes were derived using direct volume measurements and volume calculations based on lesion area and diameter. Growth rates (GRs) were compared by tissue diagnosis and measurement technique. Results: 54 lesions were evaluated including 8 benign lesions, 10 metastases, 3 lymphomas, 15 adenocarcinomas, 11 squamous carcinomas, and 7 miscellaneous lung cancers. Using direct volume measurements, median DTs were 453, 111, 15, 181, 139 and 137 days, respectively. Lung cancer DTs ranged from 23-2239 days. There were no significant differences in GRs among the different lesion types. There was considerable variability among GRs using different volume determination methods. Conclusions: Lung cancer doubling times showed a substantial range, and different volume determination methods gave considerably different DTs
A variable pressure method for characterizing nanoparticle surface charge using pore sensors.
Vogel, Robert; Anderson, Will; Eldridge, James; Glossop, Ben; Willmott, Geoff
2012-04-03
A novel method using resistive pulse sensors for electrokinetic surface charge measurements of nanoparticles is presented. This method involves recording the particle blockade rate while the pressure applied across a pore sensor is varied. This applied pressure acts in a direction which opposes transport due to the combination of electro-osmosis, electrophoresis, and inherent pressure. The blockade rate reaches a minimum when the velocity of nanoparticles in the vicinity of the pore approaches zero, and the forces on typical nanoparticles are in equilibrium. The pressure applied at this minimum rate can be used to calculate the zeta potential of the nanoparticles. The efficacy of this variable pressure method was demonstrated for a range of carboxylated 200 nm polystyrene nanoparticles with different surface charge densities. Results were of the same order as phase analysis light scattering (PALS) measurements. Unlike PALS results, the sequence of increasing zeta potential for different particle types agreed with conductometric titration.
THE QUADRANTS METHOD TO ESTIMATE QUANTITATIVE VARIABLES IN MANAGEMENT PLANS IN THE AMAZON
Directory of Open Access Journals (Sweden)
Gabriel da Silva Oliveira
2015-12-01
Full Text Available This work aimed to evaluate the accuracy in estimates of abundance, basal area and commercial volume per hectare, by the quadrants method applied to an area of 1.000 hectares of rain forest in the Amazon. Samples were simulated by random and systematic process with different sample sizes, ranging from 100 to 200 sampling points. The amounts estimated by the samples were compared with the parametric values recorded in the census. In the analysis we considered as the population all trees with diameter at breast height equal to or greater than 40 cm. The quadrants method did not reach the desired level of accuracy for the variables basal area and commercial volume, overestimating the observed values recorded in the census. However, the accuracy of the estimates of abundance, basal area and commercial volume was satisfactory for applying the method in forest inventories for management plans in the Amazon.
Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods.
Young, Stefano; Kim, Hyun J Grace; Ko, Moe Moe; Ko, War War; Flores, Carlos; McNitt-Gray, Michael F
2015-05-01
Measuring the size of nodules on chest CT is important for lung cancer staging and measuring therapy response. 3D volumetry has been proposed as a more robust alternative to 1D and 2D sizing methods. There have also been substantial advances in methods to reduce radiation dose in CT. The purpose of this work was to investigate the effect of dose reduction and reconstruction methods on variability in 3D lung-nodule volumetry. Reduced-dose CT scans were simulated by applying a noise-addition tool to the raw (sinogram) data from clinically indicated patient scans acquired on a multidetector-row CT scanner (Definition Flash, Siemens Healthcare). Scans were simulated at 25%, 10%, and 3% of the dose of their clinical protocol (CTDIvol of 20.9 mGy), corresponding to CTDIvol values of 5.2, 2.1, and 0.6 mGy. Simulated reduced-dose data were reconstructed with both conventional filtered backprojection (B45 kernel) and iterative reconstruction methods (SAFIRE: I44 strength 3 and I50 strength 3). Three lab technologist readers contoured "measurable" nodules in 33 patients under each of the different acquisition/reconstruction conditions in a blinded study design. Of the 33 measurable nodules, 17 were used to estimate repeatability with their clinical reference protocol, as well as interdose and inter-reconstruction-method reproducibilities. The authors compared the resulting distributions of proportional differences across dose and reconstruction methods by analyzing their means, standard deviations (SDs), and t-test and F-test results. The clinical-dose repeatability experiment yielded a mean proportional difference of 1.1% and SD of 5.5%. The interdose reproducibility experiments gave mean differences ranging from -5.6% to -1.7% and SDs ranging from 6.3% to 9.9%. The inter-reconstruction-method reproducibility experiments gave mean differences of 2.0% (I44 strength 3) and -0.3% (I50 strength 3), and SDs were identical at 7.3%. For the subset of repeatability cases, inter-reconstruction-method
Software metrics: Software quality metrics for distributed systems. [reliability engineering
Post, J. V.
1981-01-01
Software quality metrics was extended to cover distributed computer systems. Emphasis is placed on studying embedded computer systems and on viewing them within a system life cycle. The hierarchy of quality factors, criteria, and metrics was maintained. New software quality factors were added, including survivability, expandability, and evolvability.
The Effect of 4-week Difference Training Methods on Some Fitness Variables in Youth Handball Players
Directory of Open Access Journals (Sweden)
Abdolhossein a Parnow
2016-09-01
Full Text Available Handball is a team sport in which main activities such as sprinting, arm throwing, hitting, and so on involve. This Olympic team sport requires a standard of preparation in order to complete sixteen minutes of competitive play and to achieve success. This study, therefore, was done to determinate the effect of a 4-week different training on some physical fitness variables in youth Handball players. Thirty high-school students participated in the study and assigned into the Resistance Training (RT (n = 10: 16.75± 0.36 yr; 63.14± 4.19 kg; 174.8 ± 5.41 cm, Plyometric Training (PT (n = 10: 16.57± 0.26 yr; 65.52± 6.79 kg; 173.5 ± 5.44 cm, and Complex Training (CT (n=10, 16.23± 0.50 yr; 58.43± 10.50 kg; 175.2 ± 8.19 cm groups. Subjects were evaluated in anthropometric and physiological characteristics 48 hours before and after of a 4-week protocol. Because of study purposes, statistical analyses consisted of a repeated measure ANVOA and one-way ANOVA were used. In considering with pre to post test variables changes in the groups, data analysis showed BF, strength, speed, agility, and explosive power were affected by training protocols (P0.05. In conclusion, complex training result in advantageous effect on variables such as strength, explosive power, speed and agility in youth handball players compare with resistance and plyometric training although we also reported positive effect of these training methods. Coaches and players, therefore, could consider complex training as alternative method for other training methods.
Frank, Andrew A.
1984-01-01
A control system and method for a power delivery system, such as in an automotive vehicle, having an engine coupled to a continuously variable ratio transmission (CVT). Totally independent control of engine and transmission enable the engine to precisely follow a desired operating characteristic, such as the ideal operating line for minimum fuel consumption. CVT ratio is controlled as a function of commanded power or torque and measured load, while engine fuel requirements (e.g., throttle position) are strictly a function of measured engine speed. Fuel requirements are therefore precisely adjusted in accordance with the ideal characteristic for any load placed on the engine.
The complex variable boundary element method: Applications in determining approximative boundaries
Hromadka, T.V.
1984-01-01
The complex variable boundary element method (CVBEM) is used to determine approximation functions for boundary value problems of the Laplace equation such as occurs in potential theory. By determining an approximative boundary upon which the CVBEM approximator matches the desired constant (level curves) boundary conditions, the CVBEM is found to provide the exact solution throughout the interior of the transformed problem domain. Thus, the acceptability of the CVBEM approximation is determined by the closeness-of-fit of the approximative boundary to the study problem boundary. ?? 1984.
International Nuclear Information System (INIS)
Eaker, C.W.; Schatz, G.C.; De Leon, N.; Heller, E.J.
1984-01-01
Two methods for calculating the good action variables and semiclassical eigenvalues for coupled oscillator systems are presented, both of which relate the actions to the coefficients appearing in the Fourier representation of the normal coordinates and momenta. The two methods differ in that one is based on the exact expression for the actions together with the EBK semiclassical quantization condition while the other is derived from the Sorbie--Handy (SH) approximation to the actions. However, they are also very similar in that the actions in both methods are related to the same set of Fourier coefficients and both require determining the perturbed frequencies in calculating actions. These frequencies are also determined from the Fourier representations, which means that the actions in both methods are determined from information entirely contained in the Fourier expansion of the coordinates and momenta. We show how these expansions can very conveniently be obtained from fast Fourier transform (FFT) methods and that numerical filtering methods can be used to remove spurious Fourier components associated with the finite trajectory integration duration. In the case of the SH based method, we find that the use of filtering enables us to relax the usual periodicity requirement on the calculated trajectory. Application to two standard Henon--Heiles models is considered and both are shown to give semiclassical eigenvalues in good agreement with previous calculations for nondegenerate and 1:1 resonant systems. In comparing the two methods, we find that although the exact method is quite general in its ability to be used for systems exhibiting complex resonant behavior, it converges more slowly with increasing trajectory integration duration and is more sensitive to the algorithm for choosing perturbed frequencies than the SH based method
Self-dual metrics with self-dual Killing vectors
International Nuclear Information System (INIS)
Tod, K.P.; Ward, R.S.
1979-01-01
Twistor methods are used to derive a class of solutions to Einstein's vacuum equations, with anti-self dual Weyl tensor. In particular, all metrics with a Killing vector whose derivative is anti-self-dual and which admit a real positive-definite section are exhibited and shown to coincide with the metrics of Hawking. (author)
Author Impact Metrics in Communication Sciences and Disorder Research
Stuart, Andrew; Faucette, Sarah P.; Thomas, William Joseph
2017-01-01
Purpose: The purpose was to examine author-level impact metrics for faculty in the communication sciences and disorder research field across a variety of databases. Method: Author-level impact metrics were collected for faculty from 257 accredited universities in the United States and Canada. Three databases (i.e., Google Scholar, ResearchGate,…
Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics
Strickert, M.; Schneider, P.; Keilwagen, J.; Villmann, T.; Biehl, M.; Hammer, B.
2008-01-01
Supervised attribute relevance detection using cross-comparisons (SARDUX), a recently proposed method for data-driven metric learning, is extended from dimension-weighted Minkowski distances to metrics induced by a data transformation matrix Ω for modeling mutual attribute dependence. Given class
Multimetric indices: How many metrics?
Multimetric indices (MMI’s) often include 5 to 15 metrics, each representing a different attribute of assemblage condition, such as species diversity, tolerant taxa, and nonnative taxa. Is there an optimal number of metrics for MMIs? To explore this question, I created 1000 9-met...
Metrical Phonology: German Sound System.
Tice, Bradley S.
Metrical phonology, a linguistic process of phonological stress assessment and diagrammatic simplification of sentence and word stress, is discussed as it is found in the English and German languages. The objective is to promote use of metrical phonology as a tool for enhancing instruction in stress patterns in words and sentences, particularly in…
Extending cosmology: the metric approach
Mendoza, S.
2012-01-01
Comment: 2012, Extending Cosmology: The Metric Approach, Open Questions in Cosmology; Review article for an Intech "Open questions in cosmology" book chapter (19 pages, 3 figures). Available from: http://www.intechopen.com/books/open-questions-in-cosmology/extending-cosmology-the-metric-approach
High resolution metric imaging payload
Delclaud, Y.
2017-11-01
Alcatel Space Industries has become Europe's leader in the field of high and very high resolution optical payloads, in the frame work of earth observation system able to provide military government with metric images from space. This leadership allowed ALCATEL to propose for the export market, within a French collaboration frame, a complete space based system for metric observation.
A variable capacitance based modeling and power capability predicting method for ultracapacitor
Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang
2018-01-01
Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.
Gas permeation measurement under defined humidity via constant volume/variable pressure method
Jan Roman, Pauls
2012-02-01
Many industrial gas separations in which membrane processes are feasible entail high water vapour contents, as in CO 2-separation from flue gas in carbon capture and storage (CCS), or in biogas/natural gas processing. Studying the effect of water vapour on gas permeability through polymeric membranes is essential for materials design and optimization of these membrane applications. In particular, for amine-based CO 2 selective facilitated transport membranes, water vapour is necessary for carrier-complex formation (Matsuyama et al., 1996; Deng and Hägg, 2010; Liu et al., 2008; Shishatskiy et al., 2010) [1-4]. But also conventional polymeric membrane materials can vary their permeation behaviour due to water-induced swelling (Potreck, 2009) [5]. Here we describe a simple approach to gas permeability measurement in the presence of water vapour, in the form of a modified constant volume/variable pressure method (pressure increase method). © 2011 Elsevier B.V.
Projective-Dual Method for Solving Systems of Linear Equations with Nonnegative Variables
Ganin, B. V.; Golikov, A. I.; Evtushenko, Yu. G.
2018-02-01
In order to solve an underdetermined system of linear equations with nonnegative variables, the projection of a given point onto its solutions set is sought. The dual of this problem—the problem of unconstrained maximization of a piecewise-quadratic function—is solved by Newton's method. The problem of unconstrained optimization dual of the regularized problem of finding the projection onto the solution set of the system is considered. A connection of duality theory and Newton's method with some known algorithms of projecting onto a standard simplex is shown. On the example of taking into account the specifics of the constraints of the transport linear programming problem, the possibility to increase the efficiency of calculating the generalized Hessian matrix is demonstrated. Some examples of numerical calculations using MATLAB are presented.
Study of input variables in group method of data handling methodology
International Nuclear Information System (INIS)
Pereira, Iraci Martinez; Bueno, Elaine Inacio
2013-01-01
The Group Method of Data Handling - GMDH is a combinatorial multi-layer algorithm in which a network of layers and nodes is generated using a number of inputs from the data stream being evaluated. The GMDH network topology has been traditionally determined using a layer by layer pruning process based on a pre-selected criterion of what constitutes the best nodes at each level. The traditional GMDH method is based on an underlying assumption that the data can be modeled by using an approximation of the Volterra Series or Kolmorgorov-Gabor polynomial. A Monitoring and Diagnosis System was developed based on GMDH and ANN methodologies, and applied to the IPEN research Reactor IEA-1. The system performs the monitoring by comparing the GMDH and ANN calculated values with measured ones. As the GMDH is a self-organizing methodology, the input variables choice is made automatically. On the other hand, the results of ANN methodology are strongly dependent on which variables are used as neural network input. (author)
Tam, Vincent H; Kabbara, Samer
2006-10-01
Monte Carlo simulations (MCSs) are increasingly being used to predict the pharmacokinetic variability of antimicrobials in a population. However, various MCS approaches may differ in the accuracy of the predictions. We compared the performance of 3 different MCS approaches using a data set with known parameter values and dispersion. Ten concentration-time profiles were randomly generated and used to determine the best-fit parameter estimates. Three MCS methods were subsequently used to simulate the AUC(0-infinity) of the population, using the central tendency and dispersion of the following in the subject sample: 1) K and V; 2) clearance and V; 3) AUC(0-infinity). In each scenario, 10000 subject simulations were performed. Compared to true AUC(0-infinity) of the population, mean biases by various methods were 1) 58.4, 2) 380.7, and 3) 12.5 mg h L(-1), respectively. Our results suggest that the most realistic MCS approach appeared to be based on the variability of AUC(0-infinity) in the subject sample.
A Real-Time Analysis Method for Pulse Rate Variability Based on Improved Basic Scale Entropy
Directory of Open Access Journals (Sweden)
Yongxin Chou
2017-01-01
Full Text Available Base scale entropy analysis (BSEA is a nonlinear method to analyze heart rate variability (HRV signal. However, the time consumption of BSEA is too long, and it is unknown whether the BSEA is suitable for analyzing pulse rate variability (PRV signal. Therefore, we proposed a method named sliding window iterative base scale entropy analysis (SWIBSEA by combining BSEA and sliding window iterative theory. The blood pressure signals of healthy young and old subjects are chosen from the authoritative international database MIT/PhysioNet/Fantasia to generate PRV signals as the experimental data. Then, the BSEA and the SWIBSEA are used to analyze the experimental data; the results show that the SWIBSEA reduces the time consumption and the buffer cache space while it gets the same entropy as BSEA. Meanwhile, the changes of base scale entropy (BSE for healthy young and old subjects are the same as that of HRV signal. Therefore, the SWIBSEA can be used for deriving some information from long-term and short-term PRV signals in real time, which has the potential for dynamic PRV signal analysis in some portable and wearable medical devices.
Variability of bronchial measurements obtained by sequential CT using two computer-based methods
International Nuclear Information System (INIS)
Brillet, Pierre-Yves; Fetita, Catalin I.; Mitrea, Mihai; Preteux, Francoise; Capderou, Andre; Dreuil, Serge; Simon, Jean-Marc; Grenier, Philippe A.
2009-01-01
This study aimed to evaluate the variability of lumen (LA) and wall area (WA) measurements obtained on two successive MDCT acquisitions using energy-driven contour estimation (EDCE) and full width at half maximum (FWHM) approaches. Both methods were applied to a database of segmental and subsegmental bronchi with LA > 4 mm 2 containing 42 bronchial segments of 10 successive slices that best matched on each acquisition. For both methods, the 95% confidence interval between repeated MDCT was between -1.59 and 1.5 mm 2 for LA, and -3.31 and 2.96 mm 2 for WA. The values of the coefficient of measurement variation (CV 10 , i.e., percentage ratio of the standard deviation obtained from the 10 successive slices to their mean value) were strongly correlated between repeated MDCT data acquisitions (r > 0.72; p 2 , whereas WA values were lower for bronchi with WA 2 ; no systematic EDCE underestimation or overestimation was observed for thicker-walled bronchi. In conclusion, variability between CT examinations and assessment techniques may impair measurements. Therefore, new parameters such as CV 10 need to be investigated to study bronchial remodeling. Finally, EDCE and FWHM are not interchangeable in longitudinal studies. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Ghasemi, Jahan B.; Zolfonoun, Ehsan [Toosi University of Technology, Tehran (Korea, Republic of)
2012-05-15
Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.
International Nuclear Information System (INIS)
Ghasemi, Jahan B.; Zolfonoun, Ehsan
2012-01-01
Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms
Salonen, K; Leisola, M; Eerikäinen, T
2009-01-01
Determination of metabolites from an anaerobic digester with an acid base titration is considered as superior method for many reasons. This paper describes a practical at line compatible multipoint titration method. The titration procedure was improved by speed and data quality. A simple and novel control algorithm for estimating a variable titrant dose was derived for this purpose. This non-linear PI-controller like algorithm does not require any preliminary information from sample. Performance of this controller is superior compared to traditional linear PI-controllers. In addition, simplification for presenting polyprotic acids as a sum of multiple monoprotic acids is introduced along with a mathematical error examination. A method for inclusion of the ionic strength effect with stepwise iteration is shown. The titration model is presented with matrix notations enabling simple computation of all concentration estimates. All methods and algorithms are illustrated in the experimental part. A linear correlation better than 0.999 was obtained for both acetate and phosphate used as model compounds with slopes of 0.98 and 1.00 and average standard deviations of 0.6% and 0.8%, respectively. Furthermore, insensitivity of the presented method for overlapping buffer capacity curves was shown.
Hu, Jiexiang; Zhou, Qi; Jiang, Ping; Shao, Xinyu; Xie, Tingli
2018-01-01
Variable-fidelity (VF) modelling methods have been widely used in complex engineering system design to mitigate the computational burden. Building a VF model generally includes two parts: design of experiments and metamodel construction. In this article, an adaptive sampling method based on improved hierarchical kriging (ASM-IHK) is proposed to refine the improved VF model. First, an improved hierarchical kriging model is developed as the metamodel, in which the low-fidelity model is varied through a polynomial response surface function to capture the characteristics of a high-fidelity model. Secondly, to reduce local approximation errors, an active learning strategy based on a sequential sampling method is introduced to make full use of the already required information on the current sampling points and to guide the sampling process of the high-fidelity model. Finally, two numerical examples and the modelling of the aerodynamic coefficient for an aircraft are provided to demonstrate the approximation capability of the proposed approach, as well as three other metamodelling methods and two sequential sampling methods. The results show that ASM-IHK provides a more accurate metamodel at the same simulation cost, which is very important in metamodel-based engineering design problems.
Energy Technology Data Exchange (ETDEWEB)
Gibbons, Gary W. [DAMTP, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA U.K. (United Kingdom); Volkov, Mikhail S., E-mail: gwg1@cam.ac.uk, E-mail: volkov@lmpt.univ-tours.fr [Laboratoire de Mathématiques et Physique Théorique, LMPT CNRS—UMR 7350, Université de Tours, Parc de Grandmont, Tours, 37200 France (France)
2017-05-01
We study solutions obtained via applying dualities and complexifications to the vacuum Weyl metrics generated by massive rods and by point masses. Rescaling them and extending to complex parameter values yields axially symmetric vacuum solutions containing singularities along circles that can be viewed as singular matter sources. These solutions have wormhole topology with several asymptotic regions interconnected by throats and their sources can be viewed as thin rings of negative tension encircling the throats. For a particular value of the ring tension the geometry becomes exactly flat although the topology remains non-trivial, so that the rings literally produce holes in flat space. To create a single ring wormhole of one metre radius one needs a negative energy equivalent to the mass of Jupiter. Further duality transformations dress the rings with the scalar field, either conventional or phantom. This gives rise to large classes of static, axially symmetric solutions, presumably including all previously known solutions for a gravity-coupled massless scalar field, as for example the spherically symmetric Bronnikov-Ellis wormholes with phantom scalar. The multi-wormholes contain infinite struts everywhere at the symmetry axes, apart from solutions with locally flat geometry.
