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Sample records for mahalanobis distance metric

  1. Mahalanobis Distance Based Iterative Closest Point

    DEFF Research Database (Denmark)

    Hansen, Mads Fogtmann; Blas, Morten Rufus; Larsen, Rasmus

    2007-01-01

    the notion of a mahalanobis distance map upon a point set with associated covariance matrices which in addition to providing correlation weighted distance implicitly provides a method for assigning correspondence during alignment. This distance map provides an easy formulation of the ICP problem that permits...... a fast optimization. Initially, the covariance matrices are set to the identity matrix, and all shapes are aligned to a randomly selected shape (equivalent to standard ICP). From this point the algorithm iterates between the steps: (a) obtain mean shape and new estimates of the covariance matrices from...... the aligned shapes, (b) align shapes to the mean shape. Three different methods for estimating the mean shape with associated covariance matrices are explored in the paper. The proposed methods are validated experimentally on two separate datasets (IMM face dataset and femur-bones). The superiority of ICP...

  2. Mahalanobis distance and variable selection to optimize dose response

    International Nuclear Information System (INIS)

    Moore, D.H. II; Bennett, D.E.; Wyrobek, A.J.; Kranzler, D.

    1979-01-01

    A battery of statistical techniques are combined to improve detection of low-level dose response. First, Mahalanobis distances are used to classify objects as normal or abnormal. Then the proportion classified abnormal is regressed on dose. Finally, a subset of regressor variables is selected which maximizes the slope of the dose response line. Use of the techniques is illustrated by application to mouse sperm damaged by low doses of x-rays

  3. Distance Metric Tracking

    Science.gov (United States)

    2016-03-02

    whereBψ is any Bregman divergence and ηt is the learning rate parameter. From (Hall & Willett, 2015) we have: Theorem 1. G` = max θ∈Θ,`∈L ‖∇f(θ)‖ φmax = 1...Kullback-Liebler divergence between an initial guess of the matrix that parameterizes the Mahalanobis distance and a solution that satisfies a set of...Bregman divergence and ηt is the learning rate parameter. M̂0, µ̂0 are initialized to some initial value. In [18] a closed-form algorithm for solving

  4. KM-FCM: A fuzzy clustering optimization algorithm based on Mahalanobis distance

    Directory of Open Access Journals (Sweden)

    Zhiwen ZU

    2018-04-01

    Full Text Available The traditional fuzzy clustering algorithm uses Euclidean distance as the similarity criterion, which is disadvantageous to the multidimensional data processing. In order to solve this situation, Mahalanobis distance is used instead of the traditional Euclidean distance, and the optimization of fuzzy clustering algorithm based on Mahalanobis distance is studied to enhance the clustering effect and ability. With making the initialization means by Heuristic search algorithm combined with k-means algorithm, and in terms of the validity function which could automatically adjust the optimal clustering number, an optimization algorithm KM-FCM is proposed. The new algorithm is compared with FCM algorithm, FCM-M algorithm and M-FCM algorithm in three standard data sets. The experimental results show that the KM-FCM algorithm is effective. It has higher clustering accuracy than FCM, FCM-M and M-FCM, recognizing high-dimensional data clustering well. It has global optimization effect, and the clustering number has no need for setting in advance. The new algorithm provides a reference for the optimization of fuzzy clustering algorithm based on Mahalanobis distance.

  5. Outlier detection by robust Mahalanobis distance in geological data obtained by INAA to provenance studies

    Energy Technology Data Exchange (ETDEWEB)

    Santos, Jose O. dos, E-mail: osmansantos@ig.com.br [Instituto Federal de Educacao, Ciencia e Tecnologia de Sergipe (IFS), Lagarto, SE (Brazil); Munita, Casimiro S., E-mail: camunita@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Soares, Emilio A.A., E-mail: easoares@ufan.edu.br [Universidade Federal do Amazonas (UFAM), Manaus, AM (Brazil). Dept. de Geociencias

    2013-07-01

    The detection of outlier in geochemical studies is one of the main difficulties in the interpretation of dataset because they can disturb the statistical method. The search for outliers in geochemical studies is usually based in the Mahalanobis distance (MD), since points in multivariate space that are a distance larger the some predetermined values from center of the data are considered outliers. However, the MD is very sensitive to the presence of discrepant samples. Many robust estimators for location and covariance have been introduced in the literature, such as Minimum Covariance Determinant (MCD) estimator. When MCD estimators are used to calculate the MD leads to the so-called Robust Mahalanobis Distance (RD). In this context, in this work RD was used to detect outliers in geological study of samples collected from confluence of Negro and Solimoes rivers. The purpose of this study was to study the contributions of the sediments deposited by the Solimoes and Negro rivers in the filling of the tectonic depressions at Parana do Ariau. For that 113 samples were analyzed by Instrumental Neutron Activation Analysis (INAA) in which were determined the concentration of As, Ba, Ce, Co, Cr, Cs, Eu, Fe, Hf, K, La, Lu, Na, Nd, Rb, Sb, Sc, Sm, U, Yb, Ta, Tb, Th and Zn. In the dataset was possible to construct the ellipse corresponding to robust Mahalanobis distance for each group of samples. The samples found outside of the tolerance ellipse were considered an outlier. The results showed that Robust Mahalanobis Distance was more appropriate for the identification of the outliers, once it is a more restrictive method. (author)

  6. Outlier detection by robust Mahalanobis distance in geological data obtained by INAA to provenance studies

    International Nuclear Information System (INIS)

    Santos, Jose O. dos; Munita, Casimiro S.; Soares, Emilio A.A.

    2013-01-01

    The detection of outlier in geochemical studies is one of the main difficulties in the interpretation of dataset because they can disturb the statistical method. The search for outliers in geochemical studies is usually based in the Mahalanobis distance (MD), since points in multivariate space that are a distance larger the some predetermined values from center of the data are considered outliers. However, the MD is very sensitive to the presence of discrepant samples. Many robust estimators for location and covariance have been introduced in the literature, such as Minimum Covariance Determinant (MCD) estimator. When MCD estimators are used to calculate the MD leads to the so-called Robust Mahalanobis Distance (RD). In this context, in this work RD was used to detect outliers in geological study of samples collected from confluence of Negro and Solimoes rivers. The purpose of this study was to study the contributions of the sediments deposited by the Solimoes and Negro rivers in the filling of the tectonic depressions at Parana do Ariau. For that 113 samples were analyzed by Instrumental Neutron Activation Analysis (INAA) in which were determined the concentration of As, Ba, Ce, Co, Cr, Cs, Eu, Fe, Hf, K, La, Lu, Na, Nd, Rb, Sb, Sc, Sm, U, Yb, Ta, Tb, Th and Zn. In the dataset was possible to construct the ellipse corresponding to robust Mahalanobis distance for each group of samples. The samples found outside of the tolerance ellipse were considered an outlier. The results showed that Robust Mahalanobis Distance was more appropriate for the identification of the outliers, once it is a more restrictive method. (author)

  7. Limitations to mapping habitat-use areas in changing landscapes using the Mahalanobis distance statistic

    Science.gov (United States)

    Knick, Steven T.; Rotenberry, J.T.

    1998-01-01

    We tested the potential of a GIS mapping technique, using a resource selection model developed for black-tailed jackrabbits (Lepus californicus) and based on the Mahalanobis distance statistic, to track changes in shrubsteppe habitats in southwestern Idaho. If successful, the technique could be used to predict animal use areas, or those undergoing change, in different regions from the same selection function and variables without additional sampling. We determined the multivariate mean vector of 7 GIS variables that described habitats used by jackrabbits. We then ranked the similarity of all cells in the GIS coverage from their Mahalanobis distance to the mean habitat vector. The resulting map accurately depicted areas where we sighted jackrabbits on verification surveys. We then simulated an increase in shrublands (which are important habitats). Contrary to expectation, the new configurations were classified as lower similarity relative to the original mean habitat vector. Because the selection function is based on a unimodal mean, any deviation, even if biologically positive, creates larger Malanobis distances and lower similarity values. We recommend the Mahalanobis distance technique for mapping animal use areas when animals are distributed optimally, the landscape is well-sampled to determine the mean habitat vector, and distributions of the habitat variables does not change.

  8. Mahalanobis Distance

    Indian Academy of Sciences (India)

    defined by. (1) where the superfix T denotes matrix transpose, L denotes the common (nonsingular) covariance matrix of X in each group G 1 and G 2" It can be seen ... standard deviation. The quadratic form (1) has the effect of transforming the variables to uncorrelated standardised variables. Yand computing the (squared) ...

  9. Mahalanobis Distance

    Indian Academy of Sciences (India)

    McLachlan's research interests have ... Craniometric and anthropological studies are the first field in which the ... applied and have since attracted the attention of many workers ... shall label as Gland G 2' For example, in some community, G 1.

  10. A method for assigning species into groups based on generalized Mahalanobis distance between habitat model coefficients

    Science.gov (United States)

    Williams, C.J.; Heglund, P.J.

    2009-01-01

    Habitat association models are commonly developed for individual animal species using generalized linear modeling methods such as logistic regression. We considered the issue of grouping species based on their habitat use so that management decisions can be based on sets of species rather than individual species. This research was motivated by a study of western landbirds in northern Idaho forests. The method we examined was to separately fit models to each species and to use a generalized Mahalanobis distance between coefficient vectors to create a distance matrix among species. Clustering methods were used to group species from the distance matrix, and multidimensional scaling methods were used to visualize the relations among species groups. Methods were also discussed for evaluating the sensitivity of the conclusions because of outliers or influential data points. We illustrate these methods with data from the landbird study conducted in northern Idaho. Simulation results are presented to compare the success of this method to alternative methods using Euclidean distance between coefficient vectors and to methods that do not use habitat association models. These simulations demonstrate that our Mahalanobis-distance- based method was nearly always better than Euclidean-distance-based methods or methods not based on habitat association models. The methods used to develop candidate species groups are easily explained to other scientists and resource managers since they mainly rely on classical multivariate statistical methods. ?? 2008 Springer Science+Business Media, LLC.

  11. Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

    Science.gov (United States)

    Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

    2017-07-01

    Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

  12. [Mahalanobis distance based hyperspectral characteristic discrimination of leaves of different desert tree species].

    Science.gov (United States)

    Lin, Hai-jun; Zhang, Hui-fang; Gao, Ya-qi; Li, Xia; Yang, Fan; Zhou, Yan-fei

    2014-12-01

    The hyperspectral reflectance of Populus euphratica, Tamarix hispida, Haloxylon ammodendron and Calligonum mongolicum in the lower reaches of Tarim River and Turpan Desert Botanical Garden was measured by using the HR-768 field-portable spectroradiometer. The method of continuum removal, first derivative reflectance and second derivative reflectance were used to deal with the original spectral data of four tree species. The method of Mahalanobis Distance was used to select the bands with significant differences in the original spectral data and transform spectral data to identify the different tree species. The progressive discrimination analyses were used to test the selective bands used to identify different tree species. The results showed that The Mahalanobis Distance method was an effective method in feature band extraction. The bands for identifying different tree species were most near-infrared bands. The recognition accuracy of four methods was 85%, 93.8%, 92.4% and 95.5% respectively. Spectrum transform could improve the recognition accuracy. The recognition accuracy of different research objects and different spectrum transform methods were different. The research provided evidence for desert tree species classification, monitoring biodiversity and the analysis of area in desert by using large scale remote sensing method.

  13. Protein-protein interaction site predictions with minimum covariance determinant and Mahalanobis distance.

    Science.gov (United States)

    Qiu, Zhijun; Zhou, Bo; Yuan, Jiangfeng

    2017-11-21

    Protein-protein interaction site (PPIS) prediction must deal with the diversity of interaction sites that limits their prediction accuracy. Use of proteins with unknown or unidentified interactions can also lead to missing interfaces. Such data errors are often brought into the training dataset. In response to these two problems, we used the minimum covariance determinant (MCD) method to refine the training data to build a predictor with better performance, utilizing its ability of removing outliers. In order to predict test data in practice, a method based on Mahalanobis distance was devised to select proper test data as input for the predictor. With leave-one-validation and independent test, after the Mahalanobis distance screening, our method achieved higher performance according to Matthews correlation coefficient (MCC), although only a part of test data could be predicted. These results indicate that data refinement is an efficient approach to improve protein-protein interaction site prediction. By further optimizing our method, it is hopeful to develop predictors of better performance and wide range of application. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Assessing Gait Impairments Based on Auto-Encoded Patterns of Mahalanobis Distances from Consecutive Steps.

    Science.gov (United States)

    Muñoz-Organero, Mario; Davies, Richard; Mawson, Sue

    2017-01-01

    Insole pressure sensors capture the force distribution patterns during the stance phase while walking. By comparing patterns obtained from healthy individuals to patients suffering different medical conditions based on a given similarity measure, automatic impairment indexes can be computed in order to help in applications such as rehabilitation. This paper uses the data sensed from insole pressure sensors for a group of healthy controls to train an auto-encoder using patterns of stochastic distances in series of consecutive steps while walking at normal speeds. Two experiment groups are compared to the healthy control group: a group of patients suffering knee pain and a group of post-stroke survivors. The Mahalanobis distance is computed for every single step by each participant compared to the entire dataset sensed from healthy controls. The computed distances for consecutive steps are fed into the previously trained autoencoder and the average error is used to assess how close the walking segment is to the autogenerated model from healthy controls. The results show that automatic distortion indexes can be used to assess each participant as compared to normal patterns computed from healthy controls. The stochastic distances observed for the group of stroke survivors are bigger than those for the people with knee pain.

  15. Semiparametric Allelic Tests for Mapping Multiple Phenotypes: Binomial Regression and Mahalanobis Distance.

    Science.gov (United States)

    Majumdar, Arunabha; Witte, John S; Ghosh, Saurabh

    2015-12-01

    Binary phenotypes commonly arise due to multiple underlying quantitative precursors and genetic variants may impact multiple traits in a pleiotropic manner. Hence, simultaneously analyzing such correlated traits may be more powerful than analyzing individual traits. Various genotype-level methods, e.g., MultiPhen (O'Reilly et al. []), have been developed to identify genetic factors underlying a multivariate phenotype. For univariate phenotypes, the usefulness and applicability of allele-level tests have been investigated. The test of allele frequency difference among cases and controls is commonly used for mapping case-control association. However, allelic methods for multivariate association mapping have not been studied much. In this article, we explore two allelic tests of multivariate association: one using a Binomial regression model based on inverted regression of genotype on phenotype (Binomial regression-based Association of Multivariate Phenotypes [BAMP]), and the other employing the Mahalanobis distance between two sample means of the multivariate phenotype vector for two alleles at a single-nucleotide polymorphism (Distance-based Association of Multivariate Phenotypes [DAMP]). These methods can incorporate both discrete and continuous phenotypes. Some theoretical properties for BAMP are studied. Using simulations, the power of the methods for detecting multivariate association is compared with the genotype-level test MultiPhen's. The allelic tests yield marginally higher power than MultiPhen for multivariate phenotypes. For one/two binary traits under recessive mode of inheritance, allelic tests are found to be substantially more powerful. All three tests are applied to two different real data and the results offer some support for the simulation study. We propose a hybrid approach for testing multivariate association that implements MultiPhen when Hardy-Weinberg Equilibrium (HWE) is violated and BAMP otherwise, because the allelic approaches assume HWE

  16. Fault diagnosis of rolling bearings based on multifractal detrended fluctuation analysis and Mahalanobis distance criterion

    Science.gov (United States)

    Lin, Jinshan; Chen, Qian

    2013-07-01

    Vibration data of faulty rolling bearings are usually nonstationary and nonlinear, and contain fairly weak fault features. As a result, feature extraction of rolling bearing fault data is always an intractable problem and has attracted considerable attention for a long time. This paper introduces multifractal detrended fluctuation analysis (MF-DFA) to analyze bearing vibration data and proposes a novel method for fault diagnosis of rolling bearings based on MF-DFA and Mahalanobis distance criterion (MDC). MF-DFA, an extension of monofractal DFA, is a powerful tool for uncovering the nonlinear dynamical characteristics buried in nonstationary time series and can capture minor changes of complex system conditions. To begin with, by MF-DFA, multifractality of bearing fault data was quantified with the generalized Hurst exponent, the scaling exponent and the multifractal spectrum. Consequently, controlled by essentially different dynamical mechanisms, the multifractality of four heterogeneous bearing fault data is significantly different; by contrast, controlled by slightly different dynamical mechanisms, the multifractality of homogeneous bearing fault data with different fault diameters is significantly or slightly different depending on different types of bearing faults. Therefore, the multifractal spectrum, as a set of parameters describing multifractality of time series, can be employed to characterize different types and severity of bearing faults. Subsequently, five characteristic parameters sensitive to changes of bearing fault conditions were extracted from the multifractal spectrum and utilized to construct fault features of bearing fault data. Moreover, Hilbert transform based envelope analysis, empirical mode decomposition (EMD) and wavelet transform (WT) were utilized to study the same bearing fault data. Also, the kurtosis and the peak levels of the EMD or the WT component corresponding to the bearing tones in the frequency domain were carefully checked

  17. Is flood risk capitalized into real estate market values? : a Mahalanobis-metric matching approach to housing market in Busan, South Korea

    Science.gov (United States)

    Jung, E.; Yoon, H.

    2016-12-01

    Natural disasters are substantial source of social and economic damage around the globe. The amount of damage is larger when such catastrophe events happen in urbanized areas where the wealth is concentrated. Disasters cause losses in real estate assets, incurring additional cost of repair and maintenance of the properties. For this reason, natural hazard risk such as flooding and landslide is regarded as one of the important determinants of homebuyers' choice and preference. In this research, we aim to reveal whether the past records of flood affect real estate market values in Busan, Korea in 2014, under a hypothesis that homebuyers' perception of natural hazard is reflected on housing values, using the Mahalanobis-metric matching method. Unlike conventionally used hedonic pricing model to estimate capitalization of flood risk into the sales price of properties, the analytical method we adopt here enables inferring causal effects by efficiently controlling for observed/unobserved omitted variable bias. This matching approach pairs each inundated property (treatment variable) with a non-inundated property (control variable) with the closest Mahalanobis distance between them, and comparing their effects on residential property sales price (outcome variable). As a result, we expect price discounts for inundated properties larger than the one for comparable non-inundated properties. This research will be valuable in establishing the mitigation policies of future climate change to relieve the possible negative economic consequences from the disaster by estimating how people perceive and respond to natural hazard. This work was supported by the Korea Environmental Industry and Technology Institute (KEITI) under Grant (No. 2014-001-310007).

  18. Experimental Study on Damage Detection in Timber Specimens Based on an Electromechanical Impedance Technique and RMSD-Based Mahalanobis Distance

    Directory of Open Access Journals (Sweden)

    Dansheng Wang

    2016-10-01

    Full Text Available In the electromechanical impedance (EMI method, the PZT patch performs the functions of both sensor and exciter. Due to the high frequency actuation and non-model based characteristics, the EMI method can be utilized to detect incipient structural damage. In recent years EMI techniques have been widely applied to monitor the health status of concrete and steel materials, however, studies on application to timber are limited. This paper will explore the feasibility of using the EMI technique for damage detection in timber specimens. In addition, the conventional damage index, namely root mean square deviation (RMSD is employed to evaluate the level of damage. On that basis, a new damage index, Mahalanobis distance based on RMSD, is proposed to evaluate the damage severity of timber specimens. Experimental studies are implemented to detect notch and hole damage in the timber specimens. Experimental results verify the availability and robustness of the proposed damage index and its superiority over the RMSD indexes.

  19. Precise Positioning Method for Logistics Tracking Systems Using Personal Handy-Phone System Based on Mahalanobis Distance

    Science.gov (United States)

    Yokoi, Naoaki; Kawahara, Yasuhiro; Hosaka, Hiroshi; Sakata, Kenji

    Focusing on the Personal Handy-phone System (PHS) positioning service used in physical distribution logistics, a positioning error offset method for improving positioning accuracy is invented. A disadvantage of PHS positioning is that measurement errors caused by the fluctuation of radio waves due to buildings around the terminal are large, ranging from several tens to several hundreds of meters. In this study, an error offset method is developed, which learns patterns of positioning results (latitude and longitude) containing errors and the highest signal strength at major logistic points in advance, and matches them with new data measured in actual distribution processes according to the Mahalanobis distance. Then the matching resolution is improved to 1/40 that of the conventional error offset method.

  20. Reconstruction of hit time and hit position of annihilation quanta in the J-PET detector using the Mahalanobis distance

    Directory of Open Access Journals (Sweden)

    Sharma Neha Gupta

    2015-12-01

    Full Text Available The J-PET detector being developed at the Jagiellonian University is a positron emission tomograph composed of the long strips of polymer scintillators. At the same time, it is a detector system that will be used for studies of the decays of positronium atoms. The shape of photomultiplier signals depends on the hit time and hit position of the gamma quantum. In order to take advantage of this fact, a dedicated sampling front-end electronics that enables to sample signals in voltage domain with the time precision of about 20 ps and novel reconstruction method based on the comparison of examined signal with the model signals stored in the library has been developed. As a measure of the similarity, we use the Mahalanobis distance. The achievable position and time resolution depend on the number and values of the threshold levels at which the signal is sampled. A reconstruction method as well as preliminary results are presented and discussed.

  1. Using Mahalanobis Distance Scores for Matched Pairing of Schools in a Randomized Controlled Trial Study of Leadership and Assistance for Science Education Reform (LASER)

    Science.gov (United States)

    Zoblotsky, Todd; Ransford-Kaldon, Carolyn; Morrison, Donald M.

    2011-01-01

    The present paper describes the recruitment and site selection process that has been underway since January 2011, with particular emphasis on the use of Mahalanobis distance score to determine matched pairs of sites prior to randomization to treatment and control groups. Through a systematic winnowing process, the authors found that they could…

  2. Metrics for measuring distances in configuration spaces

    International Nuclear Information System (INIS)

    Sadeghi, Ali; Ghasemi, S. Alireza; Schaefer, Bastian; Mohr, Stephan; Goedecker, Stefan; Lill, Markus A.

    2013-01-01

    In order to characterize molecular structures we introduce configurational fingerprint vectors which are counterparts of quantities used experimentally to identify structures. The Euclidean distance between the configurational fingerprint vectors satisfies the properties of a metric and can therefore safely be used to measure dissimilarities between configurations in the high dimensional configuration space. In particular we show that these metrics are a perfect and computationally cheap replacement for the root-mean-square distance (RMSD) when one has to decide whether two noise contaminated configurations are identical or not. We introduce a Monte Carlo approach to obtain the global minimum of the RMSD between configurations, which is obtained from a global minimization over all translations, rotations, and permutations of atomic indices

  3. New neural network classifier of fall-risk based on the Mahalanobis distance and kinematic parameters assessed by a wearable device

    International Nuclear Information System (INIS)

    Giansanti, Daniele; Macellari, Velio; Maccioni, Giovanni

    2008-01-01

    Fall prevention lacks easy, quantitative and wearable methods for the classification of fall-risk (FR). Efforts must be thus devoted to the choice of an ad hoc classifier both to reduce the size of the sample used to train the classifier and to improve performances. A new methodology that uses a neural network (NN) and a wearable device are hereby proposed for this purpose. The NN uses kinematic parameters assessed by a wearable device with accelerometers and rate gyroscopes during a posturography protocol. The training of the NN was based on the Mahalanobis distance and was carried out on two groups of 30 elderly subjects with varying fall-risk Tinetti scores. The validation was done on two groups of 100 subjects with different fall-risk Tinetti scores and showed that, both in terms of specificity and sensitivity, the NN performed better than other classifiers (naive Bayes, Bayes net, multilayer perceptron, support vector machines, statistical classifiers). In particular, (i) the proposed NN methodology improved the specificity and sensitivity by a mean of 3% when compared to the statistical classifier based on the Mahalanobis distance (SCMD) described in Giansanti (2006 Physiol. Meas. 27 1081–90); (ii) the assessed specificity was 97%, the assessed sensitivity was 98% and the area under receiver operator characteristics was 0.965. (note)

  4. Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

    Science.gov (United States)

    Stephenson, D. B.

    1997-10-01

    The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.

  5. Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

    OpenAIRE

    Stephenson, D. B.

    2011-01-01

    he skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the var...

  6. Alignment-free genome tree inference by learning group-specific distance metrics.

    Science.gov (United States)

    Patil, Kaustubh R; McHardy, Alice C

    2013-01-01

    Understanding the evolutionary relationships between organisms is vital for their in-depth study. Gene-based methods are often used to infer such relationships, which are not without drawbacks. One can now attempt to use genome-scale information, because of the ever increasing number of genomes available. This opportunity also presents a challenge in terms of computational efficiency. Two fundamentally different methods are often employed for sequence comparisons, namely alignment-based and alignment-free methods. Alignment-free methods rely on the genome signature concept and provide a computationally efficient way that is also applicable to nonhomologous sequences. The genome signature contains evolutionary signal as it is more similar for closely related organisms than for distantly related ones. We used genome-scale sequence information to infer taxonomic distances between organisms without additional information such as gene annotations. We propose a method to improve genome tree inference by learning specific distance metrics over the genome signature for groups of organisms with similar phylogenetic, genomic, or ecological properties. Specifically, our method learns a Mahalanobis metric for a set of genomes and a reference taxonomy to guide the learning process. By applying this method to more than a thousand prokaryotic genomes, we showed that, indeed, better distance metrics could be learned for most of the 18 groups of organisms tested here. Once a group-specific metric is available, it can be used to estimate the taxonomic distances for other sequenced organisms from the group. This study also presents a large scale comparison between 10 methods--9 alignment-free and 1 alignment-based.

  7. The External Performance Appraisal of China Energy Regulation: An Empirical Study Using a TOPSIS Method Based on Entropy Weight and Mahalanobis Distance.

    Science.gov (United States)

    Wang, Zheng-Xin; Li, Dan-Dan; Zheng, Hong-Hao

    2018-01-30

    In China's industrialization process, the effective regulation of energy and environment can promote the positive externality of energy consumption while reducing negative externality, which is an important means for realizing the sustainable development of an economic society. The study puts forward an improved technique for order preference by similarity to an ideal solution based on entropy weight and Mahalanobis distance (briefly referred as E-M-TOPSIS). The performance of the approach was verified to be satisfactory. By separately using traditional and improved TOPSIS methods, the study carried out the empirical appraisals on the external performance of China's energy regulation during 1999~2015. The results show that the correlation between the performance indexes causes the significant difference between the appraisal results of E-M-TOPSIS and traditional TOPSIS. The E-M-TOPSIS takes the correlation between indexes into account and generally softens the closeness degree compared with traditional TOPSIS. Moreover, it makes the relative closeness degree fluctuate within a small-amplitude. The results conform to the practical condition of China's energy regulation and therefore the E-M-TOPSIS is favorably applicable for the external performance appraisal of energy regulation. Additionally, the external economic performance and social responsibility performance (including environmental and energy safety performances) based on the E-M-TOPSIS exhibit significantly different fluctuation trends. The external economic performance dramatically fluctuates with a larger fluctuation amplitude, while the social responsibility performance exhibits a relatively stable interval fluctuation. This indicates that compared to the social responsibility performance, the fluctuation of external economic performance is more sensitive to energy regulation.

  8. Research on cardiovascular disease prediction based on distance metric learning

    Science.gov (United States)

    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.

  9. Active Metric Learning for Supervised Classification

    OpenAIRE

    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...

  10. Modified Mahalanobis Taguchi System for Imbalance Data Classification

    Directory of Open Access Journals (Sweden)

    Mahmoud El-Banna

    2017-01-01

    Full Text Available The Mahalanobis Taguchi System (MTS is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS. To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs, Naive Bayes (NB, Probabilistic Mahalanobis Taguchi Systems (PTM, Synthetic Minority Oversampling Technique (SMOTE, Adaptive Conformal Transformation (ACT, Kernel Boundary Alignment (KBA, Hidden Naive Bayes (HNB, and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA.

  11. Modified Mahalanobis Taguchi System for Imbalance Data Classification

    Science.gov (United States)

    2017-01-01

    The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA). PMID:28811820

  12. A study of metrics of distance and correlation between ranked lists for compositionality detection

    DEFF Research Database (Denmark)

    Lioma, Christina; Hansen, Niels Dalum

    2017-01-01

    affects the measurement of semantic similarity. We propose a new compositionality detection method that represents phrases as ranked lists of term weights. Our method approximates the semantic similarity between two ranked list representations using a range of well-known distance and correlation metrics...... of compositionality using any of the distance and correlation metrics considered....

  13. Mahalanobis' Contributions to Sample Surveys

    Indian Academy of Sciences (India)

    Sample Survey started its operations in October 1950 under the ... and adopted random cuts for estimating the acreage under jute ... demographic factors relating to indebtedness, unemployment, ... traffic surveys, demand for currency coins and average life of .... Mahalanobis derived the optimum allocation in stratified.

  14. Metric distances derived from cosine similarity and Pearson and Spearman correlations

    OpenAIRE

    van Dongen, Stijn; Enright, Anton J.

    2012-01-01

    We investigate two classes of transformations of cosine similarity and Pearson and Spearman correlations into metric distances, utilising the simple tool of metric-preserving functions. The first class puts anti-correlated objects maximally far apart. Previously known transforms fall within this class. The second class collates correlated and anti-correlated objects. An example of such a transformation that yields a metric distance is the sine function when applied to centered data.

  15. A robust metric for screening outliers from analogue product manufacturing tests responses

    NARCIS (Netherlands)

    Krishnan, S.; Kerkhoff, H.G.

    2011-01-01

    Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defective devices from non-defective ones. An associated problem with this approach is the estimation of a robust mean and a covariance matrix. In the absence of such robust estimates, especially in the

  16. A Robust Metric for Screening Outliers from Analogue Product Manufacturing Tests Responses

    NARCIS (Netherlands)

    Krishnan, Shaji; Krishnan, Shaji; Kerkhoff, Hans G.

    2011-01-01

    Mahalanobis distance is one of the commonly used multivariate metrics for finely segregating defective devices from non-defective ones. An associated problem with this approach is the estimation of a robust mean and a covariance matrix. In the absence of such robust estimates, especially in the

  17. Learning Global-Local Distance Metrics for Signature-Based Biometric Cryptosystems

    Directory of Open Access Journals (Sweden)

    George S. Eskander Ekladious

    2017-11-01

    Full Text Available Biometric traits, such as fingerprints, faces and signatures have been employed in bio-cryptosystems to secure cryptographic keys within digital security schemes. Reliable implementations of these systems employ error correction codes formulated as simple distance thresholds, although they may not effectively model the complex variability of behavioral biometrics like signatures. In this paper, a Global-Local Distance Metric (GLDM framework is proposed to learn cost-effective distance metrics, which reduce within-class variability and augment between-class variability, so that simple error correction thresholds of bio-cryptosystems provide high classification accuracy. First, a large number of samples from a development dataset are used to train a global distance metric that differentiates within-class from between-class samples of the population. Then, once user-specific samples are available for enrollment, the global metric is tuned to a local user-specific one. Proof-of-concept experiments on two reference offline signature databases confirm the viability of the proposed approach. Distance metrics are produced based on concise signature representations consisting of about 20 features and a single prototype. A signature-based bio-cryptosystem is designed using the produced metrics and has shown average classification error rates of about 7% and 17% for the PUCPR and the GPDS-300 databases, respectively. This level of performance is comparable to that obtained with complex state-of-the-art classifiers.

  18. Sequence of maximal distance codes in graphs or other metric spaces

    Directory of Open Access Journals (Sweden)

    Charles Delorme

    2013-11-01

    Full Text Available Given a subset C in a metric space E, its successor is the subset  s(C of points at maximum distance from C in E. We study some properties of the sequence obtained by iterating this operation.  Graphs with their usual distance provide already typical examples.

  19. Two fixed point theorems on quasi-metric spaces via mw- distances

    Energy Technology Data Exchange (ETDEWEB)

    Alegre, C.

    2017-07-01

    In this paper we prove a Banach-type fixed point theorem and a Kannan-type theorem in the setting of quasi-metric spaces using the notion of mw-distance. These theorems generalize some results that have recently appeared in the literature. (Author)

  20. Fixed point results for contractions involving generalized altering distances in ordered metric spaces

    Directory of Open Access Journals (Sweden)

    Samet Bessem

    2011-01-01

    Full Text Available Abstract In this article, we establish coincidence point and common fixed point theorems for mappings satisfying a contractive inequality which involves two generalized altering distance functions in ordered complete metric spaces. As application, we study the existence of a common solution to a system of integral equations. 2000 Mathematics subject classification. Primary 47H10, Secondary 54H25

  1. Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

    Science.gov (United States)

    Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

    2017-12-01

    How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

  2. An uncertainty importance measure using a distance metric for the change in a cumulative distribution function

    International Nuclear Information System (INIS)

    Chun, Moon-Hyun; Han, Seok-Jung; Tak, Nam-IL

    2000-01-01

    A simple measure of uncertainty importance using the entire change of cumulative distribution functions (CDFs) has been developed for use in probability safety assessments (PSAs). The entire change of CDFs is quantified in terms of the metric distance between two CDFs. The metric distance measure developed in this study reflects the relative impact of distributional changes of inputs on the change of an output distribution, while most of the existing uncertainty importance measures reflect the magnitude of relative contribution of input uncertainties to the output uncertainty. The present measure has been evaluated analytically for various analytical distributions to examine its characteristics. To illustrate the applicability and strength of the present measure, two examples are provided. The first example is an application of the present measure to a typical problem of a system fault tree analysis and the second one is for a hypothetical non-linear model. Comparisons of the present result with those obtained by existing uncertainty importance measures show that the metric distance measure is a useful tool to express the measure of uncertainty importance in terms of the relative impact of distributional changes of inputs on the change of an output distribution

  3. Characterization of Diffusion Metric Map Similarity in Data From a Clinical Data Repository Using Histogram Distances

    Science.gov (United States)

    Warner, Graham C.; Helmer, Karl G.

    2018-01-01

    As the sharing of data is mandated by funding agencies and journals, reuse of data has become more prevalent. It becomes imperative, therefore, to develop methods to characterize the similarity of data. While users can group data based on the acquisition parameters stored in the file headers, these gives no indication whether a file can be combined with other data without increasing the variance in the data set. Methods have been implemented that characterize the signal-to-noise ratio or identify signal drop-outs in the raw image files, but potential users of data often have access to calculated metric maps and these are more difficult to characterize and compare. Here we describe a histogram-distance-based method applied to diffusion metric maps of fractional anisotropy and mean diffusivity that were generated using data extracted from a repository of clinically-acquired MRI data. We describe the generation of the data set, the pitfalls specific to diffusion MRI data, and the results of the histogram distance analysis. We find that, in general, data from GE scanners are less similar than are data from Siemens scanners. We also find that the distribution of distance metric values is not Gaussian at any selection of the acquisition parameters considered here (field strength, number of gradient directions, b-value, and vendor). PMID:29568257

  4. A robust new metric of phenotypic distance to estimate and compare multiple trait differences among populations

    Directory of Open Access Journals (Sweden)

    Rebecca SAFRAN, Samuel FLAXMAN, Michael KOPP, Darren E. IRWIN, Derek BRIGGS, Matthew R. EVANS, W. Chris FUNK, David A. GRAY, Eileen A. HEBE

    2012-06-01

    Full Text Available Whereas a rich literature exists for estimating population genetic divergence, metrics of phenotypic trait divergence are lacking, particularly for comparing multiple traits among three or more populations. Here, we review and analyze via simulation Hedges’ g, a widely used parametric estimate of effect size. Our analyses indicate that g is sensitive to a combination of unequal trait variances and unequal sample sizes among populations and to changes in the scale of measurement. We then go on to derive and explain a new, non-parametric distance measure, “Δp”, which is calculated based upon a joint cumulative distribution function (CDF from all populations under study. More precisely, distances are measured in terms of the percentiles in this CDF at which each population’s median lies. Δp combines many desirable features of other distance metrics into a single metric; namely, compared to other metrics, p is relatively insensitive to unequal variances and sample sizes among the populations sampled. Furthermore, a key feature of Δp—and our main motivation for developing it—is that it easily accommodates simultaneous comparisons of any number of traits across any number of populations. To exemplify its utility, we employ Δp to address a question related to the role of sexual selection in speciation: are sexual signals more divergent than ecological traits in closely related taxa? Using traits of known function in closely related populations, we show that traits predictive of reproductive performance are, indeed, more divergent and more sexually dimorphic than traits related to ecological adaptation [Current Zoology 58 (3: 423-436, 2012].

  5. Quantum Algorithm for K-Nearest Neighbors Classification Based on the Metric of Hamming Distance

    Science.gov (United States)

    Ruan, Yue; Xue, Xiling; Liu, Heng; Tan, Jianing; Li, Xi

    2017-11-01

    K-nearest neighbors (KNN) algorithm is a common algorithm used for classification, and also a sub-routine in various complicated machine learning tasks. In this paper, we presented a quantum algorithm (QKNN) for implementing this algorithm based on the metric of Hamming distance. We put forward a quantum circuit for computing Hamming distance between testing sample and each feature vector in the training set. Taking advantage of this method, we realized a good analog for classical KNN algorithm by setting a distance threshold value t to select k - n e a r e s t neighbors. As a result, QKNN achieves O( n 3) performance which is only relevant to the dimension of feature vectors and high classification accuracy, outperforms Llyod's algorithm (Lloyd et al. 2013) and Wiebe's algorithm (Wiebe et al. 2014).

  6. Product Differentiation and Brand Competition in the Italian Breakfast Cereal Market: a Distance Metric Approach

    Directory of Open Access Journals (Sweden)

    Paolo Sckokai

    2013-03-01

    Full Text Available This article employs a nation-wide sample of supermarket scanner data to study product and brand competition in the Italian breakfast cereal market. A modified Almost Ideal Demand System (AIDS, that includes Distance Metrics (DMs as proposed by Pinkse, Slade and Brett (2002, is estimated to study demand responses, substitution patterns, own-price and cross-price elasticities. Estimation results provide evidence of some degree of brand loyalty, while consumers do not seem loyal to the product type. Elasticity estimates point out the presence of patterns of substitution within products sharing the same brand and similar nutritional characteristics.

  7. Drift correction for single-molecule imaging by molecular constraint field, a distance minimum metric

    International Nuclear Information System (INIS)

    Han, Renmin; Wang, Liansan; Xu, Fan; Zhang, Yongdeng; Zhang, Mingshu; Liu, Zhiyong; Ren, Fei; Zhang, Fa

    2015-01-01

    The recent developments of far-field optical microscopy (single molecule imaging techniques) have overcome the diffraction barrier of light and improve image resolution by a factor of ten compared with conventional light microscopy. These techniques utilize the stochastic switching of probe molecules to overcome the diffraction limit and determine the precise localizations of molecules, which often requires a long image acquisition time. However, long acquisition times increase the risk of sample drift. In the case of high resolution microscopy, sample drift would decrease the image resolution. In this paper, we propose a novel metric based on the distance between molecules to solve the drift correction. The proposed metric directly uses the position information of molecules to estimate the frame drift. We also designed an algorithm to implement the metric for the general application of drift correction. There are two advantages of our method: First, because our method does not require space binning of positions of molecules but directly operates on the positions, it is more natural for single molecule imaging techniques. Second, our method can estimate drift with a small number of positions in each temporal bin, which may extend its potential application. The effectiveness of our method has been demonstrated by both simulated data and experiments on single molecular images

  8. A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

    Science.gov (United States)

    Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

    2010-01-01

    Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming

  9. Improved nonlinear fault detection strategy based on the Hellinger distance metric: Plug flow reactor monitoring

    KAUST Repository

    Harrou, Fouzi

    2017-03-18

    Fault detection has a vital role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. This paper proposes an innovative multivariate fault detection method that can be used for monitoring nonlinear processes. The proposed method merges advantages of nonlinear projection to latent structures (NLPLS) modeling and those of Hellinger distance (HD) metric to identify abnormal changes in highly correlated multivariate data. Specifically, the HD is used to quantify the dissimilarity between current NLPLS-based residual and reference probability distributions obtained using fault-free data. Furthermore, to enhance further the robustness of these methods to measurement noise, and reduce the false alarms due to modeling errors, wavelet-based multiscale filtering of residuals is used before the application of the HD-based monitoring scheme. The performances of the developed NLPLS-HD fault detection technique is illustrated using simulated plug flow reactor data. The results show that the proposed method provides favorable performance for detection of faults compared to the conventional NLPLS method.

  10. WE-E-213CD-11: A New Automatically Generated Metric for Evaluating the Spatial Precision of Deformable Image Registrations: The Distance Discordance Metric.

    Science.gov (United States)

    Saleh, Z; Apte, A; Sharp, G; Deasy, J

    2012-06-01

    We propose a new metric called Distance Discordance (DD), which is defined as the distance between two anatomic points from two moving images, which are co-located on some reference image, when deformed onto another reference image. To demonstrate the concept of DD, we created a reference software phantom which contains two objects. The first object (1) consists of a hollow box with a fixed size core and variable wall thickness. The second object (2) consists of a solid box of fixed size and arbitrary location. 7 different variations of the fixed phantom were created. Each phantom was deformed onto every other phantom using two B-Spline DIR algorithms available in Elastix and Plastimatch. Voxels were sampled from the reference phantom [1], which were also deformed from moving phantoms [2…6], and we find the differences in their corresponding location on phantom [7]. Each voxel results in a distribution of DD values, which we call distance discordance histogram (DDH). We also demonstrate this concept in 8 Head & Neck patients. The two image registration algorithms produced two different DD results for the same phantom image set. The mean values of the DDH were slightly lower for Elastix (0-1.28 cm) as compared to the values produced by Plastimatch (0-1.43 cm). The combined DDH for the H&N patients followed a lognormal distribution with a mean of 0.45 cm and std. deviation of 0.42 cm. The proposed distance discordance (DD) metric is an easily interpretable, quantitative tool that can be used to evaluate the effect of inter-patient variability on the goodness of the registration in different parts of the patient anatomy. Therefore, it can be utilized to exclude certain images based on their DDH characteristics. In addition, this metric does not rely on 'ground truth' or the presence of contoured structures. Partially supported by NIH grant R01 CA85181. © 2012 American Association of Physicists in Medicine.

  11. Series distance – an intuitive metric to quantify hydrograph similarity in terms of occurrence, amplitude and timing of hydrological events

    Directory of Open Access Journals (Sweden)

    U. Ehret

    2011-03-01

    Full Text Available Applying metrics to quantify the similarity or dissimilarity of hydrographs is a central task in hydrological modelling, used both in model calibration and the evaluation of simulations or forecasts. Motivated by the shortcomings of standard objective metrics such as the Root Mean Square Error (RMSE or the Mean Absolute Peak Time Error (MAPTE and the advantages of visual inspection as a powerful tool for simultaneous, case-specific and multi-criteria (yet subjective evaluation, we propose a new objective metric termed Series Distance, which is in close accordance with visual evaluation. The Series Distance quantifies the similarity of two hydrographs neither in a time-aggregated nor in a point-by-point manner, but on the scale of hydrological events. It consists of three parts, namely a Threat Score which evaluates overall agreement of event occurrence, and the overall distance of matching observed and simulated events with respect to amplitude and timing. The novelty of the latter two is the way in which matching point pairs on the observed and simulated hydrographs are identified: not by equality in time (as is the case with the RMSE, but by the same relative position in matching segments (rise or recession of the event, indicating the same underlying hydrological process. Thus, amplitude and timing errors are calculated simultaneously but separately, from point pairs that also match visually, considering complete events rather than only individual points (as is the case with MAPTE. Relative weights can freely be assigned to each component of the Series Distance, which allows (subjective customization of the metric to various fields of application, but in a traceable way. Each of the three components of the Series Distance can be used in an aggregated or non-aggregated way, which makes the Series Distance a suitable tool for differentiated, process-based model diagnostics.

    After discussing the applicability of established time series

  12. Information-theoretic semi-supervised metric learning via entropy regularization.

    Science.gov (United States)

    Niu, Gang; Dai, Bo; Yamada, Makoto; Sugiyama, Masashi

    2014-08-01

    We propose a general information-theoretic approach to semi-supervised metric learning called SERAPH (SEmi-supervised metRic leArning Paradigm with Hypersparsity) that does not rely on the manifold assumption. Given the probability parameterized by a Mahalanobis distance, we maximize its entropy on labeled data and minimize its entropy on unlabeled data following entropy regularization. For metric learning, entropy regularization improves manifold regularization by considering the dissimilarity information of unlabeled data in the unsupervised part, and hence it allows the supervised and unsupervised parts to be integrated in a natural and meaningful way. Moreover, we regularize SERAPH by trace-norm regularization to encourage low-dimensional projections associated with the distance metric. The nonconvex optimization problem of SERAPH could be solved efficiently and stably by either a gradient projection algorithm or an EM-like iterative algorithm whose M-step is convex. Experiments demonstrate that SERAPH compares favorably with many well-known metric learning methods, and the learned Mahalanobis distance possesses high discriminability even under noisy environments.

  13. Measuring distance “as the horse runs”: Cross-scale comparison of terrain-based metrics

    Science.gov (United States)

    Buttenfield, Barbara P.; Ghandehari, M; Leyk, S; Stanislawski, Larry V.; Brantley, M E; Qiang, Yi

    2016-01-01

    Distance metrics play significant roles in spatial modeling tasks, such as flood inundation (Tucker and Hancock 2010), stream extraction (Stanislawski et al. 2015), power line routing (Kiessling et al. 2003) and analysis of surface pollutants such as nitrogen (Harms et al. 2009). Avalanche risk is based on slope, aspect, and curvature, all directly computed from distance metrics (Gutiérrez 2012). Distance metrics anchor variogram analysis, kernel estimation, and spatial interpolation (Cressie 1993). Several approaches are employed to measure distance. Planar metrics measure straight line distance between two points (“as the crow flies”) and are simple and intuitive, but suffer from uncertainties. Planar metrics assume that Digital Elevation Model (DEM) pixels are rigid and flat, as tiny facets of ceramic tile approximating a continuous terrain surface. In truth, terrain can bend, twist and undulate within each pixel.Work with Light Detection and Ranging (lidar) data or High Resolution Topography to achieve precise measurements present challenges, as filtering can eliminate or distort significant features (Passalacqua et al. 2015). The current availability of lidar data is far from comprehensive in developed nations, and non-existent in many rural and undeveloped regions. Notwithstanding computational advances, distance estimation on DEMs has never been systematically assessed, due to assumptions that improvements are so small that surface adjustment is unwarranted. For individual pixels inaccuracies may be small, but additive effects can propagate dramatically, especially in regional models (e.g., disaster evacuation) or global models (e.g., sea level rise) where pixels span dozens to hundreds of kilometers (Usery et al 2003). Such models are increasingly common, lending compelling reasons to understand shortcomings in the use of planar distance metrics. Researchers have studied curvature-based terrain modeling. Jenny et al. (2011) use curvature to generate

  14. Mahalanobis distance screening of Arabidopsis mutants with chlorophyll fluorescence

    Czech Academy of Sciences Publication Activity Database

    Codrea, C. C.; Hakala-Yatkin, M.; Karlund-Marttila, A.; Nedbal, Ladislav; Aittokallio, T.; Nevalainen, O. S.; Tyystjärvi, E.

    2010-01-01

    Roč. 105, č. 3 (2010), s. 273-283 ISSN 0166-8595 Institutional research plan: CEZ:AV0Z60870520 Keywords : arabidopsis thaliana * chlorophyll fluorescence * fluorescence imaging * mutant detection * outlier detection Subject RIV: EH - Ecology, Behaviour Impact factor: 2.410, year: 2010 http://www.springerlink.com/content/x3586512462pn006/

  15. Evaluating Outlier Identification Tests: Mahalanobis "D" Squared and Comrey "Dk."

    Science.gov (United States)

    Rasmussen, Jeffrey Lee

    1988-01-01

    A Monte Carlo simulation was used to compare the Mahalanobis "D" Squared and the Comrey "Dk" methods of detecting outliers in data sets. Under the conditions investigated, the "D" Squared technique was preferable as an outlier removal statistic. (SLD)

  16. Randomized Approaches for Nearest Neighbor Search in Metric Space When Computing the Pairwise Distance Is Extremely Expensive

    Science.gov (United States)

    Wang, Lusheng; Yang, Yong; Lin, Guohui

    Finding the closest object for a query in a database is a classical problem in computer science. For some modern biological applications, computing the similarity between two objects might be very time consuming. For example, it takes a long time to compute the edit distance between two whole chromosomes and the alignment cost of two 3D protein structures. In this paper, we study the nearest neighbor search problem in metric space, where the pair-wise distance between two objects in the database is known and we want to minimize the number of distances computed on-line between the query and objects in the database in order to find the closest object. We have designed two randomized approaches for indexing metric space databases, where objects are purely described by their distances with each other. Analysis and experiments show that our approaches only need to compute O(logn) objects in order to find the closest object, where n is the total number of objects in the database.

  17. Distance metric learning for complex networks: Towards size-independent comparison of network structures

    Science.gov (United States)

    Aliakbary, Sadegh; Motallebi, Sadegh; Rashidian, Sina; Habibi, Jafar; Movaghar, Ali

    2015-02-01

    Real networks show nontrivial topological properties such as community structure and long-tail degree distribution. Moreover, many network analysis applications are based on topological comparison of complex networks. Classification and clustering of networks, model selection, and anomaly detection are just some applications of network comparison. In these applications, an effective similarity metric is needed which, given two complex networks of possibly different sizes, evaluates the amount of similarity between the structural features of the two networks. Traditional graph comparison approaches, such as isomorphism-based methods, are not only too time consuming but also inappropriate to compare networks with different sizes. In this paper, we propose an intelligent method based on the genetic algorithms for integrating, selecting, and weighting the network features in order to develop an effective similarity measure for complex networks. The proposed similarity metric outperforms state of the art methods with respect to different evaluation criteria.

  18. Phylo_dCor: distance correlation as a novel metric for phylogenetic profiling.

    Science.gov (United States)

    Sferra, Gabriella; Fratini, Federica; Ponzi, Marta; Pizzi, Elisabetta

    2017-09-05

    Elaboration of powerful methods to predict functional and/or physical protein-protein interactions from genome sequence is one of the main tasks in the post-genomic era. Phylogenetic profiling allows the prediction of protein-protein interactions at a whole genome level in both Prokaryotes and Eukaryotes. For this reason it is considered one of the most promising methods. Here, we propose an improvement of phylogenetic profiling that enables handling of large genomic datasets and infer global protein-protein interactions. This method uses the distance correlation as a new measure of phylogenetic profile similarity. We constructed robust reference sets and developed Phylo-dCor, a parallelized version of the algorithm for calculating the distance correlation that makes it applicable to large genomic data. Using Saccharomyces cerevisiae and Escherichia coli genome datasets, we showed that Phylo-dCor outperforms phylogenetic profiling methods previously described based on the mutual information and Pearson's correlation as measures of profile similarity. In this work, we constructed and assessed robust reference sets and propose the distance correlation as a measure for comparing phylogenetic profiles. To make it applicable to large genomic data, we developed Phylo-dCor, a parallelized version of the algorithm for calculating the distance correlation. Two R scripts that can be run on a wide range of machines are available upon request.

  19. SU-E-J-159: Intra-Patient Deformable Image Registration Uncertainties Quantified Using the Distance Discordance Metric

    International Nuclear Information System (INIS)

    Saleh, Z; Thor, M; Apte, A; Deasy, J; Sharp, G; Muren, L

    2014-01-01

    Purpose: The quantitative evaluation of deformable image registration (DIR) is currently challenging due to lack of a ground truth. In this study we test a new method proposed for quantifying multiple-image based DIRrelated uncertainties, for DIR of pelvic images. Methods: 19 patients were analyzed, each with 6 CT scans, who previously had radiotherapy for prostate cancer. Manually delineated structures for rectum and bladder, which served as ground truth structures, were delineated on the planning CT and each subsequent scan. For each patient, voxel-by-voxel DIR-related uncertainties were evaluated, following B-spline based DIR, by applying a previously developed metric, the distance discordance metric (DDM; Saleh et al., PMB (2014) 59:733). The DDM map was superimposed on the first acquired CT scan and DDM statistics were assessed, also relative to two metrics estimating the agreement between the propagated and the manually delineated structures. Results: The highest DDM values which correspond to greatest spatial uncertainties were observed near the body surface and in the bowel due to the presence of gas. The mean rectal and bladder DDM values ranged from 1.1–11.1 mm and 1.5–12.7 mm, respectively. There was a strong correlation in the DDMs between the rectum and bladder (Pearson R = 0.68 for the max DDM). For both structures, DDM was correlated with the ratio between the DIR-propagated and manually delineated volumes (R = 0.74 for the max rectal DDM). The maximum rectal DDM was negatively correlated with the Dice Similarity Coefficient between the propagated and the manually delineated volumes (R= −0.52). Conclusion: The multipleimage based DDM map quantified considerable DIR variability across different structures and among patients. Besides using the DDM for quantifying DIR-related uncertainties it could potentially be used to adjust for uncertainties in DIR-based accumulated dose distributions

  20. Auto-associative Kernel Regression Model with Weighted Distance Metric for Instrument Drift Monitoring

    International Nuclear Information System (INIS)

    Shin, Ho Cheol; Park, Moon Ghu; You, Skin

    2006-01-01

    Recently, many on-line approaches to instrument channel surveillance (drift monitoring and fault detection) have been reported worldwide. On-line monitoring (OLM) method evaluates instrument channel performance by assessing its consistency with other plant indications through parametric or non-parametric models. The heart of an OLM system is the model giving an estimate of the true process parameter value against individual measurements. This model gives process parameter estimate calculated as a function of other plant measurements which can be used to identify small sensor drifts that would require the sensor to be manually calibrated or replaced. This paper describes an improvement of auto associative kernel regression (AAKR) by introducing a correlation coefficient weighting on kernel distances. The prediction performance of the developed method is compared with conventional auto-associative kernel regression

  1. Content-based retrieval of brain tumor in contrast-enhanced MRI images using tumor margin information and learned distance metric.

    Science.gov (United States)

    Yang, Wei; Feng, Qianjin; Yu, Mei; Lu, Zhentai; Gao, Yang; Xu, Yikai; Chen, Wufan

    2012-11-01

    A content-based image retrieval (CBIR) method for T1-weighted contrast-enhanced MRI (CE-MRI) images of brain tumors is presented for diagnosis aid. The method is thoroughly evaluated on a large image dataset. Using the tumor region as a query, the authors' CBIR system attempts to retrieve tumors of the same pathological category. Aside from commonly used features such as intensity, texture, and shape features, the authors use a margin information descriptor (MID), which is capable of describing the characteristics of tissue surrounding a tumor, for representing image contents. In addition, the authors designed a distance metric learning algorithm called Maximum mean average Precision Projection (MPP) to maximize the smooth approximated mean average precision (mAP) to optimize retrieval performance. The effectiveness of MID and MPP algorithms was evaluated using a brain CE-MRI dataset consisting of 3108 2D scans acquired from 235 patients with three categories of brain tumors (meningioma, glioma, and pituitary tumor). By combining MID and other features, the mAP of retrieval increased by more than 6% with the learned distance metrics. The distance metric learned by MPP significantly outperformed the other two existing distance metric learning methods in terms of mAP. The CBIR system using the proposed strategies achieved a mAP of 87.3% and a precision of 89.3% when top 10 images were returned by the system. Compared with scale-invariant feature transform, the MID, which uses the intensity profile as descriptor, achieves better retrieval performance. Incorporating tumor margin information represented by MID with the distance metric learned by the MPP algorithm can substantially improve the retrieval performance for brain tumors in CE-MRI.

  2. Semantic metrics

    OpenAIRE

    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...

  3. Multi-site Study of Diffusion Metric Variability: Characterizing the Effects of Site, Vendor, Field Strength, and Echo Time using the Histogram Distance

    Science.gov (United States)

    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

  4. Multi-site Study of Diffusion Metric Variability: Characterizing the Effects of Site, Vendor, Field Strength, and Echo Time using the Histogram Distance.

    Science.gov (United States)

    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.

  5. On using multiple routing metrics with destination sequenced distance vector protocol for MultiHop wireless ad hoc networks

    Science.gov (United States)

    Mehic, M.; Fazio, P.; Voznak, M.; Partila, P.; Komosny, D.; Tovarek, J.; Chmelikova, Z.

    2016-05-01

    A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator.

  6. Distance walked and run as improved metrics over time-based energy estimation in epidemiological studies and prevention; evidence from medication use.

    Directory of Open Access Journals (Sweden)

    Paul T Williams

    Full Text Available The guideline physical activity levels are prescribed in terms of time, frequency, and intensity (e.g., 30 minutes brisk walking, five days a week or its energy equivalence and assume that different activities may be combined to meet targeted goals (exchangeability premise. Habitual runners and walkers may quantify exercise in terms of distance (km/day, and for them, the relationship between activity dose and health benefits may be better assessed in terms of distance rather than time. Analyses were therefore performed to test: 1 whether time-based or distance-based estimates of energy expenditure provide the best metric for relating running and walking to hypertensive, high cholesterol, and diabetes medication use (conditions known to be diminished by exercise, and 2 the exchangeability premise.Logistic regression analyses of medication use (dependent variable vs. metabolic equivalent hours per day (METhr/d of running, walking and other exercise (independent variables using cross-sectional data from the National Runners' (17,201 male, 16,173 female and Walkers' Health Studies (3,434 male, 12,384 female.Estimated METhr/d of running and walking activity were 38% and 31% greater, respectively, when calculated from self-reported time than distance in men, and 43% and 37% greater in women, respectively. Percent reductions in the odds for hypertension and high cholesterol medication use per METhr/d run or per METhr/d walked were ≥ 2-fold greater when estimated from reported distance (km/wk than from time (hr/wk. The per METhr/d odds reduction was significantly greater for the distance- than the time-based estimate for hypertension (runners: P<10(-5 for males and P=0.003 for females; walkers: P=0.03 for males and P<10(-4 for females, high cholesterol medication use in runners (P<10(-4 for males and P=0.02 for females and male walkers (P=0.01 for males and P=0.08 for females and for diabetes medication use in male runners (P<10(-3.Although causality

  7. Development Planning & Policies under Mahalanobis Strategy: A Tale of India’s Dilemma

    Directory of Open Access Journals (Sweden)

    Dr. Asim K. Karmakar

    2013-07-01

    In the above backdrop the present paper gives a short review of Mahalanobis strategy of development planning in the context of the then India’s dilemma: dynamic industrialization and static agriculture.

  8. Analysis of Molecular Variance Inferred from Metric Distances among DNA Haplotypes: Application to Human Mitochondrial DNA Restriction Data

    OpenAIRE

    Excoffier, L.; Smouse, P. E.; Quattro, J. M.

    1992-01-01

    We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as φ-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivisi...

  9. Metric learning

    CERN Document Server

    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

  10. Using Generalized Entropies and OC-SVM with Mahalanobis Kernel for Detection and Classification of Anomalies in Network Traffic

    Directory of Open Access Journals (Sweden)

    Jayro Santiago-Paz

    2015-09-01

    Full Text Available Network anomaly detection and classification is an important open issue in network security. Several approaches and systems based on different mathematical tools have been studied and developed, among them, the Anomaly-Network Intrusion Detection System (A-NIDS, which monitors network traffic and compares it against an established baseline of a “normal” traffic profile. Then, it is necessary to characterize the “normal” Internet traffic. This paper presents an approach for anomaly detection and classification based on Shannon, Rényi and Tsallis entropies of selected features, and the construction of regions from entropy data employing the Mahalanobis distance (MD, and One Class Support Vector Machine (OC-SVM with different kernels (Radial Basis Function (RBF and Mahalanobis Kernel (MK for “normal” and abnormal traffic. Regular and non-regular regions built from “normal” traffic profiles allow anomaly detection, while the classification is performed under the assumption that regions corresponding to the attack classes have been previously characterized. Although this approach allows the use of as many features as required, only four well-known significant features were selected in our case. In order to evaluate our approach, two different data sets were used: one set of real traffic obtained from an Academic Local Area Network (LAN, and the other a subset of the 1998 MIT-DARPA set. For these data sets, a True positive rate up to 99.35%, a True negative rate up to 99.83% and a False negative rate at about 0.16% were yielded. Experimental results show that certain q-values of the generalized entropies and the use of OC-SVM with RBF kernel improve the detection rate in the detection stage, while the novel inclusion of MK kernel in OC-SVM and k-temporal nearest neighbors improve accuracy in classification. In addition, the results show that using the Box-Cox transformation, the Mahalanobis distance yielded high detection rates with

  11. Mahalanobis Distance-Based Classifiers are Able to Recognize EEG Patterns by Using Few EEG Electrodes

    Science.gov (United States)

    2001-10-25

    Mouriño 3 , Angela Cattini 4 , Serenella Salinari 4 , Maria Grazia Marciani 2,5 and Febo Cincotti 5 1 Dip. Fisiologia umana e Farmacologia...Performing Organization Name(s) and Address(es) Dip. Fisiologia umana e Farmacologia, Università "La Sapienza", Rome, ITALY Performing Organization

  12. Encyclopedia of distances

    CERN Document Server

    Deza, Michel Marie

    2016-01-01

    This 4th edition of the leading reference volume on distance metrics is characterized by updated and rewritten sections on some items suggested by experts and readers, as well a general streamlining of content and the addition of essential new topics. Though the structure remains unchanged, the new edition also explores recent advances in the use of distances and metrics for e.g. generalized distances, probability theory, graph theory, coding theory, data analysis. New topics in the purely mathematical sections include e.g. the Vitanyi multiset-metric, algebraic point-conic distance, triangular ratio metric, Rossi-Hamming metric, Taneja distance, spectral semimetric between graphs, channel metrization, and Maryland bridge distance. The multidisciplinary sections have also been supplemented with new topics, including: dynamic time wrapping distance, memory distance, allometry, atmospheric depth, elliptic orbit distance, VLBI distance measurements, the astronomical system of units, and walkability distance. Lea...

  13. Metric diffusion along foliations

    CERN Document Server

    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.

  14. Analysis of transitions at two-fold redundant sites in mammalian genomes. Transition redundant approach-to-equilibrium (TREx distance metrics

    Directory of Open Access Journals (Sweden)

    Liberles David A

    2006-03-01

    sites within two-fold redundant coding systems were examined in the mouse, rat, and human genomes. The key metric (f2, the fraction of those sites that holds the same nucleotide, was measured for putative ortholog pairs. A transition redundant exchange (TREx distance was calculated from f2 for these pairs. Pyrimidine-pyrimidine transitions at these sites occur approximately 14% faster than purine-purine transitions in various lineages. Transition rate constants were similar in different genes within the same lineages; within a set of orthologs, the f2 distribution is only modest overdispersed. No correlation between disparity and overdispersion is observed. In rodents, evidence was found for greater conservation of TREx sites in genes on the X chromosome, accounting for a small part of the overdispersion, however. Conclusion The TREx metric is useful to analyze the history of transition rate constants within these mammals over the past 100 million years. The TREx metric estimates the extent to which silent nucleotide substitutions accumulate in different genes, on different chromosomes, with different compositions, in different lineages, and at different times.

  15. Encyclopedia of distances

    CERN Document Server

    Deza, Michel Marie

    2014-01-01

    This updated and revised third edition of the leading reference volume on distance metrics includes new items from very active research areas in the use of distances and metrics such as geometry, graph theory, probability theory and analysis. Among the new topics included are, for example, polyhedral metric space, nearness matrix problems, distances between belief assignments, distance-related animal settings, diamond-cutting distances, natural units of length, Heidegger’s de-severance distance, and brain distances. The publication of this volume coincides with intensifying research efforts into metric spaces and especially distance design for applications. Accurate metrics have become a crucial goal in computational biology, image analysis, speech recognition and information retrieval. Leaving aside the practical questions that arise during the selection of a ‘good’ distance function, this work focuses on providing the research community with an invaluable comprehensive listing of the main available di...

  16. Novel Mahalanobis-based feature selection improves one-class classification of early hepatocellular carcinoma.

    Science.gov (United States)

    Thomaz, Ricardo de Lima; Carneiro, Pedro Cunha; Bonin, João Eliton; Macedo, Túlio Augusto Alves; Patrocinio, Ana Claudia; Soares, Alcimar Barbosa

    2018-05-01

    Detection of early hepatocellular carcinoma (HCC) is responsible for increasing survival rates in up to 40%. One-class classifiers can be used for modeling early HCC in multidetector computed tomography (MDCT), but demand the specific knowledge pertaining to the set of features that best describes the target class. Although the literature outlines several features for characterizing liver lesions, it is unclear which is most relevant for describing early HCC. In this paper, we introduce an unconstrained GA feature selection algorithm based on a multi-objective Mahalanobis fitness function to improve the classification performance for early HCC. We compared our approach to a constrained Mahalanobis function and two other unconstrained functions using Welch's t-test and Gaussian Data Descriptors. The performance of each fitness function was evaluated by cross-validating a one-class SVM. The results show that the proposed multi-objective Mahalanobis fitness function is capable of significantly reducing data dimensionality (96.4%) and improving one-class classification of early HCC (0.84 AUC). Furthermore, the results provide strong evidence that intensity features extracted at the arterial to portal and arterial to equilibrium phases are important for classifying early HCC.

  17. 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...

  18. 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.

  19. A methodology for quantitatively managing the bug fixing process using Mahalanobis Taguchi system

    Directory of Open Access Journals (Sweden)

    Boby John

    2015-12-01

    Full Text Available The controlling of bug fixing process during the system testing phase of software development life cycle is very important for fixing all the detected bugs within the scheduled time. The presence of open bugs often delays the release of the software or result in releasing the software with compromised functionalities. These can lead to customer dissatisfaction, cost overrun and eventually the loss of market share. In this paper, the authors propose a methodology to quantitatively manage the bug fixing process during system testing. The proposed methodology identifies the critical milestones in the system testing phase which differentiates the successful projects from the unsuccessful ones using Mahalanobis Taguchi system. Then a model is developed to predict whether a project is successful or not with the bug fix progress at critical milestones as control factors. Finally the model is used to control the bug fixing process. It is found that the performance of the proposed methodology using Mahalanobis Taguchi system is superior to the models developed using other multi-dimensional pattern recognition techniques. The proposed methodology also reduces the number of control points providing the managers with more options and flexibility to utilize the bug fixing resources across system testing phase. Moreover the methodology allows the mangers to carry out mid- course corrections to bring the bug fixing process back on track so that all the detected bugs can be fixed on time. The methodology is validated with eight new projects and the results are very encouraging.

  20. Unsupervised versus Supervised Identification of Prognostic Factors in Patients with Localized Retroperitoneal Sarcoma: A Data Clustering and Mahalanobis Distance Approach

    Directory of Open Access Journals (Sweden)

    Rita De Sanctis

    2018-01-01

    Full Text Available The aim of this report is to unveil specific prognostic factors for retroperitoneal sarcoma (RPS patients by univariate and multivariate statistical techniques. A phase I-II study on localized RPS treated with high-dose ifosfamide and radiotherapy followed by surgery (ISG-STS 0303 protocol demonstrated that chemo/radiotherapy was safe and increased the 3-year relapse-free survival (RFS with respect to historical controls. Of 70 patients, twenty-six developed local, 10 distant, and 5 combined relapse. Median disease-free interval (DFI was 29.47 months. According to a discriminant function analysis, DFI, histology, relapse pattern, and the first treatment approach at relapse had a statistically significant prognostic impact. Based on scientific literature and clinical expertise, clinicopathological data were analyzed using both a supervised and an unsupervised classification method to predict the prognosis, with similar sample sizes (66 and 65, resp., in casewise approach and 70 in mean-substitution one. This is the first attempt to predict patients’ prognosis by means of multivariate statistics, and in this light, it looks noticable that (i some clinical data have a well-defined prognostic value, (ii the unsupervised model produced comparable results with respect to the supervised one, and (iii the appropriate combination of both models appears fruitful and easily extensible to different clinical contexts.

  1. Costing improvement of remanufacturing crankshaft by integrating Mahalanobis-Taguchi System and Activity based Costing

    Science.gov (United States)

    Abu, M. Y.; Nor, E. E. Mohd; Rahman, M. S. Abd

    2018-04-01

    Integration between quality and costing system is very crucial in order to achieve an accurate product cost and profit. Current practice by most of remanufacturers, there are still lacking on optimization during the remanufacturing process which contributed to incorrect variables consideration to the costing system. Meanwhile, traditional costing accounting being practice has distortion in the cost unit which lead to inaccurate cost of product. The aim of this work is to identify the critical and non-critical variables during remanufacturing process using Mahalanobis-Taguchi System and simultaneously estimate the cost using Activity Based Costing method. The orthogonal array was applied to indicate the contribution of variables in the factorial effect graph and the critical variables were considered with overhead costs that are actually demanding the activities. This work improved the quality inspection together with costing system to produce an accurate profitability information. As a result, the cost per unit of remanufactured crankshaft of MAN engine model with 5 critical crankpins is MYR609.50 while Detroit engine model with 4 critical crankpins is MYR1254.80. The significant of output demonstrated through promoting green by reducing re-melting process of damaged parts to ensure consistent benefit of return cores.

  2. Integration of Mahalanobis-Taguchi system and traditional cost accounting for remanufacturing crankshaft

    Science.gov (United States)

    Abu, M. Y.; Norizan, N. S.; Rahman, M. S. Abd

    2018-04-01

    Remanufacturing is a sustainability strategic planning which transforming the end of life product to as new performance with their warranty is same or better than the original product. In order to quantify the advantages of this strategy, all the processes must implement the optimization to reach the ultimate goal and reduce the waste generated. The aim of this work is to evaluate the criticality of parameters on the end of life crankshaft based on Taguchi’s orthogonal array. Then, estimate the cost using traditional cost accounting by considering the critical parameters. By implementing the optimization, the remanufacturer obviously produced lower cost and waste during production with higher potential to gain the profit. Mahalanobis-Taguchi System was proven as a powerful method of optimization that revealed the criticality of parameters. When subjected the method to the MAN engine model, there was 5 out of 6 crankpins were critical which need for grinding process while no changes happened to the Caterpillar engine model. Meanwhile, the cost per unit for MAN engine model was changed from MYR1401.29 to RM1251.29 while for Caterpillar engine model have no changes due to the no changes on criticality of parameters consideration. Therefore, by integrating the optimization and costing through remanufacturing process, a better decision can be achieved after observing the potential profit will be gained. The significant of output demonstrated through promoting sustainability by reducing re-melting process of damaged parts to ensure consistent benefit of return cores.

  3. Encyclopedia of distances

    CERN Document Server

    Deza, Michel Marie

    2009-01-01

    Distance metrics and distances have become an essential tool in many areas of pure and applied Mathematics. This title offers both independent introductions and definitions, while at the same time making cross-referencing easy through hyperlink-like boldfaced references to original definitions.

  4. Metrication manual

    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

  5. Representing distance, consuming distance

    DEFF Research Database (Denmark)

    Larsen, Gunvor Riber

    Title: Representing Distance, Consuming Distance Abstract: Distance is a condition for corporeal and virtual mobilities, for desired and actual travel, but yet it has received relatively little attention as a theoretical entity in its own right. Understandings of and assumptions about distance...... are being consumed in the contemporary society, in the same way as places, media, cultures and status are being consumed (Urry 1995, Featherstone 2007). An exploration of distance and its representations through contemporary consumption theory could expose what role distance plays in forming...

  6. Networks and centroid metrics for understanding football

    African Journals Online (AJOL)

    Gonçalo Dias

    games. However, it seems that the centroid metric, supported only by the position of players in the field ...... the strategy adopted by the coach (Gama et al., 2014). ... centroid distance as measures of team's tactical performance in youth football.

  7. Finite Metric Spaces of Strictly negative Type

    DEFF Research Database (Denmark)

    Hjorth, Poul G.

    If a finite metric space is of strictly negative type then its transfinite diameter is uniquely realized by an infinite extent (“load vector''). Finite metric spaces that have this property include all trees, and all finite subspaces of Euclidean and Hyperbolic spaces. We prove that if the distance...

  8. Characterizing the round sphere by mean distance

    DEFF Research Database (Denmark)

    Kokkendorff, Simon Lyngby

    2008-01-01

    We discuss the measure theoretic metric invariants extent, rendezvous number and mean distance of a general compact metric space X and relate these to classical metric invariants such as diameter and radius. In the final section we focus attention to the category of Riemannian manifolds. The main...

  9. A Kerr-NUT metric

    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)

  10. The Metric of Colour Space

    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...

  11. On the Metric-Based Approximate Minimization of Markov Chains

    DEFF Research Database (Denmark)

    Bacci, Giovanni; Bacci, Giorgio; Larsen, Kim Guldstrand

    2017-01-01

    We address the behavioral metric-based approximate minimization problem of Markov Chains (MCs), i.e., given a finite MC and a positive integer k, we are interested in finding a k-state MC of minimal distance to the original. By considering as metric the bisimilarity distance of Desharnais at al...

  12. Metrics of quantum states

    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.

  13. $\\eta$-metric structures

    OpenAIRE

    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.

  14. Supplier selection using different metric functions

    Directory of Open Access Journals (Sweden)

    Omosigho S.E.

    2015-01-01

    Full Text Available Supplier selection is an important component of supply chain management in today’s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution. Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

  15. Distance Learning

    National Research Council Canada - National Science Library

    Braddock, Joseph

    1997-01-01

    A study reviewing the existing Army Distance Learning Plan (ADLP) and current Distance Learning practices, with a focus on the Army's training and educational challenges and the benefits of applying Distance Learning techniques...

  16. Heterosis and genetic distance in rapeseed (Brasica napus L.). Use of different indicators of genetic divergence in 7x7 diallel

    OpenAIRE

    Lefort-Buson, Marianne; Guillot-Lemoine, Brigitte; Dattée, Yvette

    1986-01-01

    The paper deals with a comparison of different indicators of genetic divergence between rapeseed parental lines : the relationship coefficient defined by MALÈCOT the generalized distance D2 of Mahalanobis, and a new G2 parameter close to HANSON & CASAS' R2. The purpose of the authors is to discuss the advantages of their simultaneous use in the prediction of both heterosis values and F1 performances of hybrids from parental lines. Relationships between heterosis values and genetic distanc...

  17. Active Metric Learning from Relative Comparisons

    OpenAIRE

    Xiong, Sicheng; Rosales, Rómer; Pei, Yuanli; Fern, Xiaoli Z.

    2014-01-01

    This work focuses on active learning of distance metrics from relative comparison information. A relative comparison specifies, for a data point triplet $(x_i,x_j,x_k)$, that instance $x_i$ is more similar to $x_j$ than to $x_k$. Such constraints, when available, have been shown to be useful toward defining appropriate distance metrics. In real-world applications, acquiring constraints often require considerable human effort. This motivates us to study how to select and query the most useful ...

  18. Continuity Properties of Distances for Markov Processes

    DEFF Research Database (Denmark)

    Jaeger, Manfred; Mao, Hua; Larsen, Kim Guldstrand

    2014-01-01

    In this paper we investigate distance functions on finite state Markov processes that measure the behavioural similarity of non-bisimilar processes. We consider both probabilistic bisimilarity metrics, and trace-based distances derived from standard Lp and Kullback-Leibler distances. Two desirable...

  19. 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.

  20. Classification in medical images using adaptive metric k-NN

    Science.gov (United States)

    Chen, C.; Chernoff, K.; Karemore, G.; Lo, P.; Nielsen, M.; Lauze, F.