Metric regularity and subdifferential calculus
International Nuclear Information System (INIS)
Ioffe, A D
2000-01-01
The theory of metric regularity is an extension of two classical results: the Lyusternik tangent space theorem and the Graves surjection theorem. Developments in non-smooth analysis in the 1980s and 1990s paved the way for a number of far-reaching extensions of these results. It was also well understood that the phenomena behind the results are of metric origin, not connected with any linear structure. At the same time it became clear that some basic hypotheses of the subdifferential calculus are closely connected with the metric regularity of certain set-valued maps. The survey is devoted to the metric theory of metric regularity and its connection with subdifferential calculus in Banach spaces
Barnwell-Ménard, Jean-Louis; Li, Qing; Cohen, Alan A
2015-03-15
The loss of signal associated with categorizing a continuous variable is well known, and previous studies have demonstrated that this can lead to an inflation of Type-I error when the categorized variable is a confounder in a regression analysis estimating the effect of an exposure on an outcome. However, it is not known how the Type-I error may vary under different circumstances, including logistic versus linear regression, different distributions of the confounder, and different categorization methods. Here, we analytically quantified the effect of categorization and then performed a series of 9600 Monte Carlo simulations to estimate the Type-I error inflation associated with categorization of a confounder under different regression scenarios. We show that Type-I error is unacceptably high (>10% in most scenarios and often 100%). The only exception was when the variable categorized was a continuous mixture proxy for a genuinely dichotomous latent variable, where both the continuous proxy and the categorized variable are error-ridden proxies for the dichotomous latent variable. As expected, error inflation was also higher with larger sample size, fewer categories, and stronger associations between the confounder and the exposure or outcome. We provide online tools that can help researchers estimate the potential error inflation and understand how serious a problem this is. Copyright © 2014 John Wiley & Sons, Ltd.
Toward Capturing Momentary Changes of Heart Rate Variability by a Dynamic Analysis Method.
Directory of Open Access Journals (Sweden)
Haoshi Zhang
Full Text Available The analysis of heart rate variability (HRV has been performed on long-term electrocardiography (ECG recordings (12~24 hours and short-term recordings (2~5 minutes, which may not capture momentary change of HRV. In this study, we present a new method to analyze the momentary HRV (mHRV. The ECG recordings were segmented into a series of overlapped HRV analysis windows with a window length of 5 minutes and different time increments. The performance of the proposed method in delineating the dynamics of momentary HRV measurement was evaluated with four commonly used time courses of HRV measures on both synthetic time series and real ECG recordings from human subjects and dogs. Our results showed that a smaller time increment could capture more dynamical information on transient changes. Considering a too short increment such as 10 s would cause the indented time courses of the four measures, a 1-min time increment (4-min overlapping was suggested in the analysis of mHRV in the study. ECG recordings from human subjects and dogs were used to further assess the effectiveness of the proposed method. The pilot study demonstrated that the proposed analysis of mHRV could provide more accurate assessment of the dynamical changes in cardiac activity than the conventional measures of HRV (without time overlapping. The proposed method may provide an efficient means in delineating the dynamics of momentary HRV and it would be worthy performing more investigations.
METRICS DEVELOPMENT FOR PATENTS.
Veiga, Daniela Francescato; Ferreira, Lydia Masako
2015-01-01
To develop a proposal for metrics for patents to be applied in assessing the postgraduate programs of Medicine III - Capes. From the reading and analysis of the 2013 area documents of all the 48 areas of Capes, a proposal for metrics for patents was developed to be applied in Medicine III programs. Except for the areas Biotechnology, Food Science, Biological Sciences III, Physical Education, Engineering I, III and IV and Interdisciplinary, most areas do not adopt a scoring system for patents. The proposal developed was based on the criteria of Biotechnology, with adaptations. In general, it will be valued, in ascending order, the deposit, the granting and licensing/production. It will also be assigned higher scores to patents registered abroad and whenever there is a participation of students. This proposal can be applied to the item Intellectual Production of the evaluation form, in subsection Technical Production/Patents. The percentage of 10% for academic programs and 40% for Masters Professionals should be maintained. The program will be scored as Very Good when it reaches 400 points or over; Good, between 200 and 399 points; Regular, between 71 and 199 points; Weak up to 70 points; Insufficient, no punctuation. Desenvolver uma proposta de métricas para patentes a serem aplicadas na avaliação dos Programas de Pós-Graduação da Área Medicina III - Capes. A partir da leitura e análise dos documentos de área de 2013 de todas as 48 Áreas da Capes, desenvolveu-se uma proposta de métricas para patentes, a ser aplicada na avaliação dos programas da área. Constatou-se que, com exceção das áreas Biotecnologia, Ciência de Alimentos, Ciências Biológicas III, Educação Física, Engenharias I, III e IV e Interdisciplinar, a maioria não adota sistema de pontuação para patentes. A proposta desenvolvida baseou-se nos critérios da Biotecnologia, com adaptações. De uma forma geral, foi valorizado, em ordem crescente, o depósito, a concessão e o
Climate Classification is an Important Factor in Assessing Hospital Performance Metrics
Boland, M. R.; Parhi, P.; Gentine, P.; Tatonetti, N. P.
2017-12-01
Context/Purpose: Climate is a known modulator of disease, but its impact on hospital performance metrics remains unstudied. Methods: We assess the relationship between Köppen-Geiger climate classification and hospital performance metrics, specifically 30-day mortality, as reported in Hospital Compare, and collected for the period July 2013 through June 2014 (7/1/2013 - 06/30/2014). A hospital-level multivariate linear regression analysis was performed while controlling for known socioeconomic factors to explore the relationship between all-cause mortality and climate. Hospital performance scores were obtained from 4,524 hospitals belonging to 15 distinct Köppen-Geiger climates and 2,373 unique counties. Results: Model results revealed that hospital performance metrics for mortality showed significant climate dependence (psocioeconomic factors. Interpretation: Currently, hospitals are reimbursed by Governmental agencies using 30-day mortality rates along with 30-day readmission rates. These metrics allow Government agencies to rank hospitals according to their `performance' along these metrics. Various socioeconomic factors are taken into consideration when determining individual hospitals performance. However, no climate-based adjustment is made within the existing framework. Our results indicate that climate-based variability in 30-day mortality rates does exist even after socioeconomic confounder adjustment. Use of standardized high-level climate classification systems (such as Koppen-Geiger) would be useful to incorporate in future metrics. Conclusion: Climate is a significant factor in evaluating hospital 30-day mortality rates. These results demonstrate that climate classification is an important factor when comparing hospital performance across the United States.
Directory of Open Access Journals (Sweden)
Tomaž Vrtovec
2015-06-01
Full Text Available Objective measurement of coronal vertebral inclination (CVI is of significant importance for evaluating spinal deformities in the coronal plane. The purpose of this study is to systematically analyze and compare manual and computerized measurements of CVI in cross-sectional and volumetric computed tomography (CT images. Three observers independently measured CVI in 14 CT images of normal and 14 CT images of scoliotic vertebrae by using six manual and two computerized measurements. Manual measurements were obtained in coronal cross-sections by manually identifying the vertebral body corners, which served to measure CVI according to the superior and inferior tangents, left and right tangents, and mid-endplate and mid-wall lines. Computerized measurements were obtained in two dimensions (2D and in three dimensions (3D by manually initializing an automated method in vertebral centroids and then searching for the planes of maximal symmetry of vertebral anatomical structures. The mid-endplate lines were the most reproducible and reliable manual measurements (intra- and inter-observer variability of 0.7° and 1.2° standard deviation, SD, respectively. The computerized measurements in 3D were more reproducible and reliable (intra- and inter-observer variability of 0.5° and 0.7° SD, respectively, but were most consistent with the mid-wall lines (2.0° SD and 1.4° mean absolute difference. The manual CVI measurements based on mid-endplate lines and the computerized CVI measurements in 3D resulted in the lowest intra-observer and inter-observer variability, however, computerized CVI measurements reduce observer interaction.
International Nuclear Information System (INIS)
Balabin, Roman M.; Smirnov, Sergey V.
2011-01-01
During the past several years, near-infrared (near-IR/NIR) spectroscopy has increasingly been adopted as an analytical tool in various fields from petroleum to biomedical sectors. The NIR spectrum (above 4000 cm -1 ) of a sample is typically measured by modern instruments at a few hundred of wavelengths. Recently, considerable effort has been directed towards developing procedures to identify variables (wavelengths) that contribute useful information. Variable selection (VS) or feature selection, also called frequency selection or wavelength selection, is a critical step in data analysis for vibrational spectroscopy (infrared, Raman, or NIRS). In this paper, we compare the performance of 16 different feature selection methods for the prediction of properties of biodiesel fuel, including density, viscosity, methanol content, and water concentration. The feature selection algorithms tested include stepwise multiple linear regression (MLR-step), interval partial least squares regression (iPLS), backward iPLS (BiPLS), forward iPLS (FiPLS), moving window partial least squares regression (MWPLS), (modified) changeable size moving window partial least squares (CSMWPLS/MCSMWPLSR), searching combination moving window partial least squares (SCMWPLS), successive projections algorithm (SPA), uninformative variable elimination (UVE, including UVE-SPA), simulated annealing (SA), back-propagation artificial neural networks (BP-ANN), Kohonen artificial neural network (K-ANN), and genetic algorithms (GAs, including GA-iPLS). Two linear techniques for calibration model building, namely multiple linear regression (MLR) and partial least squares regression/projection to latent structures (PLS/PLSR), are used for the evaluation of biofuel properties. A comparison with a non-linear calibration model, artificial neural networks (ANN-MLP), is also provided. Discussion of gasoline, ethanol-gasoline (bioethanol), and diesel fuel data is presented. The results of other spectroscopic
Methods for assessment of climate variability and climate changes in different time-space scales
International Nuclear Information System (INIS)
Lobanov, V.; Lobanova, H.
2004-01-01
Main problem of hydrology and design support for water projects connects with modern climate change and its impact on hydrological characteristics as observed as well as designed. There are three main stages of this problem: - how to extract a climate variability and climate change from complex hydrological records; - how to assess the contribution of climate change and its significance for the point and area; - how to use the detected climate change for computation of design hydrological characteristics. Design hydrological characteristic is the main generalized information, which is used for water management and design support. First step of a research is a choice of hydrological characteristic, which can be as a traditional one (annual runoff for assessment of water resources, maxima, minima runoff, etc) as well as a new one, which characterizes an intra-annual function or intra-annual runoff distribution. For this aim a linear model has been developed which has two coefficients connected with an amplitude and level (initial conditions) of seasonal function and one parameter, which characterizes an intensity of synoptic and macro-synoptic fluctuations inside a year. Effective statistical methods have been developed for a separation of climate variability and climate change and extraction of homogeneous components of three time scales from observed long-term time series: intra annual, decadal and centural. The first two are connected with climate variability and the last (centural) with climate change. Efficiency of new methods of decomposition and smoothing has been estimated by stochastic modeling and well as on the synthetic examples. For an assessment of contribution and statistical significance of modern climate change components statistical criteria and methods have been used. Next step has been connected with a generalization of the results of detected climate changes over the area and spatial modeling. For determination of homogeneous region with the same
International Nuclear Information System (INIS)
Zhang Jiefang; Dai Chaoqing; Zong Fengde
2007-01-01
In this paper, with the variable separation approach and based on the general reduction theory, we successfully generalize this extended tanh-function method to obtain new types of variable separation solutions for the following Nizhnik-Novikov-Veselov (NNV) equation. Among the solutions, two solutions are new types of variable separation solutions, while the last solution is similar to the solution given by Darboux transformation in Hu et al 2003 Chin. Phys. Lett. 20 1413
Directory of Open Access Journals (Sweden)
Xuefei Guan
2011-01-01
Full Text Available In this paper, two probabilistic prognosis updating schemes are compared. One is based on the classical Bayesian approach and the other is based on newly developed maximum relative entropy (MRE approach. The algorithm performance of the two models is evaluated using a set of recently developed prognostics-based metrics. Various uncertainties from measurements, modeling, and parameter estimations are integrated into the prognosis framework as random input variables for fatigue damage of materials. Measures of response variables are then used to update the statistical distributions of random variables and the prognosis results are updated using posterior distributions. Markov Chain Monte Carlo (MCMC technique is employed to provide the posterior samples for model updating in the framework. Experimental data are used to demonstrate the operation of the proposed probabilistic prognosis methodology. A set of prognostics-based metrics are employed to quantitatively evaluate the prognosis performance and compare the proposed entropy method with the classical Bayesian updating algorithm. In particular, model accuracy, precision, robustness and convergence are rigorously evaluated in addition to the qualitative visual comparison. Following this, potential development and improvement for the prognostics-based metrics are discussed in detail.
SIVA/DIVA- INITIAL VALUE ORDINARY DIFFERENTIAL EQUATION SOLUTION VIA A VARIABLE ORDER ADAMS METHOD
Krogh, F. T.
1994-01-01
The SIVA/DIVA package is a collection of subroutines for the solution of ordinary differential equations. There are versions for single precision and double precision arithmetic. These solutions are applicable to stiff or nonstiff differential equations of first or second order. SIVA/DIVA requires fewer evaluations of derivatives than other variable order Adams predictor-corrector methods. There is an option for the direct integration of second order equations which can make integration of trajectory problems significantly more efficient. Other capabilities of SIVA/DIVA include: monitoring a user supplied function which can be separate from the derivative; dynamically controlling the step size; displaying or not displaying output at initial, final, and step size change points; saving the estimated local error; and reverse communication where subroutines return to the user for output or computation of derivatives instead of automatically performing calculations. The user must supply SIVA/DIVA with: 1) the number of equations; 2) initial values for the dependent and independent variables, integration stepsize, error tolerance, etc.; and 3) the driver program and operational parameters necessary for subroutine execution. SIVA/DIVA contains an extensive diagnostic message library should errors occur during execution. SIVA/DIVA is written in FORTRAN 77 for batch execution and is machine independent. It has a central memory requirement of approximately 120K of 8 bit bytes. This program was developed in 1983 and last updated in 1987.
International Nuclear Information System (INIS)
Do, Chuong; Hussey, Dennis; Wells, Daniel M.; Epperson, Kenny
2016-01-01
Optimization numerical method was implemented to determine several mass transfer coefficients in a crud-induced power shift risk assessment code. The approach was to utilize a multilevel strategy that targets different model parameters that first changes the major order variables, mass transfer inputs, then calibrates the minor order variables, crud source terms, according to available plant data. In this manner, the mass transfer inputs are effectively simplified as 'dependent' on the crud source terms. Two optimization studies were performed using DAKOTA, a design and analysis toolkit, with the difference between the runs, being the number of model runs using BOA, allowed for adjusting the crud source terms, therefore, reducing the uncertainty with calibration. The result of the first case showed that the current best estimated values for the mass transfer coefficients, which were derived from first principle analysis, can be considered an optimized set. When the run limit of BOA was increased for the second case, an improvement in the prediction was obtained with the results deviating slightly from the best estimated values. (author)
Energy Technology Data Exchange (ETDEWEB)
Baeza, A.; Corbacho, J.A. [LARUEX, Caceres (Spain). Environmental Radioactivity Lab.
2013-07-01
Determining the gross alpha activity concentration of water samples is one way to screen for waters whose radionuclide content is so high that its consumption could imply surpassing the Total Indicative Dose as defined in European Directive 98/83/EC. One of the most commonly used methods to prepare the sources to measure gross alpha activity in water samples is desiccation. Its main advantages are the simplicity of the procedure, the low cost of source preparation, and the possibility of simultaneously determining the gross beta activity. The preparation of the source, the construction of the calibration curves, and the measurement procedure itself involve, however, various factors that may introduce sufficient variability into the results to significantly affect the screening process. We here identify the main sources of this variability, and propose specific procedures to follow in the desiccation process that will reduce the uncertainties, and ensure that the result is indeed representative of the sum of the activities of the alpha emitters present in the sample. (orig.)
DEFF Research Database (Denmark)
Wiuf, Carsten; Pallesen, Jonatan; Foldager, Leslie
2016-01-01
variables without assuming a priori defined groups. We provide different ways to evaluate the significance of the aggregated variables based on theoretical considerations and resampling techniques, and show that under certain assumptions the FWER is controlled in the strong sense. Validity of the method...... and the results might depend on the chosen criteria. Methods that summarize, or aggregate, test statistics or p-values, without relying on a priori criteria, are therefore desirable. We present a simple method to aggregate a sequence of stochastic variables, such as test statistics or p-values, into fewer...
Implications of Metric Choice for Common Applications of Readmission Metrics
Davies, Sheryl; Saynina, Olga; Schultz, Ellen; McDonald, Kathryn M; Baker, Laurence C
2013-01-01
Objective. To quantify the differential impact on hospital performance of three readmission metrics: all-cause readmission (ACR), 3M Potential Preventable Readmission (PPR), and Centers for Medicare and Medicaid 30-day readmission (CMS).
Standardised metrics for global surgical surveillance.
Weiser, Thomas G; Makary, Martin A; Haynes, Alex B; Dziekan, Gerald; Berry, William R; Gawande, Atul A
2009-09-26
Public health surveillance relies on standardised metrics to evaluate disease burden and health system performance. Such metrics have not been developed for surgical services despite increasing volume, substantial cost, and high rates of death and disability associated with surgery. The Safe Surgery Saves Lives initiative of WHO's Patient Safety Programme has developed standardised public health metrics for surgical care that are applicable worldwide. We assembled an international panel of experts to develop and define metrics for measuring the magnitude and effect of surgical care in a population, while taking into account economic feasibility and practicability. This panel recommended six measures for assessing surgical services at a national level: number of operating rooms, number of operations, number of accredited surgeons, number of accredited anaesthesia professionals, day-of-surgery death ratio, and postoperative in-hospital death ratio. We assessed the feasibility of gathering such statistics at eight diverse hospitals in eight countries and incorporated them into the WHO Guidelines for Safe Surgery, in which methods for data collection, analysis, and reporting are outlined.
Sigma Routing Metric for RPL Protocol
Directory of Open Access Journals (Sweden)
Paul Sanmartin
2018-04-01
Full Text Available This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX. However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption.
de Sá, Joceline Cássia Ferezini; Costa, Eduardo Caldas; da Silva, Ester; Azevedo, George Dantas
2013-09-01
Polycystic ovary syndrome (PCOS) is an endocrine disorder associated with several cardiometabolic risk factors, such as central obesity, insulin resistance, type 2 diabetes, metabolic syndrome, and hypertension. These factors are associated with adrenergic overactivity, which is an important prognostic factor for the development of cardiovascular disorders. Given the common cardiometabolic disturbances occurring in PCOS women, over the last years studies have investigated the cardiac autonomic control of these patients, mainly based on heart rate variability (HRV). Thus, in this review, we will discuss the recent findings of the studies that investigated the HRV of women with PCOS, as well as noninvasive methods of analysis of autonomic control starting from basic indexes related to this methodology.
Issues in Benchmark Metric Selection
Crolotte, Alain
It is true that a metric can influence a benchmark but will esoteric metrics create more problems than they will solve? We answer this question affirmatively by examining the case of the TPC-D metric which used the much debated geometric mean for the single-stream test. We will show how a simple choice influenced the benchmark and its conduct and, to some extent, DBMS development. After examining other alternatives our conclusion is that the “real” measure for a decision-support benchmark is the arithmetic mean.
Background metric in supergravity theories
International Nuclear Information System (INIS)
Yoneya, T.
1978-01-01
In supergravity theories, we investigate the conformal anomaly of the path-integral determinant and the problem of fermion zero modes in the presence of a nontrivial background metric. Except in SO(3) -invariant supergravity, there are nonvanishing conformal anomalies. As a consequence, amplitudes around the nontrivial background metric contain unpredictable arbitrariness. The fermion zero modes which are explicitly constructed for the Euclidean Schwarzschild metric are interpreted as an indication of the supersymmetric multiplet structure of a black hole. The degree of degeneracy of a black hole is 2/sup 4n/ in SO(n) supergravity
Generalized Painleve-Gullstrand metrics
Energy Technology Data Exchange (ETDEWEB)
Lin Chunyu [Department of Physics, National Cheng Kung University, Tainan 70101, Taiwan (China)], E-mail: l2891112@mail.ncku.edu.tw; Soo Chopin [Department of Physics, National Cheng Kung University, Tainan 70101, Taiwan (China)], E-mail: cpsoo@mail.ncku.edu.tw
2009-02-02
An obstruction to the implementation of spatially flat Painleve-Gullstrand (PG) slicings is demonstrated, and explicitly discussed for Reissner-Nordstroem and Schwarzschild-anti-deSitter spacetimes. Generalizations of PG slicings which are not spatially flat but which remain regular at the horizons are introduced. These metrics can be obtained from standard spherically symmetric metrics by physical Lorentz boosts. With these generalized PG metrics, problematic contributions to the imaginary part of the action in the Parikh-Wilczek derivation of Hawking radiation due to the obstruction can be avoided.
Mustapha, K.
2017-06-03
Anomalous diffusion is a phenomenon that cannot be modeled accurately by second-order diffusion equations, but is better described by fractional diffusion models. The nonlocal nature of the fractional diffusion operators makes substantially more difficult the mathematical analysis of these models and the establishment of suitable numerical schemes. This paper proposes and analyzes the first finite difference method for solving {\\\\em variable-coefficient} fractional differential equations, with two-sided fractional derivatives, in one-dimensional space. The proposed scheme combines first-order forward and backward Euler methods for approximating the left-sided fractional derivative when the right-sided fractional derivative is approximated by two consecutive applications of the first-order backward Euler method. Our finite difference scheme reduces to the standard second-order central difference scheme in the absence of fractional derivatives. The existence and uniqueness of the solution for the proposed scheme are proved, and truncation errors of order $h$ are demonstrated, where $h$ denotes the maximum space step size. The numerical tests illustrate the global $O(h)$ accuracy of our scheme, except for nonsmooth cases which, as expected, have deteriorated convergence rates.
Directory of Open Access Journals (Sweden)
Bai Shiye
2016-05-01
Full Text Available An objective function defined by minimum compliance of topology optimization for 3D continuum structure was established to search optimal material distribution constrained by the predetermined volume restriction. Based on the improved SIMP (solid isotropic microstructures with penalization model and the new sensitivity filtering technique, basic iteration equations of 3D finite element analysis were deduced and solved by optimization criterion method. All the above procedures were written in MATLAB programming language, and the topology optimization design examples of 3D continuum structure with reserved hole were examined repeatedly by observing various indexes, including compliance, maximum displacement, and density index. The influence of mesh, penalty factors, and filter radius on the topology results was analyzed. Computational results showed that the finer or coarser the mesh number was, the larger the compliance, maximum displacement, and density index would be. When the filtering radius was larger than 1.0, the topology shape no longer appeared as a chessboard problem, thus suggesting that the presented sensitivity filtering method was valid. The penalty factor should be an integer because iteration steps increased greatly when it is a noninteger. The above modified variable density method could provide technical routes for topology optimization design of more complex 3D continuum structures in the future.
Development and validation of a new fallout transport method using variable spectral winds
International Nuclear Information System (INIS)
Hopkins, A.T.
1984-01-01
A new method was developed to incorporate variable winds into fallout transport calculations. The method uses spectral coefficients derived by the National Meteorological Center. Wind vector components are computed with the coefficients along the trajectories of falling particles. Spectral winds are used in the two-step method to compute dose rate on the ground, downwind of a nuclear cloud. First, the hotline is located by computing trajectories of particles from an initial, stabilized cloud, through spectral winds to the ground. The connection of particle landing points is the hotline. Second, dose rate on and around the hotline is computed by analytically smearing the falling cloud's activity along the ground. The feasibility of using spectral winds for fallout particle transport was validated by computing Mount St. Helens ashfall locations and comparing calculations to fallout data. In addition, an ashfall equation was derived for computing volcanic ash mass/area on the ground. Ashfall data and the ashfall equation were used to back-calculate an aggregated particle size distribution for the Mount St. Helens eruption cloud
Nonlinear Methods to Assess Changes in Heart Rate Variability in Type 2 Diabetic Patients
Energy Technology Data Exchange (ETDEWEB)
Bhaskar, Roy, E-mail: imbhaskarall@gmail.com [Indian Institute of Technology (India); University of Connecticut, Farmington, CT (United States); Ghatak, Sobhendu [Indian Institute of Technology (India)
2013-10-15
Heart rate variability (HRV) is an important indicator of autonomic modulation of cardiovascular function. Diabetes can alter cardiac autonomic modulation by damaging afferent inputs, thereby increasing the risk of cardiovascular disease. We applied nonlinear analytical methods to identify parameters associated with HRV that are indicative of changes in autonomic modulation of heart function in diabetic patients. We analyzed differences in HRV patterns between diabetic and age-matched healthy control subjects using nonlinear methods. Lagged Poincaré plot, autocorrelation, and detrended fluctuation analysis were applied to analyze HRV in electrocardiography (ECG) recordings. Lagged Poincare plot analysis revealed significant changes in some parameters, suggestive of decreased parasympathetic modulation. The detrended fluctuation exponent derived from long-term fitting was higher than the short-term one in the diabetic population, which was also consistent with decreased parasympathetic input. The autocorrelation function of the deviation of inter-beat intervals exhibited a highly correlated pattern in the diabetic group compared with the control group. The HRV pattern significantly differs between diabetic patients and healthy subjects. All three statistical methods employed in the study may prove useful to detect the onset and extent of autonomic neuropathy in diabetic patients.
Nonlinear Methods to Assess Changes in Heart Rate Variability in Type 2 Diabetic Patients
International Nuclear Information System (INIS)
Bhaskar, Roy; Ghatak, Sobhendu
2013-01-01
Heart rate variability (HRV) is an important indicator of autonomic modulation of cardiovascular function. Diabetes can alter cardiac autonomic modulation by damaging afferent inputs, thereby increasing the risk of cardiovascular disease. We applied nonlinear analytical methods to identify parameters associated with HRV that are indicative of changes in autonomic modulation of heart function in diabetic patients. We analyzed differences in HRV patterns between diabetic and age-matched healthy control subjects using nonlinear methods. Lagged Poincaré plot, autocorrelation, and detrended fluctuation analysis were applied to analyze HRV in electrocardiography (ECG) recordings. Lagged Poincare plot analysis revealed significant changes in some parameters, suggestive of decreased parasympathetic modulation. The detrended fluctuation exponent derived from long-term fitting was higher than the short-term one in the diabetic population, which was also consistent with decreased parasympathetic input. The autocorrelation function of the deviation of inter-beat intervals exhibited a highly correlated pattern in the diabetic group compared with the control group. The HRV pattern significantly differs between diabetic patients and healthy subjects. All three statistical methods employed in the study may prove useful to detect the onset and extent of autonomic neuropathy in diabetic patients
Mustapha, K.; Furati, K.; Knio, Omar; Maitre, O. Le
2017-01-01
Anomalous diffusion is a phenomenon that cannot be modeled accurately by second-order diffusion equations, but is better described by fractional diffusion models. The nonlocal nature of the fractional diffusion operators makes substantially more difficult the mathematical analysis of these models and the establishment of suitable numerical schemes. This paper proposes and analyzes the first finite difference method for solving {\\em variable-coefficient} fractional differential equations, with two-sided fractional derivatives, in one-dimensional space. The proposed scheme combines first-order forward and backward Euler methods for approximating the left-sided fractional derivative when the right-sided fractional derivative is approximated by two consecutive applications of the first-order backward Euler method. Our finite difference scheme reduces to the standard second-order central difference scheme in the absence of fractional derivatives. The existence and uniqueness of the solution for the proposed scheme are proved, and truncation errors of order $h$ are demonstrated, where $h$ denotes the maximum space step size. The numerical tests illustrate the global $O(h)$ accuracy of our scheme, except for nonsmooth cases which, as expected, have deteriorated convergence rates.
International Nuclear Information System (INIS)
Bakosi, Jozsef; Ristorcelli, Raymond J.
2010-01-01
Probability density function (PDF) methods are extended to variable-density pressure-gradient-driven turbulence. We apply the new method to compute the joint PDF of density and velocity in a non-premixed binary mixture of different-density molecularly mixing fluids under gravity. The full time-evolution of the joint PDF is captured in the highly non-equilibrium flow: starting from a quiescent state, transitioning to fully developed turbulence and finally dissipated by molecular diffusion. High-Atwood-number effects (as distinguished from the Boussinesq case) are accounted for: both hydrodynamic turbulence and material mixing are treated at arbitrary density ratios, with the specific volume, mass flux and all their correlations in closed form. An extension of the generalized Langevin model, originally developed for the Lagrangian fluid particle velocity in constant-density shear-driven turbulence, is constructed for variable-density pressure-gradient-driven flows. The persistent small-scale anisotropy, a fundamentally 'non-Kolmogorovian' feature of flows under external acceleration forces, is captured by a tensorial diffusion term based on the external body force. The material mixing model for the fluid density, an active scalar, is developed based on the beta distribution. The beta-PDF is shown to be capable of capturing the mixing asymmetry and that it can accurately represent the density through transition, in fully developed turbulence and in the decay process. The joint model for hydrodynamics and active material mixing yields a time-accurate evolution of the turbulent kinetic energy and Reynolds stress anisotropy without resorting to gradient diffusion hypotheses, and represents the mixing state by the density PDF itself, eliminating the need for dubious mixing measures. Direct numerical simulations of the homogeneous Rayleigh-Taylor instability are used for model validation.
Directory of Open Access Journals (Sweden)
Mike D.R. Zhang
2001-01-01
Full Text Available In this paper, a method for analyzing the dynamic response of a structural system with variable mass, damping and stiffness is first presented. The dynamic equations of the structural system with variable mass and stiffness are derived according to the whole working process of a bridge bucket unloader. At the end of the paper, an engineering numerical example is given.
Next-Generation Metrics: Responsible Metrics & Evaluation for Open Science
Energy Technology Data Exchange (ETDEWEB)
Wilsdon, J.; Bar-Ilan, J.; Peters, I.; Wouters, P.
2016-07-01
Metrics evoke a mixed reaction from the research community. A commitment to using data to inform decisions makes some enthusiastic about the prospect of granular, real-time analysis o of research and its wider impacts. Yet we only have to look at the blunt use of metrics such as journal impact factors, h-indices and grant income targets, to be reminded of the pitfalls. Some of the most precious qualities of academic culture resist simple quantification, and individual indicators often struggle to do justice to the richness and plurality of research. Too often, poorly designed evaluation criteria are “dominating minds, distorting behaviour and determining careers (Lawrence, 2007).” Metrics hold real power: they are constitutive of values, identities and livelihoods. How to exercise that power to more positive ends has been the focus of several recent and complementary initiatives, including the San Francisco Declaration on Research Assessment (DORA1), the Leiden Manifesto2 and The Metric Tide3 (a UK government review of the role of metrics in research management and assessment). Building on these initiatives, the European Commission, under its new Open Science Policy Platform4, is now looking to develop a framework for responsible metrics for research management and evaluation, which can be incorporated into the successor framework to Horizon 2020. (Author)
New Methods for Prosodic Transcription: Capturing Variability as a Source of Information
Directory of Open Access Journals (Sweden)
Jennifer Cole
2016-06-01
Full Text Available Understanding the role of prosody in encoding linguistic meaning and in shaping phonetic form requires the analysis of prosodically annotated speech drawn from a wide variety of speech materials. Yet obtaining accurate and reliable prosodic annotations for even small datasets is challenging due to the time and expertise required. We discuss several factors that make prosodic annotation difficult and impact its reliability, all of which relate to 'variability': in the patterning of prosodic elements (features and structures as they relate to the linguistic and discourse context, in the acoustic cues for those prosodic elements, and in the parameter values of the cues. We propose two novel methods for prosodic transcription that capture variability as a source of information relevant to the linguistic analysis of prosody. The first is 'Rapid Prosody Transcription '(RPT, which can be performed by non-experts using a simple set of unary labels to mark prominence and boundaries based on immediate auditory impression. Inter-transcriber variability is used to calculate continuous-valued prosody ‘scores’ that are assigned to each word and represent the perceptual salience of its prosodic features or structure. RPT can be used to model the relative influence of top-down factors and acoustic cues in prosody perception, and to model prosodic variation across many dimensions, including language variety,speech style, or speaker’s affect. The second proposed method is the identification of individual cues to the contrastive prosodic elements of an utterance. Cue specification provides a link between the contrastive symbolic categories of prosodic structures and the continuous-valued parameters in the acoustic signal, and offers a framework for investigating how factors related to the grammatical and situational context influence the phonetic form of spoken words and phrases. While cue specification as a transcription tool has not yet been explored as
Development of quality metrics for ambulatory pediatric cardiology: Infection prevention.
Johnson, Jonathan N; Barrett, Cindy S; Franklin, Wayne H; Graham, Eric M; Halnon, Nancy J; Hattendorf, Brandy A; Krawczeski, Catherine D; McGovern, James J; O'Connor, Matthew J; Schultz, Amy H; Vinocur, Jeffrey M; Chowdhury, Devyani; Anderson, Jeffrey B
2017-12-01
In 2012, the American College of Cardiology's (ACC) Adult Congenital and Pediatric Cardiology Council established a program to develop quality metrics to guide ambulatory practices for pediatric cardiology. The council chose five areas on which to focus their efforts; chest pain, Kawasaki Disease, tetralogy of Fallot, transposition of the great arteries after arterial switch, and infection prevention. Here, we sought to describe the process, evaluation, and results of the Infection Prevention Committee's metric design process. The infection prevention metrics team consisted of 12 members from 11 institutions in North America. The group agreed to work on specific infection prevention topics including antibiotic prophylaxis for endocarditis, rheumatic fever, and asplenia/hyposplenism; influenza vaccination and respiratory syncytial virus prophylaxis (palivizumab); preoperative methods to reduce intraoperative infections; vaccinations after cardiopulmonary bypass; hand hygiene; and testing to identify splenic function in patients with heterotaxy. An extensive literature review was performed. When available, previously published guidelines were used fully in determining metrics. The committee chose eight metrics to submit to the ACC Quality Metric Expert Panel for review. Ultimately, metrics regarding hand hygiene and influenza vaccination recommendation for patients did not pass the RAND analysis. Both endocarditis prophylaxis metrics and the RSV/palivizumab metric passed the RAND analysis but fell out during the open comment period. Three metrics passed all analyses, including those for antibiotic prophylaxis in patients with heterotaxy/asplenia, for influenza vaccination compliance in healthcare personnel, and for adherence to recommended regimens of secondary prevention of rheumatic fever. The lack of convincing data to guide quality improvement initiatives in pediatric cardiology is widespread, particularly in infection prevention. Despite this, three metrics were
Methods to quantify variable importance: implications for theanalysis of noisy ecological data
Murray, Kim; Conner, Mary M.
2009-01-01
Determining the importance of independent variables is of practical relevance to ecologists and managers concerned with allocating limited resources to the management of natural systems. Although techniques that identify explanatory variables having the largest influence on the response variable are needed to design management actions effectively, the use of various indices to evaluate variable importance is poorly understood. Using Monte Carlo simulations, we compared six different indices c...
Dargó, Gergő; Boros, Krisztina; Péter, László; Malanga, Milo; Sohajda, Tamás; Szente, Lajos; Balogh, György T
2018-05-05
The present study was aimed to develop a medium-throughput screening technique for investigation of cyclodextrin (CD)-active pharmaceutical ingredient (API) complexes. Dual-phase potentiometric lipophilicity measurement, as gold standard technique, was combined with the partition coefficient method (plotting the reciprocal of partition coefficients of APIs as a function of CD concentration). A general equation was derived for determination of stability constants of 1:1 CD-API complexes (K 1:1,CD ) based on solely the changes of partition coefficients (logP o/w N -logP app N ), without measurement of the actual API concentrations. Experimentally determined logP value (-1.64) of 6-deoxy-6[(5/6)-fluoresceinylthioureido]-HPBCD (FITC-NH-HPBCD) was used to estimate the logP value (≈ -2.5 to -3) of (2-hydroxypropyl)-ß-cyclodextrin (HPBCD). The results suggested that the amount of HPBCD can be considered to be inconsequential in the octanol phase. The decrease of octanol volume due to the octanol-CD complexation was considered, thus a corrected octanol-water phase ratio was also introduced. The K 1:1,CD values obtained by this developed method showed a good accordance with the results from other orthogonal methods. Copyright © 2018 Elsevier B.V. All rights reserved.
Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising.
Guixeres, Jaime; Bigné, Enrique; Ausín Azofra, Jose M; Alcañiz Raya, Mariano; Colomer Granero, Adrián; Fuentes Hurtado, Félix; Naranjo Ornedo, Valery
2017-01-01
The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube.
Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising
Directory of Open Access Journals (Sweden)
Jaime Guixeres
2017-10-01
Full Text Available The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking. Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy and estimate the number of online views (mean error of 0.199. The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube.
Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising
Guixeres, Jaime; Bigné, Enrique; Ausín Azofra, Jose M.; Alcañiz Raya, Mariano; Colomer Granero, Adrián; Fuentes Hurtado, Félix; Naranjo Ornedo, Valery
2017-01-01
The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube. PMID:29163251
Zimmerman, Marianna
1975-01-01
Describes a classroom activity which involved sixth grade students in a learning situation including making ice cream, safety procedures in a science laboratory, calibrating a thermometer, using metric units of volume and mass. (EB)
Energy Technology Data Exchange (ETDEWEB)
Liu, Yaou, E-mail: asiaeurope80@gmail.com [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Duan, Yunyun, E-mail: xiaoyun81.love@163.com [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); He, Yong, E-mail: yong.h.he@gmail.com [State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875 (China); Yu, Chunshui, E-mail: csyuster@gmail.com [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Wang, Jun, E-mail: jun_wang@bnu.edu.cn [State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875 (China); Huang, Jing, E-mail: sainthj@126.com [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Ye, Jing, E-mail: jingye.2007@yahoo.com.cn [Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Parizel, Paul M., E-mail: paul.parizel@ua.ac.be [Department of Radiology, Antwerp University Hospital and University of Antwerp, Wilrijkstraat 10, 2650 Edegem, 8 Belgium (Belgium); Li, Kuncheng, E-mail: kunchengli55@gmail.com [Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053 (China); Shu, Ni, E-mail: nshu55@gmail.com [State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875 (China)
2012-10-15
Objective: To investigate whole brain white matter changes in multiple sclerosis (MS) by multiple diffusion indices, we examined patients with diffusion tensor imaging and utilized tract-based spatial statistics (TBSS) method to analyze the data. Methods: Forty-one relapsing-remitting multiple sclerosis (RRMS) patients and 41 age- and gender-matched normal controls were included in this study. Diffusion weighted images were acquired by employing a single-shot echo planar imaging sequence on a 1.5 T MR scanner. Voxel-wise analyses of multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were performed with TBSS. Results: The MS patients had significantly decreased FA (9.11%), increased MD (8.26%), AD (3.48%) and RD (13.17%) in their white matter skeletons compared with the controls. Through TBSS analyses, we found abnormal diffusion changes in widespread white matter regions in MS patients. Specifically, decreased FA, increased MD and increased RD were involved in whole-brain white matter, while several regions exhibited increased AD. Furthermore, white matter regions with significant correlations between the diffusion metrics and the clinical variables (the EDSS scores, disease durations and white matter lesion loads) in MS patients were identified. Conclusion: Widespread white matter abnormalities were observed in MS patients revealed by multiple diffusion metrics. The diffusion changes and correlations with clinical variables were mainly attributed to increased RD, implying the predominant role of RD in reflecting the subtle pathological changes in MS.
International Nuclear Information System (INIS)
Liu, Yaou; Duan, Yunyun; He, Yong; Yu, Chunshui; Wang, Jun; Huang, Jing; Ye, Jing; Parizel, Paul M.; Li, Kuncheng; Shu, Ni
2012-01-01
Objective: To investigate whole brain white matter changes in multiple sclerosis (MS) by multiple diffusion indices, we examined patients with diffusion tensor imaging and utilized tract-based spatial statistics (TBSS) method to analyze the data. Methods: Forty-one relapsing-remitting multiple sclerosis (RRMS) patients and 41 age- and gender-matched normal controls were included in this study. Diffusion weighted images were acquired by employing a single-shot echo planar imaging sequence on a 1.5 T MR scanner. Voxel-wise analyses of multiple diffusion metrics, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were performed with TBSS. Results: The MS patients had significantly decreased FA (9.11%), increased MD (8.26%), AD (3.48%) and RD (13.17%) in their white matter skeletons compared with the controls. Through TBSS analyses, we found abnormal diffusion changes in widespread white matter regions in MS patients. Specifically, decreased FA, increased MD and increased RD were involved in whole-brain white matter, while several regions exhibited increased AD. Furthermore, white matter regions with significant correlations between the diffusion metrics and the clinical variables (the EDSS scores, disease durations and white matter lesion loads) in MS patients were identified. Conclusion: Widespread white matter abnormalities were observed in MS patients revealed by multiple diffusion metrics. The diffusion changes and correlations with clinical variables were mainly attributed to increased RD, implying the predominant role of RD in reflecting the subtle pathological changes in MS
Kovatchev, Boris P; Clarke, William L; Breton, Marc; Brayman, Kenneth; McCall, Anthony
2005-12-01
Continuous glucose monitors (CGMs) collect detailed blood glucose (BG) time series, which carry significant information about the dynamics of BG fluctuations. In contrast, the methods for analysis of CGM data remain those developed for infrequent BG self-monitoring. As a result, important information about the temporal structure of the data is lost during the translation of raw sensor readings into clinically interpretable statistics and images. The following mathematical methods are introduced into the field of CGM data interpretation: (1) analysis of BG rate of change; (2) risk analysis using previously reported Low/High BG Indices and Poincare (lag) plot of risk associated with temporal BG variability; and (3) spatial aggregation of the process of BG fluctuations and its Markov chain visualization. The clinical application of these methods is illustrated by analysis of data of a patient with Type 1 diabetes mellitus who underwent islet transplantation and with data from clinical trials. Normative data [12,025 reference (YSI device, Yellow Springs Instruments, Yellow Springs, OH) BG determinations] in patients with Type 1 diabetes mellitus who underwent insulin and glucose challenges suggest that the 90%, 95%, and 99% confidence intervals of BG rate of change that could be maximally sustained over 15-30 min are [-2,2], [-3,3], and [-4,4] mg/dL/min, respectively. BG dynamics and risk parameters clearly differentiated the stages of transplantation and the effects of medication. Aspects of treatment were clearly visualized by graphs of BG rate of change and Low/High BG Indices, by a Poincare plot of risk for rapid BG fluctuations, and by a plot of the aggregated Markov process. Advanced analysis and visualization of CGM data allow for evaluation of dynamical characteristics of diabetes and reveal clinical information that is inaccessible via standard statistics, which do not take into account the temporal structure of the data. The use of such methods improves the
Experiential space is hardly metric
Czech Academy of Sciences Publication Activity Database
Šikl, Radovan; Šimeček, Michal; Lukavský, Jiří
2008-01-01
Roč. 2008, č. 37 (2008), s. 58-58 ISSN 0301-0066. [European Conference on Visual Perception. 24.08-28.08.2008, Utrecht] R&D Projects: GA ČR GA406/07/1676 Institutional research plan: CEZ:AV0Z70250504 Keywords : visual space perception * metric and non-metric perceptual judgments * ecological validity Subject RIV: AN - Psychology
Coverage Metrics for Model Checking
Penix, John; Visser, Willem; Norvig, Peter (Technical Monitor)
2001-01-01
When using model checking to verify programs in practice, it is not usually possible to achieve complete coverage of the system. In this position paper we describe ongoing research within the Automated Software Engineering group at NASA Ames on the use of test coverage metrics to measure partial coverage and provide heuristic guidance for program model checking. We are specifically interested in applying and developing coverage metrics for concurrent programs that might be used to support certification of next generation avionics software.