    2010-03-01

    The performance of the k-nearest neighborhoods (k-NN) classifier is highly dependent on the distance metric used to identify the k nearest neighbors of the query points. The standard Euclidean distance is commonly used in practice. This paper investigates the performance of k-NN classifier with respect to different adaptive metrics in the context of medical imaging. We propose using adaptive metrics such that the structure of the data is better described, introducing some unsupervised learning knowledge in k-NN. We investigated four different metrics are estimated: a theoretical metric based on the assumption that images are drawn from Brownian Image Model (BIM), the normalized metric based on variance of the data, the empirical metric is based on the empirical covariance matrix of the unlabeled data, and an optimized metric obtained by minimizing the classification error. The spectral structure of the empirical covariance also leads to Principal Component Analysis (PCA) performed on it which results the subspace metrics. The metrics are evaluated on two data sets: lateral X-rays of the lumbar aortic/spine region, where we use k-NN for performing abdominal aorta calcification detection; and mammograms, where we use k-NN for breast cancer risk assessment. The results show that appropriate choice of metric can improve classification.

  1. Inferring feature relevances from metric learning

    DEFF Research Database (Denmark)

    Schulz, Alexander; Mokbel, Bassam; Biehl, Michael

    2015-01-01

    Powerful metric learning algorithms have been proposed in the last years which do not only greatly enhance the accuracy of distance-based classifiers and nearest neighbor database retrieval, but which also enable the interpretability of these operations by assigning explicit relevance weights...

  2. Metric modular spaces

    CERN Document Server

    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...

  3. Prognostic Performance Metrics

    Data.gov (United States)

    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...

  4. Overview of journal metrics

    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.

  5. Normalized compression distance of multisets with applications

    NARCIS (Netherlands)

    Cohen, A.R.; Vitányi, P.M.B.

    Pairwise normalized compression distance (NCD) is a parameter-free, feature-free, alignment-free, similarity metric based on compression. We propose an NCD of multisets that is also metric. Previously, attempts to obtain such an NCD failed. For classification purposes it is superior to the pairwise

  6. Distance between Behaviors and Rational Representations

    NARCIS (Netherlands)

    Trentelman, H.L.; Gottimukkala, S.V.

    2013-01-01

    In this paper we study notions of distance between behaviors of linear differential systems. We introduce four metrics on the space of all controllable behaviors which generalize existing metrics on the space of input-output systems represented by transfer matrices. Three of these are defined in

  7. Converging from Branching to Linear Metrics on Markov Chains

    DEFF Research Database (Denmark)

    Bacci, Giorgio; Bacci, Giovanni; Larsen, Kim Guldstrand

    2015-01-01

    time in the size of the MC. The upper-approximants are Kantorovich-like pseudometrics, i.e. branching-time distances, that converge point-wise to the linear-time metrics. This convergence is interesting in itself, since it reveals a nontrivial relation between branching and linear-time metric...

  8. On the Metric-based Approximate Minimization of Markov Chains

    DEFF Research Database (Denmark)

    Bacci, Giovanni; Bacci, Giorgio; Larsen, Kim Guldstrand

    2018-01-01

    In this paper we address the approximate minimization problem of Markov Chains (MCs) from a behavioral metric-based perspective. Specifically, given a finite MC and a positive integer k, we are looking for an MC with at most k states having minimal distance to the original. The metric considered...

  9. Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics

    NARCIS (Netherlands)

    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

  10. Brand metrics that matter

    NARCIS (Netherlands)

    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

  11. Privacy Metrics and Boundaries

    NARCIS (Netherlands)

    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

  12. Are contemporary tourists consuming distance?

    DEFF Research Database (Denmark)

    Larsen, Gunvor Riber

    2012. Background The background for this research, which explores how tourists represent distance and whether or not distance can be said to be consumed by contemporary tourists, is the increasing leisure mobility of people. Travelling for the purpose of visiting friends and relatives is increasing...... of understanding mobility at a conceptual level, and distance matters to people's manifest mobility: how they travel and how far they travel are central elements of their movements. Therefore leisure mobility (indeed all mobility) is the activity of relating across distance, either through actual corporeal...... metric representation. These representations are the focus for this research. Research Aim and Questions The aim of this research is thus to explore how distance is being represented within the context of leisure mobility. Further the aim is to explore how or whether distance is being consumed...

  13. Holographic Spherically Symmetric Metrics

    Science.gov (United States)

    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.

  14. Metric space construction for the boundary of space-time

    International Nuclear Information System (INIS)

    Meyer, D.A.

    1986-01-01

    A distance function between points in space-time is defined and used to consider the manifold as a topological metric space. The properties of the distance function are investigated: conditions under which the metric and manifold topologies agree, the relationship with the causal structure of the space-time and with the maximum lifetime function of Wald and Yip, and in terms of the space of causal curves. The space-time is then completed as a topological metric space; the resultant boundary is compared with the causal boundary and is also calculated for some pertinent examples

  15. modelling distances

    Directory of Open Access Journals (Sweden)

    Robert F. Love

    2001-01-01

    Full Text Available Distance predicting functions may be used in a variety of applications for estimating travel distances between points. To evaluate the accuracy of a distance predicting function and to determine its parameters, a goodness-of-fit criteria is employed. AD (Absolute Deviations, SD (Squared Deviations and NAD (Normalized Absolute Deviations are the three criteria that are mostly employed in practice. In the literature some assumptions have been made about the properties of each criterion. In this paper, we present statistical analyses performed to compare the three criteria from different perspectives. For this purpose, we employ the ℓkpθ-norm as the distance predicting function, and statistically compare the three criteria by using normalized absolute prediction error distributions in seventeen geographical regions. We find that there exist no significant differences between the criteria. However, since the criterion SD has desirable properties in terms of distance modelling procedures, we suggest its use in practice.

  16. Probabilistic metric spaces

    CERN Document Server

    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.

  17. Tracker Performance Metric

    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...

  18. IT Project Management Metrics

    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.

  19. 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....

  20. Metric Learning for Hyperspectral Image Segmentation

    Science.gov (United States)

    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.

  1. A metric for the Radial Basis Function Network - Application on Real Radar Data

    NARCIS (Netherlands)

    Heiden, R. van der; Groen, F.C.A.

    1996-01-01

    A Radial Basis Functions (RBF) network for pattern recognition is considered. Classification with such a network is based on distances between patterns, so a metric is always present. Using real radar data, the Euclidean metric is shown to perform poorly - a metric based on the so called Box-Cox

  2. Computing Best and Worst Shortcuts of Graphs Embedded in Metric Spaces

    DEFF Research Database (Denmark)

    Wulff-Nilsen, Christian; Luo, Jun

    2008-01-01

    Given a graph embedded in a metric space, its dilation is the maximum over all distinct pairs of vertices of the ratio between their distance in the graph and the metric distance between them. Given such a graph G with n vertices and m edges and consisting of at most two connected components, we ...

  3. Fault Management Metrics

    Science.gov (United States)

    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.

  4. Deep Transfer Metric Learning.

    Science.gov (United States)

    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.

  5. A Metric on Phylogenetic Tree Shapes.

    Science.gov (United States)

    Colijn, C; Plazzotta, G

    2018-01-01

    The shapes of evolutionary trees are influenced by the nature of the evolutionary process but comparisons of trees from different processes are hindered by the challenge of completely describing tree shape. We present a full characterization of the shapes of rooted branching trees in a form that lends itself to natural tree comparisons. We use this characterization to define a metric, in the sense of a true distance function, on tree shapes. The metric distinguishes trees from random models known to produce different tree shapes. It separates trees derived from tropical versus USA influenza A sequences, which reflect the differing epidemiology of tropical and seasonal flu. We describe several metrics based on the same core characterization, and illustrate how to extend the metric to incorporate trees' branch lengths or other features such as overall imbalance. Our approach allows us to construct addition and multiplication on trees, and to create a convex metric on tree shapes which formally allows computation of average tree shapes. © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

  6. Cyber threat metrics.

    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.

  7. 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.

  8. 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...

  9. 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...

  10. Metrical Phonology and SLA.

    Science.gov (United States)

    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…

  11. Engineering performance metrics

    Science.gov (United States)

    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.

  12. Metrics for energy resilience

    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

  13. Software Quality Assurance Metrics

    Science.gov (United States)

    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.

  14. Metrics in Keplerian orbits quotient spaces

    Science.gov (United States)

    Milanov, Danila V.

    2018-03-01

    Quotient spaces of Keplerian orbits are important instruments for the modelling of orbit samples of celestial bodies on a large time span. We suppose that variations of the orbital eccentricities, inclinations and semi-major axes remain sufficiently small, while arbitrary perturbations are allowed for the arguments of pericentres or longitudes of the nodes, or both. The distance between orbits or their images in quotient spaces serves as a numerical criterion for such problems of Celestial Mechanics as search for common origin of meteoroid streams, comets, and asteroids, asteroid families identification, and others. In this paper, we consider quotient sets of the non-rectilinear Keplerian orbits space H. Their elements are identified irrespective of the values of pericentre arguments or node longitudes. We prove that distance functions on the quotient sets, introduced in Kholshevnikov et al. (Mon Not R Astron Soc 462:2275-2283, 2016), satisfy metric space axioms and discuss theoretical and practical importance of this result. Isometric embeddings of the quotient spaces into R^n, and a space of compact subsets of H with Hausdorff metric are constructed. The Euclidean representations of the orbits spaces find its applications in a problem of orbit averaging and computational algorithms specific to Euclidean space. We also explore completions of H and its quotient spaces with respect to corresponding metrics and establish a relation between elements of the extended spaces and rectilinear trajectories. Distance between an orbit and subsets of elliptic and hyperbolic orbits is calculated. This quantity provides an upper bound for the metric value in a problem of close orbits identification. Finally the invariance of the equivalence relations in H under coordinates change is discussed.

  15. Video Analytics Evaluation: Survey of Datasets, Performance Metrics and Approaches

    Science.gov (United States)

    2014-09-01

    people with different ethnicity and gender . Cur- rently we have four subjects, but more can be added in the future. • Lighting Variations. We consider...is however not a proper distance as the triangular inequality condition is not met. For this reason, the next metric should be preferred. • the...and Alan F. Smeaton and Georges Quenot, An Overview of the Goals, Tasks, Data, Evaluation Mechanisms and Metrics, Proceedings of TRECVID 2011, NIST, USA

  16. Distance learning

    Directory of Open Access Journals (Sweden)

    Katarina Pucelj

    2006-12-01

    Full Text Available I would like to underline the role and importance of knowledge, which is acquired by individuals as a result of a learning process and experience. I have established that a form of learning, such as distance learning definitely contributes to a higher learning quality and leads to innovative, dynamic and knowledgebased society. Knowledge and skills enable individuals to cope with and manage changes, solve problems and also create new knowledge. Traditional learning practices face new circumstances, new and modern technologies appear, which enable quick and quality-oriented knowledge implementation. The centre of learning process at distance learning is to increase the quality of life of citizens, their competitiveness on the workforce market and ensure higher economic growth. Intellectual capital is the one, which represents the biggest capital of each society and knowledge is the key factor for succes of everybody, who are fully aware of this. Flexibility, openness and willingness of people to follow new IT solutions form suitable environment for developing and deciding to take up distance learning.

  17. Algorithms for Planar Graphs and Graphs in Metric Spaces

    DEFF Research Database (Denmark)

    Wulff-Nilsen, Christian

    structural properties that can be exploited. For instance, a road network or a wire layout on a microchip is typically (near-)planar and distances in the network are often defined w.r.t. the Euclidean or the rectilinear metric. Specialized algorithms that take advantage of such properties are often orders...... of magnitude faster than the corresponding algorithms for general graphs. The first and main part of this thesis focuses on the development of efficient planar graph algorithms. The most important contributions include a faster single-source shortest path algorithm, a distance oracle with subquadratic...... for geometric graphs and graphs embedded in metric spaces. Roughly speaking, the stretch factor is a real value expressing how well a (geo-)metric graph approximates the underlying complete graph w.r.t. distances. We give improved algorithms for computing the stretch factor of a given graph and for augmenting...

  18. Enterprise Sustainment Metrics

    Science.gov (United States)

    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

  19. Contextual Distance Refining for Image Retrieval

    KAUST Repository

    Islam, Almasri

    2014-01-01

    Recently, a number of methods have been proposed to improve image retrieval accuracy by capturing context information. These methods try to compensate for the fact that a visually less similar image might be more relevant because it depicts the same object. We propose a new quick method for refining any pairwise distance metric, it works by iteratively discovering the object in the image from the most similar images, and then refine the distance metric accordingly. Test show that our technique improves over the state of art in terms of accuracy over the MPEG7 dataset.

  20. Contextual Distance Refining for Image Retrieval

    KAUST Repository

    Islam, Almasri

    2014-09-16

    Recently, a number of methods have been proposed to improve image retrieval accuracy by capturing context information. These methods try to compensate for the fact that a visually less similar image might be more relevant because it depicts the same object. We propose a new quick method for refining any pairwise distance metric, it works by iteratively discovering the object in the image from the most similar images, and then refine the distance metric accordingly. Test show that our technique improves over the state of art in terms of accuracy over the MPEG7 dataset.

  1. 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

  2. Learning Low-Dimensional Metrics

    OpenAIRE

    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 ...

  3. Clustering by Partitioning around Medoids using Distance-Based ...

    African Journals Online (AJOL)

    OLUWASOGO

    outperforms both the Euclidean and Manhattan distance metrics in certain situations. KEYWORDS: PAM ... version of a dataset, compare the quality of clusters obtained from the Euclidean .... B. Theoretical Framework and Methodology.

  4. The transposition distance for phylogenetic trees

    OpenAIRE

    Rossello, Francesc; Valiente, Gabriel

    2006-01-01

    The search for similarity and dissimilarity measures on phylogenetic trees has been motivated by the computation of consensus trees, the search by similarity in phylogenetic databases, and the assessment of clustering results in bioinformatics. The transposition distance for fully resolved phylogenetic trees is a recent addition to the extensive collection of available metrics for comparing phylogenetic trees. In this paper, we generalize the transposition distance from fully resolved to arbi...

  5. Comparison of efficiency of distance measurement methodologies in mango (Mangifera indica) progenies based on physicochemical descriptors.

    Science.gov (United States)

    Alves, E O S; Cerqueira-Silva, C B M; Souza, A M; Santos, C A F; Lima Neto, F P; Corrêa, R X

    2012-03-14

    We investigated seven distance measures in a set of observations of physicochemical variables of mango (Mangifera indica) submitted to multivariate analyses (distance, projection and grouping). To estimate the distance measurements, five mango progeny (total of 25 genotypes) were analyzed, using six fruit physicochemical descriptors (fruit weight, equatorial diameter, longitudinal diameter, total soluble solids in °Brix, total titratable acidity, and pH). The distance measurements were compared by the Spearman correlation test, projection in two-dimensional space and grouping efficiency. The Spearman correlation coefficients between the seven distance measurements were, except for the Mahalanobis' generalized distance (0.41 ≤ rs ≤ 0.63), high and significant (rs ≥ 0.91; P < 0.001). Regardless of the origin of the distance matrix, the unweighted pair group method with arithmetic mean grouping method proved to be the most adequate. The various distance measurements and grouping methods gave different values for distortion (-116.5 ≤ D ≤ 74.5), cophenetic correlation (0.26 ≤ rc ≤ 0.76) and stress (-1.9 ≤ S ≤ 58.9). Choice of distance measurement and analysis methods influence the.

  6. 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

  7. Sharp metric obstructions for quasi-Einstein metrics

    Science.gov (United States)

    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.

  8. 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.

  9. Metric interpretation of gauge fields in noncommutative geometry

    International Nuclear Information System (INIS)

    Martinetti, P.

    2007-01-01

    We shall give an overview of the metric interpretation of gauge fields in noncommutative geometry, via Connes distance formula. Especially we shall focus on the Higgs fields in the standard model, and gauge fields in various models of fiber bundle. (author)

  10. Converging from branching to linear metrics on Markov chains

    DEFF Research Database (Denmark)

    Bacci, Giorgio; Bacci, Giovanni; Larsen, Kim G.

    2017-01-01

    -approximant is computable in polynomial time in the size of the MC. The upper-approximants are bisimilarity-like pseudometrics (hence, branching-time distances) that converge point-wise to the linear-time metrics. This convergence is interesting in itself, because it reveals a nontrivial relation between branching...

  11. Natural metrics and least-committed priors for articulated tracking

    DEFF Research Database (Denmark)

    Hauberg, Søren; Sommer, Stefan Horst; Pedersen, Kim Steenstrup

    2012-01-01

    of joint positions, which is embedded in a high dimensional Euclidean space. This Riemannian manifold inherits the metric from the embedding space, such that distances are measured as the combined physical length that joints travel during movements. We then develop a least-committed Brownian motion model...

  12. Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

    Science.gov (United States)

    Li, Xin; Bai, Yanqin; Peng, Yaxin; Du, Shaoyi; Ying, Shihui

    2018-03-01

    Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best nonlinear metric for the data. First, we describe the nonlinear metric by the multiple kernel representation. By this approach, we project the data into a high dimensional space, where the data can be well represented by linear ML. Then, we reformulate the linear ML by a minimization problem on the positive definite matrix group. Finally, we develop a two-step algorithm for solving this model and design an intrinsic steepest descent algorithm to learn the positive definite metric matrix. Experimental results validate that our proposed method is effective and outperforms several state-of-the-art ML methods.

  13. 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...

  14. Metrics for Performance Evaluation of Patient Exercises during Physical Therapy.

    Science.gov (United States)

    Vakanski, Aleksandar; Ferguson, Jake M; Lee, Stephen

    2017-06-01

    The article proposes a set of metrics for evaluation of patient performance in physical therapy exercises. Taxonomy is employed that classifies the metrics into quantitative and qualitative categories, based on the level of abstraction of the captured motion sequences. Further, the quantitative metrics are classified into model-less and model-based metrics, in reference to whether the evaluation employs the raw measurements of patient performed motions, or whether the evaluation is based on a mathematical model of the motions. The reviewed metrics include root-mean square distance, Kullback Leibler divergence, log-likelihood, heuristic consistency, Fugl-Meyer Assessment, and similar. The metrics are evaluated for a set of five human motions captured with a Kinect sensor. The metrics can potentially be integrated into a system that employs machine learning for modelling and assessment of the consistency of patient performance in home-based therapy setting. Automated performance evaluation can overcome the inherent subjectivity in human performed therapy assessment, and it can increase the adherence to prescribed therapy plans, and reduce healthcare costs.

  15. 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.

  16. Attack-Resistant Trust Metrics

    Science.gov (United States)

    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.

  17. The metric system: An introduction

    Science.gov (United States)

    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.

  18. 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....

  19. Two classes of metric spaces

    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.

  20. Software metrics: Software quality metrics for distributed systems. [reliability engineering

    Science.gov (United States)

    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.

  1. Multimetric indices: How many metrics?

    Science.gov (United States)

    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...

  2. Metrical Phonology: German Sound System.

    Science.gov (United States)

    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…

  3. Extending cosmology: the metric approach

    OpenAIRE

    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

  4. Numerical Calabi-Yau metrics

    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

  5. High resolution metric imaging payload

    Science.gov (United States)

    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.

  6. Weyl metrics and wormholes

    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.

  7. Metrics for image segmentation

    Science.gov (United States)

    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.

  8. 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

  9. Metric inequalities for polygons

    Directory of Open Access Journals (Sweden)

    Adrian Dumitrescu

    2013-07-01

    Full Text Available Let A1,A2,…,An be the vertices of a polygon with unit perimeter, that is Σi |Ai Ai+1|=1. We derive various tight estimates on the minimum and maximum values of the sum of pairwise distances, and respectively sum of pairwise squared distances among its vertices. In most cases such estimates on these sums in the literature were known only for convex polygons.In the second part, we turn to a problem of Braß  regarding the maximum perimeter of a simplen-gon (n odd contained in a disk of unit radius. The problem was recently solved by Audet et al. 2009, who gave an exact formula. Here we present an alternative simpler proof of this formula. We then examine what happens if the simplicity condition is dropped, and obtain an exact formula for the maximum perimeter in this case as well.

  10. Generalized Distance Transforms and Skeletons in Graphics Hardware

    NARCIS (Netherlands)

    Strzodka, R.; Telea, A.

    2004-01-01

    We present a framework for computing generalized distance transforms and skeletons of two-dimensional objects using graphics hardware. Our method is based on the concept of footprint splatting. Combining different splats produces weighted distance transforms for different metrics, as well as the

  11. Quasi-metrics, midpoints and applications

    Energy Technology Data Exchange (ETDEWEB)

    Valero, O.

    2017-07-01

    In applied sciences, the scientific community uses simultaneously different kinds of information coming from several sources in order to infer a conclusion or working decision. In the literature there are many techniques for merging the information and providing, hence, a meaningful fused data. In mostpractical cases such fusion methods are based on aggregation operators on somenumerical values, i.e. the aim of the fusion process is to obtain arepresentative number from a finite sequence of numerical data. In the aforementioned cases, the input data presents some kind of imprecision and for thisreason it is represented as fuzzy sets. Moreover, in such problems the comparisons between the numerical values that represent the information described by the fuzzy sets become necessary. The aforementioned comparisons are made by means of a distance defined on fuzzy sets. Thus, the numerical operators aggregating distances between fuzzy sets as incoming data play a central role in applied problems. Recently, J.J. Nieto and A. Torres gave some applications of the aggregation of distances on fuzzy sets to the study of real medical data in /cite{Nieto}. These applications are based on the notion of segment joining two given fuzzy sets and on the notion of set of midpoints between fuzzy sets. A few results obtained by Nieto and Torres have been generalized in turn by Casasnovas and Rossell/'{o} in /cite{Casas,Casas2}. Nowadays, quasi-metrics provide efficient tools in some fields of computer science and in bioinformatics. Motivated by the exposed facts, a study of segments joining two fuzzy sets and of midpoints between fuzzy sets when the measure, used for comparisons, is a quasi-metric has been made in /cite{Casas3, SebVal2013,TiradoValero}. (Author)

  12. Performance evaluation of a distance learning program.

    OpenAIRE

    Dailey, D. J.; Eno, K. R.; Brinkley, J. F.

    1994-01-01

    This paper presents a performance metric which uses a single number to characterize the response time for a non-deterministic client-server application operating over the Internet. When applied to a Macintosh-based distance learning application called the Digital Anatomist Browser, the metric allowed us to observe that "A typical student doing a typical mix of Browser commands on a typical data set will experience the same delay if they use a slow Macintosh on a local network or a fast Macint...

  13. METRICS DEVELOPMENT FOR PATENTS.

    Science.gov (United States)

    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

  14. A Metric for Heterotic Moduli

    Science.gov (United States)

    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.

  15. Model assessment using a multi-metric ranking technique

    Science.gov (United States)

    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.

  16. Implications of Metric Choice for Common Applications of Readmission Metrics

    OpenAIRE

    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).

  17. Issues in Benchmark Metric Selection

    Science.gov (United States)

    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.

  18. 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

  19. 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.

  20. 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.

  1. 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)

  2. Let's Make Metric Ice Cream

    Science.gov (United States)

    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)

  3. 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

  4. Coverage Metrics for Model Checking

    Science.gov (United States)

    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.

  5. 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.

  6. Stochastic learning of multi-instance dictionary for earth mover’s distance-based histogram comparison

    KAUST Repository

    Fan, Jihong; Liang, Ru-Ze

    2016-01-01

    Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover’s distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However

  7. A Single Conjunction Risk Assessment Metric: the F-Value

    Science.gov (United States)

    Frigm, Ryan Clayton; Newman, Lauri K.

    2009-01-01

    The Conjunction Assessment Team at NASA Goddard Space Flight Center provides conjunction risk assessment for many NASA robotic missions. These risk assessments are based on several figures of merit, such as miss distance, probability of collision, and orbit determination solution quality. However, these individual metrics do not singly capture the overall risk associated with a conjunction, making it difficult for someone without this complete understanding to take action, such as an avoidance maneuver. The goal of this analysis is to introduce a single risk index metric that can easily convey the level of risk without all of the technical details. The proposed index is called the conjunction "F-value." This paper presents the concept of the F-value and the tuning of the metric for use in routine Conjunction Assessment operations.

  8. Classification in medical image analysis using adaptive metric k-NN

    DEFF Research Database (Denmark)

    Chen, Chen; Chernoff, Konstantin; Karemore, Gopal

    2010-01-01

    The performance of the k-nearest neighborhoods (k-NN) classifier is highly dependent on the distance metric used to identify the k nearest neighbors of the query points. The standard Euclidean distance is commonly used in practice. This paper investigates the performance of k-NN classifier...

  9. Analytic processing of distance.

    Science.gov (United States)

    Dopkins, Stephen; Galyer, Darin

    2018-01-01

    How does a human observer extract from the distance between two frontal points the component corresponding to an axis of a rectangular reference frame? To find out we had participants classify pairs of small circles, varying on the horizontal and vertical axes of a computer screen, in terms of the horizontal distance between them. A response signal controlled response time. The error rate depended on the irrelevant vertical as well as the relevant horizontal distance between the test circles with the relevant distance effect being larger than the irrelevant distance effect. The results implied that the horizontal distance between the test circles was imperfectly extracted from the overall distance between them. The results supported an account, derived from the Exemplar Based Random Walk model (Nosofsky & Palmieri, 1997), under which distance classification is based on the overall distance between the test circles, with relevant distance being extracted from overall distance to the extent that the relevant and irrelevant axes are differentially weighted so as to reduce the contribution of irrelevant distance to overall distance. The results did not support an account, derived from the General Recognition Theory (Ashby & Maddox, 1994), under which distance classification is based on the relevant distance between the test circles, with the irrelevant distance effect arising because a test circle's perceived location on the relevant axis depends on its location on the irrelevant axis, and with relevant distance being extracted from overall distance to the extent that this dependency is absent. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Assessment of six dissimilarity metrics for climate analogues

    Science.gov (United States)

    Grenier, Patrick; Parent, Annie-Claude; Huard, David; Anctil, François; Chaumont, Diane

    2013-04-01

    Spatial analogue techniques consist in identifying locations whose recent-past climate is similar in some aspects to the future climate anticipated at a reference location. When identifying analogues, one key step is the quantification of the dissimilarity between two climates separated in time and space, which involves the choice of a metric. In this communication, spatial analogues and their usefulness are briefly discussed. Next, six metrics are presented (the standardized Euclidean distance, the Kolmogorov-Smirnov statistic, the nearest-neighbor distance, the Zech-Aslan energy statistic, the Friedman-Rafsky runs statistic and the Kullback-Leibler divergence), along with a set of criteria used for their assessment. The related case study involves the use of numerical simulations performed with the Canadian Regional Climate Model (CRCM-v4.2.3), from which three annual indicators (total precipitation, heating degree-days and cooling degree-days) are calculated over 30-year periods (1971-2000 and 2041-2070). Results indicate that the six metrics identify comparable analogue regions at a relatively large scale, but best analogues may differ substantially. For best analogues, it is also shown that the uncertainty stemming from the metric choice does generally not exceed that stemming from the simulation or model choice. A synthesis of the advantages and drawbacks of each metric is finally presented, in which the Zech-Aslan energy statistic stands out as the most recommended metric for analogue studies, whereas the Friedman-Rafsky runs statistic is the least recommended, based on this case study.

  11. Distances on Cosmological Scales with VLTI

    OpenAIRE

    Karovska, Margarita; Elvis, Martin; Marengo, Massimo

    2003-01-01

    We present here a new method using interferometric measurements of quasars, that allows the determination of direct geometrical distances on cosmic scales. Quasar Broad Emission Line Regions sizes provide a "meter rule" with which to measure the metric of the Universe. This method is less dependent of model assumptions, and even of variations in the fundamental constants (other than c). We discuss the spectral and spatial requirements on the VLTI observations needed to carry out these measure...

  12. A guide to phylogenetic metrics for conservation, community ecology and macroecology

    Science.gov (United States)

    Cadotte, Marc W.; Carvalho, Silvia B.; Davies, T. Jonathan; Ferrier, Simon; Fritz, Susanne A.; Grenyer, Rich; Helmus, Matthew R.; Jin, Lanna S.; Mooers, Arne O.; Pavoine, Sandrine; Purschke, Oliver; Redding, David W.; Rosauer, Dan F.; Winter, Marten; Mazel, Florent

    2016-01-01

    ABSTRACT The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub‐disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub‐disciplines hampers potential meta‐analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo‐diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information. Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo‐diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α‐diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices. PMID:26785932

  13. Assessment of the Log-Euclidean Metric Performance in Diffusion Tensor Image Segmentation

    Directory of Open Access Journals (Sweden)

    Mostafa Charmi

    2010-06-01

    Full Text Available Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep impact on Diffusion Tensor Image (DTI segmentation results. The geodesic metric is the best distance measure since it yields high-quality segmentation results. However, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. The main goal of this paper is to assess the possible substitution of the geodesic metric with the Log-Euclidean one to reduce the computational cost of a statistical surface evolution algorithm. Materials and Methods: We incorporated the Log-Euclidean metric in the statistical surface evolution algorithm framework. To achieve this goal, the statistics and gradients of diffusion tensor images were defined using the Log-Euclidean metric. Numerical implementation of the segmentation algorithm was performed in the MATLAB software using the finite difference techniques. Results: In the statistical surface evolution framework, the Log-Euclidean metric was able to discriminate the torus and helix patterns in synthesis datasets and rat spinal cords in biological phantom datasets from the background better than the Euclidean and J-divergence metrics. In addition, similar results were obtained with the geodesic metric. However, the main advantage of the Log-Euclidean metric over the geodesic metric was the dramatic reduction of computational cost of the segmentation algorithm, at least by 70 times. Discussion and Conclusion: The qualitative and quantitative results have shown that the Log-Euclidean metric is a good substitute for the geodesic metric when using a statistical surface evolution algorithm in DTIs segmentation.

  14. Prioritizing Urban Habitats for Connectivity Conservation: Integrating Centrality and Ecological Metrics.

    Science.gov (United States)

    Poodat, Fatemeh; Arrowsmith, Colin; Fraser, David; Gordon, Ascelin

    2015-09-01

    Connectivity among fragmented areas of habitat has long been acknowledged as important for the viability of biological conservation, especially within highly modified landscapes. Identifying important habitat patches in ecological connectivity is a priority for many conservation strategies, and the application of 'graph theory' has been shown to provide useful information on connectivity. Despite the large number of metrics for connectivity derived from graph theory, only a small number have been compared in terms of the importance they assign to nodes in a network. This paper presents a study that aims to define a new set of metrics and compares these with traditional graph-based metrics, used in the prioritization of habitat patches for ecological connectivity. The metrics measured consist of "topological" metrics, "ecological metrics," and "integrated metrics," Integrated metrics are a combination of topological and ecological metrics. Eight metrics were applied to the habitat network for the fat-tailed dunnart within Greater Melbourne, Australia. A non-directional network was developed in which nodes were linked to adjacent nodes. These links were then weighted by the effective distance between patches. By applying each of the eight metrics for the study network, nodes were ranked according to their contribution to the overall network connectivity. The structured comparison revealed the similarity and differences in the way the habitat for the fat-tailed dunnart was ranked based on different classes of metrics. Due to the differences in the way the metrics operate, a suitable metric should be chosen that best meets the objectives established by the decision maker.

  15. 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

  16. Quantum metric spaces as a model for pregeometry

    International Nuclear Information System (INIS)

    Alvarez, E.; Cespedes, J.; Verdaguer, E.

    1992-01-01

    A new arena for the dynamics of spacetime is proposed, in which the basic quantum variable is the two-point distance on a metric space. The scaling dimension (that is, the Kolmogorov capacity) in the neighborhood of each point then defines in a natural way a local concept of dimension. We study our model in the region of parameter space in which the resulting spacetime is not too different from a smooth manifold

  17. A Lorentzian Gromov-Hausdorff notion of distance

    International Nuclear Information System (INIS)

    Noldus, Johan

    2004-01-01

    This paper is the first of three in which I study the moduli space of isometry classes of (compact) globally hyperbolic spacetimes (with boundary). I introduce a notion of Gromov-Hausdorff distance which makes this moduli space into a metric space. Further properties of this metric space are studied in the next two papers. The importance of the work is in fields such as cosmology, quantum gravity and - for the mathematicians - global Lorentzian geometry

  18. 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

  19. 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

  20. Wireless sensor network performance metrics for building applications

    Energy Technology Data Exchange (ETDEWEB)

    Jang, W.S. (Department of Civil Engineering Yeungnam University 214-1 Dae-Dong, Gyeongsan-Si Gyeongsangbuk-Do 712-749 South Korea); Healy, W.M. [Building and Fire Research Laboratory, 100 Bureau Drive, Gaithersburg, MD 20899-8632 (United States)

    2010-06-15

    Metrics are investigated to help assess the performance of wireless sensors in buildings. Wireless sensor networks present tremendous opportunities for energy savings and improvement in occupant comfort in buildings by making data about conditions and equipment more readily available. A key barrier to their adoption, however, is the uncertainty among users regarding the reliability of the wireless links through building construction. Tests were carried out that examined three performance metrics as a function of transmitter-receiver separation distance, transmitter power level, and obstruction type. These tests demonstrated, via the packet delivery rate, a clear transition from reliable to unreliable communications at different separation distances. While the packet delivery rate is difficult to measure in actual applications, the received signal strength indication correlated well with the drop in packet delivery rate in the relatively noise-free environment used in these tests. The concept of an equivalent distance was introduced to translate the range of reliability in open field operation to that seen in a typical building, thereby providing wireless system designers a rough estimate of the necessary spacing between sensor nodes in building applications. It is anticipated that the availability of straightforward metrics on the range of wireless sensors in buildings will enable more widespread sensing in buildings for improved control and fault detection. (author)

  1. 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...

  2. 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

  3. Training for Distance Teaching through Distance Learning.

    Science.gov (United States)

    Cadorath, Jill; Harris, Simon; Encinas, Fatima

    2002-01-01

    Describes a mixed-mode bachelor degree course in English language teaching at the Universidad Autonoma de Puebla (Mexico) that was designed to help practicing teachers write appropriate distance education materials by giving them the experience of being distance students. Includes a course outline and results of a course evaluation. (Author/LRW)

  4. The Distance Standard Deviation

    OpenAIRE

    Edelmann, Dominic; Richards, Donald; Vogel, Daniel

    2017-01-01

    The distance standard deviation, which arises in distance correlation analysis of multivariate data, is studied as a measure of spread. New representations for the distance standard deviation are obtained in terms of Gini's mean difference and in terms of the moments of spacings of order statistics. Inequalities for the distance variance are derived, proving that the distance standard deviation is bounded above by the classical standard deviation and by Gini's mean difference. Further, it is ...

  5. Thermodynamic metrics and optimal paths.

    Science.gov (United States)

    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.

  6. 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

  7. 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.

  8. Some Metric Properties of Planar Gaussian Free Field

    Science.gov (United States)

    Goswami, Subhajit

    In this thesis we study the properties of some metrics arising from two-dimensional Gaussian free field (GFF), namely the Liouville first-passage percolation (Liouville FPP), the Liouville graph distance and an effective resistance metric. In Chapter 1, we define these metrics as well as discuss the motivations for studying them. Roughly speaking, Liouville FPP is the shortest path metric in a planar domain D where the length of a path P is given by ∫Pe gammah(z)|dz| where h is the GFF on D and gamma > 0. In Chapter 2, we present an upper bound on the expected Liouville FPP distance between two typical points for small values of gamma (the near-Euclidean regime). A similar upper bound is derived in Chapter 3 for the Liouville graph distance which is, roughly, the minimal number of Euclidean balls with comparable Liouville quantum gravity (LQG) measure whose union contains a continuous path between two endpoints. Our bounds seem to be in disagreement with Watabiki's prediction (1993) on the random metric of Liouville quantum gravity in this regime. The contents of these two chapters are based on a joint work with Jian Ding. In Chapter 4, we derive some asymptotic estimates for effective resistances on a random network which is defined as follows. Given any gamma > 0 and for eta = {etav}v∈Z2 denoting a sample of the two-dimensional discrete Gaussian free field on Z2 pinned at the origin, we equip the edge ( u, v) with conductance egamma(etau + eta v). The metric structure of effective resistance plays a crucial role in our proof of the main result in Chapter 4. The primary motivation behind this metric is to understand the random walk on Z 2 where the edge (u, v) has weight egamma(etau + etav). Using the estimates from Chapter 4 we show in Chapter 5 that for almost every eta, this random walk is recurrent and that, with probability tending to 1 as T → infinity, the return probability at time 2T decays as T-1+o(1). In addition, we prove a version of subdiffusive

  9. Technical Privacy Metrics: a Systematic Survey

    OpenAIRE

    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...

  10. Remarks on G-Metric Spaces

    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.

  11. DLA Energy Biofuel Feedstock Metrics Study

    Science.gov (United States)

    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

  12. 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.

  13. Socio-technical security metrics

    NARCIS (Netherlands)

    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

  14. Leading Gainful Employment Metric Reporting

    Science.gov (United States)

    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…

  15. Defining functional distances over Gene Ontology

    Directory of Open Access Journals (Sweden)

    del Pozo Angela

    2008-01-01

    Full Text Available Abstract Background A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e. 'gene ontology' -GO-. However, functional metrics can overcome the problems in the comparing and evaluating functional assignments and predictions. As a reference of proximity, previous approaches to compare GO terms considered linkage in terms of ontology weighted by a probability distribution that balances the non-uniform 'richness' of different parts of the Direct Acyclic Graph. Here, we have followed a different approach to quantify functional similarities between GO terms. Results We propose a new method to derive 'functional distances' between GO terms that is based on the simultaneous occurrence of terms in the same set of Interpro entries, instead of relying on the structure of the GO. The coincidence of GO terms reveals natural biological links between the GO functions and defines a distance model Df which fulfils the properties of a Metric Space. The distances obtained in this way can be represented as a hierarchical 'Functional Tree'. Conclusion The method proposed provides a new definition of distance that enables the similarity between GO terms to be quantified. Additionally, the 'Functional Tree' defines groups with biological meaning enhancing its utility for protein function comparison and prediction. Finally, this approach could be for function-based protein searches in databases, and for analysing the gene clusters produced by DNA array experiments.

  16. SU-G-BRB-16: Vulnerabilities in the Gamma Metric

    International Nuclear Information System (INIS)

    Neal, B; Siebers, J

    2016-01-01

    Purpose: To explore vulnerabilities in the gamma index metric that undermine its wide use as a radiation therapy quality assurance tool. Methods: 2D test field pairs (images) are created specifically to achieve high gamma passing rates, but to also include gross errors by exploiting the distance-to-agreement and percent-passing components of the metric. The first set has no requirement of clinical practicality, but is intended to expose vulnerabilities. The second set exposes clinically realistic vulnerabilities. To circumvent limitations inherent to user-specific tuning of prediction algorithms to match measurements, digital test cases are manually constructed, thereby mimicking high-quality image prediction. Results: With a 3 mm distance-to-agreement metric, changing field size by ±6 mm results in a gamma passing rate over 99%. For a uniform field, a lattice of passing points spaced 5 mm apart results in a passing rate of 100%. Exploiting the percent-passing component, a 10×10 cm"2 field can have a 95% passing rate when an 8 cm"2=2.8×2.8 cm"2 highly out-of-tolerance (e.g. zero dose) square is missing from the comparison image. For clinically realistic vulnerabilities, an arc plan for which a 2D image is created can have a >95% passing rate solely due to agreement in the lateral spillage, with the failing 5% in the critical target region. A field with an integrated boost (e.g whole brain plus small metastases) could neglect the metastases entirely, yet still pass with a 95% threshold. All the failure modes described would be visually apparent on a gamma-map image. Conclusion: The %gamma<1 metric has significant vulnerabilities. High passing rates can obscure critical faults in hypothetical and delivered radiation doses. Great caution should be used with gamma as a QA metric; users should inspect the gamma-map. Visual analysis of gamma-maps may be impractical for cine acquisition.

  17. Validation of network communicability metrics for the analysis of brain structural networks.

    Directory of Open Access Journals (Sweden)

    Jennifer Andreotti

    Full Text Available Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

  18. Brownian distance covariance

    OpenAIRE

    Székely, Gábor J.; Rizzo, Maria L.

    2010-01-01

    Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with...

  19. Distance-regular graphs

    NARCIS (Netherlands)

    van Dam, Edwin R.; Koolen, Jack H.; Tanaka, Hajime

    2016-01-01

    This is a survey of distance-regular graphs. We present an introduction to distance-regular graphs for the reader who is unfamiliar with the subject, and then give an overview of some developments in the area of distance-regular graphs since the monograph 'BCN'[Brouwer, A.E., Cohen, A.M., Neumaier,

  20. 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

  1. General relativity: An erfc metric

    Science.gov (United States)

    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.

  2. Permutation-invariant distance between atomic configurations

    Science.gov (United States)

    Ferré, Grégoire; Maillet, Jean-Bernard; Stoltz, Gabriel

    2015-09-01

    We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables us to directly compare different atomic environments with an arbitrary number of particles, without going through a space of reduced dimensionality (i.e., fingerprints) as an intermediate step. Moreover, this distance is naturally invariant through permutations of atoms, avoiding the time consuming associated minimization required by other common criteria (like the root mean square distance). Finally, the invariance through global rotations is accounted for by a minimization procedure in the space of rotations solved by Monte Carlo simulated annealing. A formal framework is also introduced, showing that the distance we propose verifies the property of a metric on the space of atomic configurations. Two examples of applications are proposed. The first one consists in evaluating faithfulness of some fingerprints (or descriptors), i.e., their capacity to represent the structural information of a configuration. The second application concerns structural analysis, where our distance proves to be efficient in discriminating different local structures and even classifying their degree of similarity.

  3. Permutation-invariant distance between atomic configurations

    International Nuclear Information System (INIS)

    Ferré, Grégoire; Maillet, Jean-Bernard; Stoltz, Gabriel

    2015-01-01

    We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables us to directly compare different atomic environments with an arbitrary number of particles, without going through a space of reduced dimensionality (i.e., fingerprints) as an intermediate step. Moreover, this distance is naturally invariant through permutations of atoms, avoiding the time consuming associated minimization required by other common criteria (like the root mean square distance). Finally, the invariance through global rotations is accounted for by a minimization procedure in the space of rotations solved by Monte Carlo simulated annealing. A formal framework is also introduced, showing that the distance we propose verifies the property of a metric on the space of atomic configurations. Two examples of applications are proposed. The first one consists in evaluating faithfulness of some fingerprints (or descriptors), i.e., their capacity to represent the structural information of a configuration. The second application concerns structural analysis, where our distance proves to be efficient in discriminating different local structures and even classifying their degree of similarity

  4. hdm: High-dimensional metrics

    OpenAIRE

    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...

  5. 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.

  6. Sensory Metrics of Neuromechanical Trust.

    Science.gov (United States)

    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

  7. 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.

  8. 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

  9. Sustainability Metrics: The San Luis Basin Project

    Science.gov (United States)

    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...

  10. Haptic Discrimination of Distance

    Science.gov (United States)

    van Beek, Femke E.; Bergmann Tiest, Wouter M.; Kappers, Astrid M. L.

    2014-01-01

    While quite some research has focussed on the accuracy of haptic perception of distance, information on the precision of haptic perception of distance is still scarce, particularly regarding distances perceived by making arm movements. In this study, eight conditions were measured to answer four main questions, which are: what is the influence of reference distance, movement axis, perceptual mode (active or passive) and stimulus type on the precision of this kind of distance perception? A discrimination experiment was performed with twelve participants. The participants were presented with two distances, using either a haptic device or a real stimulus. Participants compared the distances by moving their hand from a start to an end position. They were then asked to judge which of the distances was the longer, from which the discrimination threshold was determined for each participant and condition. The precision was influenced by reference distance. No effect of movement axis was found. The precision was higher for active than for passive movements and it was a bit lower for real stimuli than for rendered stimuli, but it was not affected by adding cutaneous information. Overall, the Weber fraction for the active perception of a distance of 25 or 35 cm was about 11% for all cardinal axes. The recorded position data suggest that participants, in order to be able to judge which distance was the longer, tried to produce similar speed profiles in both movements. This knowledge could be useful in the design of haptic devices. PMID:25116638

  11. Haptic discrimination of distance.

    Directory of Open Access Journals (Sweden)

    Femke E van Beek

    Full Text Available While quite some research has focussed on the accuracy of haptic perception of distance, information on the precision of haptic perception of distance is still scarce, particularly regarding distances perceived by making arm movements. In this study, eight conditions were measured to answer four main questions, which are: what is the influence of reference distance, movement axis, perceptual mode (active or passive and stimulus type on the precision of this kind of distance perception? A discrimination experiment was performed with twelve participants. The participants were presented with two distances, using either a haptic device or a real stimulus. Participants compared the distances by moving their hand from a start to an end position. They were then asked to judge which of the distances was the longer, from which the discrimination threshold was determined for each participant and condition. The precision was influenced by reference distance. No effect of movement axis was found. The precision was higher for active than for passive movements and it was a bit lower for real stimuli than for rendered stimuli, but it was not affected by adding cutaneous information. Overall, the Weber fraction for the active perception of a distance of 25 or 35 cm was about 11% for all cardinal axes. The recorded position data suggest that participants, in order to be able to judge which distance was the longer, tried to produce similar speed profiles in both movements. This knowledge could be useful in the design of haptic devices.

  12. Interface Simulation Distances

    Directory of Open Access Journals (Sweden)

    Pavol Černý

    2012-10-01

    Full Text Available The classical (boolean notion of refinement for behavioral interfaces of system components is the alternating refinement preorder. In this paper, we define a distance for interfaces, called interface simulation distance. It makes the alternating refinement preorder quantitative by, intuitively, tolerating errors (while counting them in the alternating simulation game. We show that the interface simulation distance satisfies the triangle inequality, that the distance between two interfaces does not increase under parallel composition with a third interface, and that the distance between two interfaces can be bounded from above and below by distances between abstractions of the two interfaces. We illustrate the framework, and the properties of the distances under composition of interfaces, with two case studies.

  13. Tourists consuming distance

    DEFF Research Database (Denmark)

    Larsen, Gunvor Riber

    The environmental impact of tourism mobility is linked to the distances travelled in order to reach a holiday destination, and with tourists travelling more and further than previously, an understanding of how the tourists view the distance they travel across becomes relevant. Based on interviews...... contribute to an understanding of how it is possible to change tourism travel behaviour towards becoming more sustainable. How tourists 'consume distance' is discussed, from the practical level of actually driving the car or sitting in the air plane, to the symbolic consumption of distance that occurs when...... travelling on holiday becomes part of a lifestyle and a social positioning game. Further, different types of tourist distance consumers are identified, ranging from the reluctant to the deliberate and nonchalant distance consumers, who display very differing attitudes towards the distance they all travel...

  14. 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

  15. A family of metric gravities

    Science.gov (United States)

    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

  16. Hybrid metric-Palatini stars

    Science.gov (United States)

    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

  17. Performance evaluation of a distance learning program.

    Science.gov (United States)

    Dailey, D J; Eno, K R; Brinkley, J F

    1994-01-01

    This paper presents a performance metric which uses a single number to characterize the response time for a non-deterministic client-server application operating over the Internet. When applied to a Macintosh-based distance learning application called the Digital Anatomist Browser, the metric allowed us to observe that "A typical student doing a typical mix of Browser commands on a typical data set will experience the same delay if they use a slow Macintosh on a local network or a fast Macintosh on the other side of the country accessing the data over the Internet." The methodology presented is applicable to other client-server applications that are rapidly appearing on the Internet.

  18. Metrics for Evaluation of Student Models

    Science.gov (United States)

    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…

  19. Context-dependent ATC complexity metric

    NARCIS (Netherlands)

    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,

  20. Properties of C-metric spaces

    Science.gov (United States)

    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.

  1. 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....

  2. Emergence of the scale-invariant proportion in a flock from the metric-topological interaction.

    Science.gov (United States)

    Niizato, Takayuki; Murakami, Hisashi; Gunji, Yukio-Pegio

    2014-05-01

    Recently, it has become possible to more precisely analyze flocking behavior. Such research has prompted a reconsideration of the notion of neighborhoods in the theoretical model. Flocking based on topological distance is one such result. In a topological flocking model, a bird does not interact with its neighbors on the basis of a fixed-size neighborhood (i.e., on the basis of metric distance), but instead interacts with its nearest seven neighbors. Cavagna et al., moreover, found a new phenomenon in flocks that can be explained by neither metric distance nor topological distance: they found that correlated domains in a flock were larger than the metric and topological distance and that these domains were proportional to the total flock size. However, the role of scale-free correlation is still unclear. In a previous study, we constructed a metric-topological interaction model on three-dimensional spaces and showed that this model exhibited scale-free correlation. In this study, we found that scale-free correlation in a two-dimensional flock was more robust than in a three-dimensional flock for the threshold parameter. Furthermore, we also found a qualitative difference in behavior from using the fluctuation coherence, which we observed on three-dimensional flocking behavior. Our study suggests that two-dimensional flocks try to maintain a balance between the flock size and flock mobility by breaking into several smaller flocks. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  3. Prediction Model of Collapse Risk Based on Information Entropy and Distance Discriminant Analysis Method

    Directory of Open Access Journals (Sweden)

    Hujun He

    2017-01-01

    Full Text Available The prediction and risk classification of collapse is an important issue in the process of highway construction in mountainous regions. Based on the principles of information entropy and Mahalanobis distance discriminant analysis, we have produced a collapse hazard prediction model. We used the entropy measure method to reduce the influence indexes of the collapse activity and extracted the nine main indexes affecting collapse activity as the discriminant factors of the distance discriminant analysis model (i.e., slope shape, aspect, gradient, and height, along with exposure of the structural face, stratum lithology, relationship between weakness face and free face, vegetation cover rate, and degree of rock weathering. We employ postearthquake collapse data in relation to construction of the Yingxiu-Wolong highway, Hanchuan County, China, as training samples for analysis. The results were analyzed using the back substitution estimation method, showing high accuracy and no errors, and were the same as the prediction result of uncertainty measure. Results show that the classification model based on information entropy and distance discriminant analysis achieves the purpose of index optimization and has excellent performance, high prediction accuracy, and a zero false-positive rate. The model can be used as a tool for future evaluation of collapse risk.

  4. Traversing psychological distance.

    Science.gov (United States)

    Liberman, Nira; Trope, Yaacov

    2014-07-01

    Traversing psychological distance involves going beyond direct experience, and includes planning, perspective taking, and contemplating counterfactuals. Consistent with this view, temporal, spatial, and social distances as well as hypotheticality are associated, affect each other, and are inferred from one another. Moreover, traversing all distances involves the use of abstraction, which we define as forming a belief about the substitutability for a specific purpose of subjectively distinct objects. Indeed, across many instances of both abstraction and psychological distancing, more abstract constructs are used for more distal objects. Here, we describe the implications of this relation for prediction, choice, communication, negotiation, and self-control. We ask whether traversing distance is a general mental ability and whether distance should replace expectancy in expected-utility theories. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. 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)

  6. Viscous shear in the Kerr metric

    International Nuclear Information System (INIS)

    Anderson, M.R.; Lemos, J.P.S.

    1988-01-01

    Models of viscous flows on to black holes commonly assume a zero-torque boundary condition at the radius of the last stable Keplerian orbit. It is here shown that this condition is wrong. The viscous torque is generally non-zero at both the last stable orbit and the horizon itself. The existence of a non-zero viscous torque at the horizon does not require the transfer of energy or angular momentum across any spacelike distance, and so does not violate causality. Further, in comparison with the viscous torque in the distant, Newtonian regime, the viscous torque on the horizon is often reversed, so that angular momentum is viscously advected inwards rather than outwards. This phenomenon is first suggested by an analysis of the quasi-stationary case, and then demonstrated explicitly for a series of cold, dynamical flows which fall freely from the last stable orbit in the Schwarzschild and Kerr metrics. In the steady flows constructed here, the net torque on the hole is always directed in the usual sense; any reversal in the viscous torque is offset by an increase in the convected flux of angular momentum. (author)

  7. Numerical distance protection

    CERN Document Server

    Ziegler, Gerhard

    2011-01-01

    Distance protection provides the basis for network protection in transmission systems and meshed distribution systems. This book covers the fundamentals of distance protection and the special features of numerical technology. The emphasis is placed on the application of numerical distance relays in distribution and transmission systems.This book is aimed at students and engineers who wish to familiarise themselves with the subject of power system protection, as well as the experienced user, entering the area of numerical distance protection. Furthermore it serves as a reference guide for s

  8. Product Operations Status Summary Metrics

    Science.gov (United States)

    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.

  9. Web metrics for library and information professionals

    CERN Document Server

    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...

  10. Local adjacency metric dimension of sun graph and stacked book graph

    Science.gov (United States)

    Yulisda Badri, Alifiah; Darmaji

    2018-03-01

    A graph is a mathematical system consisting of a non-empty set of nodes and a set of empty sides. One of the topics to be studied in graph theory is the metric dimension. Application in the metric dimension is the navigation robot system on a path. Robot moves from one vertex to another vertex in the field by minimizing the errors that occur in translating the instructions (code) obtained from the vertices of that location. To move the robot must give different instructions (code). In order for the robot to move efficiently, the robot must be fast to translate the code of the nodes of the location it passes. so that the location vertex has a minimum distance. However, if the robot must move with the vertex location on a very large field, so the robot can not detect because the distance is too far.[6] In this case, the robot can determine its position by utilizing location vertices based on adjacency. The problem is to find the minimum cardinality of the required location vertex, and where to put, so that the robot can determine its location. The solution to this problem is the dimension of adjacency metric and adjacency metric bases. Rodrguez-Velzquez and Fernau combine the adjacency metric dimensions with local metric dimensions, thus becoming the local adjacency metric dimension. In the local adjacency metric dimension each vertex in the graph may have the same adjacency representation as the terms of the vertices. To obtain the local metric dimension of values in the graph of the Sun and the stacked book graph is used the construction method by considering the representation of each adjacent vertex of the graph.

  11. Metrics for building performance assurance

    Energy Technology Data Exchange (ETDEWEB)

    Koles, G.; Hitchcock, R.; Sherman, M.

    1996-07-01

    This report documents part of the work performed in phase I of a Laboratory Directors Research and Development (LDRD) funded project entitled Building Performance Assurances (BPA). The focus of the BPA effort is to transform the way buildings are built and operated in order to improve building performance by facilitating or providing tools, infrastructure, and information. The efforts described herein focus on the development of metrics with which to evaluate building performance and for which information and optimization tools need to be developed. The classes of building performance metrics reviewed are (1) Building Services (2) First Costs, (3) Operating Costs, (4) Maintenance Costs, and (5) Energy and Environmental Factors. The first category defines the direct benefits associated with buildings; the next three are different kinds of costs associated with providing those benefits; the last category includes concerns that are broader than direct costs and benefits to the building owner and building occupants. The level of detail of the various issues reflect the current state of knowledge in those scientific areas and the ability of the to determine that state of knowledge, rather than directly reflecting the importance of these issues; it intentionally does not specifically focus on energy issues. The report describes work in progress and is intended as a resource and can be used to indicate the areas needing more investigation. Other reports on BPA activities are also available.

  12. Simulation of devices mobility to estimate wireless channel quality metrics in 5G networks

    Science.gov (United States)

    Orlov, Yu.; Fedorov, S.; Samuylov, A.; Gaidamaka, Yu.; Molchanov, D.

    2017-07-01

    The problem of channel quality estimation for devices in a wireless 5G network is formulated. As a performance metrics of interest we choose the signal-to-interference-plus-noise ratio, which depends essentially on the distance between the communicating devices. A model with a plurality of moving devices in a bounded three-dimensional space and a simulation algorithm to determine the distances between the devices for a given motion model are devised.

  13. ORDERED WEIGHTED DISTANCE MEASURE

    Institute of Scientific and Technical Information of China (English)

    Zeshui XU; Jian CHEN

    2008-01-01

    The aim of this paper is to develop an ordered weighted distance (OWD) measure, which is thegeneralization of some widely used distance measures, including the normalized Hamming distance, the normalized Euclidean distance, the normalized geometric distance, the max distance, the median distance and the min distance, etc. Moreover, the ordered weighted averaging operator, the generalized ordered weighted aggregation operator, the ordered weighted geometric operator, the averaging operator, the geometric mean operator, the ordered weighted square root operator, the square root operator, the max operator, the median operator and the min operator axe also the special cases of the OWD measure. Some methods depending on the input arguments are given to determine the weights associated with the OWD measure. The prominent characteristic of the OWD measure is that it can relieve (or intensify) the influence of unduly large or unduly small deviations on the aggregation results by assigning them low (or high) weights. This desirable characteristic makes the OWD measure very suitable to be used in many actual fields, including group decision making, medical diagnosis, data mining, and pattern recognition, etc. Finally, based on the OWD measure, we develop a group decision making approach, and illustrate it with a numerical example.

  14. Distance-transitive graphs

    NARCIS (Netherlands)

    Cohen, A.M.; Beineke, L.W.; Wilson, R.J.; Cameron, P.J.

    2004-01-01

    In this chapter we investigate the classification of distance-transitive graphs: these are graphs whose automorphism groups are transitive on each of the sets of pairs of vertices at distance i, for i = 0, 1,.... We provide an introduction into the field. By use of the classification of finite

  15. Distance Education in Entwicklungslandern.

    Science.gov (United States)

    German Foundation for International Development, Bonn (West Germany).

    Seminar and conference reports and working papers on distance education of adults, which reflect the experiences of many countries, are presented. Contents include the draft report of the 1979 International Seminar on Distance Education held in Addis Ababa, Ethiopia, which was jointly sponsored by the United Nations Economic Commission for Africa…

  16. Distance Education in Turkey

    Directory of Open Access Journals (Sweden)

    Dr. Nursel Selver RUZGAR,

    2004-04-01

    Full Text Available Distance Education in Turkey Assistant Professor Dr. Nursel Selver RUZGAR Technical Education Faculty Marmara University, TURKEY ABSTRACT Many countries of the world are using distance education with various ways, by internet, by post and by TV. In this work, development of distance education in Turkey has been presented from the beginning. After discussing types and applications for different levels of distance education in Turkey, the distance education was given in the cultural aspect of the view. Then, in order to create the tendencies and thoughts of graduates of Higher Education Institutions and Distance Education Institutions about being competitors in job markets, sufficiency of education level, advantages for education system, continuing education in different Institutions, a face-to-face survey was applied to 1284 graduates, 958 from Higher Education Institutions and 326 from Distance Education Institutions. The results were evaluated and discussed. In the last part of this work, suggestions to become widespread and improve the distance education in the country were made.

  17. Comparing Phylogenetic Trees by Matching Nodes Using the Transfer Distance Between Partitions.

    Science.gov (United States)

    Bogdanowicz, Damian; Giaro, Krzysztof

    2017-05-01

    Ability to quantify dissimilarity of different phylogenetic trees describing the relationship between the same group of taxa is required in various types of phylogenetic studies. For example, such metrics are used to assess the quality of phylogeny construction methods, to define optimization criteria in supertree building algorithms, or to find horizontal gene transfer (HGT) events. Among the set of metrics described so far in the literature, the most commonly used seems to be the Robinson-Foulds distance. In this article, we define a new metric for rooted trees-the Matching Pair (MP) distance. The MP metric uses the concept of the minimum-weight perfect matching in a complete bipartite graph constructed from partitions of all pairs of leaves of the compared phylogenetic trees. We analyze the properties of the MP metric and present computational experiments showing its potential applicability in tasks related to finding the HGT events.

  18. A Simple Metric for Determining Resolution in Optical, Ion, and Electron Microscope Images.

    Science.gov (United States)

    Curtin, Alexandra E; Skinner, Ryan; Sanders, Aric W

    2015-06-01

    A resolution metric intended for resolution analysis of arbitrary spatially calibrated images is presented. By fitting a simple sigmoidal function to pixel intensities across slices of an image taken perpendicular to light-dark edges, the mean distance over which the light-dark transition occurs can be determined. A fixed multiple of this characteristic distance is then reported as the image resolution. The prefactor is determined by analysis of scanning transmission electron microscope high-angle annular dark field images of Si. This metric has been applied to optical, scanning electron microscope, and helium ion microscope images. This method provides quantitative feedback about image resolution, independent of the tool on which the data were collected. In addition, our analysis provides a nonarbitrary and self-consistent framework that any end user can utilize to evaluate the resolution of multiple microscopes from any vendor using the same metric.

  19. Lipschitz Metrics for a Class of Nonlinear Wave Equations

    Science.gov (United States)

    Bressan, Alberto; Chen, Geng

    2017-12-01

    The nonlinear wave equation {u_{tt}-c(u)(c(u)u_x)_x=0} determines a flow of conservative solutions taking values in the space {H^1(R)}. However, this flow is not continuous with respect to the natural H 1 distance. The aim of this paper is to construct a new metric which renders the flow uniformly Lipschitz continuous on bounded subsets of {H^1(R)}. For this purpose, H 1 is given the structure of a Finsler manifold, where the norm of tangent vectors is defined in terms of an optimal transportation problem. For paths of piecewise smooth solutions, one can carefully estimate how the weighted length grows in time. By the generic regularity result proved in [7], these piecewise regular paths are dense and can be used to construct a geodesic distance with the desired Lipschitz property.

  20. H-Metric: Characterizing Image Datasets via Homogenization Based on KNN-Queries

    Directory of Open Access Journals (Sweden)

    Welington M da Silva

    2012-01-01

    Full Text Available Precision-Recall is one of the main metrics for evaluating content-based image retrieval techniques. However, it does not provide an ample perception of the properties of an image dataset immersed in a metric space. In this work, we describe an alternative metric named H-Metric, which is determined along a sequence of controlled modifications in the image dataset. The process is named homogenization and works by altering the homogeneity characteristics of the classes of the images. The result is a process that measures how hard it is to deal with a set of images in respect to content-based retrieval, offering support in the task of analyzing configurations of distance functions and of features extractors.

  1. 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.

  2. Metrics for Business Process Models

    Science.gov (United States)

    Mendling, Jan

    Up until now, there has been little research on why people introduce errors in real-world business process models. In a more general context, Simon [404] points to the limitations of cognitive capabilities and concludes that humans act rationally only to a certain extent. Concerning modeling errors, this argument would imply that human modelers lose track of the interrelations of large and complex models due to their limited cognitive capabilities and introduce errors that they would not insert in a small model. A recent study by Mendling et al. [275] explores in how far certain complexity metrics of business process models have the potential to serve as error determinants. The authors conclude that complexity indeed appears to have an impact on error probability. Before we can test such a hypothesis in a more general setting, we have to establish an understanding of how we can define determinants that drive error probability and how we can measure them.

  3. On Nakhleh's metric for reduced phylogenetic networks

    OpenAIRE

    Cardona, Gabriel; Llabrés, Mercè; Rosselló, Francesc; Valiente Feruglio, Gabriel Alejandro

    2009-01-01

    We prove that Nakhleh’s metric for reduced phylogenetic networks is also a metric on the classes of tree-child phylogenetic networks, semibinary tree-sibling time consistent phylogenetic networks, and multilabeled phylogenetic trees. We also prove that it separates distinguishable phylogenetic networks. In this way, it becomes the strongest dissimilarity measure for phylogenetic networks available so far. Furthermore, we propose a generalization of that metric that separates arbitrary phyl...

  4. Generalized tolerance sensitivity and DEA metric sensitivity

    OpenAIRE

    Neralić, Luka; E. Wendell, Richard

    2015-01-01

    This paper considers the relationship between Tolerance sensitivity analysis in optimization and metric sensitivity analysis in Data Envelopment Analysis (DEA). Herein, we extend the results on the generalized Tolerance framework proposed by Wendell and Chen and show how this framework includes DEA metric sensitivity as a special case. Further, we note how recent results in Tolerance sensitivity suggest some possible extensions of the results in DEA metric sensitivity.

  5. The definitive guide to IT service metrics

    CERN Document Server

    McWhirter, Kurt

    2012-01-01

    Used just as they are, the metrics in this book will bring many benefits to both the IT department and the business as a whole. Details of the attributes of each metric are given, enabling you to make the right choices for your business. You may prefer and are encouraged to design and create your own metrics to bring even more value to your business - this book will show you how to do this, too.

  6. Generalized tolerance sensitivity and DEA metric sensitivity

    Directory of Open Access Journals (Sweden)

    Luka Neralić

    2015-03-01

    Full Text Available This paper considers the relationship between Tolerance sensitivity analysis in optimization and metric sensitivity analysis in Data Envelopment Analysis (DEA. Herein, we extend the results on the generalized Tolerance framework proposed by Wendell and Chen and show how this framework includes DEA metric sensitivity as a special case. Further, we note how recent results in Tolerance sensitivity suggest some possible extensions of the results in DEA metric sensitivity.

  7. Common Metrics for Human-Robot Interaction

    Science.gov (United States)

    Steinfeld, Aaron; Lewis, Michael; Fong, Terrence; Scholtz, Jean; Schultz, Alan; Kaber, David; Goodrich, Michael

    2006-01-01

    This paper describes an effort to identify common metrics for task-oriented human-robot interaction (HRI). We begin by discussing the need for a toolkit of HRI metrics. We then describe the framework of our work and identify important biasing factors that must be taken into consideration. Finally, we present suggested common metrics for standardization and a case study. Preparation of a larger, more detailed toolkit is in progress.

  8. Chaotic inflation with metric and matter perturbations

    International Nuclear Information System (INIS)

    Feldman, H.A.; Brandenberger, R.H.

    1989-01-01

    A perturbative scheme to analyze the evolution of both metric and scalar field perturbations in an expanding universe is developed. The scheme is applied to study chaotic inflation with initial metric and scalar field perturbations present. It is shown that initial gravitational perturbations with wavelength smaller than the Hubble radius rapidly decay. The metric simultaneously picks up small perturbations determined by the matter inhomogeneities. Both are frozen in once the wavelength exceeds the Hubble radius. (orig.)

  9. Gravitational lensing in metric theories of gravity

    International Nuclear Information System (INIS)

    Sereno, Mauro

    2003-01-01

    Gravitational lensing in metric theories of gravity is discussed. I introduce a generalized approximate metric element, inclusive of both post-post-Newtonian contributions and a gravitomagnetic field. Following Fermat's principle and standard hypotheses, I derive the time delay function and deflection angle caused by an isolated mass distribution. Several astrophysical systems are considered. In most of the cases, the gravitomagnetic correction offers the best perspectives for an observational detection. Actual measurements distinguish only marginally different metric theories from each other

  10. About the possibility of a generalized metric

    International Nuclear Information System (INIS)

    Lukacs, B.; Ladik, J.

    1991-10-01

    The metric (the structure of the space-time) may be dependent on the properties of the object measuring it. The case of size dependence of the metric was examined. For this dependence the simplest possible form of the metric tensor has been constructed which fulfils the following requirements: there be two extremal characteristic scales; the metric be unique and the usual between them; the change be sudden in the neighbourhood of these scales; the size of the human body appear as a parameter (postulated on the basis of some philosophical arguments). Estimates have been made for the two extremal length scales according to existing observations. (author) 19 refs

  11. Motivation in Distance Leaming

    Directory of Open Access Journals (Sweden)

    Daniela Brečko

    1996-12-01

    Full Text Available It is estimated that motivation is one of the most important psychological functions making it possible for people to leam even in conditions that do not meet their needs. In distance learning, a form of autonomous learning, motivation is of outmost importance. When adopting this method in learning an individual has to stimulate himself and take learning decisions on his or her own. These specific characteristics of distance learning should be taken into account. This all different factors maintaining the motivation of partici­pants in distance learning are to be included. Moreover, motivation in distance learning can be stimulated with specific learning materials, clear instructions and guide-lines, an efficient feed back, personal contact between tutors and parti­cipants, stimulating learning letters, telephone calls, encouraging letters and through maintaining a positive relationship between tutor and participant.

  12. SU-G-BRB-16: Vulnerabilities in the Gamma Metric

    Energy Technology Data Exchange (ETDEWEB)

    Neal, B; Siebers, J [University of Virginia Health System, Charlottesville, VA (United States)

    2016-06-15

    Purpose: To explore vulnerabilities in the gamma index metric that undermine its wide use as a radiation therapy quality assurance tool. Methods: 2D test field pairs (images) are created specifically to achieve high gamma passing rates, but to also include gross errors by exploiting the distance-to-agreement and percent-passing components of the metric. The first set has no requirement of clinical practicality, but is intended to expose vulnerabilities. The second set exposes clinically realistic vulnerabilities. To circumvent limitations inherent to user-specific tuning of prediction algorithms to match measurements, digital test cases are manually constructed, thereby mimicking high-quality image prediction. Results: With a 3 mm distance-to-agreement metric, changing field size by ±6 mm results in a gamma passing rate over 99%. For a uniform field, a lattice of passing points spaced 5 mm apart results in a passing rate of 100%. Exploiting the percent-passing component, a 10×10 cm{sup 2} field can have a 95% passing rate when an 8 cm{sup 2}=2.8×2.8 cm{sup 2} highly out-of-tolerance (e.g. zero dose) square is missing from the comparison image. For clinically realistic vulnerabilities, an arc plan for which a 2D image is created can have a >95% passing rate solely due to agreement in the lateral spillage, with the failing 5% in the critical target region. A field with an integrated boost (e.g whole brain plus small metastases) could neglect the metastases entirely, yet still pass with a 95% threshold. All the failure modes described would be visually apparent on a gamma-map image. Conclusion: The %gamma<1 metric has significant vulnerabilities. High passing rates can obscure critical faults in hypothetical and delivered radiation doses. Great caution should be used with gamma as a QA metric; users should inspect the gamma-map. Visual analysis of gamma-maps may be impractical for cine acquisition.

  13. Einstein at a distance

    Energy Technology Data Exchange (ETDEWEB)

    Lambourne, Robert [Department of Physics and Astronomy, Open University, Milton Keynes (United Kingdom)

    2005-11-01

    This paper examines the challenges and rewards that can arise when the teaching of Einsteinian physics has to be accomplished by means of distance education. The discussion is mainly based on experiences gathered over the past 35 years at the UK Open University, where special and general relativity, relativistic cosmology and other aspects of Einsteinian physics, have been taught at a variety of levels, and using a range of techniques, to students studying at a distance.

  14. Long distance quantum teleportation

    Science.gov (United States)

    Xia, Xiu-Xiu; Sun, Qi-Chao; Zhang, Qiang; Pan, Jian-Wei

    2018-01-01

    Quantum teleportation is a core protocol in quantum information science. Besides revealing the fascinating feature of quantum entanglement, quantum teleportation provides an ultimate way to distribute quantum state over extremely long distance, which is crucial for global quantum communication and future quantum networks. In this review, we focus on the long distance quantum teleportation experiments, especially those employing photonic qubits. From the viewpoint of real-world application, both the technical advantages and disadvantages of these experiments are discussed.

  15. Early Identification of Ineffective Cooperative Learning Teams

    Science.gov (United States)

    Hsiung, C .M.; Luo, L. F.; Chung, H. C.

    2014-01-01

    Cooperative learning has many pedagogical benefits. However, if the cooperative learning teams become ineffective, these benefits are lost. Accordingly, this study developed a computer-aided assessment method for identifying ineffective teams at their early stage of dysfunction by using the Mahalanobis distance metric to examine the difference…

  16. Biomechanical CT Metrics Are Associated With Patient Outcomes in COPD

    Science.gov (United States)

    Bodduluri, Sandeep; Bhatt, Surya P; Hoffman, Eric A.; Newell, John D.; Martinez, Carlos H.; Dransfield, Mark T.; Han, Meilan K.; Reinhardt, Joseph M.

    2017-01-01

    Background Traditional metrics of lung disease such as those derived from spirometry and static single-volume CT images are used to explain respiratory morbidity in patients with chronic obstructive pulmonary disease (COPD), but are insufficient. We hypothesized that the mean Jacobian determinant, a measure of local lung expansion and contraction with respiration, would contribute independently to clinically relevant functional outcomes. Methods We applied image registration techniques to paired inspiratory-expiratory CT scans and derived the Jacobian determinant of the deformation field between the two lung volumes to map local volume change with respiration. We analyzed 490 participants with COPD with multivariable regression models to assess strengths of association between traditional CT metrics of disease and the Jacobian determinant with respiratory morbidity including dyspnea (mMRC), St Georges Respiratory Questionnaire (SGRQ) score, six-minute walk distance (6MWD), and the BODE index, as well as all-cause mortality. Results The Jacobian determinant was significantly associated with SGRQ (adjusted regression co-efficient β = −11.75,95%CI −21.6 to −1.7;p=0.020), and with 6MWD (β=321.15, 95%CI 134.1 to 508.1;p<0.001), independent of age, sex, race, body-mass-index, FEV1, smoking pack-years, CT emphysema, CT gas trapping, airway wall thickness, and CT scanner protocol. The mean Jacobian determinant was also independently associated with the BODE index (β= −0.41, 95%CI −0.80 to −0.02; p = 0.039), and mortality on follow-up (adjusted hazards ratio = 4.26, 95%CI = 0.93 to 19.23; p = 0.064). Conclusion Biomechanical metrics representing local lung expansion and contraction improve prediction of respiratory morbidity and mortality and offer additional prognostic information beyond traditional measures of lung function and static single-volume CT metrics. PMID:28044005

  17. Enhancing Authentication Models Characteristic Metrics via ...

    African Journals Online (AJOL)

    In this work, we derive the universal characteristic metrics set for authentication models based on security, usability and design issues. We then compute the probability of the occurrence of each characteristic metrics in some single factor and multifactor authentication models in order to determine the effectiveness of these ...

  18. Gravitational Metric Tensor Exterior to Rotating Homogeneous ...

    African Journals Online (AJOL)

    The covariant and contravariant metric tensors exterior to a homogeneous spherical body rotating uniformly about a common φ axis with constant angular velocity ω is constructed. The constructed metric tensors in this gravitational field have seven non-zero distinct components.The Lagrangian for this gravitational field is ...

  19. Invariant metric for nonlinear symplectic maps

    Indian Academy of Sciences (India)

    In this paper, we construct an invariant metric in the space of homogeneous polynomials of a given degree (≥ 3). The homogeneous polynomials specify a nonlinear symplectic map which in turn represents a Hamiltonian system. By minimizing the norm constructed out of this metric as a function of system parameters, we ...

  20. Fixed point theory in metric type spaces

    CERN Document Server

    Agarwal, Ravi P; O’Regan, Donal; Roldán-López-de-Hierro, Antonio Francisco

    2015-01-01

    Written by a team of leading experts in the field, this volume presents a self-contained account of the theory, techniques and results in metric type spaces (in particular in G-metric spaces); that is, the text approaches this important area of fixed point analysis beginning from the basic ideas of metric space topology. The text is structured so that it leads the reader from preliminaries and historical notes on metric spaces (in particular G-metric spaces) and on mappings, to Banach type contraction theorems in metric type spaces, fixed point theory in partially ordered G-metric spaces, fixed point theory for expansive mappings in metric type spaces, generalizations, present results and techniques in a very general abstract setting and framework. Fixed point theory is one of the major research areas in nonlinear analysis. This is partly due to the fact that in many real world problems fixed point theory is the basic mathematical tool used to establish the existence of solutions to problems which arise natur...

  1. Metric solution of a spinning mass

    International Nuclear Information System (INIS)

    Sato, H.

    1982-01-01

    Studies on a particular class of asymptotically flat and stationary metric solutions called the Kerr-Tomimatsu-Sato class are reviewed about its derivation and properties. For a further study, an almost complete list of the papers worked on the Tomimatsu-Sato metrics is given. (Auth.)

  2. On Information Metrics for Spatial Coding.

    Science.gov (United States)

    Souza, Bryan C; Pavão, Rodrigo; Belchior, Hindiael; Tort, Adriano B L

    2018-04-01

    The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

  3. Validation of Metrics for Collaborative Systems

    Directory of Open Access Journals (Sweden)

    Ion IVAN

    2008-01-01

    Full Text Available This paper describe the new concepts of collaborative systems metrics validation. The paper define the quality characteristics of collaborative systems. There are proposed a metric to estimate the quality level of collaborative systems. There are performed measurements of collaborative systems quality using a specially designed software.