Phantom metrics with Killing spinors
Directory of Open Access Journals (Sweden)
W.A. Sabra
2015-11-01
Full Text Available We study metric solutions of Einstein–anti-Maxwell theory admitting Killing spinors. The analogue of the IWP metric which admits a space-like Killing vector is found and is expressed in terms of a complex function satisfying the wave equation in flat (2+1-dimensional space–time. As examples, electric and magnetic Kasner spaces are constructed by allowing the solution to depend only on the time coordinate. Euclidean solutions are also presented.
An Analysis of Variable-Speed Wind Turbine Power-Control Methods with Fluctuating Wind Speed
Directory of Open Access Journals (Sweden)
Seung-Il Moon
2013-07-01
Full Text Available Variable-speed wind turbines (VSWTs typically use a maximum power-point tracking (MPPT method to optimize wind-energy acquisition. MPPT can be implemented by regulating the rotor speed or by adjusting the active power. The former, termed speed-control mode (SCM, employs a speed controller to regulate the rotor, while the latter, termed power-control mode (PCM, uses an active power controller to optimize the power. They are fundamentally equivalent; however, since they use a different controller at the outer control loop of the machine-side converter (MSC controller, the time dependence of the control system differs depending on whether SCM or PCM is used. We have compared and analyzed the power quality and the power coefficient when these two different control modes were used in fluctuating wind speeds through computer simulations. The contrast between the two methods was larger when the wind-speed fluctuations were greater. Furthermore, we found that SCM was preferable to PCM in terms of the power coefficient, but PCM was superior in terms of power quality and system stability.
Energy Technology Data Exchange (ETDEWEB)
Thompson, William L. [Bonneville Power Administration, Portland, OR (US). Environment, Fish and Wildlife
2001-07-01
Monitoring population numbers is important for assessing trends and meeting various legislative mandates. However, sampling across time introduces a temporal aspect to survey design in addition to the spatial one. For instance, a sample that is initially representative may lose this attribute if there is a shift in numbers and/or spatial distribution in the underlying population that is not reflected in later sampled plots. Plot selection methods that account for this temporal variability will produce the best trend estimates. Consequently, I used simulation to compare bias and relative precision of estimates of population change among stratified and unstratified sampling designs based on permanent, temporary, and partial replacement plots under varying levels of spatial clustering, density, and temporal shifting of populations. Permanent plots produced more precise estimates of change than temporary plots across all factors. Further, permanent plots performed better than partial replacement plots except for high density (5 and 10 individuals per plot) and 25% - 50% shifts in the population. Stratified designs always produced less precise estimates of population change for all three plot selection methods, and often produced biased change estimates and greatly inflated variance estimates under sampling with partial replacement. Hence, stratification that remains fixed across time should be avoided when monitoring populations that are likely to exhibit large changes in numbers and/or spatial distribution during the study period. Key words: bias; change estimation; monitoring; permanent plots; relative precision; sampling with partial replacement; temporary plots.
Directory of Open Access Journals (Sweden)
Qian Wang
2017-01-01
Full Text Available Different configurations of coupling strategies influence greatly the accuracy and convergence of the simulation results in the hybrid atomistic-continuum method. This study aims to quantitatively investigate this effect and offer the guidance on how to choose the proper configuration of coupling strategies in the hybrid atomistic-continuum method. We first propose a hybrid molecular dynamics- (MD- continuum solver in LAMMPS and OpenFOAM that exchanges state variables between the atomistic region and the continuum region and evaluate different configurations of coupling strategies using the sudden start Couette flow, aiming to find the preferable configuration that delivers better accuracy and efficiency. The major findings are as follows: (1 the C→A region plays the most important role in the overlap region and the “4-layer-1” combination achieves the best precision with a fixed width of the overlap region; (2 the data exchanging operation only needs a few sampling points closer to the occasions of interactions and decreasing the coupling exchange operations can reduce the computational load with acceptable errors; (3 the nonperiodic boundary force model with a smoothing parameter of 0.1 and a finer parameter of 20 can not only achieve the minimum disturbance near the MD-continuum interface but also keep the simulation precision.
Energy Technology Data Exchange (ETDEWEB)
Frew, Bethany A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Cole, Wesley J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mai, Trieu T [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Richards, James [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-08-01
Capacity expansion models (CEMs) are widely used to evaluate the least-cost portfolio of electricity generators, transmission, and storage needed to reliably serve demand over the evolution of many years or decades. Various CEM formulations are used to evaluate systems ranging in scale from states or utility service territories to national or multi-national systems. CEMs can be computationally complex, and to achieve acceptable solve times, key parameters are often estimated using simplified methods. In this paper, we focus on two of these key parameters associated with the integration of variable generation (VG) resources: capacity value and curtailment. We first discuss common modeling simplifications used in CEMs to estimate capacity value and curtailment, many of which are based on a representative subset of hours that can miss important tail events or which require assumptions about the load and resource distributions that may not match actual distributions. We then present an alternate approach that captures key elements of chronological operation over all hours of the year without the computationally intensive economic dispatch optimization typically employed within more detailed operational models. The updated methodology characterizes the (1) contribution of VG to system capacity during high load and net load hours, (2) the curtailment level of VG, and (3) the potential reductions in curtailments enabled through deployment of storage and more flexible operation of select thermal generators. We apply this alternate methodology to an existing CEM, the Regional Energy Deployment System (ReEDS). Results demonstrate that this alternate approach provides more accurate estimates of capacity value and curtailments by explicitly capturing system interactions across all hours of the year. This approach could be applied more broadly to CEMs at many different scales where hourly resource and load data is available, greatly improving the representation of challenges
Anisotropic rectangular metric for polygonal surface remeshing
Pellenard, Bertrand
2013-06-18
We propose a new method for anisotropic polygonal surface remeshing. Our algorithm takes as input a surface triangle mesh. An anisotropic rectangular metric, defined at each triangle facet of the input mesh, is derived from both a user-specified normal-based tolerance error and the requirement to favor rectangle-shaped polygons. Our algorithm uses a greedy optimization procedure that adds, deletes and relocates generators so as to match two criteria related to partitioning and conformity.
Anisotropic rectangular metric for polygonal surface remeshing
Pellenard, Bertrand; Morvan, Jean-Marie; Alliez, Pierre
2013-01-01
We propose a new method for anisotropic polygonal surface remeshing. Our algorithm takes as input a surface triangle mesh. An anisotropic rectangular metric, defined at each triangle facet of the input mesh, is derived from both a user-specified normal-based tolerance error and the requirement to favor rectangle-shaped polygons. Our algorithm uses a greedy optimization procedure that adds, deletes and relocates generators so as to match two criteria related to partitioning and conformity.
Metrics and Its Function in Poetry
Institute of Scientific and Technical Information of China (English)
XIAO Zhong-qiong; CHEN Min-jie
2013-01-01
Poetry is a special combination of musical and linguistic qualities-of sounds both regarded as pure sound and as mean-ingful speech. Part of the pleasure of poetry lies in its relationship with music. Metrics, including rhythm and meter, is an impor-tant method for poetry to express poetic sentiment. Through the introduction of poetic language and typical examples, the writer of this paper tries to discuss the relationship between sound and meaning.
Platelet-rich plasma differs according to preparation method and human variability.
Mazzocca, Augustus D; McCarthy, Mary Beth R; Chowaniec, David M; Cote, Mark P; Romeo, Anthony A; Bradley, James P; Arciero, Robert A; Beitzel, Knut
2012-02-15
Varying concentrations of blood components in platelet-rich plasma preparations may contribute to the variable results seen in recently published clinical studies. The purposes of this investigation were (1) to quantify the level of platelets, growth factors, red blood cells, and white blood cells in so-called one-step (clinically used commercial devices) and two-step separation systems and (2) to determine the influence of three separate blood draws on the resulting components of platelet-rich plasma. Three different platelet-rich plasma (PRP) separation methods (on blood samples from eight subjects with a mean age [and standard deviation] of 31.6 ± 10.9 years) were used: two single-spin processes (PRPLP and PRPHP) and a double-spin process (PRPDS) were evaluated for concentrations of platelets, red and white blood cells, and growth factors. Additionally, the effect of three repetitive blood draws on platelet-rich plasma components was evaluated. The content and concentrations of platelets, white blood cells, and growth factors for each method of separation differed significantly. All separation techniques resulted in a significant increase in platelet concentration compared with native blood. Platelet and white blood-cell concentrations of the PRPHP procedure were significantly higher than platelet and white blood-cell concentrations produced by the so-called single-step PRPLP and the so-called two-step PRPDS procedures, although significant differences between PRPLP and PRPDS were not observed. Comparing the results of the three blood draws with regard to the reliability of platelet number and cell counts, wide variations of intra-individual numbers were observed. Single-step procedures are capable of producing sufficient amounts of platelets for clinical usage. Within the evaluated procedures, platelet numbers and numbers of white blood cells differ significantly. The intra-individual results of platelet-rich plasma separations showed wide variations in
Image characterization metrics for muon tomography
Luo, Weidong; Lehovich, Andre; Anashkin, Edward; Bai, Chuanyong; Kindem, Joel; Sossong, Michael; Steiger, Matt
2014-05-01
Muon tomography uses naturally occurring cosmic rays to detect nuclear threats in containers. Currently there are no systematic image characterization metrics for muon tomography. We propose a set of image characterization methods to quantify the imaging performance of muon tomography. These methods include tests of spatial resolution, uniformity, contrast, signal to noise ratio (SNR) and vertical smearing. Simulated phantom data and analysis methods were developed to evaluate metric applicability. Spatial resolution was determined as the FWHM of the point spread functions in X, Y and Z axis for 2.5cm tungsten cubes. Uniformity was measured by drawing a volume of interest (VOI) within a large water phantom and defined as the standard deviation of voxel values divided by the mean voxel value. Contrast was defined as the peak signals of a set of tungsten cubes divided by the mean voxel value of the water background. SNR was defined as the peak signals of cubes divided by the standard deviation (noise) of the water background. Vertical smearing, i.e. vertical thickness blurring along the zenith axis for a set of 2 cm thick tungsten plates, was defined as the FWHM of vertical spread function for the plate. These image metrics provided a useful tool to quantify the basic imaging properties for muon tomography.
Hussain, Husniza; Khalid, Norhayati Mustafa; Selamat, Rusidah; Wan Nazaimoon, Wan Mohamud
2013-09-01
The urinary iodine micromethod (UIMM) is a modification of the conventional method and its performance needs evaluation. UIMM performance was evaluated using the method validation and 2008 Iodine Deficiency Disorders survey data obtained from four urinary iodine (UI) laboratories. Method acceptability tests and Sigma quality metrics were determined using total allowable errors (TEas) set by two external quality assurance (EQA) providers. UIMM obeyed various method acceptability test criteria with some discrepancies at low concentrations. Method validation data calculated against the UI Quality Program (TUIQP) TEas showed that the Sigma metrics were at 2.75, 1.80, and 3.80 for 51±15.50 µg/L, 108±32.40 µg/L, and 149±38.60 µg/L UI, respectively. External quality control (EQC) data showed that the performance of the laboratories was within Sigma metrics of 0.85-1.12, 1.57-4.36, and 1.46-4.98 at 46.91±7.05 µg/L, 135.14±13.53 µg/L, and 238.58±17.90 µg/L, respectively. No laboratory showed a calculated total error (TEcalc)Sigma metrics at all concentrations. Only one laboratory had TEcalc
Social Media Metrics Importance and Usage Frequency in Latvia
Ronalds Skulme
2017-01-01
Purpose of the article: The purpose of this paper was to explore which social media marketing metrics are most often used and are most important for marketing experts in Latvia and can be used to evaluate marketing campaign effectiveness. Methodology/methods: In order to achieve the aim of this paper several theoretical and practical research methods were used, such as theoretical literature analysis, surveying and grouping. First of all, theoretical research about social media metrics was...
The correlation between the connection and the metric as the ultraviolet finiteness condition
International Nuclear Information System (INIS)
Belokurov, V.V.
1990-07-01
Calculation of the ultraviolet counterterms of the bosonic affine-metric non-linear two-dimensional sigma-model are undertaken in order to illustrate a new type of the correlation between the metric and the connection. The peculiarity of the background field method and the normal coordinate expansion for affine-metric manifolds is discussed. (author). 18 refs, 9 figs
INFORMATIVE ENERGY METRIC FOR SIMILARITY MEASURE IN REPRODUCING KERNEL HILBERT SPACES
Directory of Open Access Journals (Sweden)
Songhua Liu
2012-02-01
Full Text Available In this paper, information energy metric (IEM is obtained by similarity computing for high-dimensional samples in a reproducing kernel Hilbert space (RKHS. Firstly, similar/dissimilar subsets and their corresponding informative energy functions are defined. Secondly, IEM is proposed for similarity measure of those subsets, which converts the non-metric distances into metric ones. Finally, applications of this metric is introduced, such as classification problems. Experimental results validate the effectiveness of the proposed method.
Scalar-metric and scalar-metric-torsion gravitational theories
International Nuclear Information System (INIS)
Aldersley, S.J.
1977-01-01
The techniques of dimensional analysis and of the theory of tensorial concomitants are employed to study field equations in gravitational theories which incorporate scalar fields of the Brans-Dicke type. Within the context of scalar-metric gravitational theories, a uniqueness theorem for the geometric (or gravitational) part of the field equations is proven and a Lagrangian is determined which is uniquely specified by dimensional analysis. Within the context of scalar-metric-torsion gravitational theories a uniqueness theorem for field Lagrangians is presented and the corresponding Euler-Lagrange equations are given. Finally, an example of a scalar-metric-torsion theory is presented which is similar in many respects to the Brans-Dicke theory and the Einstein-Cartan theory
Hauck, Yolande; Soler, Charles; Gérôme, Patrick; Vong, Rithy; Macnab, Christine; Appere, Géraldine; Vergnaud, Gilles; Pourcel, Christine
2015-07-01
Propionibacterium acnes plays a central role in the pathogenesis of acne and is responsible for severe opportunistic infections. Numerous typing schemes have been developed that allow the identification of phylotypes, but they are often insufficient to differentiate subtypes. To better understand the genetic diversity of this species and to perform epidemiological analyses, high throughput discriminant genotyping techniques are needed. Here we describe the development of a multiple locus variable number of tandem repeats (VNTR) analysis (MLVA) method. Thirteen VNTRs were identified in the genome of P. acnes and were used to genotype a collection of clinical isolates. In addition, publically available sequencing data for 102 genomes were analyzed in silico, providing an MLVA genotype. The clustering of MLVA data was in perfect congruence with whole genome based clustering. Analysis of the clustered regularly interspaced short palindromic repeat (CRISPR) element uncovered new spacers, a supplementary source of genotypic information. The present MLVA13 scheme and associated internet database represents a first line genotyping assay to investigate large number of isolates. Particular strains may then be submitted to full genome sequencing in order to better analyze their pathogenic potential. Copyright © 2015 Elsevier B.V. All rights reserved.
Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi
2018-04-01
Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.
Regge calculus from discontinuous metrics
International Nuclear Information System (INIS)
Khatsymovsky, V.M.
2003-01-01
Regge calculus is considered as a particular case of the more general system where the linklengths of any two neighbouring 4-tetrahedra do not necessarily coincide on their common face. This system is treated as that one described by metric discontinuous on the faces. In the superspace of all discontinuous metrics the Regge calculus metrics form some hypersurface defined by continuity conditions. Quantum theory of the discontinuous metric system is assumed to be fixed somehow in the form of quantum measure on (the space of functionals on) the superspace. The problem of reducing this measure to the Regge hypersurface is addressed. The quantum Regge calculus measure is defined from a discontinuous metric measure by inserting the δ-function-like phase factor. The requirement that continuity conditions be imposed in a 'face-independent' way fixes this factor uniquely. The term 'face-independent' means that this factor depends only on the (hyper)plane spanned by the face, not on it's form and size. This requirement seems to be natural from the viewpoint of existence of the well-defined continuum limit maximally free of lattice artefacts
Methods for the Quasi-Periodic Variability Analysis in Blazars Y. Liu ...
Indian Academy of Sciences (India)
the variability analysis in blazars in optical and radio bands, to search for possible quasi-periodic signals. 2. Power spectral density (PSD). In statistical signal processing and physics, the power spectral density (PSD) is a positive real function of a frequency variable associated with a stationary stochas- tic process. Intuitively ...
Price variability and marketing method in non-ferrous metals: Slade's analysis revisited
Gilbert, C.L.; Ferretti, F.
2002-01-01
We examine the impact of the pricing regime on price variability with reference to the non-ferrous metals industry. Theoretical arguments are ambiguous, but suggest that the extent of monopoly power is more important than the pricing regime as a determinant of variability. Slade (Quart. J. Econ. 106
van der Burg, Eeke; de Leeuw, Jan; Verdegaal, Renée
1988-01-01
Homogeneity analysis, or multiple correspondence analysis, is usually applied tok separate variables. In this paper we apply it to sets of variables by using sums within sets. The resulting technique is called OVERALS. It uses the notion of optimal scaling, with transformations that can be multiple
Directory of Open Access Journals (Sweden)
Zedong Bi
2016-08-01
Full Text Available Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded, by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy.
Symmetries of Taub-NUT dual metrics
International Nuclear Information System (INIS)
Baleanu, D.; Codoban, S.
1998-01-01
Recently geometric duality was analyzed for a metric which admits Killing tensors. An interesting example arises when the manifold has Killing-Yano tensors. The symmetries of the dual metrics in the case of Taub-NUT metric are investigated. Generic and non-generic symmetries of dual Taub-NUT metric are analyzed
International Nuclear Information System (INIS)
Pyun, J.J.
1981-01-01
As part of an effort to incorporate the variable Eulerian mesh into the second-order PIC computational method, a truncation error analysis was performed to calculate the second-order error terms for the variable Eulerian mesh system. The results that the maximum mesh size increment/decrement is limited to be α(Δr/sub i/) 2 where Δr/sub i/ is a non-dimensional mesh size of the ith cell, and α is a constant of order one. The numerical solutions of Burgers' equation by the second-order PIC method in the variable Eulerian mesh system wer compared with its exact solution. It was found that the second-order accuracy in the PIC method was maintained under the above condition. Additional problems were analyzed using the second-order PIC methods in both variable and uniform Eulerian mesh systems. The results indicate that the second-order PIC method in the variable Eulerian mesh system can provide substantial computational time saving with no loss in accuracy
International Nuclear Information System (INIS)
Vaidya, P.C.; Patel, L.K.; Bhatt, P.V.
1976-01-01
Using Galilean time and retarded distance as coordinates the usual Kerr metric is expressed in form similar to the Newman-Unti-Tamburino (NUT) metric. The combined Kerr-NUT metric is then investigated. In addition to the Kerr and NUT solutions of Einstein's equations, three other types of solutions are derived. These are (i) the radiating Kerr solution, (ii) the radiating NUT solution satisfying Rsub(ik) = sigmaxisub(i)xisub(k), xisub(i)xisup(i) = 0, and (iii) the associated Kerr solution satisfying Rsub(ik) = 0. Solution (i) is distinct from and simpler than the one reported earlier by Vaidya and Patel (Phys. Rev.; D7:3590 (1973)). Solutions (ii) and (iii) gave line elements which have the axis of symmetry as a singular line. (author)
Complexity Metrics for Workflow Nets
DEFF Research Database (Denmark)
Lassen, Kristian Bisgaard; van der Aalst, Wil M.P.
2009-01-01
analysts have difficulties grasping the dynamics implied by a process model. Recent empirical studies show that people make numerous errors when modeling complex business processes, e.g., about 20 percent of the EPCs in the SAP reference model have design flaws resulting in potential deadlocks, livelocks......, etc. It seems obvious that the complexity of the model contributes to design errors and a lack of understanding. It is not easy to measure complexity, however. This paper presents three complexity metrics that have been implemented in the process analysis tool ProM. The metrics are defined...... for a subclass of Petri nets named Workflow nets, but the results can easily be applied to other languages. To demonstrate the applicability of these metrics, we have applied our approach and tool to 262 relatively complex Protos models made in the context of various student projects. This allows us to validate...
Energy-Based Metrics for Arthroscopic Skills Assessment.
Poursartip, Behnaz; LeBel, Marie-Eve; McCracken, Laura C; Escoto, Abelardo; Patel, Rajni V; Naish, Michael D; Trejos, Ana Luisa
2017-08-05
Minimally invasive skills assessment methods are essential in developing efficient surgical simulators and implementing consistent skills evaluation. Although numerous methods have been investigated in the literature, there is still a need to further improve the accuracy of surgical skills assessment. Energy expenditure can be an indication of motor skills proficiency. The goals of this study are to develop objective metrics based on energy expenditure, normalize these metrics, and investigate classifying trainees using these metrics. To this end, different forms of energy consisting of mechanical energy and work were considered and their values were divided by the related value of an ideal performance to develop normalized metrics. These metrics were used as inputs for various machine learning algorithms including support vector machines (SVM) and neural networks (NNs) for classification. The accuracy of the combination of the normalized energy-based metrics with these classifiers was evaluated through a leave-one-subject-out cross-validation. The proposed method was validated using 26 subjects at two experience levels (novices and experts) in three arthroscopic tasks. The results showed that there are statistically significant differences between novices and experts for almost all of the normalized energy-based metrics. The accuracy of classification using SVM and NN methods was between 70% and 95% for the various tasks. The results show that the normalized energy-based metrics and their combination with SVM and NN classifiers are capable of providing accurate classification of trainees. The assessment method proposed in this study can enhance surgical training by providing appropriate feedback to trainees about their level of expertise and can be used in the evaluation of proficiency.