  4. Validation of Metrics for Collaborative Systems

    OpenAIRE

    Ion IVAN; Cristian CIUREA

    2008-01-01

    This paper describe the new concepts of collaborative systems metrics validation. The paper define the quality characteristics of collaborative systems. There are proposed a metric to estimate the quality level of collaborative systems. There are performed measurements of collaborative systems quality using a specially designed software.

  5. Software Power Metric Model: An Implementation | Akwukwuma ...

    African Journals Online (AJOL)

    ... and the execution time (TIME) in each case was recorded. We then obtain the application functions point count. Our result shows that the proposed metric is computable, consistent in its use of unit, and is programming language independent. Keywords: Software attributes, Software power, measurement, Software metric, ...

  6. Projective geometry and projective metrics

    CERN Document Server

    Busemann, Herbert

    2005-01-01

    The basic results and methods of projective and non-Euclidean geometry are indispensable for the geometer, and this book--different in content, methods, and point of view from traditional texts--attempts to emphasize that fact. Results of special theorems are discussed in detail only when they are needed to develop a feeling for the subject or when they illustrate a general method. On the other hand, an unusual amount of space is devoted to the discussion of the fundamental concepts of distance, motion, area, and perpendicularity.Topics include the projective plane, polarities and conic sectio

  7. Metrics for border management systems.

    Energy Technology Data Exchange (ETDEWEB)

    Duggan, Ruth Ann

    2009-07-01

    There are as many unique and disparate manifestations of border systems as there are borders to protect. Border Security is a highly complex system analysis problem with global, regional, national, sector, and border element dimensions for land, water, and air domains. The complexity increases with the multiple, and sometimes conflicting, missions for regulating the flow of people and goods across borders, while securing them for national security. These systems include frontier border surveillance, immigration management and customs functions that must operate in a variety of weather, terrain, operational conditions, cultural constraints, and geopolitical contexts. As part of a Laboratory Directed Research and Development Project 08-684 (Year 1), the team developed a reference framework to decompose this complex system into international/regional, national, and border elements levels covering customs, immigration, and border policing functions. This generalized architecture is relevant to both domestic and international borders. As part of year two of this project (09-1204), the team determined relevant relative measures to better understand border management performance. This paper describes those relative metrics and how they can be used to improve border management systems.

  8. The metrics of science and technology

    CERN Document Server

    Geisler, Eliezer

    2000-01-01

    Dr. Geisler's far-reaching, unique book provides an encyclopedic compilation of the key metrics to measure and evaluate the impact of science and technology on academia, industry, and government. Focusing on such items as economic measures, patents, peer review, and other criteria, and supported by an extensive review of the literature, Dr. Geisler gives a thorough analysis of the strengths and weaknesses inherent in metric design, and in the use of the specific metrics he cites. His book has already received prepublication attention, and will prove especially valuable for academics in technology management, engineering, and science policy; industrial R&D executives and policymakers; government science and technology policymakers; and scientists and managers in government research and technology institutions. Geisler maintains that the application of metrics to evaluate science and technology at all levels illustrates the variety of tools we currently possess. Each metric has its own unique strengths and...

  9. Smart Grid Status and Metrics Report Appendices

    Energy Technology Data Exchange (ETDEWEB)

    Balducci, Patrick J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Antonopoulos, Chrissi A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Clements, Samuel L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gorrissen, Willy J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kirkham, Harold [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Ruiz, Kathleen A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Smith, David L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Weimar, Mark R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gardner, Chris [APQC, Houston, TX (United States); Varney, Jeff [APQC, Houston, TX (United States)

    2014-07-01

    A smart grid uses digital power control and communication technology to improve the reliability, security, flexibility, and efficiency of the electric system, from large generation through the delivery systems to electricity consumers and a growing number of distributed generation and storage resources. To convey progress made in achieving the vision of a smart grid, this report uses a set of six characteristics derived from the National Energy Technology Laboratory Modern Grid Strategy. The Smart Grid Status and Metrics Report defines and examines 21 metrics that collectively provide insight into the grid’s capacity to embody these characteristics. This appendix presents papers covering each of the 21 metrics identified in Section 2.1 of the Smart Grid Status and Metrics Report. These metric papers were prepared in advance of the main body of the report and collectively form its informational backbone.

  10. Metrics for Polyphonic Sound Event Detection

    Directory of Open Access Journals (Sweden)

    Annamaria Mesaros

    2016-05-01

    Full Text Available This paper presents and discusses various metrics proposed for evaluation of polyphonic sound event detection systems used in realistic situations where there are typically multiple sound sources active simultaneously. The system output in this case contains overlapping events, marked as multiple sounds detected as being active at the same time. The polyphonic system output requires a suitable procedure for evaluation against a reference. Metrics from neighboring fields such as speech recognition and speaker diarization can be used, but they need to be partially redefined to deal with the overlapping events. We present a review of the most common metrics in the field and the way they are adapted and interpreted in the polyphonic case. We discuss segment-based and event-based definitions of each metric and explain the consequences of instance-based and class-based averaging using a case study. In parallel, we provide a toolbox containing implementations of presented metrics.

  11. Distance Teaching on Bornholm

    DEFF Research Database (Denmark)

    Hansen, Finn J. S.; Clausen, Christian

    2001-01-01

    The case study represents an example of a top-down introduction of distance teaching as part of Danish trials with the introduction of multimedia in education. The study is concerned with the background, aim and context of the trial as well as the role and working of the technology and the organi......The case study represents an example of a top-down introduction of distance teaching as part of Danish trials with the introduction of multimedia in education. The study is concerned with the background, aim and context of the trial as well as the role and working of the technology...

  12. Theoretical Principles of Distance Education.

    Science.gov (United States)

    Keegan, Desmond, Ed.

    This book contains the following papers examining the didactic, academic, analytic, philosophical, and technological underpinnings of distance education: "Introduction"; "Quality and Access in Distance Education: Theoretical Considerations" (D. Randy Garrison); "Theory of Transactional Distance" (Michael G. Moore);…

  13. Fast Computing for Distance Covariance

    OpenAIRE

    Huo, Xiaoming; Szekely, Gabor J.

    2014-01-01

    Distance covariance and distance correlation have been widely adopted in measuring dependence of a pair of random variables or random vectors. If the computation of distance covariance and distance correlation is implemented directly accordingly to its definition then its computational complexity is O($n^2$) which is a disadvantage compared to other faster methods. In this paper we show that the computation of distance covariance and distance correlation of real valued random variables can be...

  14. Robustness Metrics: Consolidating the multiple approaches to quantify Robustness

    DEFF Research Database (Denmark)

    Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.

    2016-01-01

    robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...

  15. Partial rectangular metric spaces and fixed point theorems.

    Science.gov (United States)

    Shukla, Satish

    2014-01-01

    The purpose of this paper is to introduce the concept of partial rectangular metric spaces as a generalization of rectangular metric and partial metric spaces. Some properties of partial rectangular metric spaces and some fixed point results for quasitype contraction in partial rectangular metric spaces are proved. Some examples are given to illustrate the observed results.

  16. Monoparametric family of metrics derived from classical Jensen-Shannon divergence

    Science.gov (United States)

    Osán, Tristán M.; Bussandri, Diego G.; Lamberti, Pedro W.

    2018-04-01

    Jensen-Shannon divergence is a well known multi-purpose measure of dissimilarity between probability distributions. It has been proven that the square root of this quantity is a true metric in the sense that, in addition to the basic properties of a distance, it also satisfies the triangle inequality. In this work we extend this last result to prove that in fact it is possible to derive a monoparametric family of metrics from the classical Jensen-Shannon divergence. Motivated by our results, an application into the field of symbolic sequences segmentation is explored. Additionally, we analyze the possibility to extend this result into the quantum realm.

  17. Measuring Information Security: Guidelines to Build Metrics

    Science.gov (United States)

    von Faber, Eberhard

    Measuring information security is a genuine interest of security managers. With metrics they can develop their security organization's visibility and standing within the enterprise or public authority as a whole. Organizations using information technology need to use security metrics. Despite the clear demands and advantages, security metrics are often poorly developed or ineffective parameters are collected and analysed. This paper describes best practices for the development of security metrics. First attention is drawn to motivation showing both requirements and benefits. The main body of this paper lists things which need to be observed (characteristic of metrics), things which can be measured (how measurements can be conducted) and steps for the development and implementation of metrics (procedures and planning). Analysis and communication is also key when using security metrics. Examples are also given in order to develop a better understanding. The author wants to resume, continue and develop the discussion about a topic which is or increasingly will be a critical factor of success for any security managers in larger organizations.

  18. Characterising risk - aggregated metrics: radiation and noise

    International Nuclear Information System (INIS)

    Passchier, W.

    1998-01-01

    The characterisation of risk is an important phase in the risk assessment - risk management process. From the multitude of risk attributes a few have to be selected to obtain a risk characteristic or profile that is useful for risk management decisions and implementation of protective measures. One way to reduce the number of attributes is aggregation. In the field of radiation protection such an aggregated metric is firmly established: effective dose. For protection against environmental noise the Health Council of the Netherlands recently proposed a set of aggregated metrics for noise annoyance and sleep disturbance. The presentation will discuss similarities and differences between these two metrics and practical limitations. The effective dose has proven its usefulness in designing radiation protection measures, which are related to the level of risk associated with the radiation practice in question, given that implicit judgements on radiation induced health effects are accepted. However, as the metric does not take into account the nature of radiation practice, it is less useful in policy discussions on the benefits and harm of radiation practices. With respect to the noise exposure metric, only one effect is targeted (annoyance), and the differences between sources are explicitly taken into account. This should make the metric useful in policy discussions with respect to physical planning and siting problems. The metric proposed has only significance on a population level, and can not be used as a predictor for individual risk. (author)

  19. 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

  20. Planning with Reachable Distances

    KAUST Repository

    Tang, Xinyu; Thomas, Shawna; Amato, Nancy M.

    2009-01-01

    reachable distance space (RD-space), in which all configurations lie in the set of constraint-satisfying subspaces. This enables us to directly sample the constrained subspaces with complexity linear in the robot's number of degrees of freedom. In addition

  1. De-severing distance

    DEFF Research Database (Denmark)

    Jensen, Hanne Louise; de Neergaard, Maja

    2016-01-01

    De-severing Distance This paper draws on the growing body of mobility literature that shows how mobility can be viewed as meaningful everyday practices (Freudendal –Pedersen 2007, Cresswell 2006) this paper examines how Heidegger’s term de-severing can help us understand the everyday coping with ...

  2. The Euclidean distance degree

    NARCIS (Netherlands)

    Draisma, J.; Horobet, E.; Ottaviani, G.; Sturmfels, B.; Thomas, R.R.; Zhi, L.; Watt, M.

    2014-01-01

    The nearest point map of a real algebraic variety with respect to Euclidean distance is an algebraic function. For instance, for varieties of low rank matrices, the Eckart-Young Theorem states that this map is given by the singular value decomposition. This article develops a theory of such nearest

  3. Electromagnetic distance measurement

    CERN Document Server

    1967-01-01

    This book brings together the work of forty-eight geodesists from twenty-five countries. They discuss various new electromagnetic distance measurement (EDM) instruments - among them the Tellurometer, Geodimeter, and air- and satellite-borne systems - and investigate the complex sources of error.

  4. Determining average yarding distance.

    Science.gov (United States)

    Roger H. Twito; Charles N. Mann

    1979-01-01

    Emphasis on environmental and esthetic quality in timber harvesting has brought about increased use of complex boundaries of cutting units and a consequent need for a rapid and accurate method of determining the average yarding distance and area of these units. These values, needed for evaluation of road and landing locations in planning timber harvests, are easily and...

  5. Prospect of Distance Learning

    Science.gov (United States)

    Rahman, Monsurur; Karim, Reza; Byramjee, Framarz

    2015-01-01

    Many educational institutions in the United States are currently offering programs through distance learning, and that trend is rising. In almost all spheres of education a developing country like Bangladesh needs to make available the expertise of the most qualified faculty to her distant people. But the fundamental question remains as to whether…

  6. 80537 based distance relay

    DEFF Research Database (Denmark)

    Pedersen, Knud Ole Helgesen

    1999-01-01

    A method for implementing a digital distance relay in the power system is described.Instructions are given on how to program this relay on a 80537 based microcomputer system.The problem is used as a practical case study in the course 53113: Micocomputer applications in the power system.The relay...

  7. Effect of Image Linearization on Normalized Compression Distance

    Science.gov (United States)

    Mortensen, Jonathan; Wu, Jia Jie; Furst, Jacob; Rogers, John; Raicu, Daniela

    Normalized Information Distance, based on Kolmogorov complexity, is an emerging metric for image similarity. It is approximated by the Normalized Compression Distance (NCD) which generates the relative distance between two strings by using standard compression algorithms to compare linear strings of information. This relative distance quantifies the degree of similarity between the two objects. NCD has been shown to measure similarity effectively on information which is already a string: genomic string comparisons have created accurate phylogeny trees and NCD has also been used to classify music. Currently, to find a similarity measure using NCD for images, the images must first be linearized into a string, and then compared. To understand how linearization of a 2D image affects the similarity measure, we perform four types of linearization on a subset of the Corel image database and compare each for a variety of image transformations. Our experiment shows that different linearization techniques produce statistically significant differences in NCD for identical spatial transformations.

  8. Statistical distance and the approach to KNO scaling

    International Nuclear Information System (INIS)

    Diosi, L.; Hegyi, S.; Krasznovszky, S.

    1990-05-01

    A new method is proposed for characterizing the approach to KNO scaling. The essence of our method lies in the concept of statistical distance between nearby KNO distributions which reflects their distinguishability in spite of multiplicity fluctuations. It is shown that the geometry induced by the distance function defines a natural metric on the parameter space of a certain family of KNO distributions. Some examples are given in which the energy dependences of distinguishability of neighbouring KNO distributions are compared in nondiffractive hadron-hadron collisions and electron-positron annihilation. (author) 19 refs.; 4 figs

  9. Metrics Are Needed for Collaborative Software Development

    Directory of Open Access Journals (Sweden)

    Mojgan Mohtashami

    2011-10-01

    Full Text Available There is a need for metrics for inter-organizational collaborative software development projects, encompassing management and technical concerns. In particular, metrics are needed that are aimed at the collaborative aspect itself, such as readiness for collaboration, the quality and/or the costs and benefits of collaboration in a specific ongoing project. We suggest questions and directions for such metrics, spanning the full lifespan of a collaborative project, from considering the suitability of collaboration through evaluating ongoing projects to final evaluation of the collaboration.

  10. Indefinite metric fields and the renormalization group

    International Nuclear Information System (INIS)

    Sherry, T.N.

    1976-11-01

    The renormalization group equations are derived for the Green functions of an indefinite metric field theory. In these equations one retains the mass dependence of the coefficient functions, since in the indefinite metric theories the masses cannot be neglected. The behavior of the effective coupling constant in the asymptotic and infrared limits is analyzed. The analysis is illustrated by means of a simple model incorporating indefinite metric fields. The model scales at first order, and at this order also the effective coupling constant has both ultra-violet and infra-red fixed points, the former being the bare coupling constant

  11. Metric learning for DNA microarray data analysis

    International Nuclear Information System (INIS)

    Takeuchi, Ichiro; Nakagawa, Masao; Seto, Masao

    2009-01-01

    In many microarray studies, gene set selection is an important preliminary step for subsequent main task such as tumor classification, cancer subtype identification, etc. In this paper, we investigate the possibility of using metric learning as an alternative to gene set selection. We develop a simple metric learning algorithm aiming to use it for microarray data analysis. Exploiting a property of the algorithm, we introduce a novel approach for extending the metric learning to be adaptive. We apply the algorithm to previously studied microarray data on malignant lymphoma subtype identification.

  12. Software metrics a rigorous and practical approach

    CERN Document Server

    Fenton, Norman

    2014-01-01

    A Framework for Managing, Measuring, and Predicting Attributes of Software Development Products and ProcessesReflecting the immense progress in the development and use of software metrics in the past decades, Software Metrics: A Rigorous and Practical Approach, Third Edition provides an up-to-date, accessible, and comprehensive introduction to software metrics. Like its popular predecessors, this third edition discusses important issues, explains essential concepts, and offers new approaches for tackling long-standing problems.New to the Third EditionThis edition contains new material relevant

  13. Shape anisotropy: tensor distance to anisotropy measure

    Science.gov (United States)

    Weldeselassie, Yonas T.; El-Hilo, Saba; Atkins, M. S.

    2011-03-01

    Fractional anisotropy, defined as the distance of a diffusion tensor from its closest isotropic tensor, has been extensively studied as quantitative anisotropy measure for diffusion tensor magnetic resonance images (DT-MRI). It has been used to reveal the white matter profile of brain images, as guiding feature for seeding and stopping in fiber tractography and for the diagnosis and assessment of degenerative brain diseases. Despite its extensive use in DT-MRI community, however, not much attention has been given to the mathematical correctness of its derivation from diffusion tensors which is achieved using Euclidean dot product in 9D space. But, recent progress in DT-MRI has shown that the space of diffusion tensors does not form a Euclidean vector space and thus Euclidean dot product is not appropriate for tensors. In this paper, we propose a novel and robust rotationally invariant diffusion anisotropy measure derived using the recently proposed Log-Euclidean and J-divergence tensor distance measures. An interesting finding of our work is that given a diffusion tensor, its closest isotropic tensor is different for different tensor distance metrics used. We demonstrate qualitatively that our new anisotropy measure reveals superior white matter profile of DT-MR brain images and analytically show that it has a higher signal to noise ratio than fractional anisotropy.

  14. Fidelity induced distance measures for quantum states

    International Nuclear Information System (INIS)

    Ma Zhihao; Zhang Fulin; Chen Jingling

    2009-01-01

    Fidelity plays an important role in quantum information theory. In this Letter, we introduce new metric of quantum states induced by fidelity, and connect it with the well-known trace metric, Sine metric and Bures metric for the qubit case. The metric character is also presented for the qudit (i.e., d-dimensional system) case. The CPT contractive property and joint convex property of the metric are also studied.

  15. Predicting speech release from masking through spatial separation in distance

    DEFF Research Database (Denmark)

    Chabot-Leclerc, Alexandre; Dau, Torsten

    2014-01-01

    of spatial release from masking (SRM) where the masker is moved, on-axis, away from the target. Two binaural models, which use the conventional audio signal-to-noise ratio (SNR) in the decision metric, and two monaural models, using a decision metric based on the SNR in the envelope domain (SNRenv), were...... considered. The predictions were compared to data from Westermann et al. [2013, POMA, 19, 050156] in condi- tions where the target was located 0.5 m in front of the listener and the masker was presented at a distance of 0.5, 2, 5 or 10 m in front of the listener. The data showed an SRM of 10 dB when moving...... the masker from a distance of 0.5 m to a distance of 10 m. The long-term monaural model based on the SNRenv metric was able to account for most of the SRM data, whereas the models that used the audio SNR did not predict any SRM, even when they included an equalizationcancellation-like process. The short...

  16. [Applicability of traditional landscape metrics in evaluating urban heat island effect].

    Science.gov (United States)

    Chen, Ai-Lian; Sun, Ran-Hao; Chen, Li-Ding

    2012-08-01

    By using 24 landscape metrics, this paper evaluated the urban heat island effect in parts of Beijing downtown area. QuickBird (QB) images were used to extract the landscape type information, and the thermal bands from Landsat Enhanced Thematic Mapper Plus (ETM+) images were used to extract the land surface temperature (LST) in four seasons of the same year. The 24 landscape pattern metrics were calculated at landscape and class levels in a fixed window with 120 mx 120 m in size, with the applicability of these traditional landscape metrics in evaluating the urban heat island effect examined. Among the 24 landscape metrics, only the percentage composition of landscape (PLAND), patch density (PD), largest patch index (LPI), coefficient of Euclidean nearest-neighbor distance variance (ENN_CV), and landscape division index (DIVISION) at landscape level were significantly correlated with the LST in March, May, and November, and the PLAND, LPI, DIVISION, percentage of like adjacencies, and interspersion and juxtaposition index at class level showed significant correlations with the LST in March, May, July, and December, especially in July. Some metrics such as PD, edge density, clumpiness index, patch cohesion index, effective mesh size, splitting index, aggregation index, and normalized landscape shape index showed varying correlations with the LST at different class levels. The traditional landscape metrics could not be appropriate in evaluating the effects of river on LST, while some of the metrics could be useful in characterizing urban LST and analyzing the urban heat island effect, but screening and examining should be made on the metrics.

  17. Metrics, Media and Advertisers: Discussing Relationship

    Directory of Open Access Journals (Sweden)

    Marco Aurelio de Souza Rodrigues

    2014-11-01

    Full Text Available This study investigates how Brazilian advertisers are adapting to new media and its attention metrics. In-depth interviews were conducted with advertisers in 2009 and 2011. In 2009, new media and its metrics were celebrated as innovations that would increase advertising campaigns overall efficiency. In 2011, this perception has changed: New media’s profusion of metrics, once seen as an advantage, started to compromise its ease of use and adoption. Among its findings, this study argues that there is an opportunity for media groups willing to shift from a product-focused strategy towards a customer-centric one, through the creation of new, simple and integrative metrics

  18. Clean Cities Annual Metrics Report 2009 (Revised)

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, C.

    2011-08-01

    Document provides Clean Cities coalition metrics about the use of alternative fuels; the deployment of alternative fuel vehicles, hybrid electric vehicles (HEVs), and idle reduction initiatives; fuel economy activities; and programs to reduce vehicle miles driven.

  19. Metric Guidelines Inservice and/or Preservice

    Science.gov (United States)

    Granito, Dolores

    1978-01-01

    Guidelines are given for designing teacher training for going metric. The guidelines were developed from existing guidelines, journal articles, a survey of colleges, and the detailed reactions of a panel. (MN)

  20. Science and Technology Metrics and Other Thoughts

    National Research Council Canada - National Science Library

    Harman, Wayne; Staton, Robin

    2006-01-01

    This report explores the subject of science and technology metrics and other topics to begin to provide Navy managers, as well as scientists and engineers, additional tools and concepts with which to...

  1. Using Activity Metrics for DEVS Simulation Profiling

    Directory of Open Access Journals (Sweden)

    Muzy A.

    2014-01-01

    Full Text Available Activity metrics can be used to profile DEVS models before and during the simulation. It is critical to get good activity metrics of models before and during their simulation. Having a means to compute a-priori activity of components (analytic activity may be worth when simulating a model (or parts of it for the first time. After, during the simulation, analytic activity can be corrected using dynamic one. In this paper, we introduce McCabe cyclomatic complexity metric (MCA to compute analytic activity. Both static and simulation activity metrics have been implemented through a plug-in of the DEVSimPy (DEVS Simulator in Python language environment and applied to DEVS models.

  2. Evaluating and Estimating the WCET Criticality Metric

    DEFF Research Database (Denmark)

    Jordan, Alexander

    2014-01-01

    a programmer (or compiler) from targeting optimizations the right way. A possible resort is to use a metric that targets WCET and which can be efficiently computed for all code parts of a program. Similar to dynamic profiling techniques, which execute code with input that is typically expected...... for the application, based on WCET analysis we can indicate how critical a code fragment is, in relation to the worst-case bound. Computing such a metric on top of static analysis, incurs a certain overhead though, which increases with the complexity of the underlying WCET analysis. We present our approach...... to estimate the Criticality metric, by relaxing the precision of WCET analysis. Through this, we can reduce analysis time by orders of magnitude, while only introducing minor error. To evaluate our estimation approach and share our garnered experience using the metric, we evaluate real-time programs, which...

  3. 16 CFR 1511.8 - Metric references.

    Science.gov (United States)

    2010-01-01

    ... 16 Commercial Practices 2 2010-01-01 2010-01-01 false Metric references. 1511.8 Section 1511.8 Commercial Practices CONSUMER PRODUCT SAFETY COMMISSION FEDERAL HAZARDOUS SUBSTANCES ACT REGULATIONS... parentheses for convenience and information only. ...

  4. Flight Crew State Monitoring Metrics, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — eSky will develop specific crew state metrics based on the timeliness, tempo and accuracy of pilot inputs required by the H-mode Flight Control System (HFCS)....

  5. Distance between images

    Science.gov (United States)

    Gualtieri, J. A.; Le Moigne, J.; Packer, C. V.

    1992-01-01

    Comparing two binary images and assigning a quantitative measure to this comparison finds its purpose in such tasks as image recognition, image compression, and image browsing. This quantitative measurement may be computed by utilizing the Hausdorff distance of the images represented as two-dimensional point sets. In this paper, we review two algorithms that have been proposed to compute this distance, and we present a parallel implementation of one of them on the MasPar parallel processor. We study their complexity and the results obtained by these algorithms for two different types of images: a set of displaced pairs of images of Gaussian densities, and a comparison of a Canny edge image with several edge images from a hierarchical region growing code.

  6. THE EXTRAGALACTIC DISTANCE DATABASE

    International Nuclear Information System (INIS)

    Tully, R. Brent; Courtois, Helene M.; Jacobs, Bradley A.; Rizzi, Luca; Shaya, Edward J.; Makarov, Dmitry I.

    2009-01-01

    A database can be accessed on the Web at http://edd.ifa.hawaii.edu that was developed to promote access to information related to galaxy distances. The database has three functional components. First, tables from many literature sources have been gathered and enhanced with links through a distinct galaxy naming convention. Second, comparisons of results both at the levels of parameters and of techniques have begun and are continuing, leading to increasing homogeneity and consistency of distance measurements. Third, new material is presented arising from ongoing observational programs at the University of Hawaii 2.2 m telescope, radio telescopes at Green Bank, Arecibo, and Parkes and with the Hubble Space Telescope. This new observational material is made available in tandem with related material drawn from archives and passed through common analysis pipelines.

  7. Classroom reconstruction of the Schwarzschild metric

    OpenAIRE

    Kassner, Klaus

    2015-01-01

    A promising way to introduce general relativity in the classroom is to study the physical implications of certain given metrics, such as the Schwarzschild one. This involves lower mathematical expenditure than an approach focusing on differential geometry in its full glory and permits to emphasize physical aspects before attacking the field equations. Even so, in terms of motivation, lacking justification of the metric employed may pose an obstacle. The paper discusses how to establish the we...

  8. Marketing communication metrics for social media

    OpenAIRE

    Töllinen, Aarne; Karjaluoto, Heikki

    2011-01-01

    The objective of this paper is to develop a conceptual framework for measuring the effectiveness of social media marketing communications. Specifically, we study whether the existing marketing communications performance metrics are still valid in the changing digitalised communications landscape, or whether it is time to rethink them, or even to devise entirely new metrics. Recent advances in information technology and marketing bring a need to re-examine measurement models. We combine two im...

  9. Some observations on a fuzzy metric space

    Energy Technology Data Exchange (ETDEWEB)

    Gregori, V.

    2017-07-01

    Let $(X,d)$ be a metric space. In this paper we provide some observations about the fuzzy metric space in the sense of Kramosil and Michalek $(Y,N,/wedge)$, where $Y$ is the set of non-negative real numbers $[0,/infty[$ and $N(x,y,t)=1$ if $d(x,y)/leq t$ and $N(x,y,t)=0$ if $d(x,y)/geq t$. (Author)

  10. 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

  11. Distance to Cure

    OpenAIRE

    Capachi, Casey

    2013-01-01

    Distance to Cure A three-part television series by Casey Capachi www.distancetocure.com   Abstract   How far would you go for health care? This three-part television series, featuring two introductory segments between each piece, focuses on the physical, cultural, and political obstacles facing rural Native American patients and the potential of health technology to break down those barriers to care.   Part one,Telemedici...

  12. Ultrametric Distance in Syntax

    Directory of Open Access Journals (Sweden)

    Roberts Mark D.

    2015-04-01

    Full Text Available Phrase structure trees have a hierarchical structure. In many subjects, most notably in taxonomy such tree structures have been studied using ultrametrics. Here syntactical hierarchical phrase trees are subject to a similar analysis, which is much simpler as the branching structure is more readily discernible and switched. The ambiguity of which branching height to choose, is resolved by postulating that branching occurs at the lowest height available. An ultrametric produces a measure of the complexity of sentences: presumably the complexity of sentences increases as a language is acquired so that this can be tested. All ultrametric triangles are equilateral or isosceles. Here it is shown that X̅ structure implies that there are no equilateral triangles. Restricting attention to simple syntax a minimum ultrametric distance between lexical categories is calculated. A matrix constructed from this ultrametric distance is shown to be different than the matrix obtained from features. It is shown that the definition of C-COMMAND can be replaced by an equivalent ultrametric definition. The new definition invokes a minimum distance between nodes and this is more aesthetically satisfying than previous varieties of definitions. From the new definition of C-COMMAND follows a new definition of of the central notion in syntax namely GOVERNMENT.

  13. Improved nonlinear fault detection strategy based on the Hellinger distance metric: Plug flow reactor monitoring

    KAUST Repository

    Harrou, Fouzi; Madakyaru, Muddu; Sun, Ying

    2017-01-01

    Fault detection has a vital role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. This paper proposes an innovative multivariate fault detection method that can be used for monitoring

  14. Large Scale Metric Learning for Distance-Based Image Classification on Open Ended Data Sets

    NARCIS (Netherlands)

    Mensink, T.; Verbeek, J.; Perronnin, F.; Csurka, G.; Farinella, G.M.; Battiato, S.; Cipolla, R,

    2013-01-01

    Many real-life large-scale datasets are open-ended and dynamic: new images are continuously added to existing classes, new classes appear over time, and the semantics of existing classes might evolve too. Therefore, we study large-scale image classification methods that can incorporate new classes

  15. Application of the Levenshtein Distance Metric for the Construction of Longitudinal Data Files

    Science.gov (United States)

    Doran, Harold C.; van Wamelen, Paul B.

    2010-01-01

    The analysis of longitudinal data in education is becoming more prevalent given the nature of testing systems constructed for No Child Left Behind Act (NCLB). However, constructing the longitudinal data files remains a significant challenge. Students move into new schools, but in many cases the unique identifiers (ID) that should remain constant…

  16. Relaxed metrics and indistinguishability operators: the relationship

    Energy Technology Data Exchange (ETDEWEB)

    Martin, J.

    2017-07-01

    In 1982, the notion of indistinguishability operator was introduced by E. Trillas in order to fuzzify the crisp notion of equivalence relation (/cite{Trillas}). In the study of such a class of operators, an outstanding property must be pointed out. Concretely, there exists a duality relationship between indistinguishability operators and metrics. The aforesaid relationship was deeply studied by several authors that introduced a few techniques to generate metrics from indistinguishability operators and vice-versa (see, for instance, /cite{BaetsMesiar,BaetsMesiar2}). In the last years a new generalization of the metric notion has been introduced in the literature with the purpose of developing mathematical tools for quantitative models in Computer Science and Artificial Intelligence (/cite{BKMatthews,Ma}). The aforementioned generalized metrics are known as relaxed metrics. The main target of this talk is to present a study of the duality relationship between indistinguishability operators and relaxed metrics in such a way that the aforementioned classical techniques to generate both concepts, one from the other, can be extended to the new framework. (Author)

  17. Improved Iris Recognition through Fusion of Hamming Distance and Fragile Bit Distance.

    Science.gov (United States)

    Hollingsworth, Karen P; Bowyer, Kevin W; Flynn, Patrick J

    2011-12-01

    The most common iris biometric algorithm represents the texture of an iris using a binary iris code. Not all bits in an iris code are equally consistent. A bit is deemed fragile if its value changes across iris codes created from different images of the same iris. Previous research has shown that iris recognition performance can be improved by masking these fragile bits. Rather than ignoring fragile bits completely, we consider what beneficial information can be obtained from the fragile bits. We find that the locations of fragile bits tend to be consistent across different iris codes of the same eye. We present a metric, called the fragile bit distance, which quantitatively measures the coincidence of the fragile bit patterns in two iris codes. We find that score fusion of fragile bit distance and Hamming distance works better for recognition than Hamming distance alone. To our knowledge, this is the first and only work to use the coincidence of fragile bit locations to improve the accuracy of matches.

  18. Baby universe metric equivalent to an interior black-hole metric

    International Nuclear Information System (INIS)

    Gonzalez-Diaz, P.F.

    1991-01-01

    It is shown that the maximally extended metric corresponding to a large wormhole is the unique possible wormhole metric whose baby universe sector is conformally equivalent ot the maximal inextendible Kruskal metric corresponding to the interior region of a Schwarzschild black hole whose gravitational radius is half the wormhole neck radius. The physical implications of this result in the black hole evaporation process are discussed. (orig.)

  19. Prototypic Development and Evaluation of a Medium Format Metric Camera

    Science.gov (United States)

    Hastedt, H.; Rofallski, R.; Luhmann, T.; Rosenbauer, R.; Ochsner, D.; Rieke-Zapp, D.

    2018-05-01

    Engineering applications require high-precision 3D measurement techniques for object sizes that vary between small volumes (2-3 m in each direction) and large volumes (around 20 x 20 x 1-10 m). The requested precision in object space (1σ RMS) is defined to be within 0.1-0.2 mm for large volumes and less than 0.01 mm for small volumes. In particular, focussing large volume applications the availability of a metric camera would have different advantages for several reasons: 1) high-quality optical components and stabilisations allow for a stable interior geometry of the camera itself, 2) a stable geometry leads to a stable interior orientation that enables for an a priori camera calibration, 3) a higher resulting precision can be expected. With this article the development and accuracy evaluation of a new metric camera, the ALPA 12 FPS add|metric will be presented. Its general accuracy potential is tested against calibrated lengths in a small volume test environment based on the German Guideline VDI/VDE 2634.1 (2002). Maximum length measurement errors of less than 0.025 mm are achieved with different scenarios having been tested. The accuracy potential for large volumes is estimated within a feasibility study on the application of photogrammetric measurements for the deformation estimation on a large wooden shipwreck in the German Maritime Museum. An accuracy of 0.2 mm-0.4 mm is reached for a length of 28 m (given by a distance from a lasertracker network measurement). All analyses have proven high stabilities of the interior orientation of the camera and indicate the applicability for a priori camera calibration for subsequent 3D measurements.

  20. PROTOTYPIC DEVELOPMENT AND EVALUATION OF A MEDIUM FORMAT METRIC CAMERA

    Directory of Open Access Journals (Sweden)

    H. Hastedt

    2018-05-01

    Full Text Available Engineering applications require high-precision 3D measurement techniques for object sizes that vary between small volumes (2–3 m in each direction and large volumes (around 20 x 20 x 1–10 m. The requested precision in object space (1σ RMS is defined to be within 0.1–0.2 mm for large volumes and less than 0.01 mm for small volumes. In particular, focussing large volume applications the availability of a metric camera would have different advantages for several reasons: 1 high-quality optical components and stabilisations allow for a stable interior geometry of the camera itself, 2 a stable geometry leads to a stable interior orientation that enables for an a priori camera calibration, 3 a higher resulting precision can be expected. With this article the development and accuracy evaluation of a new metric camera, the ALPA 12 FPS add|metric will be presented. Its general accuracy potential is tested against calibrated lengths in a small volume test environment based on the German Guideline VDI/VDE 2634.1 (2002. Maximum length measurement errors of less than 0.025 mm are achieved with different scenarios having been tested. The accuracy potential for large volumes is estimated within a feasibility study on the application of photogrammetric measurements for the deformation estimation on a large wooden shipwreck in the German Maritime Museum. An accuracy of 0.2 mm–0.4 mm is reached for a length of 28 m (given by a distance from a lasertracker network measurement. All analyses have proven high stabilities of the interior orientation of the camera and indicate the applicability for a priori camera calibration for subsequent 3D measurements.

  1. Development of a perceptually calibrated objective metric of noise

    Science.gov (United States)

    Keelan, Brian W.; Jin, Elaine W.; Prokushkin, Sergey

    2011-01-01

    A system simulation model was used to create scene-dependent noise masks that reflect current performance of mobile phone cameras. Stimuli with different overall magnitudes of noise and with varying mixtures of red, green, blue, and luminance noises were included in the study. Eleven treatments in each of ten pictorial scenes were evaluated by twenty observers using the softcopy ruler method. In addition to determining the quality loss function in just noticeable differences (JNDs) for the average observer and scene, transformations for different combinations of observer sensitivity and scene susceptibility were derived. The psychophysical results were used to optimize an objective metric of isotropic noise based on system noise power spectra (NPS), which were integrated over a visual frequency weighting function to yield perceptually relevant variances and covariances in CIE L*a*b* space. Because the frequency weighting function is expressed in terms of cycles per degree at the retina, it accounts for display pixel size and viewing distance effects, so application-specific predictions can be made. Excellent results were obtained using only L* and a* variances and L*a* covariance, with relative weights of 100, 5, and 12, respectively. The positive a* weight suggests that the luminance (photopic) weighting is slightly narrow on the long wavelength side for predicting perceived noisiness. The L*a* covariance term, which is normally negative, reflects masking between L* and a* noise, as confirmed in informal evaluations. Test targets in linear sRGB and rendered L*a*b* spaces for each treatment are available at http://www.aptina.com/ImArch/ to enable other researchers to test metrics of their own design and calibrate them to JNDs of quality loss without performing additional observer experiments. Such JND-calibrated noise metrics are particularly valuable for comparing the impact of noise and other attributes, and for computing overall image quality.

  2. a tensor theory of gravitation in a curved metric on a flat background

    International Nuclear Information System (INIS)

    Drummond, J.E.

    1979-01-01

    A theory of gravity is proposed using a tensor potential for the field on a flat metric. This potential cannot be isolated by local observations, but some details can be deduced from measurements at a distance. The requirement that the field equations for the tensor potential shall be deducible from an action integral, that the action and field equations are gauge invariant, and, conversely, that the Lagrangian in the action integral can be integrated from the field equations leads to Einstein's field equations. The requirement that the field energy-momentum tensor exists leads to a constraint on the tensor potential. If the constraint is a differential gauge condition, then it can only be the Hilbert condition giving a unique background tensor, metric tensor and tensor potential. For a continuous field inside a solid sphere the metric must be homogeneous in the spatial coordinates, and the associated field energy-momentum tensor has properties consistent with Newtonian dynamics. (author)

  3. Metrical connection in space-time, Newton's and Hubble's laws

    International Nuclear Information System (INIS)

    Maeder, A.