Empirical Information Metrics for Prediction Power and Experiment Planning
Directory of Open Access Journals (Sweden)
Christopher Lee
2011-01-01
Full Text Available In principle, information theory could provide useful metrics for statistical inference. In practice this is impeded by divergent assumptions: Information theory assumes the joint distribution of variables of interest is known, whereas in statistical inference it is hidden and is the goal of inference. To integrate these approaches we note a common theme they share, namely the measurement of prediction power. We generalize this concept as an information metric, subject to several requirements: Calculation of the metric must be objective or model-free; unbiased; convergent; probabilistically bounded; and low in computational complexity. Unfortunately, widely used model selection metrics such as Maximum Likelihood, the Akaike Information Criterion and Bayesian Information Criterion do not necessarily meet all these requirements. We define four distinct empirical information metrics measured via sampling, with explicit Law of Large Numbers convergence guarantees, which meet these requirements: Ie, the empirical information, a measure of average prediction power; Ib, the overfitting bias information, which measures selection bias in the modeling procedure; Ip, the potential information, which measures the total remaining information in the observations not yet discovered by the model; and Im, the model information, which measures the model’s extrapolation prediction power. Finally, we show that Ip + Ie, Ip + Im, and Ie — Im are fixed constants for a given observed dataset (i.e. prediction target, independent of the model, and thus represent a fundamental subdivision of the total information contained in the observations. We discuss the application of these metrics to modeling and experiment planning.
Model assessment using a multi-metric ranking technique
Fitzpatrick, P. J.; Lau, Y.; Alaka, G.; Marks, F.
2017-12-01
Validation comparisons of multiple models presents challenges when skill levels are similar, especially in regimes dominated by the climatological mean. Assessing skill separation will require advanced validation metrics and identifying adeptness in extreme events, but maintain simplicity for management decisions. Flexibility for operations is also an asset. This work postulates a weighted tally and consolidation technique which ranks results by multiple types of metrics. Variables include absolute error, bias, acceptable absolute error percentages, outlier metrics, model efficiency, Pearson correlation, Kendall's Tau, reliability Index, multiplicative gross error, and root mean squared differences. Other metrics, such as root mean square difference and rank correlation were also explored, but removed when the information was discovered to be generally duplicative to other metrics. While equal weights are applied, weights could be altered depending for preferred metrics. Two examples are shown comparing ocean models' currents and tropical cyclone products, including experimental products. The importance of using magnitude and direction for tropical cyclone track forecasts instead of distance, along-track, and cross-track are discussed. Tropical cyclone intensity and structure prediction are also assessed. Vector correlations are not included in the ranking process, but found useful in an independent context, and will be briefly reported.
Feng, Yong; Chen, Aiqing
2017-01-01
This study aimed to quantify blood pressure (BP) measurement accuracy and variability with different techniques. Thirty video clips of BP recordings from the BHS training database were converted to Korotkoff sound waveforms. Ten observers without receiving medical training were asked to determine BPs using (a) traditional manual auscultatory method and (b) visual auscultation method by visualizing the Korotkoff sound waveform, which was repeated three times on different days. The measurement error was calculated against the reference answers, and the measurement variability was calculated from the SD of the three repeats. Statistical analysis showed that, in comparison with the auscultatory method, visual method significantly reduced overall variability from 2.2 to 1.1 mmHg for SBP and from 1.9 to 0.9 mmHg for DBP (both p auscultation methods). In conclusion, the visual auscultation method had the ability to achieve an acceptable degree of BP measurement accuracy, with smaller variability in comparison with the traditional auscultatory method. PMID:29423405
Research on cardiovascular disease prediction based on distance metric learning
Ni, Zhuang; Liu, Kui; Kang, Guixia
2018-04-01
Distance metric learning algorithm has been widely applied to medical diagnosis and exhibited its strengths in classification problems. The k-nearest neighbour (KNN) is an efficient method which treats each feature equally. The large margin nearest neighbour classification (LMNN) improves the accuracy of KNN by learning a global distance metric, which did not consider the locality of data distributions. In this paper, we propose a new distance metric algorithm adopting cosine metric and LMNN named COS-SUBLMNN which takes more care about local feature of data to overcome the shortage of LMNN and improve the classification accuracy. The proposed methodology is verified on CVDs patient vector derived from real-world medical data. The Experimental results show that our method provides higher accuracy than KNN and LMNN did, which demonstrates the effectiveness of the Risk predictive model of CVDs based on COS-SUBLMNN.
The uniqueness of the Fisher metric as information metric
Czech Academy of Sciences Publication Activity Database
Le, Hong-Van
2017-01-01
Roč. 69, č. 4 (2017), s. 879-896 ISSN 0020-3157 Institutional support: RVO:67985840 Keywords : Chentsov’s theorem * mixed topology * monotonicity of the Fisher metric Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 1.049, year: 2016 https://link.springer.com/article/10.1007%2Fs10463-016-0562-0
Thermodynamic metrics and optimal paths.
Sivak, David A; Crooks, Gavin E
2012-05-11
A fundamental problem in modern thermodynamics is how a molecular-scale machine performs useful work, while operating away from thermal equilibrium without excessive dissipation. To this end, we derive a friction tensor that induces a Riemannian manifold on the space of thermodynamic states. Within the linear-response regime, this metric structure controls the dissipation of finite-time transformations, and bestows optimal protocols with many useful properties. We discuss the connection to the existing thermodynamic length formalism, and demonstrate the utility of this metric by solving for optimal control parameter protocols in a simple nonequilibrium model.
Energy Technology Data Exchange (ETDEWEB)
Romberger, Jeff [SBW Consulting, Inc., Bellevue, WA (United States)
2017-06-21
An adjustable-speed drive (ASD) includes all devices that vary the speed of a rotating load, including those that vary the motor speed and linkage devices that allow constant motor speed while varying the load speed. The Variable Frequency Drive Evaluation Protocol presented here addresses evaluation issues for variable-frequency drives (VFDs) installed on commercial and industrial motor-driven centrifugal fans and pumps for which torque varies with speed. Constant torque load applications, such as those for positive displacement pumps, are not covered by this protocol.
Fermionization of chiral string determinants in factorizable metrics
International Nuclear Information System (INIS)
Iengo, R.; Ivanov, B.
1987-11-01
We use fermionization, defined as a change of variables in the functional integration, to find chiral determinants of the string integrand in any holomorphically factorizable metric. In this way we derive and generalize the formulae proposed by Knizhnik and clarify their relation to those of Eguchi, Ooguri and Verlinde, Verlinde. (author). 20 refs
Prediction of water temperature metrics using spatial modelling in ...
African Journals Online (AJOL)
Water temperature regime dynamics should be viewed regionally, where regional divisions have an inherent underpinning by an understanding of natural thermal variability. The aim of this research was to link key water temperature metrics to readily-mapped environmental surrogates, and to produce spatial images of ...
Technical Privacy Metrics: a Systematic Survey
Wagner, Isabel; Eckhoff, David
2018-01-01
The file attached to this record is the author's final peer reviewed version The goal of privacy metrics is to measure the degree of privacy enjoyed by users in a system and the amount of protection offered by privacy-enhancing technologies. In this way, privacy metrics contribute to improving user privacy in the digital world. The diversity and complexity of privacy metrics in the literature makes an informed choice of metrics challenging. As a result, instead of using existing metrics, n...
Directory of Open Access Journals (Sweden)
Bessem Samet
2013-01-01
Full Text Available In 2005, Mustafa and Sims (2006 introduced and studied a new class of generalized metric spaces, which are called G-metric spaces, as a generalization of metric spaces. We establish some useful propositions to show that many fixed point theorems on (nonsymmetric G-metric spaces given recently by many authors follow directly from well-known theorems on metric spaces. Our technique can be easily extended to other results as shown in application.
DLA Energy Biofuel Feedstock Metrics Study
2012-12-11
moderately/highly in- vasive Metric 2: Genetically modified organism ( GMO ) hazard, Yes/No and Hazard Category Metric 3: Species hybridization...4– biofuel distribution Stage # 5– biofuel use Metric 1: State inva- siveness ranking Yes Minimal Minimal No No Metric 2: GMO hazard Yes...may utilize GMO microbial or microalgae species across the applicable biofuel life cycles (stages 1–3). The following consequence Metrics 4–6 then
Reconstructing an economic space from a market metric
Mendes, R. Vilela; Araújo, Tanya; Louçã, Francisco
2002-01-01
Using a metric related to the returns correlation, a method is proposed to reconstruct an economic space from the market data. A reduced subspace, associated to the systematic structure of the market, is identified and its dimension related to the number of terms in factor models. Example were worked out involving sets of companies from the DJIA and S&P500 indexes. Having a metric defined in the space of companies, network topology coefficients may be used to extract further information from ...
User Metrics in NASA Earth Science Data Systems
Lynnes, Chris
2018-01-01
This presentation the collection and use of user metrics in NASA's Earth Science data systems. A variety of collection methods is discussed, with particular emphasis given to the American Customer Satisfaction Index (ASCI). User sentiment on potential use of cloud computing is presented, with generally positive responses. The presentation also discusses various forms of automatically collected metrics, including an example of the relative usage of different functions within the Giovanni analysis system.
Smith, Aimée C; Roberts, Jonathan R; Wallace, Eric S; Kong, Pui; Forrester, Stephanie E
2016-02-01
Two-dimensional methods have been used to compute trunk kinematic variables (flexion/extension, lateral bend, axial rotation) and X-factor (difference in axial rotation between trunk and pelvis) during the golf swing. Recent X-factor studies advocated three-dimensional (3D) analysis due to the errors associated with two-dimensional (2D) methods, but this has not been investigated for all trunk kinematic variables. The purpose of this study was to compare trunk kinematic variables and X-factor calculated by 2D and 3D methods to examine how different approaches influenced their profiles during the swing. Trunk kinematic variables and X-factor were calculated for golfers from vectors projected onto the global laboratory planes and from 3D segment angles. Trunk kinematic variable profiles were similar in shape; however, there were statistically significant differences in trunk flexion (-6.5 ± 3.6°) at top of backswing and trunk right-side lateral bend (8.7 ± 2.9°) at impact. Differences between 2D and 3D X-factor (approximately 16°) could largely be explained by projection errors introduced to the 2D analysis through flexion and lateral bend of the trunk and pelvis segments. The results support the need to use a 3D method for kinematic data calculation to accurately analyze the golf swing.
Hoffmann, Sebastian
2015-01-01
The development of non-animal skin sensitization test methods and strategies is quickly progressing. Either individually or in combination, the predictive capacity is usually described in comparison to local lymph node assay (LLNA) results. In this process the important lesson from other endpoints, such as skin or eye irritation, to account for variability reference test results - here the LLNA - has not yet been fully acknowledged. In order to provide assessors as well as method and strategy developers with appropriate estimates, we investigated the variability of EC3 values from repeated substance testing using the publicly available NICEATM (NTP Interagency Center for the Evaluation of Alternative Toxicological Methods) LLNA database. Repeat experiments for more than 60 substances were analyzed - once taking the vehicle into account and once combining data over all vehicles. In general, variability was higher when different vehicles were used. In terms of skin sensitization potential, i.e., discriminating sensitizer from non-sensitizers, the false positive rate ranged from 14-20%, while the false negative rate was 4-5%. In terms of skin sensitization potency, the rate to assign a substance to the next higher or next lower potency class was approx.10-15%. In addition, general estimates for EC3 variability are provided that can be used for modelling purposes. With our analysis we stress the importance of considering the LLNA variability in the assessment of skin sensitization test methods and strategies and provide estimates thereof.
Socio-technical security metrics
Gollmann, D.; Herley, C.; Koenig, V.; Pieters, W.; Sasse, M.A.
2015-01-01
Report from Dagstuhl seminar 14491. This report documents the program and the outcomes of Dagstuhl Seminar 14491 “Socio-Technical Security Metrics”. In the domain of safety, metrics inform many decisions, from the height of new dikes to the design of nuclear plants. We can state, for example, that
Leading Gainful Employment Metric Reporting
Powers, Kristina; MacPherson, Derek
2016-01-01
This chapter will address the importance of intercampus involvement in reporting of gainful employment student-level data that will be used in the calculation of gainful employment metrics by the U.S. Department of Education. The authors will discuss why building relationships within the institution is critical for effective gainful employment…
Directory of Open Access Journals (Sweden)
Wen-ku Shi
2016-01-01
Full Text Available The composite stiffness of parabolic leaf springs with variable stiffness is difficult to calculate using traditional integral equations. Numerical integration or FEA may be used but will require computer-aided software and long calculation times. An efficient method for calculating the composite stiffness of parabolic leaf springs with variable stiffness is developed and evaluated to reduce the complexity of calculation and shorten the calculation time. A simplified model for double-leaf springs with variable stiffness is built, and a composite stiffness calculation method for the model is derived using displacement superposition and material deformation continuity. The proposed method can be applied on triple-leaf and multileaf springs. The accuracy of the calculation method is verified by the rig test and FEA analysis. Finally, several parameters that should be considered during the design process of springs are discussed. The rig test and FEA analytical results indicate that the calculated results are acceptable. The proposed method can provide guidance for the design and production of parabolic leaf springs with variable stiffness. The composite stiffness of the leaf spring can be calculated quickly and accurately when the basic parameters of the leaf spring are known.
Modified Pressure-Correction Projection Methods: Open Boundary and Variable Time Stepping
Bonito, Andrea
2014-10-31
© Springer International Publishing Switzerland 2015. In this paper, we design and study two modifications of the first order standard pressure increment projection scheme for the Stokes system. The first scheme improves the existing schemes in the case of open boundary condition by modifying the pressure increment boundary condition, thereby minimizing the pressure boundary layer and recovering the optimal first order decay. The second scheme allows for variable time stepping. It turns out that the straightforward modification to variable time stepping leads to unstable schemes. The proposed scheme is not only stable but also exhibits the optimal first order decay. Numerical computations illustrating the theoretical estimates are provided for both new schemes.
Modified Pressure-Correction Projection Methods: Open Boundary and Variable Time Stepping
Bonito, Andrea; Guermond, Jean-Luc; Lee, Sanghyun
2014-01-01
© Springer International Publishing Switzerland 2015. In this paper, we design and study two modifications of the first order standard pressure increment projection scheme for the Stokes system. The first scheme improves the existing schemes in the case of open boundary condition by modifying the pressure increment boundary condition, thereby minimizing the pressure boundary layer and recovering the optimal first order decay. The second scheme allows for variable time stepping. It turns out that the straightforward modification to variable time stepping leads to unstable schemes. The proposed scheme is not only stable but also exhibits the optimal first order decay. Numerical computations illustrating the theoretical estimates are provided for both new schemes.
Energy Technology Data Exchange (ETDEWEB)
Schafer, Alexandro G. [Universidade Federal do Pampa (UNIPAMPA), Bage, RS (Brazil)
2009-07-01
There are several methods for the risk assessment and risk management applied to pipelines, among them the Muhlbauer's Method. Muhlbauer is an internationally recognized authority on pipeline risk management. The purpose of this model is to evaluate the public exposure to the risk and identify ways for management that risk in fact. The assessment is made by the attribution of quantitative values to the several items that influences in the pipeline risk. Because the ultimate goal of the risk assessment is to provide a means of risk management, it is sometimes useful to make a distinction between two types of risk variables. The risk evaluator can categorize each index risk variable as either an attribute or a prevention. This paper approaches the subject of the definition of attributes and preventions in the Muhlbauer basic model of risk assessment and also presents a classification of the variables that influence the risk in agreement with those two categories. (author)
Green Chemistry Metrics with Special Reference to Green Analytical Chemistry
Directory of Open Access Journals (Sweden)
Marek Tobiszewski
2015-06-01
Full Text Available The concept of green chemistry is widely recognized in chemical laboratories. To properly measure an environmental impact of chemical processes, dedicated assessment tools are required. This paper summarizes the current state of knowledge in the field of development of green chemistry and green analytical chemistry metrics. The diverse methods used for evaluation of the greenness of organic synthesis, such as eco-footprint, E-Factor, EATOS, and Eco-Scale are described. Both the well-established and recently developed green analytical chemistry metrics, including NEMI labeling and analytical Eco-scale, are presented. Additionally, this paper focuses on the possibility of the use of multivariate statistics in evaluation of environmental impact of analytical procedures. All the above metrics are compared and discussed in terms of their advantages and disadvantages. The current needs and future perspectives in green chemistry metrics are also discussed.
Green Chemistry Metrics with Special Reference to Green Analytical Chemistry.
Tobiszewski, Marek; Marć, Mariusz; Gałuszka, Agnieszka; Namieśnik, Jacek
2015-06-12
The concept of green chemistry is widely recognized in chemical laboratories. To properly measure an environmental impact of chemical processes, dedicated assessment tools are required. This paper summarizes the current state of knowledge in the field of development of green chemistry and green analytical chemistry metrics. The diverse methods used for evaluation of the greenness of organic synthesis, such as eco-footprint, E-Factor, EATOS, and Eco-Scale are described. Both the well-established and recently developed green analytical chemistry metrics, including NEMI labeling and analytical Eco-scale, are presented. Additionally, this paper focuses on the possibility of the use of multivariate statistics in evaluation of environmental impact of analytical procedures. All the above metrics are compared and discussed in terms of their advantages and disadvantages. The current needs and future perspectives in green chemistry metrics are also discussed.
Landscape metrics for three-dimension urban pattern recognition
Liu, M.; Hu, Y.; Zhang, W.; Li, C.
2017-12-01
Understanding how landscape pattern determines population or ecosystem dynamics is crucial for managing our landscapes. Urban areas are becoming increasingly dominant social-ecological systems, so it is important to understand patterns of urbanization. Most studies of urban landscape pattern examine land-use maps in two dimensions because the acquisition of 3-dimensional information is difficult. We used Brista software based on Quickbird images and aerial photos to interpret the height of buildings, thus incorporating a 3-dimensional approach. We estimated the feasibility and accuracy of this approach. A total of 164,345 buildings in the Liaoning central urban agglomeration of China, which included seven cities, were measured. Twelve landscape metrics were proposed or chosen to describe the urban landscape patterns in 2- and 3-dimensional scales. The ecological and social meaning of landscape metrics were analyzed with multiple correlation analysis. The results showed that classification accuracy compared with field surveys was 87.6%, which means this method for interpreting building height was acceptable. The metrics effectively reflected the urban architecture in relation to number of buildings, area, height, 3-D shape and diversity aspects. We were able to describe the urban characteristics of each city with these metrics. The metrics also captured ecological and social meanings. The proposed landscape metrics provided a new method for urban landscape analysis in three dimensions.
International Nuclear Information System (INIS)
Ka-Lin, Su; Yuan-Xi, Xie
2010-01-01
By introducing a more general auxiliary ordinary differential equation (ODE), a modified variable separated ordinary differential equation method is presented for solving the (2 + 1)-dimensional sine-Poisson equation. As a result, many explicit and exact solutions of the (2 + 1)-dimensional sine-Poisson equation are derived in a simple manner by this technique. (general)
Variable order one-step methods for initial value problems I ...
African Journals Online (AJOL)
A class of variable order one-step integrators is proposed for Initial Value Problems (IVPs) in Ordinary Differential Equations (ODEs). It is based on a rational interpolant. Journal of the Nigerian Association of Mathematical Physics Vol. 10 2006: pp. 91-96 ...
SIMULATED PERFORMANCE OF TIMESCALE METRICS FOR APERIODIC LIGHT CURVES
Energy Technology Data Exchange (ETDEWEB)
Findeisen, Krzysztof; Hillenbrand, Lynne [Cahill Center for Astronomy and Astrophysics, California Institute of Technology, MC 249-17, Pasadena, CA 91125 (United States); Cody, Ann Marie, E-mail: krzys@astro.caltech.edu [Spitzer Science Center, California Institute of Technology, MC 314-6, Pasadena, CA 91125 (United States)
2015-01-10
Aperiodic variability is a characteristic feature of young stars, massive stars, and active galactic nuclei. With the recent proliferation of time-domain surveys, it is increasingly essential to develop methods to quantify and analyze aperiodic variability. We develop three timescale metrics that have been little used in astronomy—Δm-Δt plots, peak-finding, and Gaussian process regression—and present simulations comparing their effectiveness across a range of aperiodic light curve shapes, characteristic timescales, observing cadences, and signal to noise ratios. We find that Gaussian process regression is easily confused by noise and by irregular sampling, even when the model being fit reflects the process underlying the light curve, but that Δm-Δt plots and peak-finding can coarsely characterize timescales across a broad region of parameter space. We make public the software we used for our simulations, both in the spirit of open research and to allow others to carry out analogous simulations for their own observing programs.
SIMULATED PERFORMANCE OF TIMESCALE METRICS FOR APERIODIC LIGHT CURVES
International Nuclear Information System (INIS)
Findeisen, Krzysztof; Hillenbrand, Lynne; Cody, Ann Marie
2015-01-01
Aperiodic variability is a characteristic feature of young stars, massive stars, and active galactic nuclei. With the recent proliferation of time-domain surveys, it is increasingly essential to develop methods to quantify and analyze aperiodic variability. We develop three timescale metrics that have been little used in astronomy—Δm-Δt plots, peak-finding, and Gaussian process regression—and present simulations comparing their effectiveness across a range of aperiodic light curve shapes, characteristic timescales, observing cadences, and signal to noise ratios. We find that Gaussian process regression is easily confused by noise and by irregular sampling, even when the model being fit reflects the process underlying the light curve, but that Δm-Δt plots and peak-finding can coarsely characterize timescales across a broad region of parameter space. We make public the software we used for our simulations, both in the spirit of open research and to allow others to carry out analogous simulations for their own observing programs
Measuring Success: Metrics that Link Supply Chain Management to Aircraft Readiness
National Research Council Canada - National Science Library
Balestreri, William
2002-01-01
This thesis evaluates and analyzes current strategic management planning methods that develop performance metrics linking supply chain management to aircraft readiness, Our primary focus is the Marine...
Directory of Open Access Journals (Sweden)
Hukharnsusatrue, A.
2005-11-01
Full Text Available The objective of this research is to compare multiple regression coefficients estimating methods with existence of multicollinearity among independent variables. The estimation methods are Ordinary Least Squares method (OLS, Restricted Least Squares method (RLS, Restricted Ridge Regression method (RRR and Restricted Liu method (RL when restrictions are true and restrictions are not true. The study used the Monte Carlo Simulation method. The experiment was repeated 1,000 times under each situation. The analyzed results of the data are demonstrated as follows. CASE 1: The restrictions are true. In all cases, RRR and RL methods have a smaller Average Mean Square Error (AMSE than OLS and RLS method, respectively. RRR method provides the smallest AMSE when the level of correlations is high and also provides the smallest AMSE for all level of correlations and all sample sizes when standard deviation is equal to 5. However, RL method provides the smallest AMSE when the level of correlations is low and middle, except in the case of standard deviation equal to 3, small sample sizes, RRR method provides the smallest AMSE.The AMSE varies with, most to least, respectively, level of correlations, standard deviation and number of independent variables but inversely with to sample size.CASE 2: The restrictions are not true.In all cases, RRR method provides the smallest AMSE, except in the case of standard deviation equal to 1 and error of restrictions equal to 5%, OLS method provides the smallest AMSE when the level of correlations is low or median and there is a large sample size, but the small sample sizes, RL method provides the smallest AMSE. In addition, when error of restrictions is increased, OLS method provides the smallest AMSE for all level, of correlations and all sample sizes, except when the level of correlations is high and sample sizes small. Moreover, the case OLS method provides the smallest AMSE, the most RLS method has a smaller AMSE than
Multi-Robot Assembly Strategies and Metrics
MARVEL, JEREMY A.; BOSTELMAN, ROGER; FALCO, JOE
2018-01-01
We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles. In this survey, we identify the types of assemblies that are enabled by utilizing multiple robots, the algorithms that synchronize the motions of the robots to complete the assembly operations, and the metrics used to assess the quality and performance of the assemblies. PMID:29497234
Multi-Robot Assembly Strategies and Metrics.
Marvel, Jeremy A; Bostelman, Roger; Falco, Joe
2018-02-01
We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles. In this survey, we identify the types of assemblies that are enabled by utilizing multiple robots, the algorithms that synchronize the motions of the robots to complete the assembly operations, and the metrics used to assess the quality and performance of the assemblies.
Quilty, J.; Adamowski, J. F.
2015-12-01
Urban water supply systems are often stressed during seasonal outdoor water use as water demands related to the climate are variable in nature making it difficult to optimize the operation of the water supply system. Urban water demand forecasts (UWD) failing to include meteorological conditions as inputs to the forecast model may produce poor forecasts as they cannot account for the increase/decrease in demand related to meteorological conditions. Meteorological records stochastically simulated into the future can be used as inputs to data-driven UWD forecasts generally resulting in improved forecast accuracy. This study aims to produce data-driven UWD forecasts for two different Canadian water utilities (Montreal and Victoria) using machine learning methods by first selecting historical UWD and meteorological records derived from a stochastic weather generator using nonlinear input variable selection. The nonlinear input variable selection methods considered in this work are derived from the concept of conditional mutual information, a nonlinear dependency measure based on (multivariate) probability density functions and accounts for relevancy, conditional relevancy, and redundancy from a potential set of input variables. The results of our study indicate that stochastic weather inputs can improve UWD forecast accuracy for the two sites considered in this work. Nonlinear input variable selection is suggested as a means to identify which meteorological conditions should be utilized in the forecast.
Aubert, A. H.; Tavenard, R.; Emonet, R.; De Lavenne, A.; Malinowski, S.; Guyet, T.; Quiniou, R.; Odobez, J.; Merot, P.; Gascuel-odoux, C.
2013-12-01
Studying floods has been a major issue in hydrological research for years, both in quantitative and qualitative hydrology. Stream chemistry is a mix of solutes, often used as tracers, as they originate from various sources in the catchment and reach the stream by various flow pathways. Previous studies (for instance (1)) hypothesized that stream chemistry reaction to a rainfall event is not unique but varies seasonally, and according to the yearly meteorological conditions. Identifying a typology of flood temporal chemical patterns is a way to better understand catchment processes at the flood and seasonal time scale. We applied a probabilistic model (Latent Dirichlet Allocation or LDA (2)) mining recurrent sequential patterns from a dataset of floods. A set of 472 floods was automatically extracted from a daily 12-year long record of nitrate, dissolved organic carbon, sulfate and chloride concentrations. Rainfall, discharge, water table depth and temperature are also considered. Data comes from a long-term hydrological observatory (AgrHys, western France) located at Kervidy-Naizin. From each flood, a document has been generated that is made of a set of "hydrological words". Each hydrological word corresponds to a measurement: it is a triplet made of the considered variable, the time at which the measurement is made (relative to the beginning of the flood), and its magnitude (that can be low, medium or high). The documents and the number of pattern to be mined are used as input data to the LDA algorithm. LDA relies on spotting co-occurrences (as an alternative to the more traditional study of correlation) between words that appear within the flood documents. It has two nice properties that are its ability to easily deal with missing data and its additive property that allows a document to be seen as a mixture of several flood patterns. The output of LDA is a set of patterns easily represented in graphics. These patterns correspond to typical reactions to rainfall
A Method to Derive Monitoring Variables for a Cyber Security Test-bed of I and C System
International Nuclear Information System (INIS)
Han, Kyung Soo; Song, Jae Gu; Lee, Joung Woon; Lee, Cheol Kwon
2013-01-01
In the IT field, monitoring techniques have been developed to protect the systems connected by networks from cyber attacks and incidents. For the development of monitoring systems for I and C cyber security, it is necessary to review the monitoring systems in the IT field and derive cyber security-related monitoring variables among the proprietary operating information about the I and C systems. Tests for the development and application of these monitoring systems may cause adverse effects on the I and C systems. To analyze influences on the system and safely intended variables, the construction of an I and C system Test-bed should be preceded. This article proposes a method of deriving variables that should be monitored through a monitoring system for cyber security as a part of I and C Test-bed. The surveillance features and the monitored variables of NMS(Network Management System), a monitoring technique in the IT field, were reviewed in section 2. In Section 3, the monitoring variables for an I and C cyber security were derived by the of NMS and the investigation for information used for hacking techniques that can be practiced against I and C systems. The monitoring variables of NMS in the IT field and the information about the malicious behaviors used for hacking were derived as expected variables to be monitored for an I and C cyber security research. The derived monitoring variables were classified into the five functions of NMS for efficient management. For the cyber security of I and C systems, the vulnerabilities should be understood through a penetration test etc. and an assessment of influences on the actual system should be carried out. Thus, constructing a test-bed of I and C systems is necessary for the safety system in operation. In the future, it will be necessary to develop a logging and monitoring system for studies on the vulnerabilities of I and C systems with test-beds
A Method to Derive Monitoring Variables for a Cyber Security Test-bed of I and C System
Energy Technology Data Exchange (ETDEWEB)
Han, Kyung Soo; Song, Jae Gu; Lee, Joung Woon; Lee, Cheol Kwon [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2013-10-15
In the IT field, monitoring techniques have been developed to protect the systems connected by networks from cyber attacks and incidents. For the development of monitoring systems for I and C cyber security, it is necessary to review the monitoring systems in the IT field and derive cyber security-related monitoring variables among the proprietary operating information about the I and C systems. Tests for the development and application of these monitoring systems may cause adverse effects on the I and C systems. To analyze influences on the system and safely intended variables, the construction of an I and C system Test-bed should be preceded. This article proposes a method of deriving variables that should be monitored through a monitoring system for cyber security as a part of I and C Test-bed. The surveillance features and the monitored variables of NMS(Network Management System), a monitoring technique in the IT field, were reviewed in section 2. In Section 3, the monitoring variables for an I and C cyber security were derived by the of NMS and the investigation for information used for hacking techniques that can be practiced against I and C systems. The monitoring variables of NMS in the IT field and the information about the malicious behaviors used for hacking were derived as expected variables to be monitored for an I and C cyber security research. The derived monitoring variables were classified into the five functions of NMS for efficient management. For the cyber security of I and C systems, the vulnerabilities should be understood through a penetration test etc. and an assessment of influences on the actual system should be carried out. Thus, constructing a test-bed of I and C systems is necessary for the safety system in operation. In the future, it will be necessary to develop a logging and monitoring system for studies on the vulnerabilities of I and C systems with test-beds.
Reliability of TMS metrics in patients with chronic incomplete spinal cord injury.
Potter-Baker, K A; Janini, D P; Frost, F S; Chabra, P; Varnerin, N; Cunningham, D A; Sankarasubramanian, V; Plow, E B
2016-11-01
Test-retest reliability analysis in individuals with chronic incomplete spinal cord injury (iSCI). The purpose of this study was to examine the reliability of neurophysiological metrics acquired with transcranial magnetic stimulation (TMS) in individuals with chronic incomplete tetraplegia. Cleveland Clinic Foundation, Cleveland, Ohio, USA. TMS metrics of corticospinal excitability, output, inhibition and motor map distribution were collected in muscles with a higher MRC grade and muscles with a lower MRC grade on the more affected side of the body. Metrics denoting upper limb function were also collected. All metrics were collected at two sessions separated by a minimum of two weeks. Reliability between sessions was determined using Spearman's correlation coefficients and concordance correlation coefficients (CCCs). We found that TMS metrics that were acquired in higher MRC grade muscles were approximately two times more reliable than those collected in lower MRC grade muscles. TMS metrics of motor map output, however, demonstrated poor reliability regardless of muscle choice (P=0.34; CCC=0.51). Correlation analysis indicated that patients with more baseline impairment and/or those in a more chronic phase of iSCI demonstrated greater variability of metrics. In iSCI, reliability of TMS metrics varies depending on the muscle grade of the tested muscle. Variability is also influenced by factors such as baseline motor function and time post SCI. Future studies that use TMS metrics in longitudinal study designs to understand functional recovery should be cautious as choice of muscle and clinical characteristics can influence reliability.
Group covariance and metrical theory
International Nuclear Information System (INIS)
Halpern, L.
1983-01-01
The a priori introduction of a Lie group of transformations into a physical theory has often proved to be useful; it usually serves to describe special simplified conditions before a general theory can be worked out. Newton's assumptions of absolute space and time are examples where the Euclidian group and translation group have been introduced. These groups were extended to the Galilei group and modified in the special theory of relativity to the Poincare group to describe physics under the given conditions covariantly in the simplest way. The criticism of the a priori character leads to the formulation of the general theory of relativity. The general metric theory does not really give preference to a particular invariance group - even the principle of equivalence can be adapted to a whole family of groups. The physical laws covariantly inserted into the metric space are however adapted to the Poincare group. 8 references
General relativity: An erfc metric
Plamondon, Réjean
2018-06-01
This paper proposes an erfc potential to incorporate in a symmetric metric. One key feature of this model is that it relies on the existence of an intrinsic physical constant σ, a star-specific proper length that scales all its surroundings. Based thereon, the new metric is used to study the space-time geometry of a static symmetric massive object, as seen from its interior. The analytical solutions to the Einstein equation are presented, highlighting the absence of singularities and discontinuities in such a model. The geodesics are derived in their second- and first-order differential formats. Recalling the slight impact of the new model on the classical general relativity tests in the solar system, a number of facts and open problems are briefly revisited on the basis of a heuristic definition of σ. A special attention is given to gravitational collapses and non-singular black holes.
Directory of Open Access Journals (Sweden)
D. Olvera
2015-01-01
Full Text Available We expand the application of the enhanced multistage homotopy perturbation method (EMHPM to solve delay differential equations (DDEs with constant and variable coefficients. This EMHPM is based on a sequence of subintervals that provide approximate solutions that require less CPU time than those computed from the dde23 MATLAB numerical integration algorithm solutions. To address the accuracy of our proposed approach, we examine the solutions of several DDEs having constant and variable coefficients, finding predictions with a good match relative to the corresponding numerical integration solutions.
r2VIM: A new variable selection method for random forests in genome-wide association studies.
Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E
2016-01-01
Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.
Methods for Minimization and Management of Variability in Long-Term Groundwater Monitoring Results
2015-12-01
DECEMBER 2015 Poonam Kulkarni Charles Newell Claire Krebs Thomas McHugh GSI Environmental, Inc. Britt Sanford ProHydro Distribution...based on an understanding of the short-term variability and long-term attenuation rate at a particular site ( McHugh et al., 2015a). The...time is independent of these parameters ( McHugh et al., 2015c). The relative trade-off between monitoring frequency and time required to
A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method
Jun-He Yang; Ching-Hsue Cheng; Chia-Pan Chan
2017-01-01
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting m...
Multi-Metric Sustainability Analysis
Energy Technology Data Exchange (ETDEWEB)
Cowlin, Shannon [National Renewable Energy Lab. (NREL), Golden, CO (United States); Heimiller, Donna [National Renewable Energy Lab. (NREL), Golden, CO (United States); Macknick, Jordan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mann, Margaret [National Renewable Energy Lab. (NREL), Golden, CO (United States); Pless, Jacquelyn [National Renewable Energy Lab. (NREL), Golden, CO (United States); Munoz, David [Colorado School of Mines, Golden, CO (United States)
2014-12-01
A readily accessible framework that allows for evaluating impacts and comparing tradeoffs among factors in energy policy, expansion planning, and investment decision making is lacking. Recognizing this, the Joint Institute for Strategic Energy Analysis (JISEA) funded an exploration of multi-metric sustainability analysis (MMSA) to provide energy decision makers with a means to make more comprehensive comparisons of energy technologies. The resulting MMSA tool lets decision makers simultaneously compare technologies and potential deployment locations.
Sensory Metrics of Neuromechanical Trust.
Softky, William; Benford, Criscillia
2017-09-01
Today digital sources supply a historically unprecedented component of human sensorimotor data, the consumption of which is correlated with poorly understood maladies such as Internet addiction disorder and Internet gaming disorder. Because both natural and digital sensorimotor data share common mathematical descriptions, one can quantify our informational sensorimotor needs using the signal processing metrics of entropy, noise, dimensionality, continuity, latency, and bandwidth. Such metrics describe in neutral terms the informational diet human brains require to self-calibrate, allowing individuals to maintain trusting relationships. With these metrics, we define the trust humans experience using the mathematical language of computational models, that is, as a primitive statistical algorithm processing finely grained sensorimotor data from neuromechanical interaction. This definition of neuromechanical trust implies that artificial sensorimotor inputs and interactions that attract low-level attention through frequent discontinuities and enhanced coherence will decalibrate a brain's representation of its world over the long term by violating the implicit statistical contract for which self-calibration evolved. Our hypersimplified mathematical understanding of human sensorimotor processing as multiscale, continuous-time vibratory interaction allows equally broad-brush descriptions of failure modes and solutions. For example, we model addiction in general as the result of homeostatic regulation gone awry in novel environments (sign reversal) and digital dependency as a sub-case in which the decalibration caused by digital sensorimotor data spurs yet more consumption of them. We predict that institutions can use these sensorimotor metrics to quantify media richness to improve employee well-being; that dyads and family-size groups will bond and heal best through low-latency, high-resolution multisensory interaction such as shared meals and reciprocated touch; and
Metric reconstruction from Weyl scalars
Energy Technology Data Exchange (ETDEWEB)
Whiting, Bernard F; Price, Larry R [Department of Physics, PO Box 118440, University of Florida, Gainesville, FL 32611 (United States)
2005-08-07
The Kerr geometry has remained an elusive world in which to explore physics and delve into the more esoteric implications of general relativity. Following the discovery, by Kerr in 1963, of the metric for a rotating black hole, the most major advance has been an understanding of its Weyl curvature perturbations based on Teukolsky's discovery of separable wave equations some ten years later. In the current research climate, where experiments across the globe are preparing for the first detection of gravitational waves, a more complete understanding than concerns just the Weyl curvature is now called for. To understand precisely how comparatively small masses move in response to the gravitational waves they emit, a formalism has been developed based on a description of the whole spacetime metric perturbation in the neighbourhood of the emission region. Presently, such a description is not available for the Kerr geometry. While there does exist a prescription for obtaining metric perturbations once curvature perturbations are known, it has become apparent that there are gaps in that formalism which are still waiting to be filled. The most serious gaps include gauge inflexibility, the inability to include sources-which are essential when the emitting masses are considered-and the failure to describe the l = 0 and 1 perturbation properties. Among these latter properties of the perturbed spacetime, arising from a point mass in orbit, are the perturbed mass and axial component of angular momentum, as well as the very elusive Carter constant for non-axial angular momentum. A status report is given on recent work which begins to repair these deficiencies in our current incomplete description of Kerr metric perturbations.
Metric reconstruction from Weyl scalars
International Nuclear Information System (INIS)
Whiting, Bernard F; Price, Larry R
2005-01-01
The Kerr geometry has remained an elusive world in which to explore physics and delve into the more esoteric implications of general relativity. Following the discovery, by Kerr in 1963, of the metric for a rotating black hole, the most major advance has been an understanding of its Weyl curvature perturbations based on Teukolsky's discovery of separable wave equations some ten years later. In the current research climate, where experiments across the globe are preparing for the first detection of gravitational waves, a more complete understanding than concerns just the Weyl curvature is now called for. To understand precisely how comparatively small masses move in response to the gravitational waves they emit, a formalism has been developed based on a description of the whole spacetime metric perturbation in the neighbourhood of the emission region. Presently, such a description is not available for the Kerr geometry. While there does exist a prescription for obtaining metric perturbations once curvature perturbations are known, it has become apparent that there are gaps in that formalism which are still waiting to be filled. The most serious gaps include gauge inflexibility, the inability to include sources-which are essential when the emitting masses are considered-and the failure to describe the l = 0 and 1 perturbation properties. Among these latter properties of the perturbed spacetime, arising from a point mass in orbit, are the perturbed mass and axial component of angular momentum, as well as the very elusive Carter constant for non-axial angular momentum. A status report is given on recent work which begins to repair these deficiencies in our current incomplete description of Kerr metric perturbations
Strong Stability Preserving Explicit Linear Multistep Methods with Variable Step Size
Hadjimichael, Yiannis; Ketcheson, David I.; Loczi, Lajos; Né meth, Adriá n
2016-01-01
Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods (of order
Farrington, Stephen P.
2018-05-15
Systems, methods, and software for measuring the spatially variable relative dielectric permittivity of materials along a linear or otherwise configured sensor element, and more specifically the spatial variability of soil moisture in one dimension as inferred from the dielectric profile of the soil matrix surrounding a linear sensor element. Various methods provided herein combine advances in the processing of time domain reflectometry data with innovations in physical sensing apparatuses. These advancements enable high temporal (and thus spatial) resolution of electrical reflectance continuously along an insulated waveguide that is permanently emplaced in contact with adjacent soils. The spatially resolved reflectance is directly related to impedance changes along the waveguide that are dominated by electrical permittivity contrast due to variations in soil moisture. Various methods described herein are thus able to monitor soil moisture in profile with high spatial resolution.
Light Curve Periodic Variability of Cyg X-1 using Jurkevich Method ...
Indian Academy of Sciences (India)
Abstract. The Jurkevich method is a useful method to explore periodic- ity in the unevenly sampled observational data. In this work, we adopted the method to the light curve of Cyg X-1 from 1996 to 2012, and found that there is an interesting period of 370 days, which appears in both low/hard and high/soft states.
Light Curve Periodic Variability of Cyg X-1 using Jurkevich Method
Indian Academy of Sciences (India)
The Jurkevich method is a useful method to explore periodicity in the unevenly sampled observational data. In this work, we adopted the method to the light curve of Cyg X-1 from 1996 to 2012, and found that there is an interesting period of 370 days, which appears in both low/hard and high/soft states. That period may be ...
Sustainability Metrics: The San Luis Basin Project
Sustainability is about promoting humanly desirable dynamic regimes of the environment. Metrics: ecological footprint, net regional product, exergy, emergy, and Fisher Information. Adaptive management: (1) metrics assess problem, (2) specific problem identified, and (3) managemen...
Contrasting Various Metrics for Measuring Tropical Cyclone Activity
Directory of Open Access Journals (Sweden)
Jia-Yuh Yu Ping-Gin Chiu
2012-01-01
Full Text Available Popular metrics used for measuring the tropical cyclone (TC activity, including NTC (number of tropical cyclones, TCD (tropical cyclone days, ACE (accumulated cyclone energy, PDI (power dissipation index, along with two newly proposed indices: RACE (revised accumulated cyclone energy and RPDI (revised power dissipation index, are compared using the JTWC (Joint Typhoon Warning Center best-track data of TC over the western North Pacific basin. Our study shows that, while the above metrics have demonstrated various degrees of discrepancies, but in practical terms, they are all able to produce meaningful temporal and spatial changes in response to climate variability. Compared with the conventional ACE and PDI, RACE and RPDI seem to provide a more precise estimate of the total TC activity, especially in projecting the upswing trend of TC activity over the past few decades, simply because of a better approach in estimating TC wind energy. However, we would argue that there is still no need to find a ¡§universal¡¨ or ¡§best¡¨ metric for TC activity because different metrics are designed to stratify different aspects of TC activity, and whether the selected metric is appropriate or not should be determined solely by the purpose of study. Except for magnitude difference, the analysis results seem insensitive to the choice of the best-track datasets.