    1978-01-01

    The theory of gravitation in general relativity is not scale invariant. Here, we follow Dirac's proposition of a scale invariant theory of gravitation (i.e. a theory in which the equations keep their form when a transformation of scale is made). We examine some concepts of Weyl's geometry, like the metrical connection, the scale transformations and invariance, and we discuss their consequences for the equation of the geodetic motion and for its Newtonian limit. Under general conditions, we show that the only non-vanishing component of the coefficient of metrical connection may be identified with Hubble's constant. In this framework, the equivalent to the Newtonian approximation for the equation of motion contains an additional acceleration term Hdr vector /dt, which produces an expansion of gravitational systems. The velocity of this expansion is shown to increase linearly with the distance between interacting objects. The relative importance of this new expansion term to the Newtonian one varies like (2rhosub(c)/rho)sup(1/2), where rhosub(c) is the critical density of the Einsteinde Sitter model and rho is the mean density of the considered gravitational configuration. Thus, this 'generalized expansion' is important essentially for systems of mean density not too much above the critical density. Finally, our main conclusion is that in the integrable Weyl geometry, Hubble's law - like Newton's law - would appear as an intrinsic property of gravitation, being only the most visible manifestation of a general effect characterizing the gravitational interaction. (orig.) [de

  4. The dynamics of metric-affine gravity

    International Nuclear Information System (INIS)

    Vitagliano, Vincenzo; Sotiriou, Thomas P.; Liberati, Stefano

    2011-01-01

    Highlights: → The role and the dynamics of the connection in metric-affine theories is explored. → The most general second order action does not lead to a dynamical connection. → Including higher order invariants excites new degrees of freedom in the connection. → f(R) actions are also discussed and shown to be a non- representative class. - Abstract: Metric-affine theories of gravity provide an interesting alternative to general relativity: in such an approach, the metric and the affine (not necessarily symmetric) connection are independent quantities. Furthermore, the action should include covariant derivatives of the matter fields, with the covariant derivative naturally defined using the independent connection. As a result, in metric-affine theories a direct coupling involving matter and connection is also present. The role and the dynamics of the connection in such theories is explored. We employ power counting in order to construct the action and search for the minimal requirements it should satisfy for the connection to be dynamical. We find that for the most general action containing lower order invariants of the curvature and the torsion the independent connection does not carry any dynamics. It actually reduces to the role of an auxiliary field and can be completely eliminated algebraically in favour of the metric and the matter field, introducing extra interactions with respect to general relativity. However, we also show that including higher order terms in the action radically changes this picture and excites new degrees of freedom in the connection, making it (or parts of it) dynamical. Constructing actions that constitute exceptions to this rule requires significant fine tuned and/or extra a priori constraints on the connection. We also consider f(R) actions as a particular example in order to show that they constitute a distinct class of metric-affine theories with special properties, and as such they cannot be used as representative toy

  5. Relativistic distances, sizes, lengths

    International Nuclear Information System (INIS)

    Strel'tsov, V.N.

    1992-01-01

    Such notion as light or retarded distance, field size, formation way, visible size of a body, relativistic or radar length and wave length of light from a moving atom are considered. The relation between these notions is cleared up, their classification is given. It is stressed that the formation way is defined by the field size of a moving particle. In the case of the electromagnetic field, longitudinal sizes increase proportionally γ 2 with growing charge velocity (γ is the Lorentz-factor). 18 refs

  6. A PEG Construction of LDPC Codes Based on the Betweenness Centrality Metric

    Directory of Open Access Journals (Sweden)

    BHURTAH-SEEWOOSUNGKUR, I.

    2016-05-01

    Full Text Available Progressive Edge Growth (PEG constructions are usually based on optimizing the distance metric by using various methods. In this work however, the distance metric is replaced by a different one, namely the betweenness centrality metric, which was shown to enhance routing performance in wireless mesh networks. A new type of PEG construction for Low-Density Parity-Check (LDPC codes is introduced based on the betweenness centrality metric borrowed from social networks terminology given that the bipartite graph describing the LDPC is analogous to a network of nodes. The algorithm is very efficient in filling edges on the bipartite graph by adding its connections in an edge-by-edge manner. The smallest graph size the new code could construct surpasses those obtained from a modified PEG algorithm - the RandPEG algorithm. To the best of the authors' knowledge, this paper produces the best regular LDPC column-weight two graphs. In addition, the technique proves to be competitive in terms of error-correcting performance. When compared to MacKay, PEG and other recent modified-PEG codes, the algorithm gives better performance over high SNR due to its particular edge and local graph properties.

  7. PERBANDINGAN EUCLIDEAN DISTANCE DENGAN CANBERRA DISTANCE PADA FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    Sendhy Rachmat Wurdianarto

    2014-08-01

    Full Text Available Perkembangan ilmu pada dunia komputer sangatlah pesat. Salah satu yang menandai hal ini adalah ilmu komputer telah merambah pada dunia biometrik. Arti biometrik sendiri adalah karakter-karakter manusia yang dapat digunakan untuk membedakan antara orang yang satu dengan yang lainnya. Salah satu pemanfaatan karakter / organ tubuh pada setiap manusia yang digunakan untuk identifikasi (pengenalan adalah dengan memanfaatkan wajah. Dari permasalahan diatas dalam pengenalan lebih tentang aplikasi Matlab pada Face Recognation menggunakan metode Euclidean Distance dan Canberra Distance. Model pengembangan aplikasi yang digunakan adalah model waterfall. Model waterfall beriisi rangkaian aktivitas proses yang disajikan dalam proses analisa kebutuhan, desain menggunakan UML (Unified Modeling Language, inputan objek gambar diproses menggunakan Euclidean Distance dan Canberra Distance. Kesimpulan yang dapat ditarik adalah aplikasi face Recognation menggunakan metode euclidean Distance dan Canverra Distance terdapat kelebihan dan kekurangan masing-masing. Untuk kedepannya aplikasi tersebut dapat dikembangkan dengan menggunakan objek berupa video ataupun objek lainnya.   Kata kunci : Euclidean Distance, Face Recognition, Biometrik, Canberra Distance

  8. Distance collaborations with industry

    Energy Technology Data Exchange (ETDEWEB)

    Peskin, A.; Swyler, K.

    1998-06-01

    The college industry relationship has been identified as a key policy issue in Engineering Education. Collaborations between academic institutions and the industrial sector have a long history and a bright future. For Engineering and Engineering Technology programs in particular, industry has played a crucial role in many areas including advisement, financial support, and practical training of both faculty and students. Among the most important and intimate interactions are collaborative projects and formal cooperative education arrangements. Most recently, such collaborations have taken on a new dimension, as advances in technology have made possible meaningful technical collaboration at a distance. There are several obvious technology areas that have contributed significantly to this trend. Foremost is the ubiquitous presence of the Internet. Perhaps almost as important are advances in computer based imaging. Because visual images offer a compelling user experience, it affords greater knowledge transfer efficiency than other modes of delivery. Furthermore, the quality of the image appears to have a strongly correlated effect on insight. A good visualization facility offers both a means for communication and a shared information space for the subjects, which are among the essential features of both peer collaboration and distance learning.

  9. Evaluation metrics for biostatistical and epidemiological collaborations.

    Science.gov (United States)

    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.

  10. Future of the PCI Readmission Metric.

    Science.gov (United States)

    Wasfy, Jason H; Yeh, Robert W

    2016-03-01

    Between 2013 and 2014, the Centers for Medicare and Medicaid Services and the National Cardiovascular Data Registry publically reported risk-adjusted 30-day readmission rates after percutaneous coronary intervention (PCI) as a pilot project. A key strength of this public reporting effort included risk adjustment with clinical rather than administrative data. Furthermore, because readmission after PCI is common, expensive, and preventable, this metric has substantial potential to improve quality and value in American cardiology care. Despite this, concerns about the metric exist. For example, few PCI readmissions are caused by procedural complications, limiting the extent to which improved procedural technique can reduce readmissions. Also, similar to other readmission measures, PCI readmission is associated with socioeconomic status and race. Accordingly, the metric may unfairly penalize hospitals that care for underserved patients. Perhaps in the context of these limitations, Centers for Medicare and Medicaid Services has not yet included PCI readmission among metrics that determine Medicare financial penalties. Nevertheless, provider organizations may still wish to focus on this metric to improve value for cardiology patients. PCI readmission is associated with low-risk chest discomfort and patient anxiety. Therefore, patient education, improved triage mechanisms, and improved care coordination offer opportunities to minimize PCI readmissions. Because PCI readmission is common and costly, reducing PCI readmission offers provider organizations a compelling target to improve the quality of care, and also performance in contracts involve shared financial risk. © 2016 American Heart Association, Inc.

  11. A Feeling for Numbers: Shared Metric for Symbolic and Tactile Numerosities

    Directory of Open Access Journals (Sweden)

    Florian eKrause

    2013-01-01

    Full Text Available Evidence for an approximate analogue system of numbers has been provided by the finding that the comparison of two numerals takes longer and is more error prone if the semantic distance between the numbers becomes smaller (so-called numerical distance effect. Recent embodied theories suggest that analogue number representations are based on previous sensory experiences and constitute therefore a common magnitude metric shared by multiple domains. Here we demonstrate the existence of a cross-modal semantic distance effect between symbolic and tactile numerosities. Participants received tactile stimulations of different amounts of fingers while reading Arabic digits and indicated verbally whether the amount of stimulated fingers was different from the simultaneously presented digit or not. The larger the semantic distance was between the two numerosities, the faster and more accurate participants made their judgements. This cross-modal numerosity distance effect suggests a direct connection between tactile sensations and the concept of numerical magnitude. A second experiment replicated the interaction between symbolic and tactile numerosities and showed that this effect is not modulated by the participants' finger counting habits. Taken together, our data provide novel evidence for a shared metric for symbolic and tactile numerosites as an instance of an embodied representation of numbers.

  12. g-Weak Contraction in Ordered Cone Rectangular Metric Spaces

    Directory of Open Access Journals (Sweden)

    S. K. Malhotra

    2013-01-01

    Full Text Available We prove some common fixed-point theorems for the ordered g-weak contractions in cone rectangular metric spaces without assuming the normality of cone. Our results generalize some recent results from cone metric and cone rectangular metric spaces into ordered cone rectangular metric spaces. Examples are provided which illustrate the results.

  13. Defining a Progress Metric for CERT RMM Improvement

    Science.gov (United States)

    2017-09-14

    REV-03.18.2016.0 Defining a Progress Metric for CERT-RMM Improvement Gregory Crabb Nader Mehravari David Tobar September 2017 TECHNICAL ...fendable resource allocation decisions. Technical metrics measure aspects of controls implemented through technology (systems, soft- ware, hardware...implementation metric would be the percentage of users who have received anti-phishing training . • Effectiveness/efficiency metrics measure whether

  14. NASA education briefs for the classroom. Metrics in space

    Science.gov (United States)

    The use of metric measurement in space is summarized for classroom use. Advantages of the metric system over the English measurement system are described. Some common metric units are defined, as are special units for astronomical study. International system unit prefixes and a conversion table of metric/English units are presented. Questions and activities for the classroom are recommended.

  15. SOCIAL METRICS APPLIED TO SMART TOURISM

    Directory of Open Access Journals (Sweden)

    O. Cervantes

    2016-09-01

    Full Text Available We present a strategy to make productive use of semantically-related social data, from a user-centered semantic network, in order to help users (tourists and citizens in general to discover cultural heritage, points of interest and available services in a smart city. This data can be used to personalize recommendations in a smart tourism application. Our approach is based on flow centrality metrics typically used in social network analysis: flow betweenness, flow closeness and eccentricity. These metrics are useful to discover relevant nodes within the network yielding nodes that can be interpreted as suggestions (venues or services to users. We describe the semantic network built on graph model, as well as social metrics algorithms used to produce recommendations. We also present challenges and results from a prototypical implementation applied to the case study of the City of Puebla, Mexico.

  16. Landscape pattern metrics and regional assessment

    Science.gov (United States)

    O'Neill, R. V.; Riitters, K.H.; Wickham, J.D.; Jones, K.B.

    1999-01-01

    The combination of remote imagery data, geographic information systems software, and landscape ecology theory provides a unique basis for monitoring and assessing large-scale ecological systems. The unique feature of the work has been the need to develop and interpret quantitative measures of spatial pattern-the landscape indices. This article reviews what is known about the statistical properties of these pattern metrics and suggests some additional metrics based on island biogeography, percolation theory, hierarchy theory, and economic geography. Assessment applications of this approach have required interpreting the pattern metrics in terms of specific environmental endpoints, such as wildlife and water quality, and research into how to represent synergystic effects of many overlapping sources of stress.

  17. A bi-metric theory of gravitation

    International Nuclear Information System (INIS)

    Rosen, N.

    1975-01-01

    The bi-metric theory of gravitation proposed previously is simplified in that the auxiliary conditions are discarded, the two metric tensors being tied together only by means of the boundary conditions. Some of the properties of the field of a particle are investigated; there is no black hole, and it appears that no gravitational collapse can take place. Although the proposed theory and general relativity are at present observationally indistinguishable, some differences are pointed out which may some day be susceptible of observation. An alternative bi-metric theory is considered which gives for the precession of the perihelion 5/6 of the value given by general relativity; it seems less satisfactory than the present theory from the aesthetic point of view. (author)

  18. Steiner trees for fixed orientation metrics

    DEFF Research Database (Denmark)

    Brazil, Marcus; Zachariasen, Martin

    2009-01-01

    We consider the problem of constructing Steiner minimum trees for a metric defined by a polygonal unit circle (corresponding to s = 2 weighted legal orientations in the plane). A linear-time algorithm to enumerate all angle configurations for degree three Steiner points is given. We provide...... a simple proof that the angle configuration for a Steiner point extends to all Steiner points in a full Steiner minimum tree, such that at most six orientations suffice for edges in a full Steiner minimum tree. We show that the concept of canonical forms originally introduced for the uniform orientation...... metric generalises to the fixed orientation metric. Finally, we give an O(s n) time algorithm to compute a Steiner minimum tree for a given full Steiner topology with n terminal leaves....

  19. Metrical and dynamical aspects in complex analysis

    CERN Document Server

    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.

  20. Social Metrics Applied to Smart Tourism

    Science.gov (United States)

    Cervantes, O.; Gutiérrez, E.; Gutiérrez, F.; Sánchez, J. A.

    2016-09-01

    We present a strategy to make productive use of semantically-related social data, from a user-centered semantic network, in order to help users (tourists and citizens in general) to discover cultural heritage, points of interest and available services in a smart city. This data can be used to personalize recommendations in a smart tourism application. Our approach is based on flow centrality metrics typically used in social network analysis: flow betweenness, flow closeness and eccentricity. These metrics are useful to discover relevant nodes within the network yielding nodes that can be interpreted as suggestions (venues or services) to users. We describe the semantic network built on graph model, as well as social metrics algorithms used to produce recommendations. We also present challenges and results from a prototypical implementation applied to the case study of the City of Puebla, Mexico.

  1. Validation of Metrics as Error Predictors

    Science.gov (United States)

    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.

  2. Kerr metric in the deSitter background

    International Nuclear Information System (INIS)

    Vaidya, P.C.

    1984-01-01

    In addition to the Kerr metric with cosmological constant Λ several other metrics are presented giving a Kerr-like solution of Einstein's equations in the background of deSitter universe. A new metric of what may be termed as rotating deSitter space-time devoid of matter but containing null fluid with twisting null rays, has been presented. This metric reduces to the standard deSitter metric when the twist in the rays vanishes. Kerr metric in this background is the immediate generalization of Schwarzschild's exterior metric with cosmological constant. (author)

  3. MEDOF - MINIMUM EUCLIDEAN DISTANCE OPTIMAL FILTER

    Science.gov (United States)

    Barton, R. S.

    1994-01-01

    The Minimum Euclidean Distance Optimal Filter program, MEDOF, generates filters for use in optical correlators. The algorithm implemented in MEDOF follows theory put forth by Richard D. Juday of NASA/JSC. This program analytically optimizes filters on arbitrary spatial light modulators such as coupled, binary, full complex, and fractional 2pi phase. MEDOF optimizes these modulators on a number of metrics including: correlation peak intensity at the origin for the centered appearance of the reference image in the input plane, signal to noise ratio including the correlation detector noise as well as the colored additive input noise, peak to correlation energy defined as the fraction of the signal energy passed by the filter that shows up in the correlation spot, and the peak to total energy which is a generalization of PCE that adds the passed colored input noise to the input image's passed energy. The user of MEDOF supplies the functions that describe the following quantities: 1) the reference signal, 2) the realizable complex encodings of both the input and filter SLM, 3) the noise model, possibly colored, as it adds at the reference image and at the correlation detection plane, and 4) the metric to analyze, here taken to be one of the analytical ones like SNR (signal to noise ratio) or PCE (peak to correlation energy) rather than peak to secondary ratio. MEDOF calculates filters for arbitrary modulators and a wide range of metrics as described above. MEDOF examines the statistics of the encoded input image's noise (if SNR or PCE is selected) and the filter SLM's (Spatial Light Modulator) available values. These statistics are used as the basis of a range for searching for the magnitude and phase of k, a pragmatically based complex constant for computing the filter transmittance from the electric field. The filter is produced for the mesh points in those ranges and the value of the metric that results from these points is computed. When the search is concluded, the

  4. Heuristic extension of the Schwarzschild metric

    International Nuclear Information System (INIS)

    Espinosa, J.M.

    1982-01-01

    The Schwarzschild solution of Einstein's equations of gravitation has several singularities. It is known that the singularity at r = 2Gm/c 2 is only apparent, a result of the coordinates in which the solution was found. Paradoxical results occuring near the singularity show the system of coordinates is incomplete. We introduce a simple, two-dimensional metric with an apparent singularity that makes it incomplete. By a straightforward, heuristic procedure we extend and complete this simple metric. We then use the same procedure to give a heuristic derivation of the Kruskal system of coordinates, which is known to extend the Schwarzschild manifold past its apparent singularity and produce a complete manifold

  5. 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...

  6. 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...

  7. Jacobi-Maupertuis metric and Kepler equation

    Science.gov (United States)

    Chanda, Sumanto; Gibbons, Gary William; Guha, Partha

    This paper studies the application of the Jacobi-Eisenhart lift, Jacobi metric and Maupertuis transformation to the Kepler system. We start by reviewing fundamentals and the Jacobi metric. Then we study various ways to apply the lift to Kepler-related systems: first as conformal description and Bohlin transformation of Hooke’s oscillator, second in contact geometry and third in Houri’s transformation [T. Houri, Liouville integrability of Hamiltonian systems and spacetime symmetry (2016), www.geocities.jp/football_physician/publication.html], coupled with Milnor’s construction [J. Milnor, On the geometry of the Kepler problem, Am. Math. Mon. 90 (1983) 353-365] with eccentric anomaly.

  8. Interactive Distance Learning in Connecticut.

    Science.gov (United States)

    Pietras, Jesse John; Murphy, Robert J.

    This paper provides an overview of distance learning activities in Connecticut and addresses the feasibility of such activities. Distance education programs have evolved from the one dimensional electronic mail systems to the use of sophisticated digital fiber networks. The Middlesex Distance Learning Consortium has developed a long-range plan to…

  9. Distance covariance for stochastic processes

    DEFF Research Database (Denmark)

    Matsui, Muneya; Mikosch, Thomas Valentin; Samorodnitsky, Gennady

    2017-01-01

    The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes...

  10. Distance-Based Phylogenetic Methods Around a Polytomy.

    Science.gov (United States)

    Davidson, Ruth; Sullivant, Seth

    2014-01-01

    Distance-based phylogenetic algorithms attempt to solve the NP-hard least-squares phylogeny problem by mapping an arbitrary dissimilarity map representing biological data to a tree metric. The set of all dissimilarity maps is a Euclidean space properly containing the space of all tree metrics as a polyhedral fan. Outputs of distance-based tree reconstruction algorithms such as UPGMA and neighbor-joining are points in the maximal cones in the fan. Tree metrics with polytomies lie at the intersections of maximal cones. A phylogenetic algorithm divides the space of all dissimilarity maps into regions based upon which combinatorial tree is reconstructed by the algorithm. Comparison of phylogenetic methods can be done by comparing the geometry of these regions. We use polyhedral geometry to compare the local nature of the subdivisions induced by least-squares phylogeny, UPGMA, and neighbor-joining when the true tree has a single polytomy with exactly four neighbors. Our results suggest that in some circumstances, UPGMA and neighbor-joining poorly match least-squares phylogeny.

  11. DISTANCES TO DARK CLOUDS: COMPARING EXTINCTION DISTANCES TO MASER PARALLAX DISTANCES

    International Nuclear Information System (INIS)

    Foster, Jonathan B.; Jackson, James M.; Stead, Joseph J.; Hoare, Melvin G.; Benjamin, Robert A.

    2012-01-01

    We test two different methods of using near-infrared extinction to estimate distances to dark clouds in the first quadrant of the Galaxy using large near-infrared (Two Micron All Sky Survey and UKIRT Infrared Deep Sky Survey) surveys. Very long baseline interferometry parallax measurements of masers around massive young stars provide the most direct and bias-free measurement of the distance to these dark clouds. We compare the extinction distance estimates to these maser parallax distances. We also compare these distances to kinematic distances, including recent re-calibrations of the Galactic rotation curve. The extinction distance methods agree with the maser parallax distances (within the errors) between 66% and 100% of the time (depending on method and input survey) and between 85% and 100% of the time outside of the crowded Galactic center. Although the sample size is small, extinction distance methods reproduce maser parallax distances better than kinematic distances; furthermore, extinction distance methods do not suffer from the kinematic distance ambiguity. This validation gives us confidence that these extinction methods may be extended to additional dark clouds where maser parallaxes are not available.

  12. PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances

    OpenAIRE

    Tang, Zheng-Zheng; Chen, Guanhua; Alekseyenko, Alexander V.

    2016-01-01

    Motivation: Recent advances in sequencing technology have made it possible to obtain high-throughput data on the composition of microbial communities and to study the effects of dysbiosis on the human host. Analysis of pairwise intersample distances quantifies the association between the microbiome diversity and covariates of interest (e.g. environmental factors, clinical outcomes, treatment groups). In the design of these analyses, multiple choices for distance metrics are available. Most di...

  13. Stochastic Learning of Multi-Instance Dictionary for Earth Mover's Distance based Histogram Comparison

    OpenAIRE

    Fan, Jihong; Liang, Ru-Ze

    2016-01-01

    Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover's distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stoc...

  14. Quantitative properties of the Schwarzschild metric

    Czech Academy of Sciences Publication Activity Database

    Křížek, Michal; Křížek, Filip

    2018-01-01

    Roč. 2018, č. 1 (2018), s. 1-10 Institutional support: RVO:67985840 Keywords : exterior and interior Schwarzschild metric * proper radius * coordinate radius Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics http://astro.shu-bg.net/pasb/index_files/Papers/2018/SCHWARZ8.pdf

  15. Strong Ideal Convergence in Probabilistic Metric Spaces

    Indian Academy of Sciences (India)

    In the present paper we introduce the concepts of strongly ideal convergent sequence and strong ideal Cauchy sequence in a probabilistic metric (PM) space endowed with the strong topology, and establish some basic facts. Next, we define the strong ideal limit points and the strong ideal cluster points of a sequence in this ...

  16. lakemorpho: Calculating lake morphometry metrics in R.

    Science.gov (United States)

    Hollister, Jeffrey; Stachelek, Joseph

    2017-01-01

    Metrics describing the shape and size of lakes, known as lake morphometry metrics, are important for any limnological study. In cases where a lake has long been the subject of study these data are often already collected and are openly available. Many other lakes have these data collected, but access is challenging as it is often stored on individual computers (or worse, in filing cabinets) and is available only to the primary investigators. The vast majority of lakes fall into a third category in which the data are not available. This makes broad scale modelling of lake ecology a challenge as some of the key information about in-lake processes are unavailable. While this valuable in situ information may be difficult to obtain, several national datasets exist that may be used to model and estimate lake morphometry. In particular, digital elevation models and hydrography have been shown to be predictive of several lake morphometry metrics. The R package lakemorpho has been developed to utilize these data and estimate the following morphometry metrics: surface area, shoreline length, major axis length, minor axis length, major and minor axis length ratio, shoreline development, maximum depth, mean depth, volume, maximum lake length, mean lake width, maximum lake width, and fetch. In this software tool article we describe the motivation behind developing lakemorpho , discuss the implementation in R, and describe the use of lakemorpho with an example of a typical use case.

  17. Contraction theorems in fuzzy metric space

    International Nuclear Information System (INIS)

    Farnoosh, R.; Aghajani, A.; Azhdari, P.

    2009-01-01

    In this paper, the results on fuzzy contractive mapping proposed by Dorel Mihet will be proved for B-contraction and C-contraction in the case of George and Veeramani fuzzy metric space. The existence of fixed point with weaker conditions will be proved; that is, instead of the convergence of subsequence, p-convergence of subsequence is used.

  18. DIGITAL MARKETING: SUCCESS METRICS, FUTURE TRENDS

    OpenAIRE

    Preeti Kaushik

    2017-01-01

    Abstract – Business Marketing is one of the prospective which has been tremendously affected by digital world in last few years. Digital marketing refers to doing advertising through digital channels. This paper provides detailed study of metrics to measure success of digital marketing platform and glimpse of future of technologies by 2020.

  19. 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.

  20. Metric propositional neighborhood logics on natural numbers

    DEFF Research Database (Denmark)

    Bresolin, Davide; Della Monica, Dario; Goranko, Valentin

    2013-01-01

    Metric Propositional Neighborhood Logic (MPNL) over natural numbers. MPNL features two modalities referring, respectively, to an interval that is “met by” the current one and to an interval that “meets” the current one, plus an infinite set of length constraints, regarded as atomic propositions...

  1. Calabi–Yau metrics and string compactification

    Directory of Open Access Journals (Sweden)

    Michael R. Douglas

    2015-09-01

    Full Text Available Yau proved an existence theorem for Ricci-flat Kähler metrics in the 1970s, but we still have no closed form expressions for them. Nevertheless there are several ways to get approximate expressions, both numerical and analytical. We survey some of this work and explain how it can be used to obtain physical predictions from superstring theory.

  2. Goedel-type metrics in various dimensions

    International Nuclear Information System (INIS)

    Guerses, Metin; Karasu, Atalay; Sarioglu, Oezguer

    2005-01-01

    Goedel-type metrics are introduced and used in producing charged dust solutions in various dimensions. The key ingredient is a (D - 1)-dimensional Riemannian geometry which is then employed in constructing solutions to the Einstein-Maxwell field equations with a dust distribution in D dimensions. The only essential field equation in the procedure turns out to be the source-free Maxwell's equation in the relevant background. Similarly the geodesics of this type of metric are described by the Lorentz force equation for a charged particle in the lower dimensional geometry. It is explicitly shown with several examples that Goedel-type metrics can be used in obtaining exact solutions to various supergravity theories and in constructing spacetimes that contain both closed timelike and closed null curves and that contain neither of these. Among the solutions that can be established using non-flat backgrounds, such as the Tangherlini metrics in (D - 1)-dimensions, there exists a class which can be interpreted as describing black-hole-type objects in a Goedel-like universe

  3. Strong Statistical Convergence in Probabilistic Metric Spaces

    OpenAIRE

    Şençimen, Celaleddin; Pehlivan, Serpil

    2008-01-01

    In this article, we introduce the concepts of strongly statistically convergent sequence and strong statistically Cauchy sequence in a probabilistic metric (PM) space endowed with the strong topology, and establish some basic facts. Next, we define the strong statistical limit points and the strong statistical cluster points of a sequence in this space and investigate the relations between these concepts.

  4. Language Games: University Responses to Ranking Metrics

    Science.gov (United States)

    Heffernan, Troy A.; Heffernan, Amanda

    2018-01-01

    League tables of universities that measure performance in various ways are now commonplace, with numerous bodies providing their own rankings of how institutions throughout the world are seen to be performing on a range of metrics. This paper uses Lyotard's notion of language games to theorise that universities are regaining some power over being…

  5. A new universal colour image fidelity metric

    NARCIS (Netherlands)

    Toet, A.; Lucassen, M.P.

    2003-01-01

    We extend a recently introduced universal grayscale image quality index to a newly developed perceptually decorrelated colour space. The resulting colour image fidelity metric quantifies the distortion of a processed colour image relative to its original version. We evaluated the new colour image

  6. Standardised metrics for global surgical surveillance.

    Science.gov (United States)

    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.

  7. A Lagrangian-dependent metric space

    International Nuclear Information System (INIS)

    El-Tahir, A.

    1989-08-01

    A generalized Lagrangian-dependent metric of the static isotropic spacetime is derived. Its behaviour should be governed by imposing physical constraints allowing to avert the pathological features of gravity at the strong field domain. This would restrict the choice of the Lagrangian form. (author). 10 refs

  8. Clean Cities 2011 Annual Metrics Report

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, C.

    2012-12-01

    This report details the petroleum savings and vehicle emissions reductions achieved by the U.S. Department of Energy's Clean Cities program in 2011. The report also details other performance metrics, including the number of stakeholders in Clean Cities coalitions, outreach activities by coalitions and national laboratories, and alternative fuel vehicles deployed.

  9. Clean Cities 2010 Annual Metrics Report

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, C.

    2012-10-01

    This report details the petroleum savings and vehicle emissions reductions achieved by the U.S. Department of Energy's Clean Cities program in 2010. The report also details other performance metrics, including the number of stakeholders in Clean Cities coalitions, outreach activities by coalitions and national laboratories, and alternative fuel vehicles deployed.

  10. Genetic basis of a cognitive complexity metric

    NARCIS (Netherlands)

    Hansell, Narelle K; Halford, Graeme S; Andrews, Glenda; Shum, David H K; Harris, Sarah E; Davies, Gail; Franic, Sanja; Christoforou, Andrea; Zietsch, Brendan; Painter, Jodie; Medland, Sarah E; Ehli, Erik A; Davies, Gareth E; Steen, Vidar M; Lundervold, Astri J; Reinvang, Ivar; Montgomery, Grant W; Espeseth, Thomas; Hulshoff Pol, Hilleke E; Starr, John M; Martin, Nicholas G; Le Hellard, Stephanie; Boomsma, Dorret I; Deary, Ian J; Wright, Margaret J

    2015-01-01

    Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using

  11. Genetic Basis of a Cognitive Complexity Metric

    NARCIS (Netherlands)

    Hansell, N.K.; Halford, G.S.; Andrews, G.; Shum, D.H.K.; Harris, S.E.; Davies, G.; Franic, S.; Christoforou, A.; Zietsch, B.; Painter, J.; Medland, S.E.; Ehli, E.A.; Davies, G.E.; Steen, V.M.; Lundervold, A.J.; Reinvang, I.; Montgomery, G.W.; Espeseth, T.; Hulshoff Pol, H.E.; Starr, J.M.; Martin, N.G.; Le Hellard, S.; Boomsma, D.I.; Deary, I.J.; Wright, M.J.

    2015-01-01

    Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using

  12. Business model metrics : An open repository

    NARCIS (Netherlands)

    Heikkila, M.; Bouwman, W.A.G.A.; Heikkila, J.; Solaimani, S.; Janssen, W.

    2015-01-01

    Development of successful business models has become a necessity in turbulent business environments, but compared to research on business modeling tools, attention to the role of metrics in designing business models in literature is limited. Building on existing approaches to business models and

  13. Software quality metrics aggregation in industry

    NARCIS (Netherlands)

    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

  14. Invariance group of the Finster metric function

    International Nuclear Information System (INIS)

    Asanov, G.S.

    1985-01-01

    An invariance group of the Finsler metric function is introduced and studied that directly generalized the respective concept (a group of Euclidean rolations) of the Rieman geometry. A sequential description of the isotopic invariance of physical fields on the base of the Finsler geometry is possible in terms of this group

  15. 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.

  16. Site-to-Source Finite Fault Distance Probability Distribution in Probabilistic Seismic Hazard and the Relationship Between Minimum Distances

    Science.gov (United States)

    Ortega, R.; Gutierrez, E.; Carciumaru, D. D.; Huesca-Perez, E.

    2017-12-01

    We present a method to compute the conditional and no-conditional probability density function (PDF) of the finite fault distance distribution (FFDD). Two cases are described: lines and areas. The case of lines has a simple analytical solution while, in the case of areas, the geometrical probability of a fault based on the strike, dip, and fault segment vertices is obtained using the projection of spheres in a piecewise rectangular surface. The cumulative distribution is computed by measuring the projection of a sphere of radius r in an effective area using an algorithm that estimates the area of a circle within a rectangle. In addition, we introduce the finite fault distance metrics. This distance is the distance where the maximum stress release occurs within the fault plane and generates a peak ground motion. Later, we can apply the appropriate ground motion prediction equations (GMPE) for PSHA. The conditional probability of distance given magnitude is also presented using different scaling laws. A simple model of constant distribution of the centroid at the geometrical mean is discussed, in this model hazard is reduced at the edges because the effective size is reduced. Nowadays there is a trend of using extended source distances in PSHA, however it is not possible to separate the fault geometry from the GMPE. With this new approach, it is possible to add fault rupture models separating geometrical and propagation effects.

  17. Planning with Reachable Distances

    KAUST Repository

    Tang, Xinyu

    2009-01-01

    Motion planning for spatially constrained robots is difficult due to additional constraints placed on the robot, such as closure constraints for closed chains or requirements on end effector placement for articulated linkages. It is usually computationally too expensive to apply sampling-based planners to these problems since it is difficult to generate valid configurations. We overcome this challenge by redefining the robot\\'s degrees of freedom and constraints into a new set of parameters, called reachable distance space (RD-space), in which all configurations lie in the set of constraint-satisfying subspaces. This enables us to directly sample the constrained subspaces with complexity linear in the robot\\'s number of degrees of freedom. In addition to supporting efficient sampling, we show that the RD-space formulation naturally supports planning, and in particular, we design a local planner suitable for use by sampling-based planners. We demonstrate the effectiveness and efficiency of our approach for several systems including closed chain planning with multiple loops, restricted end effector sampling, and on-line planning for drawing/sculpting. We can sample single-loop closed chain systems with 1000 links in time comparable to open chain sampling, and we can generate samples for 1000-link multi-loop systems of varying topology in less than a second. © 2009 Springer-Verlag.

  18. The Graph, Geometry and Symmetries of the Genetic Code with Hamming Metric

    Directory of Open Access Journals (Sweden)

    Reijer Lenstra

    2015-07-01

    Full Text Available The similarity patterns of the genetic code result from similar codons encoding similar messages. We develop a new mathematical model to analyze these patterns. The physicochemical characteristics of amino acids objectively quantify their differences and similarities; the Hamming metric does the same for the 64 codons of the codon set. (Hamming distances equal the number of different codon positions: AAA and AAC are at 1-distance; codons are maximally at 3-distance. The CodonPolytope, a 9-dimensional geometric object, is spanned by 64 vertices that represent the codons and the Euclidian distances between these vertices correspond one-to-one with intercodon Hamming distances. The CodonGraph represents the vertices and edges of the polytope; each edge equals a Hamming 1-distance. The mirror reflection symmetry group of the polytope is isomorphic to the largest permutation symmetry group of the codon set that preserves Hamming distances. These groups contain 82,944 symmetries. Many polytope symmetries coincide with the degeneracy and similarity patterns of the genetic code. These code symmetries are strongly related with the face structure of the polytope with smaller faces displaying stronger code symmetries. Splitting the polytope stepwise into smaller faces models an early evolution of the code that generates this hierarchy of code symmetries. The canonical code represents a class of 41,472 codes with equivalent symmetries; a single class among an astronomical number of symmetry classes comprising all possible codes.

  19. Observable traces of non-metricity: New constraints on metric-affine gravity

    Science.gov (United States)

    Delhom-Latorre, Adrià; Olmo, Gonzalo J.; Ronco, Michele

    2018-05-01

    Relaxing the Riemannian condition to incorporate geometric quantities such as torsion and non-metricity may allow to explore new physics associated with defects in a hypothetical space-time microstructure. Here we show that non-metricity produces observable effects in quantum fields in the form of 4-fermion contact interactions, thereby allowing us to constrain the scale of non-metricity to be greater than 1 TeV by using results on Bahbah scattering. Our analysis is carried out in the framework of a wide class of theories of gravity in the metric-affine approach. The bound obtained represents an improvement of several orders of magnitude to previous experimental constraints.

  20. Conformal and related changes of metric on the product of two almost contact metric manifolds.

    OpenAIRE

    Blair, D. E.

    1990-01-01

    This paper studies conformal and related changes of the product metric on the product of two almost contact metric manifolds. It is shown that if one factor is Sasakian, the other is not, but that locally the second factor is of the type studied by Kenmotsu. The results are more general and given in terms of trans-Sasakian, α-Sasakian and β-Kenmotsu structures.

  1. The estimation of genetic distance and discriminant variables on breed of duck (Alabio, Bali, Khaki Campbell, Mojosari and Pegagan by morphological analysis

    Directory of Open Access Journals (Sweden)

    B Brahmantiyo

    2003-03-01

    Full Text Available A study on morphological body conformation of Alabio, Bali, Khaki Campbell, Mojosari and Pegagan ducks was carried out to determine the genetic distance and discriminant variables. This research was held in Research Institute for Animal Production, Ciawi, Bogor using 65 Alabio ducks, 40 Bali ducks, 36 Khaki Campbell ducks, 60 Mojosari ducks and 30 Pegagan ducks. Seven different body parts were measured, they were the length of femur, tibia, tarsometatarsus, the circumference of tarsometatarsus, the length of third digits, wing and maxilla. General Linear Models and simple discriminant analysis were used in this observation (SAS package program. Male and female Pegagan ducks had morphological size bigger than Alabio, Bali, Khaki Campbell and Mojosari ducks. Khaki Campbell ducks were mixed with Bali ducks (47.22% and Pegagan ducks from isolated location in South Sumatera were lightly mixed with Alabio and Bali. Mahalanobis genetic distance showed that Bali and Khaki Campbell ducks, also, Alabio and Mojosari ducks had similarity, with genetic distance of 1.420 and 1.548, respectively. Results from canonical analysis showed that the most discriminant variables were obtained from the length of femur, tibia and third digits.