Using principal component analysis for selecting network behavioral anomaly metrics
Gregorio-de Souza, Ian; Berk, Vincent; Barsamian, Alex
2010-04-01
This work addresses new approaches to behavioral analysis of networks and hosts for the purposes of security monitoring and anomaly detection. Most commonly used approaches simply implement anomaly detectors for one, or a few, simple metrics and those metrics can exhibit unacceptable false alarm rates. For instance, the anomaly score of network communication is defined as the reciprocal of the likelihood that a given host uses a particular protocol (or destination);this definition may result in an unrealistically high threshold for alerting to avoid being flooded by false positives. We demonstrate that selecting and adapting the metrics and thresholds, on a host-by-host or protocol-by-protocol basis can be done by established multivariate analyses such as PCA. We will show how to determine one or more metrics, for each network host, that records the highest available amount of information regarding the baseline behavior, and shows relevant deviances reliably. We describe the methodology used to pick from a large selection of available metrics, and illustrate a method for comparing the resulting classifiers. Using our approach we are able to reduce the resources required to properly identify misbehaving hosts, protocols, or networks, by dedicating system resources to only those metrics that actually matter in detecting network deviations.
Directory of Open Access Journals (Sweden)
Zamorska Izabela
2018-01-01
Full Text Available The subject of the paper is an application of the non-destructive vibration method for identifying the location of two cracks occurring in a beam. The vibration method is based on knowledge of a certain number of vibration frequencies of an undamaged element and the knowledge of the same number of vibration frequencies of an element with a defect. The analyzed beam, with a variable cross-sectional area, has been described according to the Bernoulli-Euler theory. To determine the values of free vibration frequencies the analytical solution, with the help of the Green’s function method, has been used.
Danilǎ, Bogdan; Harko, Tiberiu; Lobo, Francisco S. N.; Mak, M. K.
2017-02-01
We consider the internal structure and the physical properties of specific classes of neutron, quark and Bose-Einstein condensate stars in the recently proposed hybrid metric-Palatini gravity theory, which is a combination of the metric and Palatini f (R ) formalisms. It turns out that the theory is very successful in accounting for the observed phenomenology, since it unifies local constraints at the Solar System level and the late-time cosmic acceleration, even if the scalar field is very light. In this paper, we derive the equilibrium equations for a spherically symmetric configuration (mass continuity and Tolman-Oppenheimer-Volkoff) in the framework of the scalar-tensor representation of the hybrid metric-Palatini theory, and we investigate their solutions numerically for different equations of state of neutron and quark matter, by adopting for the scalar field potential a Higgs-type form. It turns out that the scalar-tensor definition of the potential can be represented as an Clairaut differential equation, and provides an explicit form for f (R ) given by f (R )˜R +Λeff, where Λeff is an effective cosmological constant. Furthermore, stellar models, described by the stiff fluid, radiation-like, bag model and the Bose-Einstein condensate equations of state are explicitly constructed in both general relativity and hybrid metric-Palatini gravity, thus allowing an in-depth comparison between the predictions of these two gravitational theories. As a general result it turns out that for all the considered equations of state, hybrid gravity stars are more massive than their general relativistic counterparts. Furthermore, two classes of stellar models corresponding to two particular choices of the functional form of the scalar field (constant value, and logarithmic form, respectively) are also investigated. Interestingly enough, in the case of a constant scalar field the equation of state of the matter takes the form of the bag model equation of state describing
Benhammouda, Brahim; Vazquez-Leal, Hector
2016-01-01
This work presents an analytical solution of some nonlinear delay differential equations (DDEs) with variable delays. Such DDEs are difficult to treat numerically and cannot be solved by existing general purpose codes. A new method of steps combined with the differential transform method (DTM) is proposed as a powerful tool to solve these DDEs. This method reduces the DDEs to ordinary differential equations that are then solved by the DTM. Furthermore, we show that the solutions can be improved by Laplace-Padé resummation method. Two examples are presented to show the efficiency of the proposed technique. The main advantage of this technique is that it possesses a simple procedure based on a few straight forward steps and can be combined with any analytical method, other than the DTM, like the homotopy perturbation method.
Zhonggang, Liang; Hong, Yan
2006-10-01
A new method of calculating fractal dimension of short-term heart rate variability signals is presented. The method is based on wavelet transform and filter banks. The implementation of the method is: First of all we pick-up the fractal component from HRV signals using wavelet transform. Next, we estimate the power spectrum distribution of fractal component using auto-regressive model, and we estimate parameter 7 using the least square method. Finally according to formula D = 2- (gamma-1)/2 estimate fractal dimension of HRV signal. To validate the stability and reliability of the proposed method, using fractional brown movement simulate 24 fractal signals that fractal value is 1.6 to validate, the result shows that the method has stability and reliability.
Energy Technology Data Exchange (ETDEWEB)
McGurk, Ross J. [Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 (United States); Bowsher, James; Das, Shiva K. [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Lee, John A [Molecular Imaging and Experimental Radiotherapy Unit, Universite Catholique de Louvain, 1200 Brussels (Belgium)
2013-04-15
Purpose: Many approaches have been proposed to segment high uptake objects in 18F-fluoro-deoxy-glucose positron emission tomography images but none provides consistent performance across the large variety of imaging situations. This study investigates the use of two methods of combining individual segmentation methods to reduce the impact of inconsistent performance of the individual methods: simple majority voting and probabilistic estimation. Methods: The National Electrical Manufacturers Association image quality phantom containing five glass spheres with diameters 13-37 mm and two irregularly shaped volumes (16 and 32 cc) formed by deforming high-density polyethylene bottles in a hot water bath were filled with 18-fluoro-deoxyglucose and iodine contrast agent. Repeated 5-min positron emission tomography (PET) images were acquired at 4:1 and 8:1 object-to-background contrasts for spherical objects and 4.5:1 and 9:1 for irregular objects. Five individual methods were used to segment each object: 40% thresholding, adaptive thresholding, k-means clustering, seeded region-growing, and a gradient based method. Volumes were combined using a majority vote (MJV) or Simultaneous Truth And Performance Level Estimate (STAPLE) method. Accuracy of segmentations relative to CT ground truth volumes were assessed using the Dice similarity coefficient (DSC) and the symmetric mean absolute surface distances (SMASDs). Results: MJV had median DSC values of 0.886 and 0.875; and SMASD of 0.52 and 0.71 mm for spheres and irregular shapes, respectively. STAPLE provided similar results with median DSC of 0.886 and 0.871; and median SMASD of 0.50 and 0.72 mm for spheres and irregular shapes, respectively. STAPLE had significantly higher DSC and lower SMASD values than MJV for spheres (DSC, p < 0.0001; SMASD, p= 0.0101) but MJV had significantly higher DSC and lower SMASD values compared to STAPLE for irregular shapes (DSC, p < 0.0001; SMASD, p= 0.0027). DSC was not significantly
Metrics for Evaluation of Student Models
Pelanek, Radek
2015-01-01
Researchers use many different metrics for evaluation of performance of student models. The aim of this paper is to provide an overview of commonly used metrics, to discuss properties, advantages, and disadvantages of different metrics, to summarize current practice in educational data mining, and to provide guidance for evaluation of student…
Context-dependent ATC complexity metric
Mercado Velasco, G.A.; Borst, C.
2015-01-01
Several studies have investigated Air Traffic Control (ATC) complexity metrics in a search for a metric that could best capture workload. These studies have shown how daunting the search for a universal workload metric (one that could be applied in different contexts: sectors, traffic patterns,
Croitoru, Anca; Apreutesei, Gabriela; Mastorakis, Nikos E.
2017-09-01
The subject of this paper belongs to the theory of approximate metrics [23]. An approximate metric on X is a real application defined on X × X that satisfies only a part of the metric axioms. In a recent paper [23], we introduced a new type of approximate metric, named C-metric, that is an application which satisfies only two metric axioms: symmetry and triangular inequality. The remarkable fact in a C-metric space is that a topological structure induced by the C-metric can be defined. The innovative idea of this paper is that we obtain some convergence properties of a C-metric space in the absence of a metric. In this paper we investigate C-metric spaces. The paper is divided into four sections. Section 1 is for Introduction. In Section 2 we recall some concepts and preliminary results. In Section 3 we present some properties of C-metric spaces, such as convergence properties, a canonical decomposition and a C-fixed point theorem. Finally, in Section 4 some conclusions are highlighted.
An Auxiliary Variable Method for Markov Chain Monte Carlo Algorithms in High Dimension
Directory of Open Access Journals (Sweden)
Yosra Marnissi
2018-02-01
Full Text Available In this paper, we are interested in Bayesian inverse problems where either the data fidelity term or the prior distribution is Gaussian or driven from a hierarchical Gaussian model. Generally, Markov chain Monte Carlo (MCMC algorithms allow us to generate sets of samples that are employed to infer some relevant parameters of the underlying distributions. However, when the parameter space is high-dimensional, the performance of stochastic sampling algorithms is very sensitive to existing dependencies between parameters. In particular, this problem arises when one aims to sample from a high-dimensional Gaussian distribution whose covariance matrix does not present a simple structure. Another challenge is the design of Metropolis–Hastings proposals that make use of information about the local geometry of the target density in order to speed up the convergence and improve mixing properties in the parameter space, while not being too computationally expensive. These two contexts are mainly related to the presence of two heterogeneous sources of dependencies stemming either from the prior or the likelihood in the sense that the related covariance matrices cannot be diagonalized in the same basis. In this work, we address these two issues. Our contribution consists of adding auxiliary variables to the model in order to dissociate the two sources of dependencies. In the new augmented space, only one source of correlation remains directly related to the target parameters, the other sources of correlations being captured by the auxiliary variables. Experiments are conducted on two practical image restoration problems—namely the recovery of multichannel blurred images embedded in Gaussian noise and the recovery of signal corrupted by a mixed Gaussian noise. Experimental results indicate that adding the proposed auxiliary variables makes the sampling problem simpler since the new conditional distribution no longer contains highly heterogeneous
Uncertainty in T1 mapping using the variable flip angle method with two flip angles
International Nuclear Information System (INIS)
Schabel, Matthias C; Morrell, Glen R
2009-01-01
Propagation of errors, in conjunction with the theoretical signal equation for spoiled gradient echo pulse sequences, is used to derive a theoretical expression for uncertainty in quantitative variable flip angle T 1 mapping using two flip angles. This expression is then minimized to derive a rigorous expression for optimal flip angles that elucidates a commonly used empirical result. The theoretical expressions for uncertainty and optimal flip angles are combined to derive a lower bound on the achievable uncertainty for a given set of pulse sequence parameters and signal-to-noise ratio (SNR). These results provide a means of quantitatively determining the effect of changing acquisition parameters on T 1 uncertainty. (note)
Analysis of electrical circuits with variable load regime parameters projective geometry method
Penin, A
2015-01-01
This book introduces electric circuits with variable loads and voltage regulators. It allows to define invariant relationships for various parameters of regime and circuit sections and to prove the concepts characterizing these circuits. Generalized equivalent circuits are introduced. Projective geometry is used for the interpretation of changes of operating regime parameters. Expressions of normalized regime parameters and their changes are presented. Convenient formulas for the calculation of currents are given. Parallel voltage sources and the cascade connection of multi-port networks are d
A Method of Approximating Expectations of Functions of Sums of Independent Random Variables
Klass, Michael J.
1981-01-01
Let $X_1, X_2, \\cdots$ be a sequence of independent random variables with $S_n = \\sum^n_{i = 1} X_i$. Fix $\\alpha > 0$. Let $\\Phi(\\cdot)$ be a continuous, strictly increasing function on $\\lbrack 0, \\infty)$ such that $\\Phi(0) = 0$ and $\\Phi(cx) \\leq c^\\alpha\\Phi(x)$ for all $x > 0$ and all $c \\geq 2$. Suppose $a$ is a real number and $J$ is a finite nonempty subset of the positive integers. In this paper we are interested in approximating $E \\max_{j \\in J} \\Phi(|a + S_j|)$. We construct a nu...
Energy Metrics for State Government Buildings
Michael, Trevor
Measuring true progress towards energy conservation goals requires the accurate reporting and accounting of energy consumption. An accurate energy metrics framework is also a critical element for verifiable Greenhouse Gas Inventories. Energy conservation in government can reduce expenditures on energy costs leaving more funds available for public services. In addition to monetary savings, conserving energy can help to promote energy security, air quality, and a reduction of carbon footprint. With energy consumption/GHG inventories recently produced at the Federal level, state and local governments are beginning to also produce their own energy metrics systems. In recent years, many states have passed laws and executive orders which require their agencies to reduce energy consumption. In June 2008, SC state government established a law to achieve a 20% energy usage reduction in state buildings by 2020. This study examines case studies from other states who have established similar goals to uncover the methods used to establish an energy metrics system. Direct energy consumption in state government primarily comes from buildings and mobile sources. This study will focus exclusively on measuring energy consumption in state buildings. The case studies reveal that many states including SC are having issues gathering the data needed to accurately measure energy consumption across all state buildings. Common problems found include a lack of enforcement and incentives that encourage state agencies to participate in any reporting system. The case studies are aimed at finding the leverage used to gather the needed data. The various approaches at coercing participation will hopefully reveal methods that SC can use to establish the accurate metrics system needed to measure progress towards its 20% by 2020 energy reduction goal. Among the strongest incentives found in the case studies is the potential for monetary savings through energy efficiency. Framing energy conservation
Inter- and Intra-method Variability of VS Profiles and VS30 at ARRA-funded Sites
Yong, A.; Boatwright, J.; Martin, A. J.
2015-12-01
The 2009 American Recovery and Reinvestment Act (ARRA) funded geophysical site characterizations at 191 seismographic stations in California and in the central and eastern United States. Shallow boreholes were considered cost- and environmentally-prohibitive, thus non-invasive methods (passive and active surface- and body-wave techniques) were used at these stations. The drawback, however, is that these techniques measure seismic properties indirectly and introduce more uncertainty than borehole methods. The principal methods applied were Array Microtremor (AM), Multi-channel Analysis of Surface Waves (MASW; Rayleigh and Love waves), Spectral Analysis of Surface Waves (SASW), Refraction Microtremor (ReMi), and P- and S-wave refraction tomography. Depending on the apparent geologic or seismic complexity of the site, field crews applied one or a combination of these methods to estimate the shear-wave velocity (VS) profile and calculate VS30, the time-averaged VS to a depth of 30 meters. We study the inter- and intra-method variability of VS and VS30 at each seismographic station where combinations of techniques were applied. For each site, we find both types of variability in VS30 remain insignificant (5-10% difference) despite substantial variability observed in the VS profiles. We also find that reliable VS profiles are best developed using a combination of techniques, e.g., surface-wave VS profiles correlated against P-wave tomography to constrain variables (Poisson's ratio and density) that are key depth-dependent parameters used in modeling VS profiles. The most reliable results are based on surface- or body-wave profiles correlated against independent observations such as material properties inferred from outcropping geology nearby. For example, mapped geology describes station CI.LJR as a hard rock site (VS30 > 760 m/s). However, decomposed rock outcrops were found nearby and support the estimated VS30 of 303 m/s derived from the MASW (Love wave) profile.
Network Community Detection on Metric Space
Directory of Open Access Journals (Sweden)
Suman Saha
2015-08-01
Full Text Available Community detection in a complex network is an important problem of much interest in recent years. In general, a community detection algorithm chooses an objective function and captures the communities of the network by optimizing the objective function, and then, one uses various heuristics to solve the optimization problem to extract the interesting communities for the user. In this article, we demonstrate the procedure to transform a graph into points of a metric space and develop the methods of community detection with the help of a metric defined for a pair of points. We have also studied and analyzed the community structure of the network therein. The results obtained with our approach are very competitive with most of the well-known algorithms in the literature, and this is justified over the large collection of datasets. On the other hand, it can be observed that time taken by our algorithm is quite less compared to other methods and justifies the theoretical findings.
Energy Technology Data Exchange (ETDEWEB)
Kelly, Brandon C. [Department of Physics, Broida Hall, University of California, Santa Barbara, CA 93106-9530 (United States); Becker, Andrew C. [Department of Astronomy, University of Washington, P.O. Box 351580, Seattle, WA 98195-1580 (United States); Sobolewska, Malgosia [Nicolaus Copernicus Astronomical Center, Bartycka 18, 00-716, Warsaw (Poland); Siemiginowska, Aneta [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Uttley, Phil [Astronomical Institute Anton Pannekoek, University of Amsterdam, Postbus 94249, 1090 GE Amsterdam (Netherlands)
2014-06-10
We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for irregular sampling and measurement errors, making them valuable for quantifying variability, forecasting and interpolating light curves, and variability-based classification. We show that the PSD of a CARMA model can be expressed as a sum of Lorentzian functions, which makes them extremely flexible and able to model a broad range of PSDs. We present the likelihood function for light curves sampled from CARMA processes, placing them on a statistically rigorous foundation, and we present a Bayesian method to infer the probability distribution of the PSD given the measured light curve. Because calculation of the likelihood function scales linearly with the number of data points, CARMA modeling scales to current and future massive time-domain data sets. We conclude by applying our CARMA modeling approach to light curves for an X-ray binary, two active galactic nuclei, a long-period variable star, and an RR Lyrae star in order to illustrate their use, applicability, and interpretation.
International Nuclear Information System (INIS)
Kelly, Brandon C.; Becker, Andrew C.; Sobolewska, Malgosia; Siemiginowska, Aneta; Uttley, Phil
2014-01-01
We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for irregular sampling and measurement errors, making them valuable for quantifying variability, forecasting and interpolating light curves, and variability-based classification. We show that the PSD of a CARMA model can be expressed as a sum of Lorentzian functions, which makes them extremely flexible and able to model a broad range of PSDs. We present the likelihood function for light curves sampled from CARMA processes, placing them on a statistically rigorous foundation, and we present a Bayesian method to infer the probability distribution of the PSD given the measured light curve. Because calculation of the likelihood function scales linearly with the number of data points, CARMA modeling scales to current and future massive time-domain data sets. We conclude by applying our CARMA modeling approach to light curves for an X-ray binary, two active galactic nuclei, a long-period variable star, and an RR Lyrae star in order to illustrate their use, applicability, and interpretation.
Inverse kinematics for the variable geometry truss manipulator via a Lagrangian dual method
Directory of Open Access Journals (Sweden)
Yanchun Zhao
2016-11-01
Full Text Available This article studies the inverse kinematics problem of the variable geometry truss manipulator. The problem is cast as an optimization process which can be divided into two steps. Firstly, according to the information about the location of the end effector and fixed base, an optimal center curve and the corresponding distribution of the intermediate platforms along this center line are generated. This procedure is implemented by solving a non-convex optimization problem that has a quadratic objective function subject to quadratic constraints. Then, in accordance with the distribution of the intermediate platforms along the optimal center curve, all lengths of the actuators are calculated via the inverse kinematics of each variable geometry truss module. Hence, the approach that we present is an optimization procedure that attempts to generate the optimal intermediate platform distribution along the optimal central curve, while the performance index and kinematic constraints are satisfied. By using the Lagrangian duality theory, a closed-form optimal solution of the original optimization is given. The numerical simulation substantiates the effectiveness of the introduced approach.
Shanafield, Margaret; Niswonger, Richard G.; Prudic, David E.; Pohll, Greg; Susfalk, Richard; Panday, Sorab
2014-01-01
Infiltration along ephemeral channels plays an important role in groundwater recharge in arid regions. A model is presented for estimating spatial variability of seepage due to streambed heterogeneity along channels based on measurements of streamflow-front velocities in initially dry channels. The diffusion-wave approximation to the Saint-Venant equations, coupled with Philip's equation for infiltration, is connected to the groundwater model MODFLOW and is calibrated by adjusting the saturated hydraulic conductivity of the channel bed. The model is applied to portions of two large water delivery canals, which serve as proxies for natural ephemeral streams. Estimated seepage rates compare well with previously published values. Possible sources of error stem from uncertainty in Manning's roughness coefficients, soil hydraulic properties and channel geometry. Model performance would be most improved through more frequent longitudinal estimates of channel geometry and thalweg elevation, and with measurements of stream stage over time to constrain wave timing and shape. This model is a potentially valuable tool for estimating spatial variability in longitudinal seepage along intermittent and ephemeral channels over a wide range of bed slopes and the influence of seepage rates on groundwater levels.
Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity
Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick
2013-01-01
Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.
Utility of different glycemic control metrics for optimizing management of diabetes.
Kohnert, Klaus-Dieter; Heinke, Peter; Vogt, Lutz; Salzsieder, Eckhard
2015-02-15
The benchmark for assessing quality of long-term glycemic control and adjustment of therapy is currently glycated hemoglobin (HbA1c). Despite its importance as an indicator for the development of diabetic complications, recent studies have revealed that this metric has some limitations; it conveys a rather complex message, which has to be taken into consideration for diabetes screening and treatment. On the basis of recent clinical trials, the relationship between HbA1c and cardiovascular outcomes in long-standing diabetes has been called into question. It becomes obvious that other surrogate and biomarkers are needed to better predict cardiovascular diabetes complications and assess efficiency of therapy. Glycated albumin, fructosamin, and 1,5-anhydroglucitol have received growing interest as alternative markers of glycemic control. In addition to measures of hyperglycemia, advanced glucose monitoring methods became available. An indispensible adjunct to HbA1c in routine diabetes care is self-monitoring of blood glucose. This monitoring method is now widely used, as it provides immediate feedback to patients on short-term changes, involving fasting, preprandial, and postprandial glucose levels. Beyond the traditional metrics, glycemic variability has been identified as a predictor of hypoglycemia, and it might also be implicated in the pathogenesis of vascular diabetes complications. Assessment of glycemic variability is thus important, but exact quantification requires frequently sampled glucose measurements. In order to optimize diabetes treatment, there is a need for both key metrics of glycemic control on a day-to-day basis and for more advanced, user-friendly monitoring methods. In addition to traditional discontinuous glucose testing, continuous glucose sensing has become a useful tool to reveal insufficient glycemic management. This new technology is particularly effective in patients with complicated diabetes and provides the opportunity to characterize
Visualizing Metrics on Areas of Interest in Software Architecture Diagrams
Byelas, Heorhiy; Telea, Alexandru; Eades, P; Ertl, T; Shen, HW
2009-01-01
We present a new method for the combined visualization of software architecture diagrams, Such as UML class diagrams or component diagrams, and software metrics defined on groups of diagram elements. Our method extends an existing rendering technique for the so-called areas of interest in system
Directory of Open Access Journals (Sweden)
Ni An
2017-04-01
Full Text Available When modeling the soil/atmosphere interaction, it is of paramount importance to determine the net radiation flux. There are two common calculation methods for this purpose. Method 1 relies on use of air temperature, while Method 2 relies on use of both air and soil temperatures. Nowadays, there has been no consensus on the application of these two methods. In this study, the half-hourly data of solar radiation recorded at an experimental embankment are used to calculate the net radiation and long-wave radiation at different time-scales (half-hourly, hourly, and daily using the two methods. The results show that, compared with Method 2 which has been widely adopted in agronomical, geotechnical and geo-environmental applications, Method 1 is more feasible for its simplicity and accuracy at shorter time-scale. Moreover, in case of longer time-scale, daily for instance, less variations of net radiation and long-wave radiation are obtained, suggesting that no detailed soil temperature variations can be obtained. In other words, shorter time-scales are preferred in determining net radiation flux.