  2. The Edit Distance as a Measure of Perceived Rhythmic Similarity

    Directory of Open Access Journals (Sweden)

    Olaf Post

    2012-07-01

    Full Text Available The ‘edit distance’ (or ‘Levenshtein distance’ measure of distance between two data sets is defined as the minimum number of editing operations – insertions, deletions, and substitutions – that are required to transform one data set to the other (Orpen and Huron, 1992. This measure of distance has been applied frequently and successfully in music information retrieval, but rarely in predicting human perception of distance. In this study, we investigate the effectiveness of the edit distance as a predictor of perceived rhythmic dissimilarity under simple rhythmic alterations. Approaching rhythms as a set of pulses that are either onsets or silences, we study two types of alterations. The first experiment is designed to test the model’s accuracy for rhythms that are relatively similar; whether rhythmic variations with the same edit distance to a source rhythm are also perceived as relatively similar by human subjects. In addition, we observe whether the salience of an edit operation is affected by its metric placement in the rhythm. Instead of using a rhythm that regularly subdivides a 4/4 meter, our source rhythm is a syncopated 16-pulse rhythm, the son. Results show a high correlation between the predictions by the edit distance model and human similarity judgments (r = 0.87; a higher correlation than for the well-known generative theory of tonal music (r = 0.64. In the second experiment, we seek to assess the accuracy of the edit distance model in predicting relatively dissimilar rhythms. The stimuli used are random permutations of the son’s inter-onset intervals: 3-3-4-2-4. The results again indicate that the edit distance correlates well with the perceived rhythmic dissimilarity judgments of the subjects (r = 0.76. To gain insight in the relationships between the individual rhythms, the results are also presented by means of graphic phylogenetic trees.

  3. Distance : between deixis and perspectivity

    OpenAIRE

    Meermann, Anastasia; Sonnenhauser, Barbara

    2015-01-01

    Discussing exemplary applications of the notion of distance in linguistic analysis, this paper shows that very different phenomena are described in terms of this concept. It is argued that in order to overcome the problems arising from this mixup, deixis, distance and perspectivity have to be distinguished and their interrelations need to be described. Thereby, distance emerges as part of a recursive process mediating between situation-bound deixis and discourse-level perspectivity. This is i...

  4. A perceptual metric for photo retouching.

    Science.gov (United States)

    Kee, Eric; Farid, Hany

    2011-12-13

    In recent years, advertisers and magazine editors have been widely criticized for taking digital photo retouching to an extreme. Impossibly thin, tall, and wrinkle- and blemish-free models are routinely splashed onto billboards, advertisements, and magazine covers. The ubiquity of these unrealistic and highly idealized images has been linked to eating disorders and body image dissatisfaction in men, women, and children. In response, several countries have considered legislating the labeling of retouched photos. We describe a quantitative and perceptually meaningful metric of photo retouching. Photographs are rated on the degree to which they have been digitally altered by explicitly modeling and estimating geometric and photometric changes. This metric correlates well with perceptual judgments of photo retouching and can be used to objectively judge by how much a retouched photo has strayed from reality.

  5. Metric-Aware Secure Service Orchestration

    Directory of Open Access Journals (Sweden)

    Gabriele Costa

    2012-12-01

    Full Text Available Secure orchestration is an important concern in the internet of service. Next to providing the required functionality the composite services must also provide a reasonable level of security in order to protect sensitive data. Thus, the orchestrator has a need to check whether the complex service is able to satisfy certain properties. Some properties are expressed with metrics for precise definition of requirements. Thus, the problem is to analyse the values of metrics for a complex business process. In this paper we extend our previous work on analysis of secure orchestration with quantifiable properties. We show how to define, verify and enforce quantitative security requirements in one framework with other security properties. The proposed approach should help to select the most suitable service architecture and guarantee fulfilment of the declared security requirements.

  6. Machine Learning for ATLAS DDM Network Metrics

    CERN Document Server

    Lassnig, Mario; The ATLAS collaboration; Vamosi, Ralf

    2016-01-01

    The increasing volume of physics data is posing a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from our ongoing automation efforts. First, we describe our framework for distributed data management and network metrics, automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for network-aware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

  7. Beyond Lovelock gravity: Higher derivative metric theories

    Science.gov (United States)

    Crisostomi, M.; Noui, K.; Charmousis, C.; Langlois, D.

    2018-02-01

    We consider theories describing the dynamics of a four-dimensional metric, whose Lagrangian is diffeomorphism invariant and depends at most on second derivatives of the metric. Imposing degeneracy conditions we find a set of Lagrangians that, apart form the Einstein-Hilbert one, are either trivial or contain more than 2 degrees of freedom. Among the partially degenerate theories, we recover Chern-Simons gravity, endowed with constraints whose structure suggests the presence of instabilities. Then, we enlarge the class of parity violating theories of gravity by introducing new "chiral scalar-tensor theories." Although they all raise the same concern as Chern-Simons gravity, they can nevertheless make sense as low energy effective field theories or, by restricting them to the unitary gauge (where the scalar field is uniform), as Lorentz breaking theories with a parity violating sector.

  8. Model Validation Using Coordinate Distance with Performance Sensitivity

    Directory of Open Access Journals (Sweden)

    Jiann-Shiun Lew

    2008-01-01

    Full Text Available This paper presents an innovative approach to model validation for a structure with significant parameter variations. Model uncertainty of the structural dynamics is quantified with the use of a singular value decomposition technique to extract the principal components of parameter change, and an interval model is generated to represent the system with parameter uncertainty. The coordinate vector, corresponding to the identified principal directions, of the validation system is computed. The coordinate distance between the validation system and the identified interval model is used as a metric for model validation. A beam structure with an attached subsystem, which has significant parameter uncertainty, is used to demonstrate the proposed approach.

  9. Combination of evidence in recommendation systems characterized by distance functions

    Energy Technology Data Exchange (ETDEWEB)

    Rocha, L. M. (Luis Mateus)

    2002-01-01

    Recommendation systems for different Document Networks (DN) such as the World Wide Web (WWW), Digitnl Libarries, or Scientific Databases, often make use of distance functions extracted from relationships among documents and between documents and semantic tags. For instance, documents In the WWW are related via a hyperlink network, while documents in bibliographic databases are related by citation and collaboration networks.Furthermore, documents can be related to semantic tags such as keywords used to describe their content, The distance functions computed from these relations establish associative networks among items of the DN, and allow recommendation systems to identify relevant associations for iudividoal users. The process of recommendation can be improved by integrating associative data from different sources. Thus we are presented with a problem of combining evidence (about assochaons between items) from different sonrces characterized by distance functions. In this paper we summarize our work on (1) inferring associations from semi-metric distance functions and (2) combining evidence from different (distance) associative DN.

  10. High-Dimensional Metrics in R

    OpenAIRE

    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...

  11. Interiors of Vaidya's radiating metric: Gravitational collapse

    International Nuclear Information System (INIS)

    Fayos, F.; Jaen, X.; Llanta, E.; Senovilla, J.M.M.

    1992-01-01

    Using the Darmois junction conditions, we give the necessary and sufficient conditions for the matching of a general spherically symmetric metric to a Vaidya radiating solution. We present also these conditions in terms of the physical quantities of the corresponding energy-momentum tensors. The physical interpretation of the results and their possible applications are studied, and we also perform a detailed analysis of previous work on the subject by other authors

  12. Anisotropic rectangular metric for polygonal surface remeshing

    KAUST Repository

    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.

  13. A Metrics Approach for Collaborative Systems

    Directory of Open Access Journals (Sweden)

    Cristian CIUREA

    2009-01-01

    Full Text Available This article presents different types of collaborative systems, their structure and classification. This paper defines the concept of virtual campus as a collaborative system. It builds architecture for virtual campus oriented on collaborative training processes. It analyses the quality characteristics of collaborative systems and propose techniques for metrics construction and validation in order to evaluate them. The article analyzes different ways to increase the efficiency and the performance level in collaborative banking systems.

  14. Preserved Network Metrics across Translated Texts

    Science.gov (United States)

    Cabatbat, Josephine Jill T.; Monsanto, Jica P.; Tapang, Giovanni A.

    2014-09-01

    Co-occurrence language networks based on Bible translations and the Universal Declaration of Human Rights (UDHR) translations in different languages were constructed and compared with random text networks. Among the considered network metrics, the network size, N, the normalized betweenness centrality (BC), and the average k-nearest neighbors, knn, were found to be the most preserved across translations. Moreover, similar frequency distributions of co-occurring network motifs were observed for translated texts networks.

  15. Anisotropic rectangular metric for polygonal surface remeshing

    KAUST Repository

    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.

  16. Smart Grid Status and Metrics Report

    Energy Technology Data Exchange (ETDEWEB)

    Balducci, Patrick J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Weimar, Mark R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kirkham, Harold [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-07-01

    To convey progress made in achieving the vision of a smart grid, this report uses a set of six characteristics derived from the National Energy Technology Laboratory Modern Grid Strategy. It measures 21 metrics to provide insight into the grid’s capacity to embody these characteristics. This report looks across a spectrum of smart grid concerns to measure the status of smart grid deployment and impacts.

  17. The Planck Vacuum and the Schwarzschild Metrics

    Directory of Open Access Journals (Sweden)

    Daywitt W. C.

    2009-07-01

    Full Text Available The Planck vacuum (PV is assumed to be the source of the visible universe. So under conditions of sufficient stress, there must exist a pathway through which energy from the PV can travel into this universe. Conversely, the passage of energy from the visible universe to the PV must also exist under the same stressful conditions. The following examines two versions of the Schwarzschild metric equation for compatability with this open-pathway idea.

  18. 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.

  19. Image characterization metrics for muon tomography

    Science.gov (United States)

    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.

  20. A Fundamental Metric for Metal Recycling Applied to Coated Magnesium

    NARCIS (Netherlands)

    Meskers, C.E.M.; Reuter, M.A.; Boin, U.; Kvithyld, A.

    2008-01-01

    A fundamental metric for the assessment of the recyclability and, hence, the sustainability of coated magnesium scrap is presented; this metric combines kinetics and thermodynamics. The recycling process, consisting of thermal decoating and remelting, was studied by thermogravimetry and differential

  1. Ideal Based Cyber Security Technical Metrics for Control Systems

    Energy Technology Data Exchange (ETDEWEB)

    W. F. Boyer; M. A. McQueen

    2007-10-01

    Much of the world's critical infrastructure is at risk from attack through electronic networks connected to control systems. Security metrics are important because they provide the basis for management decisions that affect the protection of the infrastructure. A cyber security technical metric is the security relevant output from an explicit mathematical model that makes use of objective measurements of a technical object. A specific set of technical security metrics are proposed for use by the operators of control systems. Our proposed metrics are based on seven security ideals associated with seven corresponding abstract dimensions of security. We have defined at least one metric for each of the seven ideals. Each metric is a measure of how nearly the associated ideal has been achieved. These seven ideals provide a useful structure for further metrics development. A case study shows how the proposed metrics can be applied to an operational control system.

  2. 43 CFR 12.915 - Metric system of measurement.

    Science.gov (United States)

    2010-10-01

    ... procurements, grants, and other business-related activities. Metric implementation may take longer where the... recipient, such as when foreign competitors are producing competing products in non-metric units. (End of...

  3. The Jacobi metric for timelike geodesics in static spacetimes

    Science.gov (United States)

    Gibbons, G. W.

    2016-01-01

    It is shown that the free motion of massive particles moving in static spacetimes is given by the geodesics of an energy-dependent Riemannian metric on the spatial sections analogous to Jacobi's metric in classical dynamics. In the massless limit Jacobi's metric coincides with the energy independent Fermat or optical metric. For stationary metrics, it is known that the motion of massless particles is given by the geodesics of an energy independent Finslerian metric of Randers type. The motion of massive particles is governed by neither a Riemannian nor a Finslerian metric. The properies of the Jacobi metric for massive particles moving outside the horizon of a Schwarschild black hole are described. By constrast with the massless case, the Gaussian curvature of the equatorial sections is not always negative.

  4. Factor structure of the Tomimatsu-Sato metrics

    International Nuclear Information System (INIS)

    Perjes, Z.

    1989-02-01

    Based on an earlier result stating that δ = 3 Tomimatsu-Sato (TS) metrics can be factored over the field of integers, an analogous representation for higher TS metrics was sought. It is shown that the factoring property of TS metrics follows from the structure of special Hankel determinants. A set of linear algebraic equations determining the factors was defined, and the factors of the first five TS metrics were tabulated, together with their primitive factors. (R.P.) 4 refs.; 2 tabs

  5. What can article-level metrics do for you?

    Science.gov (United States)

    Fenner, Martin

    2013-10-01

    Article-level metrics (ALMs) provide a wide range of metrics about the uptake of an individual journal article by the scientific community after publication. They include citations, usage statistics, discussions in online comments and social media, social bookmarking, and recommendations. In this essay, we describe why article-level metrics are an important extension of traditional citation-based journal metrics and provide a number of example from ALM data collected for PLOS Biology.

  6. THE DISTANCE TO M104

    Energy Technology Data Exchange (ETDEWEB)

    McQuinn, Kristen B. W. [University of Texas at Austin, McDonald Observatory, 2515 Speedway, Stop C1400 Austin, TX 78712 (United States); Skillman, Evan D. [Minnesota Institute for Astrophysics, School of Physics and Astronomy, 116 Church Street, SE, University of Minnesota, Minneapolis, MN 55455 (United States); Dolphin, Andrew E. [Raytheon Company, 1151 E. Hermans Road, Tucson, AZ 85756 (United States); Berg, Danielle [Center for Gravitation, Cosmology and Astrophysics, Department of Physics, University of Wisconsin Milwaukee, 1900 East Kenwood Boulevard, Milwaukee, WI 53211 (United States); Kennicutt, Robert, E-mail: kmcquinn@astro.as.utexas.edu [Institute for Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom)

    2016-11-01

    M104 (NGC 4594; the Sombrero galaxy) is a nearby, well-studied elliptical galaxy included in scores of surveys focused on understanding the details of galaxy evolution. Despite the importance of observations of M104, a consensus distance has not yet been established. Here, we use newly obtained Hubble Space Telescope optical imaging to measure the distance to M104 based on the tip of the red giant branch (TRGB) method. Our measurement yields the distance to M104 to be 9.55 ± 0.13 ± 0.31 Mpc equivalent to a distance modulus of 29.90 ± 0.03 ± 0.07 mag. Our distance is an improvement over previous results as we use a well-calibrated, stable distance indicator, precision photometry in a optimally selected field of view, and a Bayesian maximum likelihood technique that reduces measurement uncertainties. The most discrepant previous results are due to Tully–Fisher method distances, which are likely inappropriate for M104 given its peculiar morphology and structure. Our results are part of a larger program to measure accurate distances to a sample of well-known spiral galaxies (including M51, M74, and M63) using the TRGB method.

  7. THE DISTANCE TO M51

    Energy Technology Data Exchange (ETDEWEB)

    McQuinn, Kristen B. W. [University of Texas at Austin, McDonald Observatory, 2515 Speedway, Stop C1400 Austin, TX 78712 (United States); Skillman, Evan D. [Minnesota Institute for Astrophysics, School of Physics and Astronomy, 116 Church Street, S.E., University of Minnesota, Minneapolis, MN 55455 (United States); Dolphin, Andrew E. [Raytheon Company, 1151 E. Hermans Road, Tucson, AZ 85756 (United States); Berg, Danielle [Center for Gravitation, Cosmology and Astrophysics, Department of Physics, University of Wisconsin Milwaukee, 1900 East Kenwood Boulevard, Milwaukee, WI 53211 (United States); Kennicutt, Robert, E-mail: kmcquinn@astro.as.utexas.edu [Institute for Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom)

    2016-07-20

    Great investments of observing time have been dedicated to the study of nearby spiral galaxies with diverse goals ranging from understanding the star formation process to characterizing their dark matter distributions. Accurate distances are fundamental to interpreting observations of these galaxies, yet many of the best studied nearby galaxies have distances based on methods with relatively large uncertainties. We have started a program to derive accurate distances to these galaxies. Here we measure the distance to M51—the Whirlpool galaxy—from newly obtained Hubble Space Telescope optical imaging using the tip of the red giant branch method. We measure the distance modulus to be 8.58 ± 0.10 Mpc (statistical), corresponding to a distance modulus of 29.67 ± 0.02 mag. Our distance is an improvement over previous results as we use a well-calibrated, stable distance indicator, precision photometry in a optimally selected field of view, and a Bayesian Maximum Likelihood technique that reduces measurement uncertainties.

  8. The Distance to M51

    Science.gov (United States)

    McQuinn, Kristen. B. W.; Skillman, Evan D.; Dolphin, Andrew E.; Berg, Danielle; Kennicutt, Robert

    2016-07-01

    Great investments of observing time have been dedicated to the study of nearby spiral galaxies with diverse goals ranging from understanding the star formation process to characterizing their dark matter distributions. Accurate distances are fundamental to interpreting observations of these galaxies, yet many of the best studied nearby galaxies have distances based on methods with relatively large uncertainties. We have started a program to derive accurate distances to these galaxies. Here we measure the distance to M51—the Whirlpool galaxy—from newly obtained Hubble Space Telescope optical imaging using the tip of the red giant branch method. We measure the distance modulus to be 8.58 ± 0.10 Mpc (statistical), corresponding to a distance modulus of 29.67 ± 0.02 mag. Our distance is an improvement over previous results as we use a well-calibrated, stable distance indicator, precision photometry in a optimally selected field of view, and a Bayesian Maximum Likelihood technique that reduces measurement uncertainties. Based on observations made with the NASA/ESA Hubble Space Telescope, obtained from the Data Archive at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555.

  9. Distance criterion for hydrogen bond

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Distance criterion for hydrogen bond. In a D-H ...A contact, the D...A distance must be less than the sum of van der Waals Radii of the D and A atoms, for it to be a hydrogen bond.

  10. Social Distance and Intergenerational Relations

    Science.gov (United States)

    Kidwell, I. Jane; Booth, Alan

    1977-01-01

    Questionnaires were administered to a sample of adults to assess the extent of social distance between people of different ages. The findings suggest that the greater the age difference (younger or older) between people, the greater the social distance they feel. (Author)

  11. Quality Content in Distance Education

    Science.gov (United States)

    Yildiz, Ezgi Pelin; Isman, Aytekin

    2016-01-01

    In parallel with technological advances in today's world of education activities can be conducted without the constraints of time and space. One of the most important of these activities is distance education. The success of the distance education is possible with content quality. The proliferation of e-learning environment has brought a need for…

  12. Virtual Bioinformatics Distance Learning Suite

    Science.gov (United States)

    Tolvanen, Martti; Vihinen, Mauno

    2004-01-01

    Distance learning as a computer-aided concept allows students to take courses from anywhere at any time. In bioinformatics, computers are needed to collect, store, process, and analyze massive amounts of biological and biomedical data. We have applied the concept of distance learning in virtual bioinformatics to provide university course material…

  13. The Psychology of Psychic Distance

    DEFF Research Database (Denmark)

    Håkanson, Lars; Ambos, Björn; Schuster, Anja

    2016-01-01

    and their theoretical underpinnings assume psychic distances to be symmetric. Building on insights from psychology and sociology, this paper demonstrates how national factors and cognitive processes interact in the formation of asymmetric distance perceptions. The results suggest that exposure to other countries...

  14. Cognitive Styles and Distance Education.

    Science.gov (United States)

    Liu, Yuliang; Ginther, Dean

    1999-01-01

    Considers how to adapt the design of distance education to students' cognitive styles. Discusses cognitive styles, including field dependence versus independence, holistic-analytic, sensory preference, hemispheric preferences, and Kolb's Learning Style Model; and the characteristics of distance education, including technology. (Contains 92…

  15. Distance Learning: Practice and Dilemmas

    Science.gov (United States)

    Tatkovic, Nevenka; Sehanovic, Jusuf; Ruzic, Maja

    2006-01-01

    In accordance with the European processes of integrated and homogeneous education, the paper presents the essential viewpoints and questions covering the establishment and development of "distance learning" (DL) in Republic of Croatia. It starts from the advantages of distance learning versus traditional education taking into account…

  16. Hierarchical traits distances explain grassland Fabaceae species' ecological niches distances

    Science.gov (United States)

    Fort, Florian; Jouany, Claire; Cruz, Pablo

    2015-01-01

    Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e., ecological niches. We measured a wide range of functional traits (root traits, leaf traits, and whole plant traits) in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species' ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems) are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems) are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance. PMID:25741353

  17. Hierarchical traits distances explain grassland Fabaceae species’ ecological niches distances

    Directory of Open Access Journals (Sweden)

    Florian eFort

    2015-02-01

    Full Text Available Fabaceae species play a key role in ecosystem functioning through their capacity to fix atmospheric nitrogen via their symbiosis with Rhizobium bacteria. To increase benefits of using Fabaceae in agricultural systems, it is necessary to find ways to evaluate species or genotypes having potential adaptations to sub-optimal growth conditions. We evaluated the relevance of phylogenetic distance, absolute trait distance and hierarchical trait distance for comparing the adaptation of 13 grassland Fabaceae species to different habitats, i.e. ecological niches. We measured a wide range of functional traits (root traits, leaf traits and whole plant traits in these species. Species phylogenetic and ecological distances were assessed from a species-level phylogenetic tree and species’ ecological indicator values, respectively. We demonstrated that differences in ecological niches between grassland Fabaceae species were related more to their hierarchical trait distances than to their phylogenetic distances. We showed that grassland Fabaceae functional traits tend to converge among species with the same ecological requirements. Species with acquisitive root strategies (thin roots, shallow root systems are competitive species adapted to non-stressful meadows, while conservative ones (coarse roots, deep root systems are able to tolerate stressful continental climates. In contrast, acquisitive species appeared to be able to tolerate low soil-P availability, while conservative ones need high P availability. Finally we highlight that traits converge along the ecological gradient, providing the assumption that species with similar root-trait values are better able to coexist, regardless of their phylogenetic distance.

  18. A convergence theory for probabilistic metric spaces | Jäger ...

    African Journals Online (AJOL)

    We develop a theory of probabilistic convergence spaces based on Tardiff's neighbourhood systems for probabilistic metric spaces. We show that the resulting category is a topological universe and we characterize a subcategory that is isomorphic to the category of probabilistic metric spaces. Keywords: Probabilistic metric ...

  19. Understanding Acceptance of Software Metrics--A Developer Perspective

    Science.gov (United States)

    Umarji, Medha

    2009-01-01

    Software metrics are measures of software products and processes. Metrics are widely used by software organizations to help manage projects, improve product quality and increase efficiency of the software development process. However, metrics programs tend to have a high failure rate in organizations, and developer pushback is one of the sources…

  20. Modified intuitionistic fuzzy metric spaces and some fixed point theorems

    International Nuclear Information System (INIS)

    Saadati, R.; Sedghi, S.; Shobe, N.

    2008-01-01

    Since the intuitionistic fuzzy metric space has extra conditions (see [Gregori V, Romaguera S, Veereamani P. A note on intuitionistic fuzzy metric spaces. Chaos, Solitons and Fractals 2006;28:902-5]). In this paper, we consider modified intuitionistic fuzzy metric spaces and prove some fixed point theorems in these spaces. All the results presented in this paper are new

  1. Tide or Tsunami? The Impact of Metrics on Scholarly Research

    Science.gov (United States)

    Bonnell, Andrew G.

    2016-01-01

    Australian universities are increasingly resorting to the use of journal metrics such as impact factors and ranking lists in appraisal and promotion processes, and are starting to set quantitative "performance expectations" which make use of such journal-based metrics. The widespread use and misuse of research metrics is leading to…

  2. Robustness of climate metrics under climate policy ambiguity

    International Nuclear Information System (INIS)

    Ekholm, Tommi; Lindroos, Tomi J.; Savolainen, Ilkka

    2013-01-01

    Highlights: • We assess the economic impacts of using different climate metrics. • The setting is cost-efficient scenarios for three interpretations of the 2C target. • With each target setting, the optimal metric is different. • Therefore policy ambiguity prevents the selection of an optimal metric. • Robust metric values that perform well with multiple policy targets however exist. -- Abstract: A wide array of alternatives has been proposed as the common metrics with which to compare the climate impacts of different emission types. Different physical and economic metrics and their parameterizations give diverse weights between e.g. CH 4 and CO 2 , and fixing the metric from one perspective makes it sub-optimal from another. As the aims of global climate policy involve some degree of ambiguity, it is not possible to determine a metric that would be optimal and consistent with all policy aims. This paper evaluates the cost implications of using predetermined metrics in cost-efficient mitigation scenarios. Three formulations of the 2 °C target, including both deterministic and stochastic approaches, shared a wide range of metric values for CH 4 with which the mitigation costs are only slightly above the cost-optimal levels. Therefore, although ambiguity in current policy might prevent us from selecting an optimal metric, it can be possible to select robust metric values that perform well with multiple policy targets

  3. Graev metrics on free products and HNN extensions

    DEFF Research Database (Denmark)

    Slutsky, Konstantin

    2014-01-01

    We give a construction of two-sided invariant metrics on free products (possibly with amalgamation) of groups with two-sided invariant metrics and, under certain conditions, on HNN extensions of such groups. Our approach is similar to the Graev's construction of metrics on free groups over pointed...

  4. The universal connection and metrics on moduli spaces

    International Nuclear Information System (INIS)

    Massamba, Fortune; Thompson, George

    2003-11-01

    We introduce a class of metrics on gauge theoretic moduli spaces. These metrics are made out of the universal matrix that appears in the universal connection construction of M. S. Narasimhan and S. Ramanan. As an example we construct metrics on the c 2 = 1 SU(2) moduli space of instantons on R 4 for various universal matrices. (author)

  5. ST-intuitionistic fuzzy metric space with properties

    Science.gov (United States)

    Arora, Sahil; Kumar, Tanuj

    2017-07-01

    In this paper, we define ST-intuitionistic fuzzy metric space and the notion of convergence and completeness properties of cauchy sequences is studied. Further, we prove some properties of ST-intuitionistic fuzzy metric space. Finally, we introduce the concept of symmetric ST Intuitionistic Fuzzy metric space.

  6. Term Based Comparison Metrics for Controlled and Uncontrolled Indexing Languages

    Science.gov (United States)

    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…

  7. Software architecture analysis tool : software architecture metrics collection

    NARCIS (Netherlands)

    Muskens, J.; Chaudron, M.R.V.; Westgeest, R.

    2002-01-01

    The Software Engineering discipline lacks the ability to evaluate software architectures. Here we describe a tool for software architecture analysis that is based on metrics. Metrics can be used to detect possible problems and bottlenecks in software architectures. Even though metrics do not give a

  8. Otherwise Engaged : Social Media from Vanity Metrics to Critical Analytics

    NARCIS (Netherlands)

    Rogers, R.

    2018-01-01

    Vanity metrics is a term that captures the measurement and display of how well one is doing in the “success theater” of social media. The notion of vanity metrics implies a critique of metrics concerning both the object of measurement as well as their capacity to measure unobtrusively or only to

  9. Meter Detection in Symbolic Music Using Inner Metric Analysis

    NARCIS (Netherlands)

    de Haas, W.B.; Volk, A.

    2016-01-01

    In this paper we present PRIMA: a new model tailored to symbolic music that detects the meter and the first downbeat position of a piece. Given onset data, the metrical structure of a piece is interpreted using the Inner Metric Analysis (IMA) model. IMA identifies the strong and weak metrical

  10. Regional Sustainability: The San Luis Basin Metrics Project

    Science.gov (United States)

    There are a number of established, scientifically supported metrics of sustainability. Many of the metrics are data intensive and require extensive effort to collect data and compute. Moreover, individual metrics may not capture all aspects of a system that are relevant to sust...

  11. Metrics to describe the effects of landscape pattern on hydrology in a lotic peatland

    Science.gov (United States)

    Yuan, J.; Cohen, M. J.; Kaplan, D. A.; Acharya, S.; Larsen, L.; Nungesser, M.

    2013-12-01

    Strong reciprocal interactions exist between landscape patterns and ecological processes. Hydrology is the dominant abiotic driver of ecological processes in wetlands, particularly flowing wetlands, but is both the control on and controlled by the geometry of vegetation patterning. Landscape metrics are widely used to quantitatively link pattern and process. Our goal here was to use several candidate spatial pattern metrics to predict the effects of wetland vegetation pattern on hydrologic regime, specifically hydroperiod, in the ridge-slough patterned landscape of the Everglades. The metrics focus on the capacity for longitudinally connected flow, and thus the ability of this low-gradient patterned landscape to route water from upstream. We first explored flow friction cost (FFC), a weighted spatial distance procedure wherein ridges have a high flow cost than sloughs by virtue of their elevation and vegetation structure, to evaluate water movement through different landscape configurations. We also investigated existing published flow metrics, specifically the Directional Connectivity Index (DCI) and Landscape Discharge Competence (LDC), that seek to quantify connectivity, one of the sentinel targets of ecological restoration. Hydroperiod was estimated using a numerical hydrologic model (SWIFT 2D) in real and synthetic landscapes with varying vegetation properties ( patch anisotropy, ridge density). Synthetic landscapes were constrained by the geostatistical properties of the best conserved patterned, and contained five anisotropy levels and seven ridge density levels. These were used to construct the relationship between landscape metrics and hydroperiod. Then, using historical images from 1940 to 2004, we applied the metrics toback-cast hydroperiod. Current vegetation maps were used to test scale dependency for each metric. Our results suggest that both FFC and DCI are good predictors of hydroperiod under free flowing conditions, and that they can be used

  12. Hacia una visión holística de la distancia en los negocios internacionales: el caso colombiano || Towards Holistic Version of Distance in International Business: The Colombian Case

    Directory of Open Access Journals (Sweden)

    Caicedo Marulanda, Carolina

    2017-06-01

    Full Text Available Este artículo presenta nuevas estimaciones de distancia en los negocios internacionales entre Colombia y 57 países de Europa, América, Asia, África y Oceanía. El concepto de distancia que utilizamos trasciende el plano de lo institucional e incorpora tanto aspectos institucionales como aquellos que aún no han sido considerados en la literatura como el mercado laboral, la práctica mercantil y la innovación. De esta forma, a partir de la construcción de un índice sintético de distancia nosotros calculamos las distancias entre Colombia y los países de la muestra usando el concepto de distancia de Mahalanobis en las dimensiones aquí analizadas. Nuestros resultados muestran que si bien hay avances en la globalización sobre los negocios internacionales entre Colombia y los países de la muestra, todavía existen restricciones a las que se enfrentan las empresas colombianas que están interesadas en incursionar estos mercados buscando beneficiarse de los acuerdos de libre comercio. || This article presents new estimations of the distance in international business between Colombia and 57 countries in Europe, America, Asia, Africa and Oceania. The concept of distance that we use transcends the institutional level and incorporates both institutional aspects and those that have not yet been considered in the literature such as labor market, business practice and innovation. In this way, we build a holistic distance index and discuss the results for the specific case of Colombia. Thus, from the construction of a synthetic index of distance, we calculated the distances between Colombia and the countries of the sample using the Mahalanobis distance in the dimensions analyzed here. Our results show that although there is progress in the globalization of international business between Colombia and the countries of the sample there are still restrictions faced by Colombian companies that are interested in entering these markets seeking to benefit

  13. Tracking frequency laser distance gauge

    International Nuclear Information System (INIS)

    Phillips, J.D.; Reasenberg, R.D.

    2005-01-01

    Advanced astronomical missions with greatly enhanced resolution and physics missions of unprecedented accuracy will require laser distance gauges of substantially improved performance. We describe a laser gauge, based on Pound-Drever-Hall locking, in which the optical frequency is adjusted to maintain an interferometer's null condition. This technique has been demonstrated with pm performance. Automatic fringe hopping allows it to track arbitrary distance changes. The instrument is intrinsically free of the nm-scale cyclic bias present in traditional (heterodyne) high-precision laser gauges. The output is a radio frequency, readily measured to sufficient accuracy. The laser gauge has operated in a resonant cavity, which improves precision, can suppress the effects of misalignments, and makes possible precise automatic alignment. The measurement of absolute distance requires little or no additional hardware, and has also been demonstrated. The proof-of-concept version, based on a stabilized HeNe laser and operating on a 0.5 m path, has achieved 10 pm precision with 0.1 s integration time, and 0.1 mm absolute distance accuracy. This version has also followed substantial distance changes as fast as 16 mm/s. We show that, if the precision in optical frequency is a fixed fraction of the linewidth, both incremental and absolute distance precision are independent of the distance measured. We discuss systematic error sources, and present plans for a new version of the gauge based on semiconductor lasers and fiber-coupled components

  14. Reducing the distance in distance-caregiving by technology innovation

    Directory of Open Access Journals (Sweden)

    Lazelle E Benefield

    2007-07-01

    Full Text Available Lazelle E Benefield1, Cornelia Beck21College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA; 2Pat & Willard Walker Family Memory Research Center, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USAAbstract: Family caregivers are responsible for the home care of over 34 million older adults in the United States. For many, the elder family member lives more than an hour’s distance away. Distance caregiving is a growing alternative to more familiar models where: 1 the elder and the family caregiver(s may reside in the same household; or 2 the family caregiver may live nearby but not in the same household as the elder. The distance caregiving model involves elders and their family caregivers who live at some distance, defined as more than a 60-minute commute, from one another. Evidence suggests that distance caregiving is a distinct phenomenon, differs substantially from on-site family caregiving, and requires additional assistance to support the physical, social, and contextual dimensions of the caregiving process. Technology-based assists could virtually connect the caregiver and elder and provide strong support that addresses the elder’s physical, social, cognitive, and/or sensory impairments. Therefore, in today’s era of high technology, it is surprising that so few affordable innovations are being marketed for distance caregiving. This article addresses distance caregiving, proposes the use of technology innovation to support caregiving, and suggests a research agenda to better inform policy decisions related to the unique needs of this situation.Keywords: caregiving, family, distance, technology, elders

  15. Equivalence of massive propagator distance and mathematical distance on graphs

    International Nuclear Information System (INIS)

    Filk, T.

    1992-01-01

    It is shown in this paper that the assignment of distance according to the massive propagator method and according to the mathematical definition (length of minimal path) on arbitrary graphs with a bound on the degree leads to equivalent large scale properties of the graph. Especially, the internal scaling dimension is the same for both definitions. This result holds for any fixed, non-vanishing mass, so that a really inequivalent definition of distance requires the limit m → 0

  16. Language distance and tree reconstruction

    International Nuclear Information System (INIS)

    Petroni, Filippo; Serva, Maurizio

    2008-01-01

    Languages evolve over time according to a process in which reproduction, mutation and extinction are all possible. This is very similar to haploid evolution for asexual organisms and for the mitochondrial DNA of complex ones. Exploiting this similarity, it is possible, in principle, to verify hypotheses concerning the relationship among languages and to reconstruct their family tree. The key point is the definition of the distances among pairs of languages in analogy with the genetic distances among pairs of organisms. Distances can be evaluated by comparing grammar and/or vocabulary, but while it is difficult, if not impossible, to quantify grammar distance, it is possible to measure a distance from vocabulary differences. The method used by glottochronology computes distances from the percentage of shared 'cognates', which are words with a common historical origin. The weak point of this method is that subjective judgment plays a significant role. Here we define the distance of two languages by considering a renormalized edit distance among words with the same meaning and averaging over the two hundred words contained in a Swadesh list. In our approach the vocabulary of a language is the analogue of DNA for organisms. The advantage is that we avoid subjectivity and, furthermore, reproducibility of results is guaranteed. We apply our method to the Indo-European and the Austronesian groups, considering, in both cases, fifty different languages. The two trees obtained are, in many respects, similar to those found by glottochronologists, with some important differences as regards the positions of a few languages. In order to support these different results we separately analyze the structure of the distances of these languages with respect to all the others

  17. Language distance and tree reconstruction

    Science.gov (United States)

    Petroni, Filippo; Serva, Maurizio

    2008-08-01

    Languages evolve over time according to a process in which reproduction, mutation and extinction are all possible. This is very similar to haploid evolution for asexual organisms and for the mitochondrial DNA of complex ones. Exploiting this similarity, it is possible, in principle, to verify hypotheses concerning the relationship among languages and to reconstruct their family tree. The key point is the definition of the distances among pairs of languages in analogy with the genetic distances among pairs of organisms. Distances can be evaluated by comparing grammar and/or vocabulary, but while it is difficult, if not impossible, to quantify grammar distance, it is possible to measure a distance from vocabulary differences. The method used by glottochronology computes distances from the percentage of shared 'cognates', which are words with a common historical origin. The weak point of this method is that subjective judgment plays a significant role. Here we define the distance of two languages by considering a renormalized edit distance among words with the same meaning and averaging over the two hundred words contained in a Swadesh list. In our approach the vocabulary of a language is the analogue of DNA for organisms. The advantage is that we avoid subjectivity and, furthermore, reproducibility of results is guaranteed. We apply our method to the Indo-European and the Austronesian groups, considering, in both cases, fifty different languages. The two trees obtained are, in many respects, similar to those found by glottochronologists, with some important differences as regards the positions of a few languages. In order to support these different results we separately analyze the structure of the distances of these languages with respect to all the others.

  18. Extremal limits of the C metric: Nariai, Bertotti-Robinson, and anti-Nariai C metrics

    International Nuclear Information System (INIS)

    Dias, Oscar J.C.; Lemos, Jose P.S.

    2003-01-01

    In two previous papers we have analyzed the C metric in a background with a cosmological constant Λ, namely, the de-Sitter (dS) C metric (Λ>0), and the anti-de Sitter (AdS) C metric (Λ 0, Λ=0, and Λ 2 xS-tilde 2 ) to each point in the deformed two-sphere S-tilde 2 corresponds a dS 2 spacetime, except for one point which corresponds to a dS 2 spacetime with an infinite straight strut or string. There are other important new features that appear. One expects that the solutions found in this paper are unstable and decay into a slightly nonextreme black hole pair accelerated by a strut or by strings. Moreover, the Euclidean version of these solutions mediate the quantum process of black hole pair creation that accompanies the decay of the dS and AdS spaces

  19. Massless and massive quanta resulting from a mediumlike metric tensor

    International Nuclear Information System (INIS)

    Soln, J.

    1985-01-01

    A simple model of the ''primordial'' scalar field theory is presented in which the metric tensor is a generalization of the metric tensor from electrodynamics in a medium. The radiation signal corresponding to the scalar field propagates with a velocity that is generally less than c. This signal can be associated simultaneously with imaginary and real effective (momentum-dependent) masses. The requirement that the imaginary effective mass vanishes, which we take to be the prerequisite for the vacuumlike signal propagation, leads to the ''spontaneous'' splitting of the metric tensor into two distinct metric tensors: one metric tensor gives rise to masslesslike radiation and the other to a massive particle. (author)

  20. Principle of space existence and De Sitter metric

    International Nuclear Information System (INIS)

    Mal'tsev, V.K.

    1990-01-01

    The selection principle for the solutions of the Einstein equations suggested in a series of papers implies the existence of space (g ik ≠ 0) only in the presence of matter (T ik ≠0). This selection principle (principle of space existence, in the Markov terminology) implies, in the general case, the absence of the cosmological solution with the De Sitter metric. On the other hand, the De Sitter metric is necessary for describing both inflation and deflation periods of the Universe. It is shown that the De Sitter metric is also allowed by the selection principle under discussion if the metric experiences the evolution into the Friedmann metric

  1. Pragmatic security metrics applying metametrics to information security

    CERN Document Server

    Brotby, W Krag

    2013-01-01

    Other books on information security metrics discuss number theory and statistics in academic terms. Light on mathematics and heavy on utility, PRAGMATIC Security Metrics: Applying Metametrics to Information Security breaks the mold. This is the ultimate how-to-do-it guide for security metrics.Packed with time-saving tips, the book offers easy-to-follow guidance for those struggling with security metrics. Step by step, it clearly explains how to specify, develop, use, and maintain an information security measurement system (a comprehensive suite of metrics) to

  2. Pythagoras's theorem on a two-dimensional lattice from a `natural' Dirac operator and Connes's distance formula

    Science.gov (United States)

    Dai, Jian; Song, Xing-Chang

    2001-07-01

    One of the key ingredients of Connes's noncommutative geometry is a generalized Dirac operator which induces a metric (Connes's distance) on the pure state space. We generalize such a Dirac operator devised by Dimakis et al, whose Connes distance recovers the linear distance on an one-dimensional lattice, to the two-dimensional case. This Dirac operator has the local eigenvalue property and induces a Euclidean distance on this two-dimensional lattice, which is referred to as `natural'. This kind of Dirac operator can be easily generalized into any higher-dimensional lattices.

  3. THE ROLE OF ARTICLE LEVEL METRICS IN SCIENTIFIC PUBLISHING

    Directory of Open Access Journals (Sweden)

    Vladimir TRAJKOVSKI

    2016-04-01

    Full Text Available Emerging metrics based on article-level does not exclude traditional metrics based on citations to the journal, but complements them. Article-level metrics (ALMs provide a wide range of metrics about the uptake of an individual journal article by the scientific community after publication. They include citations, statistics of usage, discussions in online comments and social media, social bookmarking, and recommendations. In this editorial, the role of article level metrics in publishing scientific papers has been described. Article-Level Metrics (ALMs are rapidly emerging as important tools to quantify how individual articles are being discussed, shared, and used. Data sources depend on the tool, but they include classic metrics indicators depending on citations, academic social networks (Mendeley, CiteULike, Delicious and social media (Facebook, Twitter, blogs, and Youtube. The most popular tools used to apply this new metrics are: Public Library of Science - Article-Level Metrics, Altmetric, Impactstory and Plum Analytics. Journal Impact Factor (JIF does not consider impact or influence beyond citations count as this count reflected only through Thomson Reuters’ Web of Science® database. JIF provides indicator related to the journal, but not related to a published paper. Thus, altmetrics now becomes an alternative metrics for performance assessment of individual scientists and their contributed scholarly publications. Macedonian scholarly publishers have to work on implementing of article level metrics in their e-journals. It is the way to increase their visibility and impact in the world of science.

  4. Outsourced Similarity Search on Metric Data Assets

    DEFF Research Database (Denmark)

    Yiu, Man Lung; Assent, Ira; Jensen, Christian S.

    2012-01-01

    . Outsourcing offers the data owner scalability and a low initial investment. The need for privacy may be due to the data being sensitive (e.g., in medicine), valuable (e.g., in astronomy), or otherwise confidential. Given this setting, the paper presents techniques that transform the data prior to supplying......This paper considers a cloud computing setting in which similarity querying of metric data is outsourced to a service provider. The data is to be revealed only to trusted users, not to the service provider or anyone else. Users query the server for the most similar data objects to a query example...

  5. New Metrics from a Fractional Gravitational Field

    International Nuclear Information System (INIS)

    El-Nabulsi, Rami Ahmad

    2017-01-01

    Agop et al. proved in Commun. Theor. Phys. (2008) that, a Reissner–Nordstrom type metric is obtained, if gauge gravitational field in a fractal spacetime is constructed by means of concepts of scale relativity. We prove in this short communication that similar result is obtained if gravity in D-spacetime dimensions is fractionalized by means of the Glaeske–Kilbas–Saigo fractional. Besides, non-singular gravitational fields are obtained without using extra-dimensions. We present few examples to show that these gravitational fields hold a number of motivating features in spacetime physics. (paper)

  6. Energy Metrics for State Government Buildings

    Science.gov (United States)

    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

  7. Multi-Robot Assembly Strategies and Metrics

    Science.gov (United States)

    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

  8. Metric preheating and limitations of linearized gravity

    International Nuclear Information System (INIS)

    Bassett, Bruce A.; Tamburini, Fabrizio; Kaiser, David I.; Maartens, Roy

    1999-01-01

    During the preheating era after inflation, resonant amplification of quantum field fluctuations takes place. Recently it has become clear that this must be accompanied by resonant amplification of scalar metric fluctuations, since the two are united by Einstein's equations. Furthermore, this 'metric preheating' enhances particle production, and leads to gravitational rescattering effects even at linear order. In multi-field models with strong preheating (q>>1), metric perturbations are driven non-linear, with the strongest amplification typically on super-Hubble scales (k→0). This amplification is causal, being due to the super-Hubble coherence of the inflaton condensate, and is accompanied by resonant growth of entropy perturbations. The amplification invalidates the use of the linearized Einstein field equations, irrespective of the amount of fine-tuning of the initial conditions. This has serious implications on all scales - from large-angle cosmic microwave background (CMB) anisotropies to primordial black holes. We investigate the (q,k) parameter space in a two-field model, and introduce the time to non-linearity, t nl , as the timescale for the breakdown of the linearized Einstein equations. t nl is a robust indicator of resonance behavior, showing the fine structure in q and k that one expects from a quasi-Floquet system, and we argue that t nl is a suitable generalization of the static Floquet index in an expanding universe. Backreaction effects are expected to shut down the linear resonances, but cannot remove the existing amplification, which threatens the viability of strong preheating when confronted with the CMB. Mode-mode coupling and turbulence tend to re-establish scale invariance, but this process is limited by causality and for small k the primordial scale invariance of the spectrum may be destroyed. We discuss ways to escape the above conclusions, including secondary phases of inflation and preheating solely to fermions. The exclusion principle

  9. Alternative kinetic energy metrics for Lagrangian systems

    Science.gov (United States)

    Sarlet, W.; Prince, G.

    2010-11-01

    We examine Lagrangian systems on \\ {R}^n with standard kinetic energy terms for the possibility of additional, alternative Lagrangians with kinetic energy metrics different to the Euclidean one. Using the techniques of the inverse problem in the calculus of variations we find necessary and sufficient conditions for the existence of such Lagrangians. We illustrate the problem in two and three dimensions with quadratic and cubic potentials. As an aside we show that the well-known anomalous Lagrangians for the Coulomb problem can be removed by switching on a magnetic field, providing an appealing resolution of the ambiguous quantizations of the hydrogen atom.

  10. Differential geometry bundles, connections, metrics and curvature

    CERN Document Server

    Taubes, Clifford Henry

    2011-01-01

    Bundles, connections, metrics and curvature are the 'lingua franca' of modern differential geometry and theoretical physics. This book will supply a graduate student in mathematics or theoretical physics with the fundamentals of these objects. Many of the tools used in differential topology are introduced and the basic results about differentiable manifolds, smooth maps, differential forms, vector fields, Lie groups, and Grassmanians are all presented here. Other material covered includes the basic theorems about geodesics and Jacobi fields, the classification theorem for flat connections, the

  11. Multi-Robot Assembly Strategies and Metrics.

    Science.gov (United States)

    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.

  12. Indefinite metric and regularization of electrodynamics

    International Nuclear Information System (INIS)

    Gaudin, M.

    1984-06-01

    The invariant regularization of Pauli and Villars in quantum electrodynamics can be considered as deriving from a local and causal lagrangian theory for spin 1/2 bosons, by introducing an indefinite metric and a condition on the allowed states similar to the Lorentz condition. The consequences are the asymptotic freedom of the photon's propagator. We present a calcultion of the effective charge to the fourth order in the coupling as a function of the auxiliary masses, the theory avoiding all mass divergencies to this order [fr

  13. Metrics for comparing plasma mass filters

    Energy Technology Data Exchange (ETDEWEB)

    Fetterman, Abraham J.; Fisch, Nathaniel J. [Department of Astrophysical Sciences, Princeton University, Princeton, New Jersey 08540 (United States)

    2011-10-15

    High-throughput mass separation of nuclear waste may be useful for optimal storage, disposal, or environmental remediation. The most dangerous part of nuclear waste is the fission product, which produces most of the heat and medium-term radiation. Plasmas are well-suited to separating nuclear waste because they can separate many different species in a single step. A number of plasma devices have been designed for such mass separation, but there has been no standardized comparison between these devices. We define a standard metric, the separative power per unit volume, and derive it for three different plasma mass filters: the plasma centrifuge, Ohkawa filter, and the magnetic centrifugal mass filter.

  14. Metrics for comparing plasma mass filters

    International Nuclear Information System (INIS)

    Fetterman, Abraham J.; Fisch, Nathaniel J.

    2011-01-01

    High-throughput mass separation of nuclear waste may be useful for optimal storage, disposal, or environmental remediation. The most dangerous part of nuclear waste is the fission product, which produces most of the heat and medium-term radiation. Plasmas are well-suited to separating nuclear waste because they can separate many different species in a single step. A number of plasma devices have been designed for such mass separation, but there has been no standardized comparison between these devices. We define a standard metric, the separative power per unit volume, and derive it for three different plasma mass filters: the plasma centrifuge, Ohkawa filter, and the magnetic centrifugal mass filter.

  15. Decision Analysis for Metric Selection on a Clinical Quality Scorecard.

    Science.gov (United States)

    Guth, Rebecca M; Storey, Patricia E; Vitale, Michael; Markan-Aurora, Sumita; Gordon, Randolph; Prevost, Traci Q; Dunagan, Wm Claiborne; Woeltje, Keith F

    2016-09-01

    Clinical quality scorecards are used by health care institutions to monitor clinical performance and drive quality improvement. Because of the rapid proliferation of quality metrics in health care, BJC HealthCare found it increasingly difficult to select the most impactful scorecard metrics while still monitoring metrics for regulatory purposes. A 7-step measure selection process was implemented incorporating Kepner-Tregoe Decision Analysis, which is a systematic process that considers key criteria that must be satisfied in order to make the best decision. The decision analysis process evaluates what metrics will most appropriately fulfill these criteria, as well as identifies potential risks associated with a particular metric in order to identify threats to its implementation. Using this process, a list of 750 potential metrics was narrowed to 25 that were selected for scorecard inclusion. This decision analysis process created a more transparent, reproducible approach for selecting quality metrics for clinical quality scorecards. © The Author(s) 2015.

  16. Balanced metrics for vector bundles and polarised manifolds

    DEFF Research Database (Denmark)

    Garcia Fernandez, Mario; Ross, Julius

    2012-01-01

    leads to a Hermitian-Einstein metric on E and a constant scalar curvature Kähler metric in c_1(L). For special values of α, limits of balanced metrics are solutions of a system of coupled equations relating a Hermitian-Einstein metric on E and a Kähler metric in c1(L). For this, we compute the top two......We consider a notion of balanced metrics for triples (X, L, E) which depend on a parameter α, where X is smooth complex manifold with an ample line bundle L and E is a holomorphic vector bundle over X. For generic choice of α, we prove that the limit of a convergent sequence of balanced metrics...

  17. Construction of Einstein-Sasaki metrics in D≥7

    International Nuclear Information System (INIS)

    Lue, H.; Pope, C. N.; Vazquez-Poritz, J. F.

    2007-01-01

    We construct explicit Einstein-Kaehler metrics in all even dimensions D=2n+4≥6, in terms of a 2n-dimensional Einstein-Kaehler base metric. These are cohomogeneity 2 metrics which have the new feature of including a NUT-type parameter, or gravomagnetic charge, in addition to..' in addition to mass and rotation parameters. Using a canonical construction, these metrics all yield Einstein-Sasaki metrics in dimensions D=2n+5≥7. As is commonly the case in this type of construction, for suitable choices of the free parameters the Einstein-Sasaki metrics can extend smoothly onto complete and nonsingular manifolds, even though the underlying Einstein-Kaehler metric has conical singularities. We discuss some explicit examples in the case of seven-dimensional Einstein-Sasaki spaces. These new spaces can provide supersymmetric backgrounds in M theory, which play a role in the AdS 4 /CFT 3 correspondence

  18. National Metrical Types in Nineteenth Century Art Song

    Directory of Open Access Journals (Sweden)

    Leigh VanHandel

    2010-01-01

    Full Text Available William Rothstein’s article “National metrical types in music of the eighteenth and early nineteenth centuries” (2008 proposes a distinction between the metrical habits of 18th and early 19th century German music and those of Italian and French music of that period. Based on theoretical treatises and compositional practice, he outlines these national metrical types and discusses the characteristics of each type. This paper presents the results of a study designed to determine whether, and to what degree, Rothstein’s characterizations of national metrical types are present in 19th century French and German art song. Studying metrical habits in this genre may provide a lens into changing metrical conceptions of 19th century theorists and composers, as well as to the metrical habits and compositional style of individual 19th century French and German art song composers.

  19. Metrication: An economic wake-up call for US industry

    Science.gov (United States)

    Carver, G. P.

    1993-03-01

    As the international standard of measurement, the metric system is one key to success in the global marketplace. International standards have become an important factor in international economic competition. Non-metric products are becoming increasingly unacceptable in world markets that favor metric products. Procurement is the primary federal tool for encouraging and helping U.S. industry to convert voluntarily to the metric system. Besides the perceived unwillingness of the customer, certain regulatory language, and certain legal definitions in some states, there are no major impediments to conversion of the remaining non-metric industries to metric usage. Instead, there are good reasons for changing, including an opportunity to rethink many industry standards and to take advantage of size standardization. Also, when the remaining industries adopt the metric system, they will come into conformance with federal agencies engaged in similar activities.

  20. Use of different exposure metrics for understanding multi-modal travel injury risk

    Directory of Open Access Journals (Sweden)

    S. Ilgin Guler

    2016-08-01

    Full Text Available The objective of this work is to identify characteristics of different metrics of exposure for quantifying multi-modal travel injury risk. First, a discussion on the use of time-based and trip-based metrics for road user exposure to injury risk, considering multiple travel modes, is presented. The main difference between a time-based and trip-based metric is argued to be that a time-based metric reflects the actual duration of time spent on the road exposed to the travel risks. This can be proven to be important when considering multiple modes since different modes typically different speeds and average travel distances. Next, the use of total number of trips, total time traveled, and mode share (time-based or trip-based is considered to compare the injury risk of a given mode at different locations. It is argued that using mode share the safety concept which focuses on absolute numbers can be generalized. Quantitative results are also obtained from combining travel survey data with police collision reports for ten counties in California. The data are aggregated for five modes: (i cars, (ii SUVs, (iii transit riders, (iv bicyclists, and (v pedestrians. These aggregated data are used to compare travel risk of different modes with time-based or trip-based exposure metrics. These quantitative results confirm the initial qualitative discussions. As the penetration of mobile probes for transportation data collection increases, the insights of this study can provide guidance on how to best utilize the added value of such data to better quantify travel injury risk, and improve safety.

  1. A remodelling metric for angular fibre distributions and its application to diseased carotid bifurcations.

    LENUS (Irish Health Repository)

    Creane, Arthur

    2012-07-01

    Many soft biological tissues contain collagen fibres, which act as major load bearing constituents. The orientation and the dispersion of these fibres influence the macroscopic mechanical properties of the tissue and are therefore of importance in several areas of research including constitutive model development, tissue engineering and mechanobiology. Qualitative comparisons between these fibre architectures can be made using vector plots of mean orientations and contour plots of fibre dispersion but quantitative comparison cannot be achieved using these methods. We propose a \\'remodelling metric\\' between two angular fibre distributions, which represents the mean rotational effort required to transform one into the other. It is an adaptation of the earth mover\\'s distance, a similarity measure between two histograms\\/signatures used in image analysis, which represents the minimal cost of transforming one distribution into the other by moving distribution mass around. In this paper, its utility is demonstrated by considering the change in fibre architecture during a period of plaque growth in finite element models of the carotid bifurcation. The fibre architecture is predicted using a strain-based remodelling algorithm. We investigate the remodelling metric\\'s potential as a clinical indicator of plaque vulnerability by comparing results between symptomatic and asymptomatic carotid bifurcations. Fibre remodelling was found to occur at regions of plaque burden. As plaque thickness increased, so did the remodelling metric. A measure of the total predicted fibre remodelling during plaque growth, TRM, was found to be higher in the symptomatic group than in the asymptomatic group. Furthermore, a measure of the total fibre remodelling per plaque size, TRM\\/TPB, was found to be significantly higher in the symptomatic vessels. The remodelling metric may prove to be a useful tool in other soft tissues and engineered scaffolds where fibre adaptation is also present.

  2. Distinguishability notion based on Wootters statistical distance: Application to discrete maps

    Science.gov (United States)

    Gomez, Ignacio S.; Portesi, M.; Lamberti, P. W.

    2017-08-01

    We study the distinguishability notion given by Wootters for states represented by probability density functions. This presents the particularity that it can also be used for defining a statistical distance in chaotic unidimensional maps. Based on that definition, we provide a metric d ¯ for an arbitrary discrete map. Moreover, from d ¯ , we associate a metric space with each invariant density of a given map, which results to be the set of all distinguished points when the number of iterations of the map tends to infinity. Also, we give a characterization of the wandering set of a map in terms of the metric d ¯ , which allows us to identify the dissipative regions in the phase space. We illustrate the results in the case of the logistic and the circle maps numerically and analytically, and we obtain d ¯ and the wandering set for some characteristic values of their parameters. Finally, an extension of the metric space associated for arbitrary probability distributions (not necessarily invariant densities) is given along with some consequences. The statistical properties of distributions given by histograms are characterized in terms of the cardinal of the associated metric space. For two conjugate variables, the uncertainty principle is expressed in terms of the diameters of the associated metric space with those variables.

  3. Academy Distance Learning Tools (IRIS) -

    Data.gov (United States)

    Department of Transportation — IRIS is a suite of front-end web applications utilizing a centralized back-end Oracle database. The system fully supports the FAA Academy's Distance Learning Program...

  4. Distance labeling schemes for trees

    DEFF Research Database (Denmark)

    Alstrup, Stephen; Gørtz, Inge Li; Bistrup Halvorsen, Esben

    2016-01-01

    We consider distance labeling schemes for trees: given a tree with n nodes, label the nodes with binary strings such that, given the labels of any two nodes, one can determine, by looking only at the labels, the distance in the tree between the two nodes. A lower bound by Gavoille et al. [Gavoille...... variants such as, for example, small distances in trees [Alstrup et al., SODA, 2003]. We improve the known upper and lower bounds of exact distance labeling by showing that 1/4 log2(n) bits are needed and that 1/2 log2(n) bits are sufficient. We also give (1 + ε)-stretch labeling schemes using Theta...

  5. Distance Education in Technological Age

    Directory of Open Access Journals (Sweden)

    R .C. SHARMA

    2005-04-01

    Full Text Available Distance Education in Technological AgeRomesh Verma (Editor, New Delhi: Anmol Publications, 2005, ISBN 81-261-2210-2, pp. 419 Reviewed by R C SHARMARegional DirectorIndira Gandhi National Open University-INDIA The advancements in information and communication technologies have brought significant changes in the way the open and distance learning are provided to the learners. The impact of such changes is quite visible in both developed and developing countries. Switching over to online mode, joining hands with private initiatives and making a presence in foreign waters, are some of the hallmarks of the open and distance education (ODE institutions in developing countries. The compilation of twenty six essays on themes as applicable to ODE has resulted in the book, “Distance Education in Technological Age”. These essays follow a progressive style of narration, starting from describing conceptual framework of distance education, how the distance education was emerged on the global scene and in India, and then goes on to discuss emergence of online distance education and research aspects in ODE. The initial four chapters provide a detailed account of historical development and growth of distance education in India and State Open University and National Open University Model in India . Student support services are pivot to any distance education and much of its success depends on how well the support services are provided. These are discussed from national and international perspective. The issues of collaborative learning, learning on demand, life long learning, learning-unlearning and re-learning model and strategic alliances have also given due space by the authors. An assortment of technologies like communication technology, domestic technology, information technology, mass media and entertainment technology, media technology and educational technology give an idea of how these technologies are being adopted in the open universities. The study

  6. Distance Education in Technological Age

    OpenAIRE

    R .C. SHARMA

    2005-01-01

    Distance Education in Technological AgeRomesh Verma (Editor), New Delhi: Anmol Publications, 2005, ISBN 81-261-2210-2, pp. 419 Reviewed by R C SHARMARegional DirectorIndira Gandhi National Open University-INDIA The advancements in information and communication technologies have brought significant changes in the way the open and distance learning are provided to the learners. The impact of such changes is quite visible in both developed and developing countries. Switching over to online mode...

  7. A Distance Bounding Protocol for Location-Cloaked Applications.

    Science.gov (United States)

    Molina-Martínez, Cristián; Galdames, Patricio; Duran-Faundez, Cristian

    2018-04-26

    Location-based services (LBSs) assume that users are willing to release trustworthy and useful details about their whereabouts. However, many location privacy concerns have arisen. For location privacy protection, several algorithms build a cloaking region to hide a user’s location. However, many applications may not operate adequately on cloaked locations. For example, a traditional distance bounding protocol (DBP)—which is run by two nodes called the prover and the verifier—may conclude an untight and useless distance between these two entities. An LBS (verifier) may use this distance as a metric of usefulness and trustworthiness of the location claimed by the user (prover). However, we show that if a tight distance is desired, traditional DBP can refine a user’s cloaked location and compromise its location privacy. To find a proper balance, we propose a location-privacy-aware DBP protocol. Our solution consists of adding some small delays before submitting any user’s response. We show that several issues arise when a certain delay is chosen, and we propose some solutions. The effectiveness of our techniques in balancing location refinement and utility is demonstrated through simulation.

  8. A Distance Bounding Protocol for Location-Cloaked Applications

    Directory of Open Access Journals (Sweden)

    Cristián Molina-Martínez

    2018-04-01

    Full Text Available Location-based services (LBSs assume that users are willing to release trustworthy and useful details about their whereabouts. However, many location privacy concerns have arisen. For location privacy protection, several algorithms build a cloaking region to hide a user’s location. However, many applications may not operate adequately on cloaked locations. For example, a traditional distance bounding protocol (DBP—which is run by two nodes called the prover and the verifier—may conclude an untight and useless distance between these two entities. An LBS (verifier may use this distance as a metric of usefulness and trustworthiness of the location claimed by the user (prover. However, we show that if a tight distance is desired, traditional DBP can refine a user’s cloaked location and compromise its location privacy. To find a proper balance, we propose a location-privacy-aware DBP protocol. Our solution consists of adding some small delays before submitting any user’s response. We show that several issues arise when a certain delay is chosen, and we propose some solutions. The effectiveness of our techniques in balancing location refinement and utility is demonstrated through simulation.

  9. Fanpage metrics analysis. "Study on content engagement"

    Science.gov (United States)

    Rahman, Zoha; Suberamanian, Kumaran; Zanuddin, Hasmah Binti; Moghavvemi, Sedigheh; Nasir, Mohd Hairul Nizam Bin Md

    2016-08-01

    Social Media is now determined as an excellent communicative tool to connect directly with consumers. One of the most significant ways to connect with the consumers through these Social Networking Sites (SNS) is to create a facebook fanpage with brand contents and to place different posts periodically on these fanpages. In measuring social networking sites' effectiveness, corporate houses are now analyzing metrics in terms of calculating engagement rate, number of comments/share and likings in fanpages. So now, it is very important for the marketers to know the effectiveness of different contents or posts of fanpages in order to increase the fan responsiveness and engagement rate in the fan pages. In the study the authors have analyzed total 1834 brand posts from 17 international brands of Electronics companies. Data of 9 months (From December 2014 to August 2015) have been collected for analyses, which were available online in the Brand' fan pages. An econometrics analysis is conducted using Eviews 9, to determine the impact of different contents on fanpage engagement. The study picked the four most frequently posted content to determine their impact on PTA (people Talking About) metrics and Fanpage engagement activities.

  10. 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.

  11. Value of the Company and Marketing Metrics

    Directory of Open Access Journals (Sweden)

    André Luiz Ramos

    2013-12-01

    Full Text Available Thinking marketing strategies from a resource-based perspective (Barney, 1991, proposing assets as either tangible, organizational and human, and from Constantin and Luch’s vision (1994, where strategic resources can be tanbigle or intangible, internal or external to the firm, raises a research approach on Marketing and Finance. According to Srivastava, Shervani and Fahey (1998 there are 3 market assets types, which generate firm value. Firm value can be measured by discounted cashflow, compromising marketing activities with value generation forcasts (Anderson, 1982; Day, Fahey, 1988; Doyle, 2000; Rust et al., 2004a. The economic value of marketing strategies and marketing metrics are calling strategy researchers’ and marketing managers’ attention, making clear the need for building a bridge able to articulate marketing and finance form a strategic perspective. This article proposes an analytical framework based on different scientific approaches envolving risk and return promoted by marketing strategies and points out advances concerning both methodological approaches and marketing strategies and its impact on firm metrics and value, usgin Srinivasan and Hanssens (2009 as a start point.

  12. Defining a standard metric for electricity savings

    International Nuclear Information System (INIS)

    Koomey, Jonathan; Akbari, Hashem; Blumstein, Carl; Brown, Marilyn; Brown, Richard; Calwell, Chris; Carter, Sheryl; Cavanagh, Ralph; Chang, Audrey; Claridge, David; Craig, Paul; Diamond, Rick; Eto, Joseph H; Fulkerson, William; Gadgil, Ashok; Geller, Howard; Goldemberg, Jose; Goldman, Chuck; Goldstein, David B; Greenberg, Steve

    2010-01-01

    The growing investment by governments and electric utilities in energy efficiency programs highlights the need for simple tools to help assess and explain the size of the potential resource. One technique that is commonly used in this effort is to characterize electricity savings in terms of avoided power plants, because it is easier for people to visualize a power plant than it is to understand an abstraction such as billions of kilowatt-hours. Unfortunately, there is no standardization around the characteristics of such power plants. In this letter we define parameters for a standard avoided power plant that have physical meaning and intuitive plausibility, for use in back-of-the-envelope calculations. For the prototypical plant this article settles on a 500 MW existing coal plant operating at a 70% capacity factor with 7% T and D losses. Displacing such a plant for one year would save 3 billion kWh/year at the meter and reduce emissions by 3 million metric tons of CO 2 per year. The proposed name for this metric is the Rosenfeld, in keeping with the tradition among scientists of naming units in honor of the person most responsible for the discovery and widespread adoption of the underlying scientific principle in question-Dr Arthur H Rosenfeld.

  13. Defining a standard metric for electricity savings

    Energy Technology Data Exchange (ETDEWEB)

    Koomey, Jonathan [Lawrence Berkeley National Laboratory and Stanford University, PO Box 20313, Oakland, CA 94620-0313 (United States); Akbari, Hashem; Blumstein, Carl; Brown, Marilyn; Brown, Richard; Calwell, Chris; Carter, Sheryl; Cavanagh, Ralph; Chang, Audrey; Claridge, David; Craig, Paul; Diamond, Rick; Eto, Joseph H; Fulkerson, William; Gadgil, Ashok; Geller, Howard; Goldemberg, Jose; Goldman, Chuck; Goldstein, David B; Greenberg, Steve, E-mail: JGKoomey@stanford.ed

    2010-01-15

    The growing investment by governments and electric utilities in energy efficiency programs highlights the need for simple tools to help assess and explain the size of the potential resource. One technique that is commonly used in this effort is to characterize electricity savings in terms of avoided power plants, because it is easier for people to visualize a power plant than it is to understand an abstraction such as billions of kilowatt-hours. Unfortunately, there is no standardization around the characteristics of such power plants. In this letter we define parameters for a standard avoided power plant that have physical meaning and intuitive plausibility, for use in back-of-the-envelope calculations. For the prototypical plant this article settles on a 500 MW existing coal plant operating at a 70% capacity factor with 7% T and D losses. Displacing such a plant for one year would save 3 billion kWh/year at the meter and reduce emissions by 3 million metric tons of CO{sub 2} per year. The proposed name for this metric is the Rosenfeld, in keeping with the tradition among scientists of naming units in honor of the person most responsible for the discovery and widespread adoption of the underlying scientific principle in question-Dr Arthur H Rosenfeld.

  14. Covariant electrodynamics in linear media: Optical metric

    Science.gov (United States)

    Thompson, Robert T.

    2018-03-01

    While the postulate of covariance of Maxwell's equations for all inertial observers led Einstein to special relativity, it was the further demand of general covariance—form invariance under general coordinate transformations, including between accelerating frames—that led to general relativity. Several lines of inquiry over the past two decades, notably the development of metamaterial-based transformation optics, has spurred a greater interest in the role of geometry and space-time covariance for electrodynamics in ponderable media. I develop a generally covariant, coordinate-free framework for electrodynamics in general dielectric media residing in curved background space-times. In particular, I derive a relation for the spatial medium parameters measured by an arbitrary timelike observer. In terms of those medium parameters I derive an explicit expression for the pseudo-Finslerian optical metric of birefringent media and show how it reduces to a pseudo-Riemannian optical metric for nonbirefringent media. This formulation provides a basis for a unified approach to ray and congruence tracing through media in curved space-times that may smoothly vary among positively refracting, negatively refracting, and vacuum.

  15. Axisymmetric plasma equilibria in a Kerr metric

    Science.gov (United States)

    Elsässer, Klaus

    2001-10-01

    Plasma equilibria near a rotating black hole are considered within the multifluid description. An isothermal two-component plasma with electrons and positrons or ions is determined by four structure functions and the boundary conditions. These structure functions are the Bernoulli function and the toroidal canonical momentum per mass for each species. The quasi-neutrality assumption (no charge density, no toroidal current) allows to solve Maxwell's equations analytically for any axisymmetric stationary metric, and to reduce the fluid equations to one single scalar equation for the stream function \\chi of the positrons or ions, respectively. The basic smallness parameter is the ratio of the skin depth of electrons to the scale length of the metric and fluid quantities, and, in the case of an electron-ion plasma, the mass ratio m_e/m_i. The \\chi-equation can be solved by standard methods, and simple solutions for a Kerr geometry are available; they show characteristic flow patterns, depending on the structure functions and the boundary conditions.

  16. Defining a Standard Metric for Electricity Savings

    Energy Technology Data Exchange (ETDEWEB)

    Brown, Marilyn; Akbari, Hashem; Blumstein, Carl; Koomey, Jonathan; Brown, Richard; Calwell, Chris; Carter, Sheryl; Cavanagh, Ralph; Chang, Audrey; Claridge, David; Craig, Paul; Diamond, Rick; Eto, Joseph H.; Fulkerson, William; Gadgil, Ashok; Geller, Howard; Goldemberg, Jose; Goldman, Chuck; Goldstein, David B.; Greenberg, Steve; Hafemeister, David; Harris, Jeff; Harvey, Hal; Heitz, Eric; Hirst, Eric; Hummel, Holmes; Kammen, Dan; Kelly, Henry; Laitner, Skip; Levine, Mark; Lovins, Amory; Masters, Gil; McMahon, James E.; Meier, Alan; Messenger, Michael; Millhone, John; Mills, Evan; Nadel, Steve; Nordman, Bruce; Price, Lynn; Romm, Joe; Ross, Marc; Rufo, Michael; Sathaye, Jayant; Schipper, Lee; Schneider, Stephen H; Sweeney, James L; Verdict, Malcolm; Vorsatz, Diana; Wang, Devra; Weinberg, Carl; Wilk, Richard; Wilson, John; Worrell, Ernst

    2009-03-01

    The growing investment by governments and electric utilities in energy efficiency programs highlights the need for simple tools to help assess and explain the size of the potential resource. One technique that is commonly used in this effort is to characterize electricity savings in terms of avoided power plants, because it is easier for people to visualize a power plant than it is to understand an abstraction such as billions of kilowatt-hours. Unfortunately, there is no standardization around the characteristics of such power plants. In this letter we define parameters for a standard avoided power plant that have physical meaning and intuitive plausibility, for use in back-of-the-envelope calculations. For the prototypical plant this article settles on a 500 MW existing coal plant operating at a 70percent capacity factor with 7percent T&D losses. Displacing such a plant for one year would save 3 billion kW h per year at the meter and reduce emissions by 3 million metric tons of CO2 per year. The proposed name for this metric is the Rosenfeld, in keeping with the tradition among scientists of naming units in honor of the person most responsible for the discovery and widespread adoption of the underlying scientific principle in question--Dr. Arthur H. Rosenfeld.

  17. Computing the Stretch Factor of Paths, Trees, and Cycles in Weighted Fixed Orientation Metrics

    DEFF Research Database (Denmark)

    Wulff-Nilsen, Christian

    2008-01-01

    Let G be a graph embedded in the L_1-plane. The stretch factor of G is the maximum over all pairs of distinct vertices p and q of G of the ratio L_1^G(p,q)/L_1(p,q), where L_1^G(p,q) is the L_1-distance in G between p and q. We show how to compute the stretch factor of an n-vertex path in O(n*(log...... n)^2) worst-case time and O(n) space and we mention generalizations to trees and cycles, to general weighted fixed orientation metrics, and to higher dimensions....

  18. Comprehensive Metric Education Project: Implementing Metrics at a District Level Administrative Guide.

    Science.gov (United States)

    Borelli, Michael L.

    This document details the administrative issues associated with guiding a school district through its metrication efforts. Issues regarding staff development, curriculum development, and the acquisition of instructional resources are considered. Alternative solutions are offered. Finally, an overall implementation strategy is discussed with…

  19. Moving from gamma passing rates to patient DVH-based QA metrics in pretreatment dose QA

    Energy Technology Data Exchange (ETDEWEB)

    Zhen, Heming; Nelms, Benjamin E.; Tome, Wolfgang A. [Department of Medical Physics, University of Wisconsin, Madison, Wisconsin 53705 (United States); Department of Human Oncology, University of Wisconsin, Madison, Wisconsin 53792 and Canis Lupus LLC, Merrimac, Wisconsin 53561 (United States); Department of Medical Physics, University of Wisconsin, Madison, Wisconsin 53705 and Department of Human Oncology, University of Wisconsin, Madison, Wisconsin 53792 (United States)

    2011-10-15

    Purpose: The purpose of this work is to explore the usefulness of the gamma passing rate metric for per-patient, pretreatment dose QA and to validate a novel patient-dose/DVH-based method and its accuracy and correlation. Specifically, correlations between: (1) gamma passing rates for three 3D dosimeter detector geometries vs clinically relevant patient DVH-based metrics; (2) Gamma passing rates of whole patient dose grids vs DVH-based metrics, (3) gamma passing rates filtered by region of interest (ROI) vs DVH-based metrics, and (4) the capability of a novel software algorithm that estimates corrected patient Dose-DVH based on conventional phan-tom QA data are analyzed. Methods: Ninety six unique ''imperfect'' step-and-shoot IMRT plans were generated by applying four different types of errors on 24 clinical Head/Neck patients. The 3D patient doses as well as the dose to a cylindrical QA phantom were then recalculated using an error-free beam model to serve as a simulated measurement for comparison. Resulting deviations to the planned vs simulated measured DVH-based metrics were generated, as were gamma passing rates for a variety of difference/distance criteria covering: dose-in-phantom comparisons and dose-in-patient comparisons, with the in-patient results calculated both over the whole grid and per-ROI volume. Finally, patient dose and DVH were predicted using the conventional per-beam planar data as input into a commercial ''planned dose perturbation'' (PDP) algorithm, and the results of these predicted DVH-based metrics were compared to the known values. Results: A range of weak to moderate correlations were found between clinically relevant patient DVH metrics (CTV-D95, parotid D{sub mean}, spinal cord D1cc, and larynx D{sub mean}) and both 3D detector and 3D patient gamma passing rate (3%/3 mm, 2%/2 mm) for dose-in-phantom along with dose-in-patient for both whole patient volume and filtered per-ROI. There was

  20. Lossy gossip and composition of metrics

    NARCIS (Netherlands)

    Brouwer, A.E.; Draisma, J.; Frenk, B.J.

    2015-01-01

    We study the monoid generated by n × n distance matrices under tropical (or min-plus) multiplication. Using the tropical geometry of the orthogonal group, we prove that this monoid is a finite polyhedral fan of dimension $(\\begin{array}{c} n \\\\ 2 \\end{array})$ , and we compute the structure of this