Johnson, Kenneth L.; White, K, Preston, Jr.
2012-01-01
The NASA Engineering and Safety Center was requested to improve on the Best Practices document produced for the NESC assessment, Verification of Probabilistic Requirements for the Constellation Program, by giving a recommended procedure for using acceptance sampling by variables techniques. This recommended procedure would be used as an alternative to the potentially resource-intensive acceptance sampling by attributes method given in the document. This document contains the outcome of the assessment.
On characterizations of quasi-metric completeness
Energy Technology Data Exchange (ETDEWEB)
Dag, H.; Romaguera, S.; Tirado, P.
2017-07-01
Hu proved in [4] that a metric space (X, d) is complete if and only if for any closed subspace C of (X, d), every Banach contraction on C has fixed point. Since then several authors have investigated the problem of characterizing the metric completeness by means of fixed point theorems. Recently this problem has been studied in the more general context of quasi-metric spaces for different notions of completeness. Here we present a characterization of a kind of completeness for quasi-metric spaces by means of a quasi-metric versions of Hu’s theorem. (Author)
An Inclusive Design Method for Addressing Human Variability and Work Performance Issues
Directory of Open Access Journals (Sweden)
Amjad Hussain
2013-07-01
Full Text Available Humans play vital roles in manufacturing systems, but work performance is strongly influenced by factors such as experience, age, level of skill, physical and cognitive abilities and attitude towards work. Current manufacturing system design processes need to consider these human variability issues and their impact on work performance. An ‘inclusive design’ approach is proposed to consider the increasing diversity of the global workforce in terms of age, gender, cultural background, skill and experience. The decline in physical capabilities of older workers creates a mismatch between job demands and working capabilities which can be seen in manufacturing assembly that typically requires high physical demands for repetitive and accurate motions. The inclusive design approach leads to a reduction of this mismatch that results in a more productive, safe and healthy working environment giving benefits to the organization and individuals in terms of workforce satisfaction, reduced turnover, higher productivity and improved product quality.
Moody, John A.; Ebel, Brian A.
2012-01-01
We developed a difference infiltrometer to measure time series of non-steady infiltration rates during rainstorms at the point scale. The infiltrometer uses two, tipping bucket rain gages. One gage measures rainfall onto, and the other measures runoff from, a small circular plot about 0.5-m in diameter. The small size allows the infiltration rate to be computed as the difference of the cumulative rainfall and cumulative runoff without having to route water through a large plot. Difference infiltrometers were deployed in an area burned by the 2010 Fourmile Canyon Fire near Boulder, Colorado, USA, and data were collected during the summer of 2011. The difference infiltrometer demonstrated the capability to capture different magnitudes of infiltration rates and temporal variability associated with convective (high intensity, short duration) and cyclonic (low intensity, long duration) rainstorms. Data from the difference infiltrometer were used to estimate saturated hydraulic conductivity of soil affected by the heat from a wildfire. The difference infiltrometer is portable and can be deployed in rugged, steep terrain and does not require the transport of water, as many rainfall simulators require, because it uses natural rainfall. It can be used to assess infiltration models, determine runoff coefficients, identify rainfall depth or rainfall intensity thresholds to initiate runoff, estimate parameters for infiltration models, and compare remediation treatments on disturbed landscapes. The difference infiltrometer can be linked with other types of soil monitoring equipment in long-term studies for detecting temporal and spatial variability at multiple time scales and in nested designs where it can be linked to hillslope and basin-scale runoff responses.
Concerning an application of the method of least squares with a variable weight matrix
Sukhanov, A. A.
1979-01-01
An estimate of a state vector for a physical system when the weight matrix in the method of least squares is a function of this vector is considered. An iterative procedure is proposed for calculating the desired estimate. Conditions for the existence and uniqueness of the limit of this procedure are obtained, and a domain is found which contains the limit estimate. A second method for calculating the desired estimate which reduces to the solution of a system of algebraic equations is proposed. The question of applying Newton's method of tangents to solving the given system of algebraic equations is considered and conditions for the convergence of the modified Newton's method are obtained. Certain properties of the estimate obtained are presented together with an example.
Directory of Open Access Journals (Sweden)
Zizhou Lao
2018-05-01
Full Text Available For model-based state of charge (SOC estimation methods, the battery model parameters change with temperature, SOC, and so forth, causing the estimation error to increase. Constantly updating model parameters during battery operation, also known as online parameter identification, can effectively solve this problem. In this paper, a lithium-ion battery is modeled using the Thevenin model. A variable forgetting factor (VFF strategy is introduced to improve forgetting factor recursive least squares (FFRLS to variable forgetting factor recursive least squares (VFF-RLS. A novel method based on VFF-RLS for the online identification of the Thevenin model is proposed. Experiments verified that VFF-RLS gives more stable online parameter identification results than FFRLS. Combined with an unscented Kalman filter (UKF algorithm, a joint algorithm named VFF-RLS-UKF is proposed for SOC estimation. In a variable-temperature environment, a battery SOC estimation experiment was performed using the joint algorithm. The average error of the SOC estimation was as low as 0.595% in some experiments. Experiments showed that VFF-RLS can effectively track the changes in model parameters. The joint algorithm improved the SOC estimation accuracy compared to the method with the fixed forgetting factor.
Larter, K F; Rees, B B
2017-06-01
In many experiments, euthanasia, or humane killing, of animals is necessary. Some methods of euthanasia cause death through cessation of respiratory or cardiovascular systems, causing oxygen levels of blood and tissues to drop. For experiments where the goal is to measure the effects of environmental low oxygen (hypoxia), the choice of euthanasia technique, therefore, may confound the results. This study examined the effects of four euthanasia methods commonly used in fish biology (overdose of MS-222, overdose of clove oil, rapid cooling and blunt trauma to the head) on variables known to be altered during hypoxia (haematocrit, plasma cortisol, blood lactate and blood glucose) or reflecting gill damage (trypan blue exclusion) and energetic status (ATP, ADP and ATP:ADP) in Gulf killifish Fundulus grandis after 24 h exposure to well-aerated conditions (normoxia, 7·93 mg O 2 l -1 , c. 150 mm Hg or c. 20 kPa) or reduced oxygen levels (0·86 mg O 2 l -1 , c. 17 mm Hg or c. 2·2 kPa). Regardless of oxygen treatment, fish euthanized by an overdose of MS-222 had higher haematocrit and lower gill ATP:ADP than fish euthanized by other methods. The effects of 24 h hypoxic exposure on these and other variables, however, were equivalent among methods of euthanasia (i.e. there were no significant interactions between euthanasia method and oxygen treatment). The choice of an appropriate euthanasia method, therefore, will depend upon the magnitude of the treatment effects (e.g. hypoxia) relative to potential artefacts caused by euthanasia on the variables of interest. © 2017 The Fisheries Society of the British Isles.
Villaverde-Morcillo, S; Esteso, M C; Castaño, C; Santiago-Moreno, J
2016-02-01
Many post-mortem sperm collection techniques have been described for mammalian species, but their use in birds is scarce. This paper compares the efficacy of two post-mortem sperm retrieval techniques - the flushing and float-out methods - in the collection of rooster sperm, in conjunction with the use of two extenders, i.e., L&R-84 medium and Lake 7.1 medium. To determine whether the protective effects of these extenders against refrigeration are different for post-mortem and ejaculated sperm, pooled ejaculated samples (procured via the massage technique) were also diluted in the above extenders. Post-mortem and ejaculated sperm variables were assessed immediately at room temperature (0 h), and after refrigeration at 5°C for 24 and 48 h. The flushing method retrieved more sperm than the float-out method (596.5 ± 75.4 million sperm vs 341.0 ± 87.6 million sperm; p < 0.05); indeed, the number retrieved by the former method was similar to that obtained by massage-induced ejaculation (630.3 ± 78.2 million sperm). For sperm collected by all methods, the L&R-84 medium provided an advantage in terms of sperm motility variables at 0 h. In the refrigerated sperm samples, however, the Lake 7.1 medium was associated with higher percentages of viable sperm, and had a greater protective effect (p < 0.05) with respect to most motility variables. In conclusion, the flushing method is recommended for collecting sperm from dead birds. If this sperm needs to be refrigerated at 5°C until analysis, Lake 7.1 medium is recommended as an extender. © 2015 Blackwell Verlag GmbH.
DEFF Research Database (Denmark)
Gravesen, Jens
2015-01-01
and found the MacAdam ellipses which are often interpreted as defining the metric tensor at their centres. An important question is whether it is possible to define colour coordinates such that the Euclidean distance in these coordinates correspond to human perception. Using cubic splines to represent......The space of colours is a fascinating space. It is a real vector space, but no matter what inner product you put on the space the resulting Euclidean distance does not correspond to human perception of difference between colours. In 1942 MacAdam performed the first experiments on colour matching...
Product Operations Status Summary Metrics
Takagi, Atsuya; Toole, Nicholas
2010-01-01
The Product Operations Status Summary Metrics (POSSUM) computer program provides a readable view into the state of the Phoenix Operations Product Generation Subsystem (OPGS) data pipeline. POSSUM provides a user interface that can search the data store, collect product metadata, and display the results in an easily-readable layout. It was designed with flexibility in mind for support in future missions. Flexibility over various data store hierarchies is provided through the disk-searching facilities of Marsviewer. This is a proven program that has been in operational use since the first day of the Phoenix mission.
Web metrics for library and information professionals
Stuart, David
2014-01-01
This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional.Th...
Staley, James R.
2017-01-01
ABSTRACT Mendelian randomization, the use of genetic variants as instrumental variables (IV), can test for and estimate the causal effect of an exposure on an outcome. Most IV methods assume that the function relating the exposure to the expected value of the outcome (the exposure‐outcome relationship) is linear. However, in practice, this assumption may not hold. Indeed, often the primary question of interest is to assess the shape of this relationship. We present two novel IV methods for investigating the shape of the exposure‐outcome relationship: a fractional polynomial method and a piecewise linear method. We divide the population into strata using the exposure distribution, and estimate a causal effect, referred to as a localized average causal effect (LACE), in each stratum of population. The fractional polynomial method performs metaregression on these LACE estimates. The piecewise linear method estimates a continuous piecewise linear function, the gradient of which is the LACE estimate in each stratum. Both methods were demonstrated in a simulation study to estimate the true exposure‐outcome relationship well, particularly when the relationship was a fractional polynomial (for the fractional polynomial method) or was piecewise linear (for the piecewise linear method). The methods were used to investigate the shape of relationship of body mass index with systolic blood pressure and diastolic blood pressure. PMID:28317167
A method to screen obstructive sleep apnea using multi-variable non-intrusive measurements
International Nuclear Information System (INIS)
De Silva, S; Abeyratne, U R; Hukins, C
2011-01-01
Obstructive sleep apnea (OSA) is a serious sleep disorder. The current standard OSA diagnosis method is polysomnography (PSG) testing. PSG requires an overnight hospital stay while physically connected to 10–15 channels of measurement. PSG is expensive, inconvenient and requires the extensive involvement of a sleep technologist. As such, it is not suitable for community screening. OSA is a widespread disease and more than 80% of sufferers remain undiagnosed. Simplified, unattended and cheap OSA screening methods are urgently needed. Snoring is commonly associated with OSA but is not fully utilized in clinical diagnosis. Snoring contains pseudo-periodic packets of energy that produce characteristic vibrating sounds familiar to humans. In this paper, we propose a multi-feature vector that represents pitch information, formant information, a measure of periodic structure existence in snore episodes and the neck circumference of the subject to characterize OSA condition. Snore features were estimated from snore signals recorded in a sleep laboratory. The multi-feature vector was applied to a neural network for OSA/non-OSA classification and K-fold cross-validated using a random sub-sampling technique. We also propose a simple method to remove a specific class of background interference. Our method resulted in a sensitivity of 91 ± 6% and a specificity of 89 ± 5% for test data for AHI THRESHOLD = 15 for a database consisting of 51 subjects. This method has the potential as a non-intrusive, unattended technique to screen OSA using snore sound as the primary signal
Application of odex drilling method in a variably fractured volcanic/igneous environment
International Nuclear Information System (INIS)
Murphy, J.
1992-01-01
A case history of a subsurface investigation at a geothermal waste disposal facility within a volcanic flow regime illustrates a classic example of critical drilling problems arising from severe air and mud circulation loss. Extremely dense dacite and rhyolite rock alternating with severely fractured flow margins (interconnected with numerous voids and caverns) has provided the scenario for open-quotes gravel pilesclose quotes of substantial size between competent dacite flows. The interconnected void space at numerous depths beneath the site is great enough to create complete loss of circulation while using more than 3000 cubic feet per minute (cfm) of air at 350 pounds per square inch (psi). This initial failed effort also included the use of a foam additive. The technologies employed at this site to address the problem of circulation loss included air rotary casing hammer methods, mud rotary (with beat pulp additives and linen additives), boring wall stabilization, telescoped casing and ultimately the ODEX casing advancement system. The relative success of this seldom used method invites a discussion of the principals of the under-reamer drilling method (ODEX) and the physical limitations of the system. A practical knowledge of the advantages and disadvantages of each drilling method is necessary when designing an investigation addressing problems of soil and water contamination. Additionally, by addressing the methods that were unsuccessful, geologists, contractors and engineers can gain insight into the value and application of the various technologies available for similar drilling problems
Tayebi, A.; Shekari, Y.; Heydari, M. H.
2017-07-01
Several physical phenomena such as transformation of pollutants, energy, particles and many others can be described by the well-known convection-diffusion equation which is a combination of the diffusion and advection equations. In this paper, this equation is generalized with the concept of variable-order fractional derivatives. The generalized equation is called variable-order time fractional advection-diffusion equation (V-OTFA-DE). An accurate and robust meshless method based on the moving least squares (MLS) approximation and the finite difference scheme is proposed for its numerical solution on two-dimensional (2-D) arbitrary domains. In the time domain, the finite difference technique with a θ-weighted scheme and in the space domain, the MLS approximation are employed to obtain appropriate semi-discrete solutions. Since the newly developed method is a meshless approach, it does not require any background mesh structure to obtain semi-discrete solutions of the problem under consideration, and the numerical solutions are constructed entirely based on a set of scattered nodes. The proposed method is validated in solving three different examples including two benchmark problems and an applied problem of pollutant distribution in the atmosphere. In all such cases, the obtained results show that the proposed method is very accurate and robust. Moreover, a remarkable property so-called positive scheme for the proposed method is observed in solving concentration transport phenomena.
Computer Simulation of Nonuniform MTLs via Implicit Wendroff and State-Variable Methods
Directory of Open Access Journals (Sweden)
L. Brancik
2011-04-01
Full Text Available The paper deals with techniques for a computer simulation of nonuniform multiconductor transmission lines (MTLs based on the implicit Wendroff and the statevariable methods. The techniques fall into a class of finitedifference time-domain (FDTD methods useful to solve various electromagnetic systems. Their basic variants are extended and modified to enable solving both voltage and current distributions along nonuniform MTL’s wires and their sensitivities with respect to lumped and distributed parameters. An experimental error analysis is performed based on the Thomson cable whose analytical solutions are known, and some examples of simulation of both uniform and nonuniform MTLs are presented. Based on the Matlab language programme, CPU times are analyzed to compare efficiency of the methods. Some results for nonlinear MTLs simulation are presented as well.
Polymeric nanoparticles: A study on the preparation variables and characterization methods.
Crucho, Carina I C; Barros, Maria Teresa
2017-11-01
Since the emergence of Nanotechnology in the past decades, the development and design of nanomaterials has become an important field of research. An emerging component in this field is nanomedicine, wherein nanoscale materials are being developed for use as imaging agents or for drug delivery applications. Much work is currently focused in the preparation of well-defined nanomaterials in terms of size and shape. These factors play a significantly role in the nanomaterial behavior in vivo. In this context, this review focuses on the toolbox of available methods for the preparation of polymeric nanoparticles. We highlight some recent examples from the literature that demonstrate the influence of the preparation method on the physicochemical characteristics of the nanoparticles. Additionally, in the second part, the characterization methods for this type of nanoparticles are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.
METRIC EVALUATION PIPELINE FOR 3D MODELING OF URBAN SCENES
Directory of Open Access Journals (Sweden)
M. Bosch
2017-05-01
Full Text Available Publicly available benchmark data and metric evaluation approaches have been instrumental in enabling research to advance state of the art methods for remote sensing applications in urban 3D modeling. Most publicly available benchmark datasets have consisted of high resolution airborne imagery and lidar suitable for 3D modeling on a relatively modest scale. To enable research in larger scale 3D mapping, we have recently released a public benchmark dataset with multi-view commercial satellite imagery and metrics to compare 3D point clouds with lidar ground truth. We now define a more complete metric evaluation pipeline developed as publicly available open source software to assess semantically labeled 3D models of complex urban scenes derived from multi-view commercial satellite imagery. Evaluation metrics in our pipeline include horizontal and vertical accuracy and completeness, volumetric completeness and correctness, perceptual quality, and model simplicity. Sources of ground truth include airborne lidar and overhead imagery, and we demonstrate a semi-automated process for producing accurate ground truth shape files to characterize building footprints. We validate our current metric evaluation pipeline using 3D models produced using open source multi-view stereo methods. Data and software is made publicly available to enable further research and planned benchmarking activities.
Metric Evaluation Pipeline for 3d Modeling of Urban Scenes
Bosch, M.; Leichtman, A.; Chilcott, D.; Goldberg, H.; Brown, M.
2017-05-01
Publicly available benchmark data and metric evaluation approaches have been instrumental in enabling research to advance state of the art methods for remote sensing applications in urban 3D modeling. Most publicly available benchmark datasets have consisted of high resolution airborne imagery and lidar suitable for 3D modeling on a relatively modest scale. To enable research in larger scale 3D mapping, we have recently released a public benchmark dataset with multi-view commercial satellite imagery and metrics to compare 3D point clouds with lidar ground truth. We now define a more complete metric evaluation pipeline developed as publicly available open source software to assess semantically labeled 3D models of complex urban scenes derived from multi-view commercial satellite imagery. Evaluation metrics in our pipeline include horizontal and vertical accuracy and completeness, volumetric completeness and correctness, perceptual quality, and model simplicity. Sources of ground truth include airborne lidar and overhead imagery, and we demonstrate a semi-automated process for producing accurate ground truth shape files to characterize building footprints. We validate our current metric evaluation pipeline using 3D models produced using open source multi-view stereo methods. Data and software is made publicly available to enable further research and planned benchmarking activities.
Environmental cost of using poor decision metrics to prioritize environmental projects.
Pannell, David J; Gibson, Fiona L
2016-04-01
Conservation decision makers commonly use project-scoring metrics that are inconsistent with theory on optimal ranking of projects. As a result, there may often be a loss of environmental benefits. We estimated the magnitudes of these losses for various metrics that deviate from theory in ways that are common in practice. These metrics included cases where relevant variables were omitted from the benefits metric, project costs were omitted, and benefits were calculated using a faulty functional form. We estimated distributions of parameters from 129 environmental projects from Australia, New Zealand, and Italy for which detailed analyses had been completed previously. The cost of using poor prioritization metrics (in terms of lost environmental values) was often high--up to 80% in the scenarios we examined. The cost in percentage terms was greater when the budget was smaller. The most costly errors were omitting information about environmental values (up to 31% loss of environmental values), omitting project costs (up to 35% loss), omitting the effectiveness of management actions (up to 9% loss), and using a weighted-additive decision metric for variables that should be multiplied (up to 23% loss). The latter 3 are errors that occur commonly in real-world decision metrics, in combination often reducing potential benefits from conservation investments by 30-50%. Uncertainty about parameter values also reduced the benefits from investments in conservation projects but often not by as much as faulty prioritization metrics. © 2016 Society for Conservation Biology.
Method for the generation of variable density metal vapors which bypasses the liquidus phase
Kunnmann, Walter; Larese, John Z.
2001-01-01
The present invention provides a method for producing a metal vapor that includes the steps of combining a metal and graphite in a vessel to form a mixture; heating the mixture to a first temperature in an argon gas atmosphere to form a metal carbide; maintaining the first temperature for a period of time; heating the metal carbide to a second temperature to form a metal vapor; withdrawing the metal vapor and the argon gas from the vessel; and separating the metal vapor from the argon gas. Metal vapors made using this method can be used to produce uniform powders of the metal oxide that have narrow size distribution and high purity.